RIO GRANDE NATIONAL FOREST HISTORIC CLIMATE ASSESSMENT
Prepared for the United States Department of Agriculture Forest Service and Rocky Mountain Research Station by the Colorado Climate Center
Peter Goble
Nolan J. Doesken
Linda Joyce
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EXECUTIVE SUMMARY Located in south-central Colorado, the Rio Grande National Forest covers 2906 square miles of federally protected land. The climatic conditions experienced within the Rio Grande National Forest are heavily influenced by its landlocked, continental positioning, combined with its mid- latitude location. Most importantly, the climate of the area varies greatly over short distances due to complex topography and large differences in elevation. The Forest ranges in elevation from 7600 to 14335 feet above sea level (USDA 2016). In this report the recent recorded history of the Forest’s climate is explored. Using the data available, the mean state, variability, and historic trends of the Forest’s climate are summarized with an emphasis on temperatures, precipitation, and snowpack. The historic climate summary is rounded out with information on several of the Forest’s extreme weather events, physical descriptions of known mountain weather patterns that apply to the Forest, and an assessment of some of the largest needs for future weather observation.
Data used to complete this report were primarily collected by, and obtained from, the following organizations: the National Weather Service, Oregon State University, the National Aeronautics and Space Administration, and the United States Department of Agriculture. Data are analyzed from four of the National Weather Service’s Cooperative Observing Network (COOP). The COOP sites used in this report were Crestone, Hermit, Saguache, and Wolf Creek Pass. The Del Norte Station was consistently used to represent the approximate climate of low mountain valleys within the Rio Grande National Forest. The Hermit station is used to approximate high mountain valleys, and the Wolf Creek Pass/Wolf Creek Summit stations are used to approximate mountain pass-like weather. Precipitation and snowpack data are utilized from both manual snow course sites and automated Snowpack Telemetry (SNOTEL) sites. The SNOTEL sites used are Wolf Creek Summit and Slumgullion. Manual snow core measurements came from the Wolf Creek Summit, Santa Maria, Pool Table Mountain, and Cochetopa Pass sites. Wind observations are obtained from the Remote Automated Weather Station (RAWS) network, and include the Blue Park, Bighorn, and Great Sand Dunes stations. Modeled data are used for a complete spatial representation of the Forest. Model data used come from North American Regional Reanalysis (NARR), and the Parameter-elevation Relationships on Independent Slopes (PRISM).
Temperature and Precipitation Averages across the Forest: Using spatially gridded climate data, the mean annual temperature across the Forest was found to be cool, between 28 and 40 F over the 1981- 2010 period, depending on location. The warmest areas are in the San Luis Valley and the coolest areas are the high elevation peaks. Large temperature swings are observed from summer to winter across the Forest. Mean winter temperatures (DJF) range from 14-24 F. Mean spring temperatures (MAM) range from 25-40 F. Mean summer temperatures (JJA) range from 46-60 F. Mean fall temperatures (SON) range from 30-39 F.
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The contour plot above depicts annual average temperature for south-central Colorado on a latitude-longitude plane. The Rio Grande National Forest is outlined in black. Data are provided at 4km resolution by the PRISM climate group at Oregon State for the 19810-2010 period of record.
Large temperature swings are also observed from day to night (maximum temperature to minimum temperature). Diurnal variability is largest in the mountain valleys and smallest over mountain peaks. Using spatially gridded climate data, annual average precipitation in the Forest varies from about 12” to 55”. This large spatial variability in precipitation exists as a function of elevation, and whether or not a location is favored for orographic lift by prevailing winds. Meteorological summer (June, July, August) brings more total rainfall to the Forest than any other season as monsoonal moisture allows all locations of the Forest to average five or more inches of rainfall. For the lowest and middle elevations of the Forest, the monsoon season of July through September is most important for the production of precipitation. The highest elevation areas within the Forest average consistently higher precipitation totals from July through April with a short dry season in May and June. Precipitation and snowpack were found to be highest over the southwest end of the Forest.
Temperature and Precipitation in Mountain Valleys and Passes. The longest climate records come from National Weather Service Cooperative Observing Network in the Rio Grande National Forest (Del Norte, Hermit, Wolf Creek). These stations are not only important to use in an historic climate assessment of the Forest because of their length of record, but also because these data are ground-truth weather
3 observations. Maximum temperatures at the high mountain valley station of Hermit are similar to low valley station at Del Norte year-round, but July is one of two months where the average maximum temperature is slightly higher at the Hermit station (Table 1). The average minimum temperature for high mountain valley station, Hermit, is cooler for Hermit than Del Norte every month of the year. The average maximum temperature at the mountain pass station at Wolf Creek is cooler than for Hermit and Del Norte in every month of the year. The average January minimum at Wolf Creek, however, is warmer than both the average January low for Del Norte and Hermit, but still cold at 6.1 F.
Temperature variations are greater in the winter than in the summer and are greater for minimum temperatures than maximum temperatures. The observed range of 15-day running average minimum daily temperatures for Del Norte is from 38.1 to 56.1 F in July and from -19.2 to 27.2 F in January. This range goes from 26.3 to 50.6 F in July and from -35.9 to 22.2 F in January for Hermit. Wolf Creek pass has an observed range from 28.5 to 47.9 F in July and from -17.8 to 21.0 F in January. Cool nighttime air makes for a frost-free season of roughly 20-120 days depending on location, which is short relative to the majority of the United States, and even Colorado.
Table 1. Average maximum and minimum temperatures (1981-2010) for the Del Norte, Hermit, and Wolf Creek stations. January July Average Average Average Average Maximum minimum Maximum Minimum Low Mountain 32.4 F 2.6 F 77 45.8 Valley (Del Norte) High Mountain 30.3 F -3.5 77.2 41.1 Valley (Hermit) Mountain Pass 39.5 6.1 65.6 40.6 (Wolfe Creek)
Because not all stations have the same period of record, precipitation variability was measured over the 1980-2015 period of record. The amount of precipitation received in any given year is highly variable as it depends on the storm tracks taken by a highly chaotic and dynamic atmosphere. Total variability in annual precipitation is greatest in the areas of the Forest that receive the largest amounts of precipitation climatologically.
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The contour plot shown above illustrates the amount of precipitation (inches) expected annually for south-central Colorado. The Rio Grande National Forest is outlined in black. Data are provided at 4km resolution by the PRISM climate group at Oregon State for the 1981-2010 period of record.
For the lowest and middle elevations of the Forest, the monsoon season of July through September is most important for the production of precipitation. The highest elevation areas within the Forest average consistently higher precipitation totals from July through April with a short dry season in May and June. Precipitation and snowpack were found to be highest over the southwest end of the Forest. Precipitation variation from year-to-year is large relative to annual averages. Differences between precipitation in wet years and dry years can be as much as a factor of two. The low mountain valley of Del Norte, averages 9.37 of precipitation, yet the range between the 1980-2015 period encompassed only 4.78 inches of accumulation in 2002 and 15.67 inches in 1985. For Hermit, which is representative of high mountain valleys, average annual precipitation is 14.74”. Yearly totals that have been observed range from 8.36” in 2002 to 22.10” in 1990. Wolf Creek Pass, which represents mountain pass conditions in this report, averages 47.95” of precipitation, but keep in mind that mountain passes in the north and east parts of the forest will receive less. The range of annual precipitation received at Wolf Creek pass extends from 25.80” in 2002 to 59.47” in 1986.
The Rio Grande National Forest air is typically quite dry, particularly with respect to other more populated regions around the country. Surface vapor pressure averages between two and six
5 millimeters of mercury. There is a diurnal cycle to airflow in which cold air pools in the valleys at night and moves back upslope in midday and afternoon hours. This circulation is driven by radiative heating and cooling, and often produces afternoon thunderstorms, especially during the monsoon season. Large 24-hr precipitation totals can occur even in the driest parts of the RGNF. The highest 24-hr precipitation measurements at Del Norte, Hermit, and Wolf Creek Pass are 2.55”, 3.05”, and 4.10” respectively. Heavy precipitation is most likely to occur in the late summer and early fall for low and high mountain valleys. Up on the mountain passes heavy daily totals are more likely in winter.
Snowfall: Reliable observations of temperature and snowfall are not available with temporal consistency at elevations above 9,000 ft. Precipitation and snowpack data are available for high elevations between 9,000 and 11,000 ft through the USDA Snowpack Telemetry Network. Complete maps of climate averages for the Rio Grande National Forest can be constructed from reanalysis data, or model- estimated data that is calibrated based on observations, such as the PRISM and North American Regional Reanalysis. Unsurprisingly, the same parts of the Forest that receive the most precipitation also receive the most snowfall. Over 300” falls on average annually on both the western and southwesternmost flanks of the forest. The largest measured snowfall total in the forest was 55” on January 15th of 1997 at Wolf Creek Pass.
Snowpack: Average April 1st snowpack based on the years of 1949-2014 is as follows: 5.71” for Cochetopa Pass, 5.16” for Pool Table Mountain, 3.65” for Santa Maria, and 31.12” for Wolf Creek Pass. All sites other than Wolf Creek Pass have at least one year of record in which no measurable snowpack existed at the beginning of April. The lowest year for Wolf Creek was 9.90” of snowpack in 1977. The distribution of April 1st snowpack measurements from these four snow course sites reiterates two focal themes about the Rio Grande National Forest Climate: 1.The precipitation in the area is highly variable. 2. The southwest end of the Forest is the wettest area of the forest.
Wind Averages: Winds most often blow out of the west and southwest during the day. At night the wind most typically blows downhill as the coolest, most dense air drains into the valleys. Winds measured at different stations in the area most typically come from the direction of the highest nearby topographic feature at night.
Historic Trend Observations for Temperature and Precipitation: In-situ climate data with long and consistent historic record in the Forest are regrettably sparse. Several nearby stations have long records going back to about 100 years. All stations in or near the Forest with lengthy records have some data discontinuities, compromising the ability to perform robust trend analysis. Only three United States Historical Climate Network-approved stations are found either within the Forest (Hermit), or within twenty miles of the USFS boundary (Del Norte, Saguache)that have years of continuous, or near continuous data. Trends in maximum daily temperature, minimum daily temperature, and precipitation were analyzed at these three stations going back to 1900-1909, 1950-1959, and 1980-1989.
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The trend line above illustrates annual average maximum daily temperatures at the Saguache Cooperative Observing Network Weather Station. The black line depicts the ten-year running average. This trend is significantly positive at 99% confidence. Not all trends in this study carry the same significance.
Since the beginning of the 20th century, temperatures are on the increase, and significantly in some cases. Significance of increases is not consistent from site-to-site. In the case of both Saguache and Del Note temperatures have risen significantly over the last century (0.12 F/decade and 0.42 F/decade respectively), but minimum daily temperatures have not increased significantly. Minimum daily temperatures have risen significantly (0.39 F/decade) while maximum temperatures have not for the Hermit station.
Precipitation has increased for Del Norte, but decreased for Saguache and Hermit. Total annual precipitation is up 0.13”/decade since the beginning of the 20th century for Del Norte, which is statistically significant. The only season in which the increase in precipitation is significant is fall. Annual precipitation is down 0.34”/decade for Hermit, which is also significant. Decreases in annual precipitation for Hermit are primarily driven by change in springtime precipitation. There are no seasons of significant decrease for Saguache. Historic observed trends in precipitation are still relatively small in most cases when contrasted against year-to-year variability.
Seasonal peak snowpack trends were analyzed not though the USHCN stations, but through manual snow course measurements. While historic trends in seasonal peak snowpack are not yet statistically significant at 95% confidence or greater, there has not been an above average year for seasonal peak snowpack since 2010. This should be monitored closely in coming years.
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TABLE OF CONTENTS
EXECUTIVE SUMMARY…………………..………………………………………………………………………………………………………..2
TABLE OF CONTENTS……………………………………………………………………………………………………………………………….8
CHAPTER 1: HISTORIC TEMPERATURE OBSERVATIONS……………………………………………………………….……………9
CHAPTER 2: HISTORIC PRECIPITATION OBSERVATIONS…………………………………………………….…………..……….17
CHAPTER 3: HISTORIC SNOWFALL OBSERVATIONS.………………………………………………………..……………………..26
CHAPTER 4: HISTORIC SNOWPACK OBSERVATIONS…………………………………………………………………..…………..32
CHAPTER 5: HISTORIC WIND OBSERVATIONS…………………………………………………………………………………………35
CHAPTER 6: RECORDED WATER BALANCE EXTREMES…………………………………………………..……………………….41
CHAPTER 7: UNDERSTANDING A MOUNTAIN CLIMATE………………………………………………………………………….45
CHAPTER 8: RECORDED INDICATIONS OF CLIMATE CHANGE………………………………………………………………….52
CHAPTER 9: CURRENT DATA LIMITATIONS……………………………………………………………………………..……………..73
CONCLUSIONS……………………………………………………………………………………………………………………………………….74
REFERENCES………………………………………………………………………………………………………………………………………….76
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CHAPTER 1: HISTORIC TEMPERATURE OBSERVATIONS
Temperature Averages: The Rio Grande National Forest’s high elevation, interior continental positioning, and mid-latitude location lend itself well to large temperature swings both from day to night and from summer to winter. The mountainous landscape helps to drive sometimes large differences in temperature between high and low points in the Forest. Mean annual temperatures generally decrease consistently with elevation at a rate of roughly 3.5 degrees F/1000 ft of elevation (Lukas et al 2014). The spatial pattern in mean annual temperatures (figure 1.1) was analyzed for this study using 1981-2010 normals from the PRISM climate group (Daly 2016) where a normal refers to the average a 30-year record of continuous climate data for a given location (NCEI 2016). The mean annual temperature across the Forest was found to be cool. PRISM shows a temperature range, between 28 and 40 F over the 1981-2010 period, depending on location. The warmest areas are down in the San Luis Valley and the coolest temperatures are found in the high elevations on the eastern and western sides of the Forest. Mean winter temperatures (DJF) range from 14-24 F. Mean spring temperatures (MAM) range from 25- 40 F. Mean summer temperatures (JJA) range from 46-60 F. Mean fall temperatures (SON) range from 30-39 F.
Figure 1.1: The contour plot above depicts annual average temperature for south-central Colorado on a latitude- longitude plane. The Rio Grande National Forest is outlined in black. Data are provided at 4km resolution by the PRISM climate group at Oregon State for the 1981-2010 period of record.
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Maximum annual temperatures range from 40-58 F in the Rio Grande National Forest. Maximum temperatures vary more strongly with elevation than minimum temperatures. This is owing to the fact that mountain peaks, especially when absent of snow cover, attenuate the sun’s energy much more effectively than the surrounding free atmosphere at the same elevation. When the land heats up near mountain top it is easily replaced by cooler, less buoyant air. On a warm summer afternoon temperatures can decrease by as much as 5.4 degrees Fahrenheit/1000 ft of elevation gain (9.8 C/km). Average daily maximum winter temperatures (DJF) range from 23-35 F. Average daily maximum spring temperatures (MAM) range from 38-55 F. Average daily maximum summer temperatures (JJA) range from 68-78 F. Average daily maximum fall temperatures (SON) range from 43-57 F.
Figure 1.2: The contour plot above depicts annual average maximum daily temperature for south-central Colorado on a latitude-longitude plane. The Rio Grande National Forest is outlined in black. Data are provided at 4km resolution by the PRISM climate group at Oregon State for the 1981-2010 period of record.
Minimum temperatures in the Rio Grande National Forest averaged in the 16-30 degree Fahrenheit range depending on location between 1980 and 2010. Much like with maximum temperatures, on the Sangre de Cristo (east) side of the Rio Grande National Forest minimum temperatures still decrease rapidly with height. Cold air draining off of the mountains at night will spread out over the widest part of the San Luis Valley, and not create an inversion deep enough to cause temperatures to increase with height all the way up the slopes. On the San Juan (west) side there is less of an elevation-driven gradient. The land surface radiates energy away to space more efficiently at night than the free
10 atmosphere above it. This effect is most pronounced for snow-covered surfaces. As the air near the surface cools it becomes denser than the surrounding atmosphere and sinks. Because the western portion of the Rio Grande National Forest is surrounded by mountains on three sides the coolest of this air is effectively trapped in the high mountain valleys.
Average daily minimum winter temperatures (DJF) range from 0-13 F. Average daily minimum spring temperatures (MAM) range from 14-24 F. Average daily minimum summer temperatures (JJA) range from 33-44 F. Average daily minimum fall temperatures (SON) range from 19-30 F.
Figure 1.3: The contour plot above depicts annual average daily minimum temperature for south-central Colorado on a latitude-longitude plane. The Rio Grande National Forest is outlined in black. Data are provided at 4km resolution by the PRISM climate group at Oregon State for the 1981-2010 period of record.
The longest climate records come from National Weather Service Cooperative Observing Network in the Rio Grande National Forest. These stations are not only important to use in an historic climate assessment of the Forest because of their length of record, but also because these data are ground- truth weather observations. The stations of Del Norte, Hermit, and Wolf Creek Pass were used extensively in this study. Their locations are shown in figure 1.4. Records for these stations were obtained from the National Center for Environmental Information (NCEI 2016). These stations capture the climate representative of the San Luis Valley near the Forest, the high Rio Grande Valley within the Forest, and the Forest near mountain pass height respectively. The temperature data from weather
11 stations will be analyzed in two ways here: monthly climate normals are given for the 30-year period of 1981-2010. Then, for a closer look at the data, 15-day running averages are assessed using each station’s entire period of record. For Del Norte this record extends from 1893 to 2016. For Hermit the record is from 1923 to 2016. The Wolf Creek Pass record is shorter. It begins in 1958 and ends in 1986. The lack of recent data is far from ideal, but it is the best consistent climate temperature record in the Forest above 9000 ft available through NCEI.
In order to smooth day-to-day variability that is more stochastic in nature here we will examine monthly maximum and minimum temperature normals (figure 1.5). Monthly normals were compiled. Where it was necessary to have data at daily resolution, data for these stations were downloaded from the National Center for Environmental Information, and subject to quality checks from the Colorado Climate Center.
Figure 1.4: The image above depicts the locations of three Cooperative Observing Network stations used extensively in this study on a topographic map. The Del Norte station characterizes the climate of a low mountain valley, the Hermit station a high mountain valley, and Wolf Creek Pass, a mountain pass. The Rio Grande National Forest is outlined in black.
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For each of the three key Cooperative Observing Network stations the hottest month of the year on average is July, and the coldest month on average is January. For Del Norte, the low mountain valley station, the average July maximum daily temperature over the 1981-2010 period has been 77.0 F, and the average July minimum has been 45.8 F. The average maximum January temperature is 32.4 F, and the average minimum January temperature is a chilly 2.6 F. For Hermit, the high mountain valley station, the average July maximum temperature is 77.2 F. Maximum temperatures at Hermit are similar to Del Norte year-round, but July is one of two months where the average maximum temperature is higher at the Hermit station (figure 1.5). Average minimum temperature for the month of July in Hermit is 41.1. The average minimum temperature is cooler for Hermit than Del Norte every month of the year. The average January high at Hermit is below freezing, and comes in at 30.3 F. The average January minimum is a rather frigid -3.5. The Wolf Creek station up at mountain pass height exhibits less range in monthly temperature normals. The average July maximum temperature is 65.6 F. The average July minimum is 40.6. Wolf Creek average high temperatures are cooler than for Hermit and Del Norte in every month of the year. In January, the average maximum is 29.4 F. The average minimum, however, is warmer than both the expected low for Del Norte and Hermit, but still cold at 6.1 F. The average monthly minimum is warmer for Wolf Creek than Hermit from the months of October through March and warmer than Del Norte in December and January.
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Figure 1.5: The three subplots shown here illustrate the average maximum (red), minimum (blue), and mean (purple) daily temperature for each month of the year at three locations. These three locations include a low mountain valley (LMV) near the Forest (Del Norte), a high mountain valley (HMV) in the center of the Forest (Hermit), and a mountain pass (MP) on the southwestern edge of the Forest (Wolf Creek Pass). Data were computed using the station record from the National Center for Environmental Information.
Temperature Variability: Temperature is prone not only to wide variations in the Rio Grande National Forest based on location within the Forest and time of year, but also exudes marked year-to-year variations in temperature. Using data records once again from Del Norte, Hermit, and Wolf Creek Pass statistics were computed for the 15-day running average temperature for each day of the year. A 15-day running average was used because there is significant inter-monthly differences in the mean and variance of temperatures. Raw daily values were not used because in this case some of the variance can be attributed to random noise. For instance, knowing whether an extreme low temperature occurred on the 9th or 10th of December is interesting information, but not particularly useful when assessing climate averages. This smoothing method does not make a large difference when analyzing temperature statistics, but becomes a handy tool when considering precipitation.
Temperature variations are greater in the winter than in the summer, and are greater for minimum temperatures than for maximum temperatures. The range of observed 15-day running maximum temperatures for Del Norte goes from 65.5 to 88.3 F in July and from 11.2 to 55.6 F in January. In Hermit, this range is from 58.8 to 87.0 F in July and from 1.3 to 53.2 F in January. Wolf Creek Pass shows the smallest variation with an observed 15-day running temperature range from 53.7 to 75.7 F in July and from 8.0 to 51.3 F in January.
Minimum temperatures are more variable than maximum temperatures, especially in high mountain valleys where if winds stay high through the night minimum temperatures stay warmer, but with a snow-covered surface, a clear sky, and calm winds minimum temperatures can bomb. The observed range of 15-day running average minimum daily temperatures for Del Norte is from 38.1 to 56.1 F in July and from -19.2 to 27.2 F in January. This range goes from 26.3 to 50.6 F in July and from - 35.9 to 22.2 F in January for Hermit. Wolf Creek pass has an observed range from 28.5 to 47.9 F in July and from -17.8 to 21.0 F in January. Because of how dry the Forest is and because of its elevation it is able to consistently cool more efficiently at night than most of the rest of the United States and thus minimum temperatures are lower during the summer here than most locations across the US.
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Figure 1.6: The six-panel plot illustrated here depicts 15-day running average maximum (top) and minimum (bottom) temperatures for the three indicator COOP sites plotted in figure 1.4: Del Norte (left), Hermit (center), and Wolf Creek Pass (right). In the top three panels the average (black), maximum (red), and minimum (purple) 15-day running maximum temperature is plotted. In the bottom three panels the average (black), maximum (purple), and minimum (blue) 15-day running minimum temperature is plotted centered around every day of the year. Data were computed using the station record from the National Center for Environmental Information.
Frost Free Season: The length of frost free season was also analyzed for Del Norte and Hermit was analyzed for the 1985-2015 period of record. Because of the cool average temperatures and large diurnal temperature range in the San Luis Valley the Forest does not experience a lengthy frost free season. The average frost free season from 1985-2015 for Del Norte, which resides just outside the Forest, is 112 days. The average time frame between the last frost of the spring/summer and first frost of the summer/fall at the Hermit COOP station is a mere 52 days. For the sake of comparison, this is a substantially shorter frost free season than parts of the country that are traditionally considered cold such as Minneapolis, MN (175 days), Bismarck, ND (129 days), Glasgow, MT (124 days), and even Vail, CO (69 days). The number of consecutive frost free days during the warm season at Hermit has a standard deviation of 21 days. In some years there is only a very short frost free season. 2012 and 2014 are the longest frost free seasons on record at 91 days each.
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Figure 1.7: The plot shown here depicts the number of consecutive days between the last frost of the spring/summer, and first frost of summer/fall as a function of year for Del Norte (dark blue) and Hermit (light blue).
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CHAPTER 2: HISTORIC PRECIPITATION OBSERVATIONS
Precipitation Averages: Precipitation data were obtained for this study much in the same way as temperature. The pattern of spatial variation for the Rio Grande National Forest was captured using 4- km resolution reanalysis data from the PRISM climate group. In order to assess temporal variance and precipitation distribution ground truth Cooperative Observing Network data were obtained from NCEI. Ground truth high elevation precipitation data are available at higher elevation since the late 1970s. These data were incorporated in analysis as well. This section will feature data once again from the Del Norte, Hermit, and Wolf Creek Pass weather stations. It will also feature data from the Wolf Creek Summit, and Slumgullion Snowpack Telemetry stations. The Wolf Creek Summit and Wolf Creek Pass precipitation records were normalized against one another to allow for one complete precipitation record for the area from 1949 to 2016.
Like temperature, expected precipitation varies most obviously within the Rio Grande National Forest by elevation (figure 2.1). Higher elevation locations receive more precipitation than lower elevation areas. Unlike with temperature there are large variations in the amount of precipitation expected at a given elevation. This elevation-independent variability is highly dependent on which mountains air is raised over first when flowing across the Rio Grande National Forest, and whether the area is on the windward, or leeward side of the mountain peaks during a typical storm pattern.
In order to understand the preferred precipitation patterns seen in the Forest it is worth further exploring and explaining how precipitation is formed. Precipitation, regardless of whether it is a thunderstorm in the tropics or a blizzard in Siberia, is created by lifting a layer of air. When air is lifted, it must expand to equalize in pressure with its environment. Expansion of air takes work, and doing that work takes energy. Energy can neither be created, nor destroyed, so internal energy, which can be thought of as heat, is used. This makes the rising air cooler. Air rising and expanding in this manner will cool at a rate of 5.38 F/1000 ft (9.8 C/km) of elevation gain. As air cools its maximum potential capacity for water vapor decreases exponentially, so once the air has cooled sufficiently it will lose the capacity necessary to carry its current level of water vapor. When this happens, condensation must occur. The amount of cooling needed to catalyze condensation varies largely based on the temperature and vapor pressure of air before it is lifted. If air motion is vigorous enough precipitation will follow as condensation continues.
Now let’s get back to the Forest. There are three primary ways in which a layer of air can be lifted in the area: The ground may be heated sufficiently during the day such that air nearest the ground forms a warm bubble, or low density bubble, and rises. For an example of this, think of a summer afternoon thunderstorm. Another primary method of lifting air seen in the Rio Grande National Forest is lift along a frontal boundary. When air masses of highly contrasting temperature and moisture levels interact with one another, as during a cold frontal passage, air becomes stretched on the boundary between the two air masses. The warmer, moister air mass is lifted both through being stretched and through being replaced by cooler, denser air at the surface. Finally, when air crosses an orographic barrier such as a mountain, it must rise to overtake that barrier. This third lifting mechanism is the driver
17 behind the gradients in precipitation across the Rio Grande National Forest at a given elevation. In many instances the orographic lifting mechanism may combine with one or both of the other two mentioned.
Climatologically, air most often flows from west to east aloft. This gives the western slopes the first shot at accumulating precipitation by lifting air orographically. As a result, locations at high elevations on the west side of mountain ranges with no other mountains in front of the air’s path are preferred for maximum precipitation. This is why the mountains at the southwestern edge of the Forest receive the most precipitation annually.
Figure 2.1: The contour plot shown above illustrates the amount of precipitation (inches) expected annually for south-central Colorado. The Rio Grande National Forest is outlined in black. Data are provided at 4km resolution by the PRISM climate group at Oregon State for the 1981-2010 period of record.
PRISM 4km resolution climate normals show us how the very south and southwest fringes of the Forest benefit through the winter months with 10-15” of precipitation on average over the three-month climatological winter, December, January, and February (figure 2.2). Meanwhile, the lowest sections of the Rio Grande Valley within the Forest average fewer than two inches of precipitation over this same span. In spring precipitation totals in the valley remain low. Totals at higher elevation begin to taper as the polar jet retreats northward. Meteorologic summer (June, July, August) brings more total rainfall to the Forest than any other season as monsoonal moisture allows all locations of the Forest to average five or more inches of rainfall. In September and October precipitation may remain more evenly
18 distributed among high and low elevations. Once the cool season begins in earnest the mountain peaks and passes will again receive much more precipitation than the valleys.
Figure 2.2: The four-panel contour plot above shows the PRISM 4km-modeled precipitation for south-central Colorado for each of the four meteorologic seasons: winter (upper left), spring (upper right), summer (lower left), and fall (lower right). The Rio Grande National Forest is outlined in black. Precipitation averages here have been computed from the 1981-2010 period of record.
Average monthly precipitation was calculated for the Del Norte, Hermit, and Wolf Creek Pass Cooperative Observing Network stations for the years of 1981-2010. Annual average accumulations were calculated as well. In addition, 15-day running average precipitation was calculated for the entire period of record for Del Norte, Hermit, and Wolf Creek. Since the Wolf Creek Pass station’s record ended in 2001, the Wolf Creek Summit Snowpack Telemetry Station’s precipitation record was used to complete the dataset through present date. Precipitation from the Wolf Creek Pass and Wolf Creek Summit Stations were normalized against one another to produce a full record.
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For the Del Norte, and Hermit stations August is the wettest month of the year followed closely by July. These stations average 1.88” and 2.62” respectively in August, and average 1.56” and 2.19” respectively in July. Monthly totals for the high and low mountain valleys outside of the monsoon season (from November through June) are less than 1.00” on average. Mountain passes, such as Wolf Creek, benefit from both monsoonal flow and interaction with the Polar Jet. Wolf Creek average over three inches of precipitation in all months other than the brief dry season of May and June. The 1981- 2010 average accumulations for Del Norte, Hermit, and Wolf Creek are 10.56”, 14.14”, and 45.68”.
Figure 2.3: The plot above shows the average monthly precipitation totals (inches) for the Del Norte, Hermit, and Wolf Creek Pass Cooperative Observing Network Stations. Normals were calculated based on accumulations from 1981-2010.
Seasonally, there is a pronounced peak in expected precipitation for the valleys of the Rio Grande National Forest during the summer monsoon season. The only months of the year in which Del Norte 1981-2010 precipitaiton normals are over one inch areaverages over an inch of precipitation are July, August, and September with averages of 1.56, 1.88, and 1.18” respectively. In this season, air masses originating in the Gulf of Mexico with higher concentrations of water vapor are more frequently funneled into the region. This water vapor can be converted to precipitation in the valleys more easily during the summer as well. Ample sunshine interacts with prominent mountain peaks and creates warm bubbles of moist air to be sent skyward and rained out over both the peaks and valleys. In most other months of the year Del Norte averages 0.50-1.00” of precipitation. The driest season is mid-to-late winter. January and February precipitation averages are 0.39 and 0.36” respectively (figure 2.4). The seasonal cycle of precipitation for Hermit is similar to Del Norte. July and August average 2.19 and 2.62”
20 of precipitation respectively for Hermit. December and January average only 0.68 and 0.65”. Totals in the shoulder seasons do not scale linearly between the wet summer and dry winter. Early fall conditions may stay wet like the summer. Spring and late fall are dry like the winter.
In September and October daytime solar heating becomes less and less sufficient for thunderstorms, but as conditions get cooler cold air intrusions from the north and northwest become more frequent. This change in storm type favors increases in precipitation at high elevation, but decreases in precipitation in the mountain valleys. As a consequence of this, seasonal precipitation patterns look very different on the mountain peaks and passes than it does in the valleys. Wolf Creek Pass sees the benefit of both types of storms, and consistently averages between 3 and 4.5” of precipitation between July and March. May and June are the dry season here, and monthly average precipitation is below 2”. The magnitude of precipitation seen up near Wolf Creek Pass is unique to the south and southwest fringes of the Forest, but the seasonality of precipitation it experiences is not. Other mountain peak and mountain pass locations will dry out in the months of May and June, but see higher sustained precipitation averages from July through March. The Slumgullion Snowpack Telemetry weather station, which is located on Slumgullion pass on the northwestern side of the Forest, receives roughly half of the precipitation that Wolf Creek Pass does, but has a similar seasonal cycle (figure 2.2).
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Figure 2.4: The four-panel plot depicted above shows average 15-day running precipitation accumulations at Del Norte (upper left), Hermit (upper right), Wolf Creek Pass (lower left), and Slumgullion (lower right). For example, the point on the plot at July 8th in the lower right panel is showing the average accumulation for Slumgullion from July 1st through July 15th. Data for this plot come from the National Center for Environmental Information and the Snowpack Telemetry Network.
Precipitation Variability: Because not all stations have the same period of record, precipitation variability was measured over the 1980-2015 period of record when constructing the histograms seen in figure 2.5. The amount of precipitation received in any given year is highly variable as it depends on the storm tracks taken by a highly chaotic and dynamic atmosphere. Total variability in annual precipitation is greatest in the areas of the Forest that receive the largest amounts of precipitation climatologically. Conversely, precipitation varies most as a percent of normal in areas that receive less precipitation climatologically (figure 2.5). The low mountain valley of Del Norte, CO averages 9.37” of precipitation annually. The lowest year of precipitation for Del Norte, Colorado from 1980-2015 was 2002 with only 4.78” of accumulation. The highest year was 1985 with an accumulation of 15.67”. This total is still quite small when compared against any location in the eastern half of the United States. The high mountain valley where the Hermit station is situated receives an average of 14.74” when examining the entire historical record. The lowest year since 1980 was also 2002 with a total of 8.36”. The highest year was 1990 with an accumulation of 22.10”. Wolf Creek Pass receives much higher totals because it is in an ideal position for capturing precipitation. The lowest year on record likewise came from the bad drought year of 2002. This year produced an accumulation of 25.80”, which is still higher than any year on record for Hermit or Del Norte, but an incredible low anomaly by Wolf Creek standards. The highest year on record since 1980 was 1986 with a total of 59.47”.
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Figure 2.5: The three histograms shown here depict the number of years in which the annual precipitation accumulation total fell within a given range for Del Norte (left), Hermit (center), and Wolf Creek Pass (right). Each of the bars on the histograms have a width of 1.0”. For example, the highest bar on the histogram representing Del Norte indicates that in eight of the years of record annual precipitation measured between 11 and 12 inches.
Figure 2.6: The timeseries above shows the annual precipitation at the hybrid Wolf Creek Pass/Wolf Creek Summit Station from 1958-2015. This timeseries is simply another means of showcasing the year-to-year variability shown in figure 2.5. For Del Norte and Hermit timeseries see chapter 8.
Magnitude and seasonal timing of the largest 24 hour (24-hr) totals were analyzed for all years of record for the Del Norte (low mountain valley), Hermit (high mountain valley), and Wolf Creek Pass (mountain pass) stations. This is 1921-2015 for Del Norte, 1923-2015 for Hermit, and 1949-2015 for the Wolf Creek Pass – Wolf Creek Summit hybrid station. The Del Norte record does extend back to 1893, but there were too many missing data prior to 1921 to use the data for maximum 24-hr total analysis. The driest parts of the Rio Grande National Forest are not immune to large 24-hr precipitation totals. This is particularly true during the monsoon season in July through October. The average highest 24-hr total in a given year for Hermit since 1923 is 1.20”, which is just over 8% of the station’s annual expected precipitation. The median highest total is 1.01”, or 6.9% of the annual average. Up at Wolf Creek Pass the average highest 24-hr precipitation accumulation in a given year is 2.44”, or 5% of the annual average. The median highest 24-hr total is 2.29”, or 4.8% of the annual average. In Del Norte, just outside the Forest, the average highest 24-total in a given year is only 0.72”, but this is 8% of the annual average accumulation. The highest 24-hr total on record in Del Norte since 1921 is 2.55” on March 29th,
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1985. The highest 24-hr total on record for Hermit since 1922 is 3.05” on October 9th, 2005. The highest 24-hr total on record for Wolf Creek Pass since 1958 is 4.10” on December 21st, 1978. According to NOAA Atlas statistics (PF Data 2016) a once in ten year 24-hr rainfall event for Del Norte, Hermit, and Wolf Creek would be 1.21”, 2.05”, and 3.77” respectively.
Figure 2.7: The three histograms shown here depict the number of years in which the maximum 24-hr precipitation accumulation total fell within a given range for Del Norte (left), Hermit (center), and Wolf Creek Pass (right). Each of the bars on the histograms have a width of 0.25”. For example, the highest bar on the histogram representing Del Norte indicates that in 34 of the years of record the maximum 24-hr precipitation total measured was between 0.75 and 1.00”. Data are from the National Center for Environmental Information and the Snowpack Telemetry Network.
The time of year in which maximum annual 24-hr precipitation events occur varies markedly with elevation. Low mountain valley locations receive the vast majority of their largest annual 24-hr totals in the warm season from May to October. July carries the most weight in the distribution. Higher up in the Forest the distribution begins to shift, and July through December becomes the time of most likely occurrence. October carries the most weight in the distribution of any month. The least weight in the distribution is carried by late winter and spring. Up on Wolf Creek Pass there have only been two years since 1958 where the largest precipitation event of the year occurred between March and June. In most years it occurs between September and January. Here October carries the most weight in the distribution.
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Figure 2.8: The three histograms shown here depict the number of years in which the maximum 24-hr precipitation accumulation total occurred within a given month for Del Norte (left), Hermit (center), and Wolf Creek Pass (right). For example, the highest bar on the histogram representing Del Norte (left) indicates that in 16 of the years of record the maximum 24-hr precipitation total occurred in August.
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CHAPTER 3: HISTORIC SNOWFALL OBSERVATIONS
Historic snowfall observations are especially sparse in the Rio Grande National Forest. There is only one active Cooperative Observing Network station with snowfall records embedded within the Forest (Hermit) with two more just outside the Forest (Del Norte and Crestone). The Wolf Creek Pass station has snowfall data, but these data end in 1986. There are other Cooperative Observing Network stations in the Rio Grande National Forest. Locations include Creede and Rio Grande Reservoir, but none of these stations have over 30 years of complete snowfall data. Snowpack Telemetry stations have been beneficial for measuring winter precipitation, but these stations do not measure snowfall, only the liquid water equivalent of snowfall and liquid water equivalent of total snow depth (snowpack). To fill in these large data gaps snowfall estimates will be provided using 12km resolution North American Regional Reanalysis (NARR) data from the 1985-2014 time period. These data are output from numerical weather models, and are bias corrected using ground truth data where available.
Snow does not always fall with the same snow-to-liquid ratio. As temperatures become colder the amount of snowfall/unit liquid water content increases (Kyle and Wesley 1996). This is due to the fact that air saturates at exponentially lower vapor pressures as temperature decreases, so cold snows tend to produce drier flakes. These flakes allow for more air pocket space when accumulating. Thus accumulations with the same total amount of water content generally pile up higher in colder conditions. The average snow-to-liquid ratio for the Rio Grande National Forest area about 15:1 (Baxter 2005). This relationship is not constant with elevation, but for simplicity’s sake snowfall is estimated here using the mean amount of frozen precipitation from North American Regional Reanalysis for the Forest/year with the assumption that the ratio of 15:1 holds. This estimation method likely underestimates snowfall at high elevations by a small margin.
Seasonal average snowfall in the Forest is highest at high elevations along the southwest border. Annual averages taper quickly moving northward and eastward. The spatial accumulation pattern is nearly identical to the spatial accumulation pattern for annual precipitation both snow and liquid. At 12km resolution it is likely that snowfall totals over the high mountains of the Sangre de Cristos are underestimated. The Sangre de Cristos reach a maximum height of 14,335 feet, but no single gridspace has an average height above 12,000 feet at this resolution.
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Figure 3.1: The contour plot shown above illustrates the estimated amount of snowfall (inches) expected annually for south-central Colorado. The Rio Grande National Forest is outlined in black. Data are from North American Regional Reanalysis for the 1985-2014 period of record. Snowfall estimates were generated by multiplying NARR annual frozen precipitation estimates by a factor of 15.
In order to better understand the seasonality of snowfall in the Rio Grande National Forest monthly average snowfall was calculated for the Hermit, Del Norte, and Crestone stations (figure 3.2). Yearly 24-hr maximum snowfall events were analyzed for Del Norte, Hermit, and Wolf Creek Pass stations (figure 3.2).
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Figure 3.2: The image above depicts the locations of four Cooperative Observing Network stations used to illustrate the variability of snowfall both spatially and seasonally in the Rio Grande National Forest. The Forest is outlined in black.
Del Norte’s seasonal snowfall patterns reflect those of the lowest and driest areas in the Forest. Here the snowiest month of the year is March, which averages 9-10” of snowfall. All months between November and February average 5-7”. Snow has not been observed at Del Norte in the months of June through August. There have been three snowfall events recorded in September, the earliest being on September 27th in the year of 1936. The shoulder seasons of May and October occasionally see snow accumulation. The latest snowfall on record for Del Norte is May 27th. This occurred in 2009.
The Hermit Cooperative Observing Network station, which is ideally located to serve as a proxy for the high mountain valleys of the Rio Grande National Forest, has a remarkably consistent average snow season from December through April. During these months the station has historically averaged 8- 11” of snowfall/month (figure 3.3). The snowiest average month is March, but only by a narrow margin. October averages just over 4” of snowfall, and November averages 7-8”. May and September do receive snowfall, but these events are not common.
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The Crestone station, which sits at the base of the Sangre de Cristos on the east side of the Forest, is in a slightly more snowy location. Here three months of the year receive over 10” of snow accumulation on average; January, March, and April. November and February average 7-8”. October typically see over 3” of accumulation, and May over 2”.
Figure 3.3: The three histograms shown here depict the number of years in which the maximum 24-hr snowfall accumulation total occurred within a given month for Del Norte (left), Hermit (center), and Crestone (right). For example, the highest bar on the histogram representing Del Norte (left) indicates that in 9 of the years of record the maximum 24-hr snowfall accumulation occurred in March.
Annual maximum 24-hr snowfall totals at both the Del Norte and Hermit weather stations are typically somewhere between 6 and 12” (figure 3.4). The highest recorded 24-hr total is 15.4”. For the Wolf Creek Pass station the average annual 24-hr maximum snowfall event is much higher, 29.7”. The largest snowfall total recorded in a 24-hr period at this site is 55” on January 15th, 1997.
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Figure 3.4: The three histograms shown here depict the number of years in which the maximum 24-hr snowfall event fell within a given range for Del Norte (left), Hermit (center), and Wolf Creek Pass (right). Each of the bars on the histograms has a width of 2”. For example, the highest bar on the histogram representing Del Norte indicates that in 24 of the years of record the maximum 24-hr snowfall total measured was between 8 and 10”.
In order to better categorize the variability of snowfall in the Rio Grande National Forest the North American Regional Reanalysis (NARR) dataset was used once more. The average frozen precipitation accumulation for each tercile of the Forest as a function of elevation was computed. These totals were then ranked from lowest to highest and plotted for the years from 1985 to 2014 (figure 3.5). These data highlight the importance of the upper-most regions of the Rio Grande National Forest for snowpack and water supply. Not only does much more frozen precipitation fall in the highest elevation tercile, year-to-year variability is also greater. The lowest frozen precipitation accumulation total on record for high elevations was 9.48” (54 percent) or normal. This occurred in 2002. The highest frozen precipitation accumulation total for low elevations was 4.36” (192 percent of normal) in 1987. The highest frozen precipitation accumulation total for high elevations was 24.83” (140 percent of normal) in 1990. Middle elevations received anywhere from 4-12” of frozen precipitation/year over the span of 1985-2014.
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Figure 3.5: The three lines plotted above show the amount of frozen precipitation accumulation for each year from 1985-2014 ranked from driest to wettest. Frozen precipitation totals are averages of nine indicator grid spaces of approximately 12km resolution. The turquoise line labeled “low” shows annual frozen precipitation averaged among three low elevation grid spaces. The blue-green line labeled “medium” shows annual frozen precipitation averaged among three mid-range elevation grid spaces. The blue line labeled “high” shows annual frozen precipitation averaged among three high elevation grid spaces. Data are from North American Regional Reanalysis.
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CHAPTER 4: HISTORIC SNOWPACK OBSERVATIONS
Traditionally snowpack has been observed at snow courses. These are observation sites that are typically rather remote, and visited anywhere from once to several times a season. Observers arrive at scheduled intervals through the season to measure the volumetric water content of the existing snow cover. This is accomplished by excavating large cylindrical cores of snow from snow surface to ground level using a metal pipe. April 1st snowpack data were analyzed from four snow course sites within the Rio Grande National Forest that have reported from 1949 to present date. These sites include Cochetopa Pass, Santa Maria, Pool Table Mountain, and Wolf Creek Pass (figure 4.1).
Figure 4.1: The image above depicts the locations of four Snow Pack Telemetry Snow Survey sites used to illustrate the variability of snowpack both spatially and seasonally in the Rio Grande National Forest. The Forest is outlined in black.
Average April 1st snowpack based on the years of 1949-2014 for the sites shown in figure 4.2 is as follows: 5.71” for Cochetopa Pass, 5.16” for Pool Table Mountain, 3.65” for Santa Maria, and 31.12”
32 for Wolf Creek Pass. All sites other than Wolf Creek Pass have at least one year of record in which no measurable snowpack existed at the beginning of April. The lowest year for Wolf Creek was 9.90” of snowpack in 1977. The distribution of April 1st snowpack measurements from these four snow course sites reiterates two focal themes about the Rio Grande National Forest Climate: 1.The precipitation in the area is highly variable. 2. The southwest end of the Forest (near Wolf Creek Pass) is critical to the water supply of the Forest and downstream.
Figure 4.2: The four-panel plot illustrated here shows the April 1st measured snowpack totals from four snow survey sites within the Forest. All years from 1949-2014 have been ranked from lowest to highest. Snowpack is shown for Cochetopa Pass (upper left), Pool Table Mountain (upper right), Santa Maria (lower left), and Wolf Creek Pass (lower right)
On average, snowpack builds at a steady rate from late October through the month of March for the higher elevations of the Rio Grande National Forest. After March, snowpack begins to rapidly erode starting with the lowest elevations that typically receive snowpack. Higher elevations may continue to reliably see increases in snowpack until the month of May. Remaining seasonal snowpack will typically melt rapidly through the month of May and early June. In a season with high snowpack and below average spring temperatures, seasonal snowmelt may continue into the month of July.
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Figure 4.3: The timeseries above shows the amount of snowpack present at the Wolf Creek Summit SNOTEL station as a function of time. The three lines plotted depct the 1981-2010 median snowpack year (purple), the 1981-2010 mean snowpack year (blue), and the 2015-2016 snow year (green).
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CHAPTER 5: HISTORIC SURFACE WIND OBSERVATIONS
Observed weather balloon measurements taken by the National Weather Service show that prevailing winds in the Rio Grande National Forest at and above mountain top level come from the west. The evidence of this is not especially easy to see using surface stations because airflow fractures into smaller, weaker eddies near the ground surface much like at the edge of a stream. Mountains further complicate the breakdown of airflow near the land surface. The Remote Automated Weather Stations (RAWS) network has installed over 50 weather stations to monitor wind over western Colorado, which offers the best chance to catalog airflow patterns nearest the land surface in forested areas or over BLM rangelands. There are three stations in the Rio Grande National Forest: Blue Park, Big Horn, and Great Sand Dunes. The Blue Park and Big Horn station records go back to 1992 and 1993 respectively. The Great Sand Dunes station only has a data record extending back to 2004.
Figure 5.1: The image above depicts the locations of three Remote Automated Weather Stations in and around the Rio Grande National Forest. The Forest is outlined in black.
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All three of the RAWS stations in the Rio Grande National Forest show a strong preference for winds blowing out of the west during the daytime. Nighttime winds exhibit a much different relationship. For the Blue Park station, nighttime winds tend to come out of the northeast. For the Bighorn station, nighttime winds preferentially blow out of the southwest. For the Great Sand Dunes nocturnal winds typically come from the southeast. This may seems confusing, but nocturnal winds from these three stations share an important common factor: they all are blowing down off of the highest nearby topographic surface. For Blue Park these winds come off of Pool Table Mountain. For Bighorn nocturnal winds are blowing down from Black Mountain and Pinorealosa Mountain. For Great Sand Dunes nocturnal winds are blowing down off of the high peaks of the Sangre de Cristos where Blanca Peak and the North Zapata Ridge are located. Surface wind speeds tend to be faster during the day than at night. Wind patterns are only shown for Blue Park in this document for the sake of saving space.
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Figure 5.2: The image above is a wind rose for the Blue Park, CO RAWS station in the Rio Grande National Forest for the month of January during day hours. A wind rose illustrates the probability of wind coming from any given direction. Each set of boxes protruding from the midpoint of the figure represents all wind coming from within plus or minus 11.25 degrees of x-direction. Each concentric circle moving out from the middle represents increased probability of wind coming from x-direction. For example, this figure shows that there is between a 20 and 24% chance that at any given time during the daytime in January that winds will be blowing within plus or minus 11.25 degrees of straight west (270 degrees). The color-coded boxes represent increasing wind speed ranges. The longer a box is, the greater the probability that the observed wind speed is within that range.
Figure 5.3: The image above is a wind rose for the Blue Park, CO RAWS station in the Rio Grande National Forest for the month of January during night hours. A wind rose illustrates the probability of wind coming from any given direction. Each set of boxes protruding from the midpoint of the figure represents all wind coming from within plus
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or minus 11.25 degrees of x-direction. Each concentric circle moving out from the middle represents increased probability of wind coming from x-direction. For example, this figure shows that there is a slightly greater than 6% chance that at any given time during the nighttime in January that winds will be blowing within plus or minus 11.25 degrees of straight west (270 degrees). The color-coded boxes represent increasing wind speed ranges. The longer a box is, the greater the probability that the observed wind speed is within that range.
Figure 5.4: The image above is a wind rose for the Blue Park, CO RAWS station in the Rio Grande National Forest for the month of July during day hours. A wind rose illustrates the probability of wind coming from any given direction. Each set of boxes protruding from the midpoint of the figure represents all wind coming from within plus or minus 11.25 degrees of x-direction. Each concentric circle moving out from the middle represents increased probability of
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wind coming from x-direction. For example, this figure shows that there is between and eight and 10% chance that at any given time during the daytime in July that winds will be blowing within plus or minus 11.25 degrees of straight west (270 degrees). The color-coded boxes represent increasing wind speed ranges. The longer a box is, the greater the probability that the observed wind speed is within that range.
Figure 5.5: The image above is a wind rose for the Blue Park, CO RAWS station in the Rio Grande National Forest for the month of July during night hours. A wind rose illustrates the probability of wind coming from any given direction. Each set of boxes protruding from the midpoint of the figure represents all wind coming from within plus or minus 11.25 degrees of x-direction. Each concentric circle moving out from the middle represents increased probability of wind coming from x-direction. For example, this figure shows that there is a slightly greater than 6%
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chance that at any given time during the nighttime in January that winds will be blowing within plus or minus 11.25 degrees of straight east (90 degrees). The color-coded boxes represent increasing wind speed ranges. The longer a box is, the greater the probability that the observed wind speed is within that range.
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CHAPTER 6: RECORDED WATER BALANCE EXTREMES
Extreme Snowfall: The southwest end of the Rio Grande National Forest is well-situated for occasionally receiving very large snowfall totals. In the 1978-79 snow season Wolf Creek Pass accumulated a total of 837.5” of snowfall, and recorded a maximum snow depth of 251” on March 31st (Doesken 2005). Over its 1958-1986 tenure as a cooperative observing network station, Wolf Creek Pass recorded over three feet of snow in a 24-hr period a total of eight times. The maximum total ever recorded in a 24-hr period was 55”. While actual snowfall measurements are sparse it is likely that similar totals have occurred at other locations along the Continental Divide on the southwest side of the Forest.
Figure 6.1: The image above shows the location at which the seasonal snow total of 837.5” was measured.
Floods: Occurrence of extreme, short-duration precipitation events is less common in the Rio Grande National Forest than many other parts of Colorado (McKee and Doesken 1977). The forest is also less prone to spring flooding caused by heavy precipitation falling on top of large amounts of melting snow than other places in Colorado. This is due to the climatologically-low precipitation totals experienced in south-central Colorado in the months of May and June. Peak flow occurs when seasonal precipitation is at a minimum (figure 6.2). By contrast, these are the wettest months of the year in northeast Colorado and the Urban Corridor.
The highest daily average flow recorded on the Rio Grande at Del Norte (immediately downstream of the Forest) occurred in October of 1911. Daily flow on October 8th of 1911 averaged
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14,000 cubic ft/second. The second highest flow occurred in late June of 1927. Daily flow averaged over 12,000 cubic ft/second at Del Norte on this occasion. The flooding of the summer of 1927 was due to rapid snowmelt. It was a more severe flooding event for most of the San Luis Valley than October of 1911, and persisted for a longer period (Follansbee and Sawyer 1948). The streamflow total of the last 50 years at Del Norte occurred in June of 1985, and peaked at a daily average of just under 9,000 cubic ft/second.
Figure 6.2: The plot above shows the average (black), highest (blue), and lowest (red) 15-day averaged streamflows for the Rio Grande at Del Norte from 1901-2015.
Drought: The Forest can on occasion suffer from prolonged periods of below average surface water balance. The most severe such period occurred in 2001-2003. The Forest has been in long-term drought more recently as well from 2011-2013.
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Figure 6.3:The map of Colorado given in the figure above indicates the standing drought classifications as of August 30th, 2011. 20-30th percentile wetness is shown as D0 (yellow). 10-20th percentile wetness is shown as D1 (tan). 5- 10th percentile wetness is shown as D2 (orange). 2-5th percentile wetness is shown as D3 (red). 0-2nd percentile wetness is shown as D4 (dark red). Drought classifications are based on a seasonal blend of indicators such as precipitation, evapotranspiration, snowpack, soil moisture, streamflow, and recorded drought impacts.
Dry spells farther south along the Rio Grande have been shown to correlate with periods of La Niña (Scurlock 1998). In the Rio Grande National Forest near the headwaters of the river this is not exactly the case. The region is slightly favored for wetter conditions during El Niño, but the widely-known climate phenomenon only explains 5% of the variance in the Palmer Drought Severity Index over the region. Major droughts have occurred in ENSO-neutral to slightly ENSO-positive conditions. The super El Niño events from the last 20 years (1997 and 2015) have been associated with wetter than average conditions (figure 6.x). Due to sample size this relationship should not necessarily be expected to hold for every future super El Niño.
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Figure 6.4: The two plots above show the El Niño Southern Oscillation Multivariate Index (blue), and Modified Palmer Drought Severity Index (red) for the San Juans and Uncompahgre Plateau of Colorado.
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CHAPTER 7: UNDERSTANDING A MOUNTAIN CLIMATE
Humidity: In comparison with major United States population hubs, air in the Rio Grande National Forest is low in moisture content year-round (figure 7.1). A study of figure 7.1 shows that for both the Forest and the areas around the country used to draw a comparison, atmospheric water vapor is highest during the summer and lowest during the winter. This is a direct consequence of the fact that air can hold exponentially more water vapor at warmer temperatures.
Figure 7.1: The plot above shows the average monthly atmospheric water vapor pressure for various locations around the United States. Data provided here are from North American Regional Reanalysis and cover the 1985- 2014 time frame. Vapor pressure is given in millimeters of mercury. The average sea-level atmospheric pressure is 760 millimeters of mercury.
Unlike other locations shown in figure 7.1, the Forest air stays dry through the summer. The intercontinental positioning, local topographic features, and the high elevation of the Forest play critical roles in keeping the air relatively dry year-round. Water vapor tends to be highest near major source regions. Major source regions of water vapor are large, warm bodies of water such as tropical oceans and seas, and in some cases, regions of warm air with wet near-surface soils. The sun’s energy can be used to evaporate large amounts of water and sometimes saturate the air in these regions. The Forest neither fits the description of a water vapor source region, nor is it close to a water vapor source region.
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Air that is moist at least in a sense relative to the Forest may be drawn in from the subtropical Pacific or from the Gulf of Mexico, particularly during monsoon season.
Cold Air Pooling: As discussed in chapter 1, minimum temperatures in the mountain valleys of the Rio Grande National Forest can become extremely cold. Minimum temperatures may reach levels lower than -30 F in the winter. Snow-covered surfaces effectively radiate away energy on clear, calm winter nights. As energy radiates away the near-surface atmosphere cools. The coldest of air becomes the densest, and drains down-gradient into mountain valleys. A temperature inversion, which is an environment in which temperature increases with increasing height, forms. The height of these inversions builds to the height of the ridge tops (Whiteman 1982). These inversions are generally strongest near sunrise. After sunrise it takes 3-5 hours for a mountain valley inversion to erode; mix out (Whiteman 1982). This amount of time will vary in part as a function of inversion depth, and in part as a function of season. Wintertime inversions generally take more time to mix out than summer inversions.
Figure 7.2: The two-panel cartoon above depicts the anticipated airflow pattern generated on cool, clear nights over snow-covered surfaces. Panel 1 (left) shows three parcels of atmosphere outlined with white, dashed circles at equal elevation at 4:00 PM. Panel 2 (right) shows the location of these three parcels of atmosphere by 3:00 AM. The size of the cartoon circles is inversely proportional to their density, or directly proportional to their specific volume.
Afternoon Thunderstorm Cycle: Much like the way mountain airflow can be set to drain downslope by cooling the surface, it can be forced upslope by warming the surface. The diurnal thunderstorm cycle over the mountains of Colorado is outlined in detail by Robert Banta 1984. The process is outlined here in more simplistic terms.
Pooling of cold air in mountain valleys is strongest in cold, snow-covered situations as discussed in the section above. However, the coolest, densest air also settles in valleys on clear, calm summer nights. In the early morning the atmosphere will generally be most strongly stratified according to density. This is depicted for an approximate time of 5:30 AM upper left panel of figure 7.3.
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Throughout the morning the land surface is warmed by solar energy. The land surface absorbs sunlight much more effectively than free atmosphere above it. This warms the air nearest the ground preferentially. Air residing on mountain slopes heats up and becomes less dense than air at the same elevation out over the plains and valleys. Some of the sunlight that reaches the top of the atmosphere is either absorbed or reflected by the atmosphere before reaching the ground. Consequentially the solar energy that impinges on the earth’s surface is more intense at higher elevations. A difference between temperature (density) of elevated air near a mountain surface vs temperature (density) of elevated air over the plains and valleys develops most quickly for the highest terrain. This phenomenon is represented in the upper-right panel of figure 7.3.
Once this warm bubble of air is created over the mountain peaks it will begin to rise. On a typical thunderstorm-producing day, air will have begun to rise off of the peaks by solar noon (1:00 PM during daylight savings). As the air rises it cools, and water vapor is condensed. Towering cumulus clouds form over the mountain peaks. These clouds are advected off-center from the mountain peaks in the direction of prevailing upper atmospheric flow. Airflow sweeps in from the valleys and plains to replace warm bubbles of air rising off the mountain peaks. A circulation has been developed (figure 7.3 lower- left). In the Forest, the lee (east) side of the San Juans serves as the primary genesis zone for thunderstorms (Banta 1987).
If moisture is sufficient within the thunderheads, water droplets become large and heavy and fall as rain. Evaporation from rainfall cools the air. Cooler air is denser and tends to sink, so downdrafts develop where the rain is falling and spreads across the valleys and plains (figure 7.3 lower-right). Thunderstorm activity in southern Colorado peaks between 3:00 and 5:00 PM (Easterling and Robinson 1985).
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Figure 7.3: The four-panel cartoon above shows the expected evolution of wind, clouds, and precipitation development on a day when a typical summertime afternoon thunderstorm occurs. Snapshots of this development are shown for 5:00 AM (upper left), 11:00 AM (upper right), 1:00 PM (lower left), and 4:00 PM (lower right). The yellow arrows represent solar energy impinging on the land surface. Arrow thickness is proportional to the intensity of this energy. White arrows represent airflow. Black dashed circles represent parcels of atmosphere. To track the flow of a parcel one may track a number from panel to panel. The size of each circle is directly proportional to its specific volume (volume divided by mass). Circles shaded in light gray represent a saturated atmosphere. Circles shaded in dark gray represent a saturated and precipitating atmosphere.
Lightning: With the development of afternoon thunderstorms comes the potential for lightning. For the most part, the Rio Grande National Forest experiences fewer lightning strikes than surrounding areas of Colorado. The Forest averages between one and two lightning flashes/square kilometer in a year (figure 7.4) (Hodanish 2011). In general, lightning strikes are more frequent at higher elevations. More lightning strikes are recorded along the southern and western edge of the Forest than anywhere else, one of the
48 thunderstorm source regions in Colorado established in Banta 1987. There is only one recorded lightning fatality in the Forest.
Figure 7.4: The map above marks the density of lightning strikes across the state of Colorado (Hodanish 2011).
While the Rio Grande National Forest may not be a hot bed for lightning strikes it is still important for outdoor recreationalists who seek out the Forest to be aware of general lightning safety guidelines. This is especially true during the monsoon season when afternoon thunderstorms are most frequent. When thunderstorms occur, seek the shelter of a building or an automobile. If this is not an option, seek out heavily wooded areas for shelter. It is particularly hazardous to be above treeline in situations where clouds are developing vertically. If thunderheads begin to develop, hike down.
Snowfall and Snowpack Patterns : Snowpackduring the cold season may differ considerably on scales as fine as acres., a scale much smaller than what has been consistently measured or modeled. Much like cold air pooling and afternoon thunderstorm development these patterns are the result of interaction between prevailing airflow and mountainous terrain. There are several drivers of fine-scale snowpack variability to be considered. Firstly, snowpack will build more easily on north-facing slopes than south- facing slopes. South-facing slopes receive considerably more sunlight than north-facing slopes in the winter. In winter the sun hangs low in the southern sky. Consider the sun’s location on the winter
49 solstice at noon. On the winter solstice the earth is tilted 23.5 degrees away from the sun. Therefore at a location 37.5 degrees north of the equator, such as the Forest, the sun hits the earth at an angle that is a minimum of 61 degrees from directly overhead (at noon). Solar energy penetrating at this angle will have only 48% of the intensity of direct sunlight. Now consider a north and south-facing mountain ridge with an elevation gradient of 10 degrees on both sides (figure 7.5). The slope on the south side would receive sunlight at an angle of 51 degrees from overhead, or 63% of full intensity. The slope on the north side would receive sunlight at an angle of 71 degrees from overhead, or 33% of full intensity. Snowfall therefore melts much more rapidly during periods of clear weather in the cold season on south-facing slopes.
Figure 7.5: The cartoon above snows a mountain ridgeline on a clear winter day. The south face is marked “S” and the north face is marked “N.” The yellow arrows indicate direction of sunlight. White lines on the surface of the ridgeline represent what may be a typical wintertime snowpack pattern following a spell of clear weather.
Snowpack may also vary from one side of a mountain peak to the other as a result of the direction of prevailing winds during snowfall. In a broader spatial sense, snowfall is greater on the windward side of mountain ranges, but when examining the tops of individual hills more snowfall will actually accumulate on the downwind side (figure 7.6). Snow falling on the upwind side of the mountain will often be windswept over the crest of the mountain and settle in an eddy on the downwind side.
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Figure 7.6: The cartoon above snows a mountain ridgeline on a snowy winter day where winds are blowing from the west. The west face is marked “W” and the east face is marked “E.” The white arrows indicate direction of airflow. White lines on the surface of the ridgeline represent what may be a typical wintertime snowfall accumulation pattern.
Vegetation differences may impact snowpack on small scales as well. Heavily wooded areas can intercept horizontally-blowing snow, and reduce near-surface wind speeds, which improves conditions for falling snow to settle. Wooded areas are also more insolated on clear, cool evenings, which may increase melt rates at times.
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CHAPTER 8: RECORDED INDICATIONS OF CLIMATE CHANGE
Temperature and Precipitation: The Rio Grande National Forest is disadvantaged with only a very limited amount of historic climate measurements to use in tracking observed changes in the climate to date. There is only one weather station that is a part of the United States Historical Climatology Network (USHCN) within the Forest itself. This station is called Hermit. It is positioned in the middle of the Rio Grande Valley 9 miles east northeast of the mouth of the Rio Grande Reservoir. The nearest USHCN stations not within the Forest boundary are Telluride to the northwest, and Saguache, Del Norte, which the Forest surrounds on three sides, and Manassa to the southeast. Del Norte also sits within a mile of the Rio Grande, and is fewer than five miles from the National Forest by closest approach. The Del Norte, Hermit, and Saguache stations were carefully quality checked and bias corrected, and serve as the three main stations for tracking historical temperature and precipitation trends in the Rio Grande National Forest since the 1900s, 1950s, and 1980s. The Colorado Climate Center did make one data correction to the Hermit station for the spring of 1921. Spring precipitation for Hermit clearly needed additional quality control as the USHCN data provided were erroneously high. 1921 spring precipitation for Hermit is approximated as being equal to the station’s mean precipitation over the entire 1900-2015 time series. USHCN data were not used in previous sections of text as they are available at only monthly and yearly resolution, but not daily.
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Figure 8.1: The image above is a map of southern Colorado. The Rio Grande National Forest is outlined in black. The three UHCN bias corrected stations used in this trend analysis study are marked by black dots.
Trends in maximum temperature, minimum temperature and precipitation were measured for each of these three stations. Comparisons were made between current levels (2005-2014) and 1900- 1909, 1950-1959, and 1980-1989 levels. Statistical significance of trends was assessed for each station using a Mann-Kendall test for monotonic increases or decreases. This is a test commonly employed by the National Center for Atmospheric Research (The Climate Data Guide). A Mann-Kendall test for significance checks the sign of one observation minus all of the observations preceding it individually. If there are enough more positive changes with time than negative changes for the given sample size (in this case, the number of years) then the trend will be identified as significantly positive. Mathematically, it can be written as follows:
= 𝑛𝑛−1 𝑛𝑛 ( )
𝑆𝑆 � � 𝑠𝑠𝑠𝑠𝑠𝑠 𝑥𝑥𝑗𝑗 − 𝑥𝑥𝑘𝑘 𝑘𝑘−1 𝑗𝑗−𝑘𝑘+1
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Here the S represents the net amount of positive changes from the jth to the kth observation, the nth year is the final year in the time series, x is the array of observations (be it temperature or precipitation) being analyzed, and the jth and kth observations are the two observations currently being compared in the summation.
There are a few important points to note if using a summary of statistically significant (or insignificant) climate trends for decision making purposes. Firstly, the magnitude of a trend and significance of a trend are not directly comparable. The Saguache weather station shows a greater observed increase in maximum daily temperatures between 1980-1989 levels and present-day levels than between 1900-1909 levels and present day levels. However, because there are more years of data between 1900 and present day there is a greater degree of statistical confidence that the overall trend from 1900-present is not a random occurrence. Secondly, significance is being analyzed for more than one station, at all seasons of the year, and on more than one timescale. If all data used in this analysis were replaced with random data it is a near statistical certainty that some trends would appear significant with at least 95% confidence. When trends are cohesive for either a given season or the annual mean between different weather stations and on different timescales they should bear more weight in any decision-making process.
Del Norte: Annual precipitation at Del Norte has increased by an average of 0.13”/decade over 1900- 1909 levels. While this is a statistically significant increase at 99% confidence, it is still a small value with respect to the year-to-year variability that has been observed in annual precipitation. Owing to some anomalously dry years since 2009, the annual precipitation at Del Norte has fallen by 1.06”/decade since the 1980s. This decrease is also significant at 99% confidence. Maximum temperature increases since both 1901-1910 levels, and from the 1980s to present date are statistically significant at 95% confidence. Del Norte maximum daily temperatures have risen at an average rate of 0.67 F/decade since the 1980s. Minimum temperatures have also increased since the 1900s and 1980s, but not enough to qualify as statistically significant at 95% confidence.
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Figure 8.2: The timeseries above show bias corrected annual average precipitation (top), maximum temperature (middle), and minimum temperature (bottom) data for the Hermit Cooperative Observing Network weather station. Annual totals are given by colored lines, and decadal averages are given by black lines.
The annual precipitation trend at Del Norte is significantly positive at 99% confidence. Breaking the seasons down into winter (DJF), spring (MAM), summer (JJA), and fall (SON), no seasons stand out as significant at such a high confidence level. Summer, which is the wet season at Del Norte, shows no decadal trend in precipitation from 1900-1909 levels. Since the 1980s precipitation has been trending downwards at Del Norte in all seasons except winter. The decreases of -0.47”/decade in summer and 1.06”/decade annually are significant at 95% confidence (table 8.1). Precipitation over the past decade is down 2.54” since the 1980s, which represents a 22% decrease from 1980s levels. This trend is worrying, but not cohesive across longer timescales.
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Figure 8.3: The four-panel timeseries plot above depicts seasonal precipitation for the Del Norte Cooperative Observing network station. Seasonal totals are given for every year from 1900-2014. Totals are displayed for winter (top left), spring (top right), summer (bottom left), and fall (bottom right).Yearly totals are displayed in green. Decadal averages are displayed in black.
Table 8.1: The table shown here reveals the decadal average trend in precipitation for the Del Norte USHCN bias corrected station between 1900 and 2014 (row 1), 1950 and 2014 (row 2), and 1980 and 2014 (row 3). Trends are given for each meteorologic season: Winter (DJF), spring (MAM), summer (JJA), and fall (SON) as well as the annual trend. Statistically significant trends are indicated according to shading. Significant increase at 95% confidence is given in light green. Significant increase at 99% confidence is given in dark green. Significant decrease at 95% confidence is given in light yellow (no example here). Significant decrease at 99% confidence is given in dark yellow.
Increases in maximum daily temperatures for Del Norte are significant for both winter and summer at 99% confidence. This signal is cohesive across timescales going back to the 1980s, 1950s, and 1900s.
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Winter maximum daily temperatures, however, have gotten colder. The magnitude of winter cooling since 1900 is comparable to the magnitude of spring and summer warming. Because winter maximum temperatures are by nature more variable on year-to-year timescales these decreases are not considered statistically significant using a Mann-Kendall test. Annual maximum temperatures are up 1.7 Fahrenheit since the 1980s, but only 1.2 F since the 1900s.
Figure 8.4: The four-panel timeseries plot above depicts seasonal average daily maximum temperature for the Del Norte Cooperative Observing network station. Seasonal totals are given for every year from 1900-2014. Averages are displayed for winter (top left), spring (top right), summer (bottom left), and fall (bottom right). Average seasonal maximums are displayed in red. Decadal averages are displayed in black.
Table 8.2: The table shown here reveals the decadal average trend in maximum daily temperatures for the Del Norte USHCN bias corrected station between 1900 and 2014 (row 1), 1950 and 2014 (row 2), and 1980 and 2014
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(row 3). Increases are given for each meteorologic season: Winter (DJF), spring (MAM), summer (JJA), and fall (SON) as well as the annual trend. Statistically significant trends are indicated according to shading. Significant increase at 95% confidence is given in light red. Significant increase at 99% confidence is given in dark red. Significant decrease at 95% confidence is given in light blue. Significant decrease at 99% confidence is given in dark blue (no example here).
Minimum daily temperatures have increased for Del Norte for spring, summer, and fall across all timescales. These increases are statistically significant with at least 95% confidence for the spring and summer going back to the 1980s and 1950s. Trends dating back to the 1900s are positive, but not statistically significant. As is the case with daily maximum temperatures, daily minimum winter temperatures have decreased for Del Norte since the 1900s, 1950s, and 1980s.
Figure 8.5: The four-panel timeseries plot above depicts seasonal average daily minimum temperature for the Del Norte Cooperative Observing network station. Seasonal totals are given for every year from 1900-2014. Averages are displayed for winter (top left), spring (top right), summer (bottom left), and fall (bottom right). Averages seasonal minimums are displayed in blue. Decadal averages are displayed in black.
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Table 8.3: The table shown here reveals the decadal average trend in minimum daily temperatures for the Del Norte USHCN bias corrected station between 1900 and 2014 (row 1), 1950 and 2014 (row 2), and 1980 and 2014 (row 3). Trends are given for each meteorologic season: Winter (DJF), spring (MAM), summer (JJA), and fall (SON) as well as the annual trend. Statistically significant trends are indicated according to shading. Significant increase at 95% confidence is given in light red. Significant increase at 99% confidence is given in dark red. Significant decrease at 95% confidence is given in light blue (no example here). Significant decrease at 99% confidence is given in dark blue (no example here).
Hermit: Annual average precipitation at the Hermit station is down 3.57” from 1900-1910 levels. This represents a 21% decrease in annual precipitation. This decrease is statistically significant at 99% confidence. Both maximum and minimum daily temperatures have risen at the Hermit USHCN station as well. Maximum daily temperatures are only up 0.07 F/decade since the 1900s, which is not a statistically significant trend. Minimum daily temperatures, however, are up 0.39 F/decade from 1900-1910 levels. This is a statistically significant increase at 99% confidence. Declines in precipitation at Hermit have been heavily weighted towards the first half of the past century. Maximum temperature increases have been stronger since the 1980s than previous periods. Minimum temperature increases have been rather consistent since the 1900s.
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Figure 8.6: The timeseries above show bias corrected annual average precipitation (top), maximum temperature (middle), and minimum temperature (bottom) data for the Hermit Cooperative Observing Network weather station. Annual totals are given by colored lines, and decadal averages are given by black lines.
Seasonal precipitation trends have yo-yoed over the past century for the Hermit station in the Upper Rio Grande Valley. Spring has been the one season with a consistent trend. Spring precipitation has consistently decreased since the early 1900s, 1950s, and 1980s to present levels. This trend is significantly negative at 99% confidence across timescales. The annual average precipitation is just over 17”. The average summer precipitation from 2005-2014 is 1.7” lower than the average summer precipitation from 1980-1989. Winter precipitation has increased, but not by significant margin.
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Figure 8.7: The four-panel timeseries plot above depicts seasonal precipitation for the Hermit Cooperative Observing network station. Seasonal totals are given for every year from 1900-2014. Totals are displayed for winter (top left), spring (top right), summer (bottom left), and fall (bottom right).Yearly totals are displayed in green. Decadal averages are displayed in black.
Table 8.4: The table shown here reveals the decadal average trend in precipitation for the Hermit USHCN bias corrected station between 1900 and 2014 (row 1), 1950 and 2014 (row 2), and 1980 and 2014 (row 3). Trends are given for each meteorologic season: Winter (DJF), spring (MAM), summer (JJA), and fall (SON) as well as the annual trend. Statistically significant trends are indicated according to shading. Significant increase at 95% confidence is given in light green (no example here). Significant increase at 99% confidence is given in dark green (no example here). Significant decrease at 95% confidence is given in light yellow. Significant decrease at 99% confidence is given in dark yellow.
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Maximum daily temperature trends were either significant at very high confidence (99%), or not significant at all. Spring and summer temperatures have increased from 1900s, 1950s, and 1980s levels. Winter and spring temperature variability has been higher in recent years. Temperatures for these seasons hit a century-long low in the 1980s, but rebounded to a century-long high in the early 2000s. Summer maximum temperatures have shown the most consistent increases through the course of the century at Hermit. Daily average maximum summer temperatures have increased by 1.9 F since the beginning of the century. All USHCN stations are quality checked, but the Colorado Climate Center does have some concerns with the Hermit station’s heterogeneity in weather observers participating and thermometers used over the 1980s and 90s.
Figure 8.8: The four-panel timeseries plot above depicts seasonal average daily maximum temperature for the Hermit Cooperative Observing network station. Seasonal totals are given for every year from 1900-2014. Seasonal averages are displayed for winter (top left), spring (top right), summer (bottom left), and fall (bottom right).Yearly averages are displayed in red. Decadal averages for each season are displayed in black.
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Table 8.5: The table shown here reveals the decadal average trend in maximum daily temperatures for the Hermit USHCN bias corrected station between 1900 and 2014 (row 1), 1950 and 2014 (row 2), and 1980 and 2014 (row 3). Increases are given for each meteorologic season: Winter (DJF), spring (MAM), summer (JJA), and fall (SON) as well as the annual trend. Statistically significant trends are indicated according to shading. Significant increase at 95% confidence is given in light red (no example here). Significant increase at 99% confidence is given in dark red. Significant decrease at 95% confidence is given in light blue (no example here). Significant decrease at 99% confidence is given in dark blue (no example here).
Minimum daily temperature increases at Hermit are cohesive across seasons and timescales. Daily average minimum temperatures over the 2005-2014 decade are 4.1 F higher than 1900-1909 levels, 1.9 F higher than 1950-1959 levels, and 1.4 F higher than 1980-1989 levels. The season showing the largest minimum daily temperature trends in the historic record is spring. Spring temperatures are up 4.8 F over 1900-1909 levels. Daily minimum summer temperatures have decreased since the 1980s, but the trend is not significant.
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Figure 8.9: The four-panel timeseries plot above depicts seasonal average daily minimum temperature for the Hermit Cooperative Observing network station. Seasonal totals are given for every year from 1900-2014. Seasonal averages are displayed for winter (top left), spring (top right), summer (bottom left), and fall (bottom right).Yearly averages are displayed in blue. Decadal averages for each season are displayed in black.
Table 8.3: The table shown here reveals the decadal average trend in minimum daily temperatures for the Hermit USHCN bias corrected station between 1900 and 2014 (row 1), 1950 and 2014 (row 2), and 1980 and 2014 (row 3). Trends are given for each meteorologic season: Winter (DJF), spring (MAM), summer (JJA), and fall (SON) as well as the annual trend. Statistically significant trends are indicated according to shading. Significant increase at 95% confidence is given in light red. Significant increase at 99% confidence is given in dark red. Significant decrease at 95% confidence is given in light blue (no example here). Significant decrease at 99% confidence is given in dark blue (no example here).
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Saguache: Both annual precipitation and annual minimum temperatures for Saguache have not undergone significant changes over the last century. Daily maximum temperatures, however, have increased with a high level of statistical significance. Increases in maximum daily temperature have accelerated since the 1950s.
Figure 8.10: The timeseries above show bias corrected annual average precipitation (top), maximum temperature (middle), and minimum temperature (bottom) data for the Saguache Cooperative Observing Network weather station. Annual totals are given by colored lines, and decadal averages are given by black lines.
Annual precipitation at Saguache, CO has decreased at a rate of 0.13”/decade since the beginning of the 20th century. It has decreased by double that rate since the 1980s. This being said, decreases are not great enough to be statistically significant at 95% confidence. The only season in which precipitation has increased over the past century is winter. No seasonal trends are statistically significant.
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Figure 8.11: The four-panel timeseries plot above depicts seasonal precipitation for the Saguache Cooperative Observing network station. Seasonal totals are given for every year from 1900-2014. Totals are displayed for winter (top left), spring (top right), summer (bottom left), and fall (bottom right).Yearly totals are displayed in green. Decadal averages are displayed in black.
Table 8.7: The table shown here reveals the decadal average trend in precipitation for the Saguache USHCN bias corrected station between 1900 and 2014 (row 1), 1950 and 2014 (row 2), and 1980 and 2014 (row 3). Trends are given for each meteorologic season: Winter (DJF), spring (MAM), summer (JJA), and fall (SON) as well as the annual trend. Statistically significant trends are indicated according to shading. Significant increase at 95% confidence is given in light green (no example here). Significant increase at 99% confidence is given in dark green (no example here). Significant decrease at 95% confidence is given in light yellow (no example here). Significant decrease at 99% confidence is given in dark yellow (no example here).
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Maximum temperatures have increased significantly since the 1900s in every season. Maximum daily temperatures from 2005-2014 were 3.3 F warmer than the 1900s during the winter, 6.1 F warmer during the spring, 4.6 F warmer during the summer, and 3.8 F warmer during the fall. For the winter, summer, and fall much of this warming occurred during the first half of the 20th century. Spring temperature trends are closer to linear, and resultantly are statistically significant over short and long time frames.
Figure 8.12: The four-panel timeseries plot above depicts seasonal average daily maximum temperature for the Saguache Cooperative Observing network station. Seasonal totals are given for every year from 1900- 2014.Averages are displayed for winter (top left), spring (top right), summer (bottom left), and fall (bottom right).Yearly averages are displayed in red. Decadal averages are displayed in black.
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Table 8.8: The table shown here reveals the decadal average trend in maximum daily temperatures for the Saguache USHCN bias corrected station between 1900 and 2014 (row 1), 1950 and 2014 (row 2), and 1980 and 2014 (row 3). Trends are given for each meteorologic season: Winter (DJF), spring (MAM), summer (JJA), and fall (SON) as well as the annual trend. Statistically significant trends are indicated according to shading. Significant increase at 95% confidence is given in light red. Significant increase at 99% confidence is given in dark red. Significant decrease at 95% confidence is given in light blue (no example here). Significant decrease at 99% confidence is given in dark blue (no example here).
The maximum temperature trends at the Saguache station are quite convincingly upwards, so it’s curious that no minimum temperature trends are evident. Daily maximum temperatures have increased by at least 3.3 F in every season over 1900-1909 levels, and yet no season shows increases in daily average minimum temperature greater than 0.3 F. The difference between the hottest and coldest winter daily average minimum temperature is over 15 degrees Fahrenheit. The difference between the hottest and coldest summer daily average minimum temperature is over 8 degrees Fahrenheit. Clearly, in this case, background year-to-year climate variability has overpowered any consistent trend.
Figure 8.13: The four-panel timeseries plot above depicts seasonal average daily minimum temperature for the Saguache Cooperative Observing network station. Seasonal totals are given for every year from 1900-2014. Averages are displayed for winter (top left), spring (top right), summer (bottom left), and fall (bottom right).Yearly averages are displayed in blue. Decadal average seasons are displayed in black.
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Table 8.9: The table shown here reveals the decadal average trend in minimum daily temperatures for the Del Norte USHCN bias corrected station between 1900 and 2014 (row 1), 1950 and 2014 (row 2), and 1980 and 2014 (row 3). Trends are given for each meteorologic season: Winter (DJF), spring (MAM), summer (JJA), and fall (SON) as well as the annual trend. Statistically significant trends are indicated according to shading. Significant increase at 95% confidence is given in light red (no example here). Significant increase at 99% confidence is given in dark red (no example here). Significant decrease at 95% confidence is given in light blue (no example here). Significant decrease at 99% confidence is given in dark blue (no example here).
Based on the three USHCN indicator stations temperatures have increased in and around the Rio Grande National Forest over the past 115 years. For Del Norte and Saguache this warming is driven primarily by increases in maximum temperature. For Hermit the warming is primarily driven by increases in minimum temperature
Snowpack Trends: The lifeblood of the Rio Grande National Forest’s hydrologic system is the annual snowpack received over the high terrain each cold season. Historic snowpack trends were assessed using the four snow courses from section four (see figure 4.2). These stations do not have as lengthy of a historic record as the USHCN stations used for temperature and precipitation trend analysis. Not all stations had complete snow course records dating back to 1949. On years where one or more snow courses were missing data, the April 1st snow water equivalent was estimated using North American Regional Reanalysis data. NARR March monthly SWE data was substituted for an April 1st snow course average for the years with missing snow course data. The model measurements would have had a low bias due to low resolution. This bias was corrected by dividing the model mean SWE year, and then multiplying by the average April 1st snow course measurement.
April 1st snowpack in the Rio Grande National Forest is decreasing. Since 1949 this decrease has moved at a rate of 0.44”/decade. This is a 4% of normal decrease/decade. While this trend is alarming, there is not yet sufficient evidence to declare the trend significant. This is due to the large amount of background variability. One standard deviation in April 1st snowpack is 4.04”. From 2011-2016 the Forest has been on a dry streak. Peak season snowpack has not been above average since 2010. The last time snow course average snowpack peaked at about 15”, or what we’ll call a banner year, was 2008. In 2011-2013 this has meant drought. In 2014-2016, spring precipitation has been greater than average, so low snowpack did not translate directly to warm season drought.
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Figure 8.14: The scatterplot above shows snow course-averaged April 1st snow water equivalent for every year from 1949-2016 (green). The least squares line has been plotted in gray.
Relation Between Atmospheric Trends and CO2: Atmospheric CO2 concentrations have been measured at the Mauna Loa Observatory since 1959 by the Earth System Research Laboratory (ESRL 2016) (figure 8.15).
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Figure 8.15: The timeseries above is shows the recorded atmospheric carbon dioxide concentrations at the Mauna Loa Observatory in Hawaii as provided by the Earth System Research Laboratory. The black line shows annual
average CO2 concentrations from 1959 to 2016. The red curve shows monthly observed CO2 concentrations from 1959 to present date.
Increases in concentration of carbon dioxide, as well as other greenhouse gases, have raised
concern about globally warming temperatures. Physically these concerns are due to the fact that CO2 increases the atmosphere’s capability to trap longwave radiation emitted by the earth’s surface, and lower atmosphere, that would otherwise escape out to space. These gasses do not proportionally decrease the amount of solar energy reflected by earth’s atmosphere back out to space. The earth must therefore develop a warmer surface temperature in order to maintain radiative equilibrium. Not all regions of the globe, or even Colorado, have been, or will be, impacted equally.
The increase in carbon dioxide from 1959-2015 explains 11-26% of the variance in average annual maximum and minimum temperatures for the three stations selected in this study, and correlation is not necessarily equivalent to causation. Historic temperature increases averaged across the entire state of Colorado correlate more strongly with increases in greenhouse gas emissions (Lukas et al 2014). Bias removal executed by the National Climate Data Center is not perfect. Furthermore,
71 temperature trends may still be influenced by a myriad of other factors beyond the scope of natural variability, and forcing from increased greenhouse gas concentrations. These include but are not limited to changes in weather observers, weather service-approved changes in station location, changes in instrumentation, and changes in local vegetation. A higher density of weather stations would have likely helped to reinforce existing evidence of Rio Grande National Forest of localized anthropogenic climate change.
Physical relationship between increased CO2 concentrations is less obvious, but changing the earth’s radiative energy balance in turn impacts the global circulation. This may impact precipitation. Similarly, warming the atmosphere increases its capacity for water vapor, which may impact precipitation. Annual precipitation accumulation is down at the Hermit and Saguache stations since the 1900s, but not the Del Norte station. Precipitation has gone down for all three stations since the 1980s, significantly so for Del Norte and Hermit, but the 1980s were an anomalously wet decade for the Rio Grande National Forest area. Less than 8% of the variance in precipitation since the late 1950s can be explained by increasing atmospheric CO2 concentrations.
Snowpack has decreased with time in the Rio Grande National Forest since 1959. The correlation between global carbon dioxide concentrations and April 1st snowpack in the Forest is only - 0.15. This means only 4% of the variance in seasonal snowpack since the late 1950’s can be explained by
decreases driven by increasing atmospheric CO2 concentrations.
One of the largest problems with temperature trend analysis in the Rio Grande National Forest is the lack of available data to assess changes in temperature trends as a function of elevation. The Forest has a maximum elevation of 14,345 ft, but there are no thermometer records available dating back beyond 1958 for elevations above 9,000 ft. Since the late 1970s the Snowpack Telemetry Network has installed stations in the 9,000-11,000 ft range within the Forest, but the temperature records were found to produce a positive bias in minimum temperature trend (Oyler et el 2014).
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CHAPTER 9: CURRENT DATA LIMITATIONS
Poor Radar Coverage: Poor radar coverage in the Rio Grande National Forest is an ongoing concern. Quality radar coverage exists for eastern Colorado, and the Grand Junction area, but much of the western portion of the state is not covered (Gochis et al 2016). One of the benefits of radar would be improved nowcasting and weather warnings, but well-placed radar would have climate monitoring applications as well. With appropriately-placed radar, high resolution estimates of precipitation would be possible. This would help resolve high-resolution gradients in precipitation that cannot currently be discerned with reanalysis data, improved snowpack estimates, and help with efforts such as drought early warning, and river flow forecasts (Gochis et al 2016).
Altitudinal Gradients: Weather stations with long climate records in the Rio Grande National Forest are typically Cooperative Observing Network (COOP) stations. COOP sites are dispersed in an even sense across the state of Colorado, but stations in mountainous areas are typically located in mountain valleys. The Snowpack Telemetry (SNOTEL) Network has provided an appropriate sample of Forest precipitation and snowpack between 9,000 and 11,000 feet. Historic temperature observations at high elevations within the Forest are scarce. Precipitation measurements above 11,000 feet are nearly non-existent as well.
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CONCLUSIONS
The combination of low-density weather station observations from the Cooperative Observing Network, the Snowpack Telemetry Network, snow course measurements, and the Remote Automated Weather Station Network in tandem with modeled data from the PRISM Climate Group and North American Regional Reanalysis offer a suitable framework for summarizing the climate of the Rio Grande National Forest. Observations used in this study detail the mean state, variability, and trends of temperature, precipitation and snowpack. The local behavior of climate variables such as snowfall, humidity, and wind are outlined to a lesser degree. Combining these data with previous reviews of Colorado climate, mountainous climates, and mid-latitude weather it is found that elevation and global position can be used to explain much of what has been observed about the climate of the Forest.
PRISM 4-km resolution reanalysis data from 1981-2010 show that the Rio Grande National Forest is most often blanketed by a cold-dry mass of air with mean annual temperatures ranging from 28-40 F. North American Regional Reanalysis suggest that these air masses are typically low in water vapor content as well. Observational data with longer period of record support these findings where available. Winter-summer and night-day temperature changes are large. COOP temperature data show that differences in mean temperature between the warmest and coolest times of year are between 30 and 40 F. These same data suggest that the difference between average daily maximum and minimum temperature is roughly 25-30 F. The combination of cool average temperatures and high diurnal temperature variance makes for a short frost free season, approximately 60 days in the high mountain valleys of the Forest and 110 days near the entrance to the Forest. Temperature variance is higher for valleys than peaks and higher for winter than summer. Spatial variance in temperature, maximum temperature more so than minimum, is primarily driven by altitude.
Once again using PRISM climate normals from 1981-2010 the annual average precipitation within the Forest was found to be between 25 and 30 inches. The wettest locations of the Forest lie on its southwest boundary, and receive an average of nearly 50” annually. Valley locations near the base of the Forest receive less than 10” of precipitation/year. Elevation was found to be a primary control on spatial variability of precipitation, but direction of wind flow during storm events is also important. Air masses tend to be more moisture-starved by the time they reach the northern or eastern mountains of the Forest. For the lowest and middle parts of the Forest the monsoon season of July through September is the most important time of year for the production of precipitation. The highest elevation areas of the Forest average consistently higher precipitation from July through April with a short dry season in May and June. Year-to-year variability in precipitation is large. Using Del Norte, Hermit, and Wolf Creek Pass stations as precipitation indicator stations, the range of observed annual precipitation totals over the history of these three stations spanned from 4.78” at Del Norte in 2002 to 59.47” at Wolf Creek Pass in 1986.
Wind data collected by Remote Automated Weather Stations in and near the Forest support the following conclusions: Winds blow preferentially from west to east, or southwest to northeast, throughout the Forest during the day, but with considerable directional variability. Daytime winds increase in intensity when blowing down a mountain slope versus blowing up a mountain slope, or on an
74 even gradient. Nighttime winds are more consistent in nature. These winds blow down from the direction the highest nearby topographic feature as cold air drains into the mountain valleys.
Extremes in wet and dry conditions that have been experienced in the Forest are explored in this summary. The extremes explored include flooding in the 1927 spring season, the record snowfall season at Wolf Creek Pass in the 1978-1979, and droughts of the early 21st century.
The Rio Grande National Forest is subject to the influence of some well-documented, mountain- forced weather patterns. Understanding of these patterns is key for a holistic understanding of the Forest’s historic climate, but they have not been measured with the frequency and consistency of daily temperatures and precipitation. An outline has been presented for three such patterns: cold air drainage, diurnal thunderstorm development, and settling of snowpack. The coldest air pools in valleys at night, especially during the wintertime. Warm air rises off the peaks and cools during the day, most primarily during summer. Snowbanks are formed and maintained based on the flow of prevailing winds and insolation received.
Bias-corrected, long-term temperature, precipitation, and snowpack data were vetted for indications of climate change. Such stations are few and far between in south-central Colorado, which brings the unfortunate side effect of watering down conclusions about local climate change based solely on historic data. Temperatures were found to be increasing in the Forest long-term. At least 10% of the variance, and as much as 26% of the variance, in annual temperatures observed in the Forest can be explained by the long-term upward trend in atmospheric carbon dioxide concentrations. Other sources aside from natural variability that impact the observed temperature record may exist. These include but are not limited to changes in weather observers, National Weather Service-sanctioned changes in station location, changes in measurement equipment, and changes in land use immediately around the stations. Precipitation is decreasing significantly in some areas, but tends in precipitation are still small with respect to year-to-year variation. Snowpack is decreasing, but not significantly so, across the entirety of the Forest.
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