U.S. Fish & Wildlife Service Antioch Dunes National Wildlife Refuge
Climate Inventory and Summary
By Rachel Esralew, Hydrologist, Pacific Southwest Region Inventory and Monitoring Program
U.S. Department of the Interior U.S. Fish and Wildlife Service Executive Summary
The purpose of this report is to summarize existing and observed trends in temperature and precipitation patterns and forecast climate change projections for temperature and precipitation near the Antioch Dunes National Wildlife Refuge (Antioch). This report is in support of a Natural Resources Management Plan (NRMP) for the refuge.
The mean monthly temperature near Antioch ranged from 40.5 to 79.6 °F with minimum temperatures in January and December and maximum temperatures in July. Mean total water year precipitation near Antioch was 12.51 inches per year (ranging from 5.77 to 24.8 inches per year). Monthly and annual precipitation are highly variable; even though December 2014 was one of the wettest on record, the driest year in the San Joaquin Drainage Climate Division also occurred in 2014. Average daily reference evapotranspiration over the period of record is 0.15 inch and has ranged from 0 to 0.41 inches over the period of record.
One might expect a greater likelihood of warmer conditions near Antioch during the warm phase of the Pacific Decadal Oscillation (PDO) and positive phase of the Pacific North American pattern (PNA). No associated was observed between any parameter and El Niño/La Niña, or any teleconnection index and precipitation.
All seasons and months showed increases temperature over the period 1893 to 2014, but no precipitation trends were observed for any time period tested. Only cool season average temperature increased constantly and persistently over every time period tested. Increases in cool season average temperatures ranged from 0.02 to 0.07 °F per year (ranging from 1.6 to 2.4 °F over the time periods tested).
Within the refuge boundary, changes in 30-year forecasts for precipitation were most uncertain among models, showing either decreases or increases by 2100. Changes in mean 30-year precipitation at Antioch ranged from -17.9 to +31.5 percent (-9.8 to 17.3 inches).
Changes in 30-year forecasts for maximum and minimum temperature showed an increase under all model and emission scenarios by 2100, with increases in historic mean maximum temperature ranging from +3.7 to +7.9 °F by 2100, while increases in the historic mean minimum temperature ranged from +0.9 to +6.8 °F.
Changes in 30-year forecasts for water demand (climatic water deficit) showed an increase under all models from 2070 to 2100 (+1.3 to +7.1 inches per year) with the exception of the Csiro model, in which decreases were observed (-0.9 inches). Increases represent a 3 to 16.7 percent increase in water demand.
Models showing increases in water demand indicates that outside source of water might be needed in the future to maintain existing habitats. The refuge does not currently irrigate habitat with external water supply. Investigation into the water requirements for vegetation and ROC targets would be helpful for planning to determine whether outside sources of water might be needed in the future to offset deficits.
Background
Antioch Dunes National Wildlife Refuge is a wildlife refuge established in 1980 to conserve habitat for three endangered species: Lange’s metalmark butterfly (Apodemia mormo langei), Contra Costa wallflower (Erysimum capitatum angustatum) and Antioch Dunes evening primrose (Oenothera deltoides howellii). The refuge consists of 55 acres of former dunes, and is connected to 12 acres of land owned by Pacific Gas and Electric Company (PG&E). This area is an isolated patch that was part of a larger dune system. Restoration and improvement to dune habitat is currently underway (U.S. Fish and Wildlife Service, 2002).
The refuge manages habitat through a variety of restoration and enhancement projects, including survey and monitoring; captive breeding of Lange’s; weed control using manual, mechanical, and herbicides; import of sand for dune restoration; revegetation using native plants; and prescribed burns and management of firebreaks (U.S. Fish and Wildlife Service, 2002).
The refuge is adjacent to the San Joaquin River and is tidally influenced. The riparian corridor is approximately 10 feet wide and includes steep embankments along the river’s edge. The San Joaquin River near the refuge is a saline system. As of 2002, tides result in water level fluctuations from about 3 feet above sea level at high tide to about 2.2 feet below sea level at low tide during a typical tidal cycle. The refuge overlays shallow groundwater, with water levels between 15 and 30 feet below land surface as of 1999. The refuge does not use much water for management, with the exception of a fire hydrant used for fire suppression (U.S. Fish and Wildlife Service, 2002: 23).
The Natural Resources Management Plan for Antioch Dunes National Wildlife Refuge (referred to in the remainder of this report at “Antioch”) is designed to assist refuges with development and prioritization of management strategies to help address key resources of concern (ROC). The process to establish an NRMP includes evaluating threats to ROCs, of which climate variability and climate change are major influences (G. Block, Pacific Southwest Region Inventory and Monitoring Specialist, oral communication, October 2014). Selected priority ROCs for the NRMP project include Lange’s metalmark butterfly, Contra Costa wallflower, Antioch Dunes evening primrose, and dune habitat (G. Block, USFWS Biologist, oral communication, June 2015).
Climate change has the potential to threaten ROCs and refuge operations in a variety of ways. Changes in precipitation and temperature extremes as a result of climate change have the possibility to affect the abundance and distribution of selected ROCs that utilize refuge habitats. Sea level rise and increases in storm surge will likely have an impact on dune habitat if actions are not taken to protect shorelines. However, summary of sea level rise impacts were beyond the scope of this report.
The purpose of this report is to summarize existing and observed temperature and precipitation patterns and trends near the refuge and in an area of interest or influence to refuge resources. This includes 1.) a summary of recent averages in temperature and precipitation, 2.) an analysis of correlation between temperature and precipitation and larger global teleconnection indexes, 3.) historic trends in temperature and precipitation, and 4.) projections of temperature and precipitation under selected global climate models and a variety of climate change scenarios. Methods
Identification of Hydrologic Data Used in Summary Identification of Spatial Boundary Conditions to Inventory Hydroclimate and Hydrologic Monitoring Data
All climate stations that provided data for this report were selected by defining a region of hydrologic influence for climate (climate RHI) for Antioch. The climate RHI was estimated by conducting a spatial cluster analysis of 30-year mean temperature and precipitation from the Parameter-elevation Regressions on Independent Slopes Model (PRISM; PRISM Climate Group 2014, see description of dataset in later sections). The Iso Cluster tool was used in Arc 10.1 (ESRI, 2012) and run with a Maximum Likelihood Estimator to assign distinct classifications among groups of cells in the input rasters (30-year mean temperature and precipitation). This clustering was used to select areas of similar temperature and precipitation among a boundary area. The boundary mask was set as the Level 3 Ecoregion (Marine West Coast Forest, Griffith et al. 2008). A maximum of 3 possible classifications were calculated throughout the selected area. A 30 mile buffer from the refuge was intersected with the resulting classification to select a relatively local area to the refuge. Lines were generalized manually to create a polygon to represent the climate RHI (figure 1).
Inventory of Hydroclimate and Hydrologic Monitoring Data
All climate monitoring stations that provided data for this report were selected within the climate RHI boundary described above. Monitoring station locations and data were referenced and obtained using only publicly available internet sources and refuge archival records. If fully processed and readily available in digital format at the time of this report, data from selected monitoring stations were used to characterize recent hydrologic conditions and to assess trends. If monitoring station information for the same station was provided on more than one database or server, then a decision was made: if a server provided more easily accessible location information or hydrologic data, or included a longer period of record for that station, then that server was selected. Not all data from stations inventoried as shown in appendix B table B1 were used in this report because some stations’ periods of record were too short to identify trends or to describe hydrologic variability. However, omitted stations were listed for potential use in other assessments.
Climate monitoring stations were inventoried to determine which stations provided data that represented climate conditions at the refuge or in the climate RHI. Sources of climate station information included the California Irrigation Management Information System (CIMIS; California Department of Water Resources 2015a), Integrated Pest Management Program California Weather Database (IPM, University of California–Davis 2015), U.S. Historical Climatology Network (USHCN, Easterling et al. 2009), California Data Exchange Center (CDEC; California Department of Water Resources 2015b), the Global Historical Climatology Network (GHCN, National Oceanic and Atmospheric Administration 2015a), and MesoWest Climate Data Portal (University of Utah 2015). 76 climate stations within the climate RHI were located (figure 1; appendix B, table B1); at least one station was found from each of the data sources listed above.
Modeled Hydroclimate and Hydrologic Data
Additional geospatial models were used to supplement information from stations or to account for variation in parameters over space. The two main geospatial models used to supplement monitoring station information in assessing water resources for Antioch were PRISM and Basin Characterization Model (BCM; Flint and Flint 2012).
The PRISM model was used to map 30-year mean precipitation for the region surrounding the refuge. PRISM is an analytical model that uses climate monitoring data, a digital elevation model (DEM; topography and orographic features), and atmospheric characteristics to generate estimates of monthly and annual precipitation and temperature (PRISM Climate Group 2014).
BCM was used to project effects of climate change on temperature, precipitation, climatic water deficit (CWD), and groundwater recharge. BCM is driven by high resolution (270-meter) temperature and precipitation data downscaled from PRISM that is used to characterize water budget at the land surface. Calculation of variables associated with water budget incorporates static inputs (elevation, bedrock properties, soil properties), and downscaled or modeled time variable inputs (precipitation/snow, temperature, derivatives from solar radiation) to produce water budget outputs (CWD,1 runoff, recharge) for current conditions and forecasted for a range of climate change scenarios (Flint and Flint 2007). As part of CWD, potential evapotranspiration (PET)2 is the total amount of water that can evaporate/transpire given temperature, solar radiation, and other variables. Actual evapotranspiration (AET), which is used to calculate CWD, is controlled by soil characteristics (porosity, field capacity, wilting point, and infiltration to bedrock) (Flint and Flint 2007).
1 CWD is the difference between PET and AET and represents the amount of additional water that would have evaporated or transpired had it been present in the soils (Flint and Flint 2007). Negative values indicate water storage. 2 Reference evapotranspiration (ETo), measured at CIMIS stations, more closely resembles PET than AET because it is measured primarily from climate factors (solar radiation, humidity, vapor pressure, air temperature, and wind speed), but unlike AET, it does not take into account the ability of underlying soils to store or transmit water to recharge or the atmosphere. Differences in modeled PET and ETo likely occur because a reference crop is not defined in PET and because weather data measured at a station in which ETo is estimated are typically collected from a well-defined reference environment (well-irrigated and well- maintained grass area). ETo can be measured accurately only at the climate station; accordingly, PET is used to estimate PET over large areas. For this reason, PET is more useful than ETo for comparing water demand between areas.
Figure 1. Mean annual precipitation, inventoried climate stations, and selected regional boundaries near Antioch Dunes National Wildlife Refuge Analysis Methods for Climate Characterization of Recent Conditions To evaluate existing climate characteristics relevant to Antioch, climate station information was summarized to estimate precipitation, temperatures, and evapotranspiration conditions that affect the refuge. In general, climate data were used to assess the following near the refuge: range of observed daily and monthly temperatures range of observed monthly and annual precipitation comparison of both temperature and precipitation near the refuge and in the Antioch Dunes drainage basin Two climate stations were selected for analysis of recent conditions of temperature, precipitation, and reference evapotranspiration (ETo) (past 30 years). The Antioch Pumping Plant 3 station (station 5, figure 1; Contra Costa Water District Station ID ANTIOCH.C accessed from IPM, referred to as “Antioch Pumping Plant”) was optimal for estimating temperature and precipitation conditions at the refuge because the period of record was 1955–present and this station is located only 3.25 miles from the refuge. Antioch Pumping Plant was the closest station to the refuge with at least 30 years of record (figure 1). The Brentwood station (CIMIS station 47) was selected to evaluate ETo because it was the closest station to the refuge (8.75 miles, figure 1) with the longest and most consistent period of record for this parameter (1985–2015).
To plan for effective water resource management, an understanding of the expected interannual variability of climate, or climate predictability, is required. Climate change may pose further uncertainty regarding this variability; however, a baseline understanding of the current variability in climate conditions that affect the refuge can help evaluate future impacts associated with the magnitude, frequency, and duration of climate conditions.
An understanding of global climate factors and large-scale circulation patterns that influence the variability of temperature and precipitation at a scale relevant to refuge water resources is useful for understanding climate predictability. Numerous studies have examined the use of teleconnection indices that indicate the effect of these large-scale circulation patterns on local climate (temperature and precipitation).
For example, the El Niño–Southern Oscillation (ENSO) phenomenon3 as indicated by the Southern Oscillation Index4 (SOI), is related to precipitation, snow accumulation, and streamflow in western North America (Cayan et al. 1998; Francis et al. 1998). During El Niño, the southwest tends to be wet and the northwest tends to be dry (negative SOI)—and conversely so for La Niña (positive SOI) (Dettinger et al.
3 El Niño is an oscillation of the ocean temperatures in the equatorial Pacific that has implications for global weather. El Niño is characterized by unusually warm ocean temperatures, whereas La Niña is characterized by unusually cool temperatures in the equatorial Pacific (National Oceanic and Atmospheric Administration 2015b). 4 The SOI is an index that combines the Southern Oscillation (differences in ocean temperatures in the equatorial Pacific) and is computed as monthly mean sea level pressure anomalies at Tahiti and Darwin (National Oceanic and Atmospheric Administration 2015c). 1998). Redmond and Koch (1991) showed that October–March precipitation was most strongly correlated with SOI averaged over the July–November period. Another teleconnection index commonly analyzed is the Pacific Decadal Oscillation (PDO),5 which is related to precipitation and temperature. Gershunov and Barnett (1998) demonstrated that when PDO and ENSO are in phase (El Niño—warm PDO; La Niña—cold PDO), the ENSO climate signals described above are stronger and more stable with regard to winter precipitation in the western United States, whereas out-of-phase relations between PDO and ENSO have a weaker climate signal.
Precipitation and temperature data from the Livermore climate station (station 20, figure 1; USHCN station ID 44997, referred to as “Livermore”) was compared with SOI and PDO to determine if these teleconnections were strongly linked to temperature and precipitation affecting the refuge and whether these teleconnections can be used to predict climate characteristics at and near the refuge. This station was selected because precipitation and temperature data were available since 1903, and was the closest station to the refuge (22 miles) with the longest period of record.
A Kruskal–Wallis test6 was used to compare the distribution of cool-season precipitation (October– March, as percent above mean) and temperature (average annual in degrees Fahrenheit [°F]) to the distribution of SOI (July–November) and PDO (October–March). SOI was divided into phases of El Niño years (SOI of less than or equal to -0.5), neutral years (SOI between -0.5 and 0.5), and La Niña years (SOI greater than or equal to 0.5). PDO was divided into phases of warm years (PDO greater than 0.5), neutral years (PDO between 0.5 and -0.5), and cool years (PDO less than -0.5). Temperature and precipitation values for each year were assigned the teleconnection categories listed above based on the corresponding year. The Kruskal–Wallis test was run to compare more than one distribution in multi- distribution groups to determine which distributions were different. Results of the Kruskal–Wallis test are presented as a table in this report. A boxplot was developed to show differences in the distributions of temperature and precipitation between teleconnection groups.
Estimation of Trends in Response to Climate Change and Anthropogenic Stressors
To evaluate existing precipitation and temperature trends as a result of climate change, time-series trends in annual and seasonal precipitation and temperature were evaluated for the Livermore station.
Long-term information (1903–present) was available for this location, and these areas represented different regions of the study area. Time-series were generated from monthly precipitation (total inches) and monthly temperature (maximum, minimum, and range of difference between maximum and minimum) for the following aggregated time-periods: seasonal (four seasons), cool-season (October–
5 The PDO is a pattern of Pacific climate variability that shifts phases on an inter-decadal scale (20–30 years) and is detected as warm or cool surface waters in the Pacific Ocean north of 20 degrees latitude (National Oceanic and Atmospheric Administration 2015d). 6 The Kruskal–Wallis test was used to compare multiple datasets simultaneously to determine if the locations of distributions among all groups were statistically different at a p-value of 0.05. March), and annual. In addition, time-series were generated for precipitation and temperature (range of difference between maximum and minimum only) for 12 separate months. The Kendall’s tau statistical time-series trend test was run to test whether all time-series trends were statistically significant at a p-value of 0.05 (Sen 1968; Dietz 1989; Kendall and Gibbons 1990) and compute the Sen slope.7
Because the Kendall’s tau statistical test is used to estimate the presence of a monotonic trend (singular direction with time), smaller scale shifts (shifts in climate within the period of record tested) in climate may result in signal noise that precludes accurate detection of trends over a long period of time (Helsel and Hirsch 2002:323–334). To determine which parameters had the most persistent trends (trends that remained significant and in the same direction for variable time periods over the period of record), the following time-periods were tested: 1910–2013, 1925–2013, 1950–2013, and 1984–2013 (last 30 years).
Literature on the impact of climate change on temperature and precipitation was summarized for Antioch. Point Blue Conservation Science (2011) summarized climate change projections from a variety of literature sources for selected ecoregions within California. Antioch is within the San Joaquin Valley ecoregion, but is close to the intersection of the Sacramento Valley ecoregion, and Central Western California ecoregion. Therefore, a summary of the range of conditions expected for each of these ecoregions was summarized.
Climate change projections for temperature, precipitation, PET, CWD, and recharge within the refuge boundaries were modeled by comparing four climate change scenarios overlayed with BCM model inputs and outputs by comparing mean conditions for 1971–2010, 2010–2039 (near future), and 2070–2099 (distant future). Climate change scenarios were modeled in BCM using six different General Circulation Models (GCMs): Geophysical Fluid Dynamics Laboratory (GFDL) model, Model for Interdisciplinary Research on Climate (MIROC Medres), Beijing Climate Center China Meteorological Administration Model (BCC_CSM), Bergen Climate Model Version 2 (BCCR_BCM2), Parallel Climate Model General Circulation Model (PCM), and the Commonwealth Scientific and Industrial Research Organization (CSIRO). All models were run using medium to high carbon dioxide emissions or medium to high increase in carbon dioxide concentrations; all models were run using the A2 emissions scenario,8 with the
7 Kendall’s tau test is a non-parametric statistical test that can be used to indicate the likelihood of upward or downward trends in data with time. Tau coefficients range from -1.0 to 1.0; a tau of -1.0 indicates that every datum decreased with time, and a tau of 1.0 indicates that every datum increased with time. A trend slope is a measure of trend magnitude that was computed using the Sen slope estimator. The Sen slope is estimated by computing the median of all slopes between each possible data pair in the time-series (Sen 1968). 8 Several families of emission scenarios are discussed in the International Panel on Climate Change’s fourth assessment report. Scenario A2 is the carbon emissions in a differentiated world and is characterized by self-reliance in terms of resources and less emphasis on economic, social, and cultural interactions between global regions. Economic growth is uneven, and the income gap between now industrialized and developing parts of the world does not narrow (Solomon et al. 2007). exception of BCC_CSM which was run under the similar RCP6.09 carbon concentration scenario (Flint and Flint 2012).
Climate Inventory and Summary
Hydroclimatic Settting Antioch is located in the northern California Central Valley just inland of the San Francisco Bay Area (Bay Area). Meteorological conditions in northern California are predominantly determined by the north Pacific high pressure system. Antioch is located on the eastern edge of this system (Ruffner 1985). Large- scale subsidence (areas where large masses of cooler, drier air descend from higher to lower elevations, causing an increase in barometric pressure), which occurs over the subtropical regions, is the major cause of the north Pacific high pressure system (Nuss 2014).
In May–October, storms generally progress in a northerly direction to the California coast because the north Pacific high pressure center moves north from subtropical regions. As a result, there is little to no rainfall in the summer (Ruffner 1985). In the winter (November–April) this pressure system moves southward which allows storm centers to move into California (Nuss 2014). The majority of rain falls during the winter season due to the increasing presence of mid-latitude storms.
The area around Antioch has a modified Mediterranean climate with hot dry summers and moist mild winter. The area near the refuge experiences cooler winters and hotter summers than the Bay Area to the west. Marine air may influence temperatures in the areas closest to the Bay Area by moderating temperatures that are more extreme farther inland. However, ocean influence is negligible on hot days when winds blow off shore (Pacific Energy Center, 2006).
The Palmer Drought Severity Index (PDSI) responds to long-term weather conditions and provides a coarse-level indication of regional meteorological wet or dry periods (National Center for Atmospheric Research 2013, figure 2). The index incorporates antecedent precipitation, moisture supply, and moisture demand that may reflect the climate of previous years (Dai et al. 2004). Although Antioch is within the San Joaquin Drainage Climate Division (divisions with computed PDSI values), the refuge is near the intersection of four climate divisions with computed PDSI values (San Joaquin Drainage, Sacramento Drainage, North Coast Drainage, and Central Coast Drainage).
Within the San Joaquin Drainage, recent (1980–2014) dry periods generally include 1984 to 1994, 1999 to 2004, 2007 to 2009, and 2012-2014 (figure 2. Recent wet periods generally include 1982 to 1983, 1995 to 1998, 2005 to 2006, and 2010 to 2011. Of these, 1982-1983, 1995, 1998, and 2005 were extremely wet, and 2007-2008, and 2013-2014 were extremely dry. From 1895 to 2014, the wettest year on record
9 Representative Concentration Pathways (RCP) are four greenhouse gas concentration trajectories adopted by the International Panel on Climate Change for its fifth assessment report (Richard et al. 2008). Each trajectory represents a possible range of radiative forcing values in the year 2100 relative to pre-industrial values. from 1895 to 2013 was 1983 (6.75) and the driest year on record was 2014 (-6.74). The last decade contained the highest number of dry years on record.
Figure 2. Palmer Drought Severity Index for the San Joaquin Drainage of California, 1895–2014
Recent Conditions Monthly precipitation and temperature data was averaged for the Antioch Pumping Plant climate station. The mean monthly temperature near Antioch was 61.4 °F and ranged from 40.5 to 79.6 °F (based on data from 1985 to 2014, January 1985 and July 1988, respectively). Minimum temperatures generally occur in January and December and maximum temperatures generally occur in July (figure 3). Over the period 1985–2014, the greatest observed temperature near Antioch occurred on July 22nd to 23rd, 1991 (110 °F). Over the same period, the lowest observed temperature near Antioch occurred on January 22nd and 23rd, 1995 (20 °F).
Annual and monthly precipitation near Antioch is highly variable. Mean total water year precipitation was 12.51 inches per year (ranging from 5.77 to 24.79 inches per year)10 near the refuge. The greatest
10 Data are from Antioch Pumping Plant climate station for water years 1985–2014. precipitation generally occurs in December through February. February precipitation is highly variable. June–September is generally driest with the exception of some rare small rain events (figure 3). Over the period 1985–2014, the greatest precipitation near Antioch in 1 day was on October 13th, 2009 (3.09 inches), followed by December 118th, 2014 (2.24 inches). To highlight the annual and monthly variability in precipitation: even though December 2014 was one of the wettest on record, the driest year in the San Joaquin Drainage Climate Division also occurred in 2014.
Figure 3. Monthly and annual precipitation, and monthly temperature, for the Antioch Pumping Plant 3 Climate Station (Station ID ANTIOCH.C accessed from Integrated Pest Management Program California Weather Database), 1985-2014.
ETo near Antioch is variable throughout the year based on data from CIMIS station 47 (1985–2014; figure 4). Average daily ETo over the period of record is 0.15 inch and has ranged from 0 (many dates in December through January) to 0.41 inch (June 9, 2002) over the period of record. Monthly ETo ranged from 0.02 to 0.3 inch (July and January, respectively).
Figure 4. Reference evapotranspiration at Brentwood (California Irrigation Management Information System station 47), 1985–2014.
Historic Climate Trends One might expect a greater likelihood of warmer conditions near Antioch during the warm phase of the Pacific Decadal Oscillation (PDO) and positive phase of the Pacific North American pattern (PNA) (appendix A figure A1; appendix B table B2). Statistically significant differences in both maximum and minimum temperatures were observed at the Livermore climate station for the phases of PNA, and maximum temperatures for the phases of PDO. However, no significant associations between teleconnections and temperature were observed in the Antioch Dunes Drainage Basin. No statistically significant associations were observed between any parameter and El Niño/La Niña (SOI), or any teleconnection index and precipitation.
All seasons and months showed increases in minimum, average, and maximum temperature over the period 1893 to 2014 (figure 5), and no precipitation trends were observed for any time period tested. Many temperature trends still increased until 1950, but trends remained variable for many parameters in the middle of the century. However, only cool season average temperature increased constantly and persistently over every time period tested (showed trends in every time period tested). Increases in cool season average temperatures were relatively small and ranged from 0.02 to 0.07 °F per year (ranging from 1.6 to 2.4 °F over the time periods tested). With the exception of cool season maximum temperature and September minimum and average temperature which increased slightly since 1985, temperatures during all other months and seasons have stabilized since 1985.
Figure 4. Trends in annual maximum and minimum temperature at Livermore Climate Station, 1893-2014
Figure 5. Trends in total annual precipitation at the Livermore Climate Station, 1893–2014
Climate Change Temperature and Precipitation
Climate change could shift the hydroclimate of the western United States. The warming of 0.6–1.1 °F observed during the last half century over the western United States affected the relationship between climate and hydrologic response (Smith et al. 2000; Barnett et al. 2008).
Regional models predict mean annual temperatures will increase from 4.32 to 4.5 F by 2070 in the San Joaquin Valley and Sacramento Valley ecoregions, respectively. In both ecoregions, diurnal temperatures will narrow by -.5 to -.7 F by 2070. Warmer winters are predicted for both ecoregions, and earlier spring warming and increased summery temperatures are predicted for the San Joaquin Valley ecoregion (Point Blue Conservation Science 2011).
Regional models for the Central Western California Ecoregion predict a lesser increase in annual temperatures, but also predict an increase in extreme temperature events. Regional models predict mean annual temperatures will increase 2.9–3.4 F by 2070 for the Central Western California Ecoregion, while other studies that focused on the Central Coast hydrologic region (within the Central Western California Ecoregion) indicate a temperature increase of 4.1 F will occur with a doubling of atmospheric carbon dioxide (Point Blue Conservation Science 2011). In addition, according to regional climate models, extreme temperature events are expected to increase in the central coast, with mean maximum and minimum temperatures projected to increase by 3.6 and 3.5 F, respectively. In the Central Western California Ecoregion, the number of days exceeding 89.9 F is projected to increase 12 days per year along with a 15-day per year increase in the frequency of extremely hot days (Point Blue Conservation Science 2011). On average, the frost-free growing season is projected to start 34 days sooner and last approximately 47 days longer. The models show the number of extreme cold days decreasing by 57 days along with 8 fewer days below 32 F (Point Blue Conservation Science 2011).
Predictions in change of precipitation vary greatly among different models for all ecoregions surrounding Antioch. For the San Joaquin and Sacramento Valley ecoregions, decreases in mean annual rainfall range from 0.9 to 3.2 inches and 1.8 to 6.9 inches by 2070, respectively. For the Central Western California Ecoregion, some predictions show a decrease in mean annual precipitation of 2.4 to 7.4 inches by 2070. However, other models show that even with a doubling of carbon dioxide, there will be no significant change in precipitation patterns on the central coast (Point Blue Conservation Science 2011).
At Antioch, changes in 30-year forecasts for precipitation values were uncertain among models, showing either decreases or increases by 2100. Changes in mean 30-year mean precipitation at Antioch (14.4 inches) ranged from -33.2 to +16.7 percent of historic values (-3.7 to +2.5 inches) by 2100, with the Miroc Medres Model showing the greatest decrease and Csiro Model showing the greatest increase (table 1). In the nearer term (2010-2040), changes in 30-year forecasts for precipitation ranged from -17.9 to 7.1 percent of historic values (-2.2 to +1.1 inches).
Changes in 30-year forecasts for maximum and minimum temperature showed an increase under all model and emission scenarios by 2100 (table 1). By 2100, increases in historic mean maximum temperature (73.5F) ranged from +3.7 to +7.9 °F by 2100, while increases in the historic mean minimum temperature (49.5F) ranged from +0.9 to +6.8 °F. The GFDL and Miroc Medres Models showed the greatest increases and BCCR and Csiro models showed the least increases. In the nearer term (2010- 2040), changes in 30-year forecasts for maximum temperature ranged from +0.8 to 2.1 °F and changes in 30-year forecasts for minimum temperature ranged from -0.02 to +1.4, with slight decreases observed for the BCCR model.
PET, which is directly related to temperature, also showed increases for every model and time period through 2100. Changes in mean 30-year mean PET at Antioch (50.6 inches) ranged from +2.8 to +6.2 percent of historic values ( +1.5 to +3.3 inches) by 2100, with the Miroc Medres and GFDL Model showing the greatest increases and Csiro Model showing the least increase (table 1).
Changes in 30-year forecasts for water demand (climate water deficit, CWD) showed an increase under all models from 2070 to 2100 with the exception of the Csiro model, in which decreases were observed (table 1). By 2100, CWD increases from the historic value (36.2 inches) ranged from +1.3 to +7.1 inches per year, representing a 3 to 16.7 percent increase in water demand, with the greatest increases predicted by the GFDL and Miroc Medres Models. The Csiro model showed a decrease in water demand by 2.4 percent (-0.9), however. In the nearer term (2010-2040), CWD increases ranged from +0.4 to +2.8 inches per year, representing a +0.9 to +7.5 percent increase in water demand. In the nearer term, the Csiro model showed a decrease in water demand by 2.6 percent (-1.0 inches), however, slightly more than the decrease observed by 2100.
The drier models that show the greatest increases in CWD also show decreases in precipitation. This indicates that outside source of water might be needed in the future to maintain existing habitats. The refuge does not currently irrigate habitat with external water supply. Furthermore, the water requirements for native vegetation at the refuge was not determined as part of this report. Investigation into the water requirements for vegetation and ROC targets would be helpful for planning to determine whether outside sources of water might be needed in the future to offset deficits.
1981- Climate variable 2010 (inches or Historic
degrees Celcius) Medres Medres Medres
2010-2039 2040-2069 2070-2099 BCM BCC_CSM BCC_CSM BCC_CSM
2010-2039 PCM 2040-2069 PCM 2070-2099 PCM
2010-2039 Csiro 2040-2069 Csiro 2070-2099 Csiro
2010-2039 BCCR 2010-2039 Miroc 2040-2069 BCCR 2040-2069 Miroc 2070-2099 BCCR 2070-2099 Miroc
2010-2039 GFDL 2040-2069 GFDL 2070-2099 GFDL
Precipitation 14.4 15.4 14.2 14.9 12.2 12.2 14.3 15.5 13.5 13.7 11.0 13.5 15.1 16.9 14.2 11.2 10.6 14.6 15.4 (inches)
Tmax (mean F) 73.5 74.3 74.5 75.2 75.5 75.6 75.1 75.6 75.5 77.0 78.0 76.6 77.0 77.2 78.1 80.1 81.4 78.7 79.0
Tmin (mean F) 49.5 49.5 49.5 50.8 50.2 50.4 49.5 50.6 50.4 52.7 52.3 51.5 51.2 52.5 53.2 56.2 55.3 50.4 53.3
Potential ET 50.6 50.7 50.7 51.4 51.2 51.2 50.9 51.3 51.3 52.3 52.3 51.7 51.8 52.1 52.6 53.9 54.0 52.6 52.8 (inches)
Climatic Water Deficit (CWD, 36.2 35.3 36.6 36.6 39.0 39.0 36.6 35.8 37.8 38.5 41.3 38.2 36.8 35.4 38.4 42.7 43.3 38.0 37.5 inches) Key: BCM, Basin Characterization Model (Flint and Flint, 2012); F = degrees Fahrenheit; ET = evapotranspiration Csiro = Commonwealth Scientific and Industrial Organisation model; BCCR = Bergen Climate Model Version 2, ; GFDL = General Circulation Model Climate Change Model from Geophysical Fluid Dynamics Laboratory); Miroc Medres = Model for Interdiscipinary Research on Climate; BCC_CSM = Beijing Climate Center, China Meterological Administration; PCM = General Circulation Model Climate Change Model from Parallel Climate Model NA = not available Notes: Csiro developed by the Centre for Australian Weather and Climate Research BCCR developed by Bjerknes Centre for Climate Research (Norway) Miroc Medres developed by the Center for Climate System Research, Tokyo, Japan and National Institute for Environmental Studies, Ibaraki, Japan All climate variables were derived from 270 grid-cell data layers as input (precipitation and temperature) and output (snowpack, actual ET, potential ET, and CWD) from the Basin Characterization Model (BCM) (Flint and Flint, 2012; Flint and Flint, 2007) and clipped to the boundary of consideration Historic snowpack was analyzed for the period 1971-2000
Table 1. Historic and future estimated values for selected climate variables for Antioch Dunes National Wildlife Refuge using the Basin Characterization Model
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Appendix A
Figure A1. Comparison of mean October-March precipitation and temperature and July- November El Niño Southern Oscillation (SOI) for the previous year, near Antioch Dunes National Wildlife Refuge (Eureka Woodley Island Climate Station) for the period 1951– 2010 (PDO, Pacific Decadal Oscillation; ENSO, El Niño Southern Oscillation; precipitation is in inches; temperature is in degrees Fahrenheit)
Appendix B
Table B1. Climate stations on and near Antioch Dunes National Wildlife Refuge. Map Station Name Survey Name Agency/network Station Identification Period of Temporal Temporal Temporal Temporal Temporal Temporal Eleva- Number hosting data server Record resolution - resolution - resolution - resolution - resolution - resolution - tion (figure Temp Evap Precip Humidity Sol. Rad. Wind (feet) 7) Speed 1 H H H H H H Russell Road Independent Observer Independent Observer Russell_Road.P 2005-2010 10
2 H H H Eagle Point Independent Observer Independent Observer Eagle_Point-01.P 2007-2007 12
3 D D Vacaville Vacaville Fire Station NCDC VACAVLLE.C 1951- present 110
4 D D Stockton Fire Station #4 Stockton Fire Station NCDC STOCKTON.C 1951- present 12
5 Contra Costa Water D D D Antioch Pumping Plant 3 NCDC ANTIOCH.C 1955- present 60 District 6 H H H H H H San Joaquin Livermore-01 UCDIPM Livermore-01.P 2003-2009 197 WEATHERNET
7 Lodi City of Lodi NCDC LODI.C 1951- present D D D 40 8 Livermore Independent Observer NCDC LIVERMOR.C 1951- present D D 480 9 Federal Aviation H H H H Buchanan Field UOU KCCR 1997- present 23 Administration 10 Fairfield/Travis Air Force Federal Aviation H H H H UOU KSUU 1997- present 62 Base Administration 11 Livermore Municipal Federal Aviation H H H H UOU KLVK 1997- present 397 Airport Administration 12 Roddy Ranch Golf Club Contra Costa County CADWR RRG 2010- present D 403 13 Dubli-San Ramon Fire D Contra Costa County CADWR DBF 2004- present 355 House 14 San Francisco Public H San Antonio Reservoir CADWR SNV 2014- present 498 Utilities Commission 15 D Danville Library Contra Costa County CADWR DVB 2006- present 364
16 Harvey O Banks Pumping California Department H D H CADWR HBP 2008- present 4 Plant of Water Resources 17 San Joaquin River At California Department H CADWR VNI 1987-1997 0 Venice Island of Water Resources 18 California Department H Stockton Fire Station CADWR SFS 1996- present 14 of Water Resources 19 US Historical D D Vacaville NWS 49200 1893-2009 110 Climatology Network 20 US Historical D D Livermore NWS 44997 1903-2013 480 Climatology Network 21 US Historical D D Lodi NWS 45032 1893-2013 40 Climatology Network 22 California Irrigation H H H H H H Dixon Management CADWR 121 2014- present 37 Information System 23 California Irrigation H H H H H H Hastings Tract East Management CADWR 212 2009- present 7 Information System 24 California Irrigation H H H H H H Twitchell Island Management CADWR 140 1997- present -1 Information System 25 California Irrigation H H H H H H Brentwood Management CADWR 47 1985- present 45 Information System 26 California Irrigation H H H H H H Concord Management CADWR 170 2001- present 35 Information System 27 Livermore California, CA Global Historical D NCDC GHCND:USR0000CLVR 1990-2007 80 US Climatology Network 28 Global Historical D Antioch 5 S, CA US NCDC GHCND:USC00040230 1948-1950 41 Climatology Network 29 Global Historical D D D D Walnut Grove, CA US NCDC GHCND:USC00049428 1953-1961 2 Climatology Network 30 Global Historical D D Livermore, CA US NCDC GHCND:USC00044997 1953-1959 48 Climatology Network 31 Antioch Pump Plant 3, Global Historical D D D D NCDC GHCND:USC00040232 1955-1986 6 CA US Climatology Network 32 Walnut Creek 2 ENE, CA Global Historical D NCDC GHCND:USC00049426 1948-1951 22 US Climatology Network 33 Walnut Creek 2 ESE, CA Global Historical D D NCDC GHCND:USC00049423 1883-1955 15 US Climatology Network 34 Global Historical D Fairfield, CA US NCDC GHCND:USC00042933 1948-1951 2 Climatology Network 35 Global Historical D Walmar School, CA US NCDC GHCND:USC00049420 1960-1973 12 Climatology Network 36 Global Historical D Lafayette 0.7 E, CA US NCDC GHCND:US1CACC0006 2009- present 25 Climatology Network 37 Global Historical D Martinez 0.8 SSE, CA US NCDC GHCND:US1CACC0001 2008- present 25 Climatology Network 38 Walnut Creek 1.7 SSE, Global Historical D NCDC GHCND:US1CACC0004 2009- present 24 CA US Climatology Network 39 Concord Buchanan Field, Global Historical D D D NCDC GHCND:USW00023254 1999-2007 2 CA US Climatology Network 40 Pleasant Hill 1.2 ESE, CA Global Historical D NCDC GHCND:US1CACC0003 2008-2012 6 US Climatology Network 41 Global Historical D D D D Brannan Island, Ca NCDC GHCND:USC00041043 1968-1977 3 Climatology Network 42 Global Historical D Concord 3 E, CA US NCDC GHCND:USC00041962 1957-1974 19 Climatology Network 43 Global Historical D Concord 2 SE, CA US NCDC GHCND:USC00041961 1956-1957 26 Climatology Network 44 Global Historical D D Concord Airport, CA US NCDC GHCND:USC00041960 1947-1950 2 Climatology Network 45 Lafayette 1.9 WSW, CA Global Historical D NCDC GHCND:US1CACC0010 2009- present 52 US Climatology Network 46 Global Historical D Martinez 2.2 Sw, CA US NCDC GHCND:US1CACC0011 2009- present 69 Climatology Network Map Station Name Survey Name Agency/network Station Identification Period of Temporal Temporal Temporal Temporal Temporal Temporal Eleva- Number hosting data server Record resolution - resolution - resolution - resolution - resolution - resolution - tion (figure Temp Evap Precip Humidity Sol. Rad. Wind (feet) 1) Speed 47 Livermore Municipal Global Historical D D D NCDC GHCND:USW00023285 2007- present 39 Airport, CA US Climatology Network 48 Walnut Creek 1.4 NE, CA Global Historical D NCDC GHCND:US1CACC0019 2009- present 16 US Climatology Network 49 Global Historical D D D Travis Field Afb, CA US NCDC GHCND:USW00023202 1947- present 6 Climatology Network 50 Briones California, CA Global Historical D NCDC GHCND:USR0000CBRI 1994- present 145 US Climatology Network 51 Walnut Creek 1.4 SSE, Global Historical D NCDC GHCND:US1CACC0018 2009- present 28 CA US Climatology Network 52 Concord 0.8 WNW, CA Global Historical D NCDC GHCND:US1CACC0016 2009- present 12 US Climatology Network 53 Global Historical D Alamo 1.0 WSW, CA US NCDC GHCND:US1CACC0014 2009-2014 33 Climatology Network 54 Global Historical D Oakley 1.7 W, CA US NCDC GHCND:US1CACC0013 2009-2010 7 Climatology Network 55 Global Historical D D Rio Vista, CA US NCDC GHCND:USC00047446 1959-1967 2 Climatology Network 56 Antioch 2.2 WSW, CA Global Historical D NCDC GHCND:US1CACC0012 2009- present 18 US Climatology Network 57 Global Historical D D D D Mandeville Island, CA US NCDC GHCND:USC00045296 1955-1965 1 Climatology Network 58 Concord Wastewater Global Historical D D NCDC GHCND:USC00041967 2011- present 4 Plant, CA US Climatology Network 59 Global Historical D D Lafayette 2 NNE, CA US NCDC GHCND:USC00044633 1957-1977 54 Climatology Network 60 Global Historical D Antioch 2.2 SSE, CA US NCDC GHCND:US1CACC0021 2010- present 25 Climatology Network 61 Global Historical D Martinez 2 S, CA US NCDC GHCND:USC00045371 1948-1951 23 Climatology Network 62 Global Historical D Brentwood 6 SW, CA US NCDC GHCND:USC00041060 1950-1951 23 Climatology Network 63 Port Chicago Naval D, Global Historical D D NCDC GHCND:USC00047070 1946-1975 5 CA US Climatology Network 64 Antioch Fibrebrd Mil, CA Global Historical D D NCDC GHCND:USC00040227 1960-1975 3 US Climatology Network 65 Global Historical D D Crockett, CA US NCDC GHCND:USC00042177 1958-1977 1 Climatology Network 66 Global Historical D Benicia 1.2 SW, CA US NCDC GHCND:US1CASO0002 2010- present 4 Climatology Network 67 Global Historical D Benicia 0.2 SSW, CA US NCDC GHCND:US1CASO0001 2010- present 40 Climatology Network 68 Global Historical D Benicia 1.3 W, CA US NCDC GHCND:US1CASO0003 2011- present 30 Climatology Network 69 Global Historical D D Alamo 1 N, CA US NCDC GHCND:USC00040064 1957-1959 38 Climatology Network 70 Global Historical D D D D Joice Island, CA US NCDC GHCND:USC00044392 1955-1959 1 Climatology Network 71 Global Historical D Martinez 3 SSE, CA US NCDC GHCND:USC00045372 1964-1969 24 Climatology Network 72 Global Historical D D Martinez, CA US NCDC GHCND:USC00045377 1906-1953 2 Climatology Network 73 Martinez Water Plant, Global Historical D D NCDC GHCND:USC00045378 1998-2012 4 CA US Climatology Network 74 Global Historical D Alamo 1 N, CA US NCDC GHCND:USC00045000 1956-1957 45 Climatology Network 75 Global Historical D Rio Vista 8.5 S, CA US NCDC GHCND:US1CASA0021 2009- present 0 Climatology Network 76 Global Historical D Benicia 1.0 N, CA US NCDC GHCND:US1CASO0006 2012- present 25 Climatology Network Key: USGS = U.S. Geological Survey; CADWR = California Department of Water Resources; UCD = University of California Davis; IPM = Integrated Pest Management Database; USHCN = U.S. Historical Climatology Network; UOU = University of Utah; NCDC, National Climatic Data Center; NWS, National Weather Service Temp = temperature; Evap = reference evapotranspiration; Sol. Rad. = Solar Radiation H = hourly continuous; D = daily continuous; M = monthly continuous * = Inactive site Notes: Temporal resolution represents finest temporal resolution of parameter information available in digital form.
Table B2. Kruskal-Wallis non-parametric test comparing differences in the distribution of temperature and precipitation near Antioch Dunes National Wildlife Refuge, between phases of the Southern Oscillation Index, Pacific Decadal Oscillation, and Pacific North American Pattern, for the period 1951-2014, from the Livermore Climate Station (USHCN Station 44997).
October October October June through October through June through through through March September through March March PNA September March PDO PNA Index SOI Phase PDO Index Index Phase SOI Phase (El Index Phase Phase Climate variable (El Phase (Warm (Negative Nino/Neutral (Warm (Negative Nino/Neutral Phase/Neutral/ Phase/Neutral /La Nina)- Phase/Neutral Phase/Neutral/ /La Nina)-p- Cool Phase)- /Positive Chi-square /Cool Phase)- Positive Phase)- value Chi-square Phase)-Chi- p-value p-value square Precipitation (annual percent above mean for 3.52 0.17 0.90 0.64 1.20 0.55 1951-2010) Maximum temperature (mean annual in degrees 4.78 0.09 4.10 0.13 9.57 0.01 Fahrenheit) Minimum temperature (mean annual in degrees 3.76 0.15 8.09 0.02 7.58 0.02 Fahrenheit)
Key: SOI = Souther Oscillation Index; PDO = Pacific Decadal Oscillation; PNA = Pacific North American Pattern Notes: June through September SOI values were averaged for the year prior to, and October through March were average for the same year as, the annual average of precipitation and temperature values
El Nino with was assumed to be an SOI of less than or equal to -0.05, neutral phase was assumed to be an SOI between -0.05 and 0.05, and La Nina phase was assumed to be an SOI of greater than or equal to 0.05
Warm and cool phase were assumed to be negative and positive PDO index values, respectively Negative phase was assumed to be a PNA of less than or equal to -0.05, neutral phase was assumed to be a PNA between -0.05 and 0.05, and positive phase was assumed to be a PDO of greater than or equal to 0.05 Table B3. Results of time-series trend analysis of annual and seasonal precipitation and temperature from the Eureka Woodley Island climate station (station 42910) near Antioch Dunes National Wildlife Refuge.
1925- 1950- 1985- 1893- 1893- 1893-2014 1893- 1925- 1893- 2014 1925- 1950- 1950- 2014 1950- 1985- 1985- 2014 1985- Time Period/Parameters 2014 2014 p- Percent of 2014 2014 2014 p- Percent 2014 2014 2014 p- Percent 2014 2014 2014 p- Percent 2014 tau value median Median tau value of Median tau value of Median tau value of Median median median median
Annual Precipitation -0.01 0.91 -0.01 13.68 0.05 0.47 0.09 13.68 -0.03 0.71 -0.06 13.75 0.05 0.724 0.19 13.68 Max Temperature 0.41 0.00 0.03 71.50 0.29 0.00 0.03 71.87 0.41 0.00 0.05 71.95 0.24 0.059 0.07 72.81 Average Temperature 0.59 0.00 0.05 58.62 0.45 0.00 0.04 59.18 0.39 0.00 0.04 59.33 0.19 0.134 0.05 60.02 Min Temperature 0.60 0.00 0.08 45.79 0.48 0.00 0.07 46.28 0.26 0.00 0.04 46.70 0.14 0.287 0.05 46.83 Winter Precipitation -0.01 0.82 -0.03 7.33 0.01 0.89 0.03 7.19 -0.03 0.71 -0.11 7.32 -0.02 0.919 -0.30 7.30 Max Temperature 0.16 0.01 0.02 57.33 0.13 0.06 0.03 57.37 0.29 0.00 0.08 57.33 0.16 0.196 0.06 57.83 Average Temperature 0.28 0.00 0.04 47.65 0.19 0.01 0.04 47.92 0.20 0.02 0.05 48.23 0.28 0.026 0.14 48.45 Min Temperature 0.26 0.00 0.07 37.87 0.17 0.02 0.06 38.43 0.03 0.70 0.02 38.80 0.14 0.277 0.15 38.20 Spring Precipitation -0.05 0.44 -0.14 3.14 -0.01 0.89 -0.05 3.11 0.01 0.90 0.03 3.02 -0.08 0.544 -0.95 3.02 Max Temperature 0.26 0.00 0.04 68.62 0.19 0.01 0.05 69.18 0.28 0.00 0.09 69.43 0.09 0.498 0.05 71.30 Average Temperature 0.42 0.00 0.06 56.18 0.29 0.00 0.06 57.03 0.32 0.00 0.09 57.45 0.05 0.695 0.03 58.62 Min Temperature 0.48 0.00 0.09 44.33 0.35 0.00 0.07 45.13 0.32 0.00 0.08 45.23 -0.02 0.858 -0.01 45.57 Summer Precipitation 0.04 0.49 0.00 0.04 0.04 0.60 0.00 0.05 -0.04 0.64 0.00 0.06 -0.12 0.386 -0.89 0.07 Max Temperature 0.31 0.00 0.03 85.23 0.20 0.00 0.03 86.07 0.21 0.01 0.04 86.17 0.21 0.101 0.08 86.48 Average Temperature 0.51 0.00 0.05 69.18 0.39 0.00 0.05 69.97 0.29 0.00 0.04 70.48 0.21 0.097 0.06 70.90 Min Temperature 0.62 0.00 0.09 53.32 0.51 0.00 0.08 54.12 0.31 0.00 0.06 54.73 0.11 0.382 0.04 55.25 Fall Precipitation 0.07 0.25 0.20 2.06 0.11 0.14 0.42 2.12 -0.03 0.72 -0.20 2.22 -0.04 0.775 -0.38 2.12 Max Temperature 0.18 0.00 0.02 74.97 0.04 0.55 0.01 75.35 0.06 0.45 0.01 75.37 0.11 0.382 0.05 75.57 Average Temperature 0.42 0.00 0.05 61.04 0.24 0.00 0.03 61.57 0.11 0.21 0.02 61.80 0.17 0.188 0.08 61.91 Min Temperature 0.50 0.00 0.08 47.32 0.39 0.00 0.08 47.95 0.09 0.32 0.02 48.33 0.22 0.093 0.09 48.35 Cool Season Precipitation -0.01 0.88 -0.02 11.95 0.07 0.34 0.22 4.65 -0.02 0.80 -0.08 5.03 0.03 0.860 0.30 5.21 Max Temperature 0.18 0.00 0.02 62.58 0.11 0.13 0.01 76.25 0.14 0.10 0.02 76.30 0.26 0.048 0.08 76.48 Average Temperature 0.38 0.00 0.04 51.48 0.35 0.00 0.03 62.28 0.17 0.04 0.02 62.55 0.27 0.035 0.09 63.08 Min Temperature 0.43 0.00 0.07 40.47 0.46 0.00 0.07 48.37 0.16 0.06 0.03 49.05 0.23 0.074 0.10 49.07 January Precipitation -0.10 0.10 -0.31 2.39 -0.06 0.39 -0.27 2.30 -0.15 0.07 -0.89 2.23 -0.11 0.415 -1.67 1.85 Max Temperature 0.15 0.02 0.03 55.40 0.15 0.03 0.05 55.40 0.25 0.00 0.10 55.40 0.12 0.344 0.09 56.80 Average Temperature 0.19 0.00 0.05 46.10 0.19 0.01 0.06 46.50 0.20 0.02 0.08 46.65 0.15 0.253 0.08 47.38 Min Temperature 0.16 0.01 0.06 36.80 0.17 0.02 0.08 37.05 0.05 0.55 0.03 37.70 0.05 0.695 0.11 37.70 February Precipitation 0.02 0.70 0.08 2.17 -0.01 0.93 -0.03 2.22 0.07 0.39 0.41 2.20 -0.11 0.392 -1.25 2.64 Max Temperature 0.13 0.04 0.02 60.00 0.17 0.02 0.04 59.95 0.23 0.01 0.07 60.10 0.00 1.000 0.00 60.70 Average Temperature 0.19 0.00 0.04 49.68 0.17 0.02 0.05 49.75 0.14 0.09 0.05 50.10 -0.06 0.643 -0.05 50.85 Min Temperature 0.20 0.00 0.07 39.35 0.13 0.07 0.06 40.15 0.05 0.59 0.03 40.30 0.01 0.915 0.01 40.05 March Precipitation -0.05 0.44 -0.16 1.83 0.02 0.83 0.07 1.83 0.02 0.83 0.12 1.75 -0.15 0.232 -2.13 1.82 Max Temperature 0.17 0.01 0.04 63.60 0.14 0.05 0.04 63.90 0.32 0.00 0.13 63.80 0.11 0.401 0.11 66.15 Average Temperature 0.29 0.00 0.06 52.35 0.24 0.00 0.07 52.98 0.36 0.00 0.14 53.10 0.05 0.697 0.04 54.55 Min Temperature 0.34 0.00 0.09 41.45 0.27 0.00 0.09 42.00 0.30 0.00 0.12 42.20 0.03 0.803 0.03 42.75
1925- 1950- 1985- 1893- 1893- 1893-2014 1893- 1925- 1893- 2014 1925- 1950- 1950- 2014 1950- 1985- 1985- 2014 1985- Time Period/Parameters 2014 2014 p- Percent of 2014 2014 2014 p- Percent 2014 2014 2014 p- Percent 2014 2014 2014 p- Percent 2014 tau value median Median tau value of Median tau value of Median tau value of Median median median median
April Precipitation 0.03 0.61 0.12 0.71 -0.05 0.48 -0.24 0.87 -0.09 0.31 -0.52 0.88 0.14 0.276 1.77 0.61 Max Temperature 0.13 0.03 0.03 68.15 0.13 0.08 0.04 68.60 0.11 0.20 0.05 69.10 -0.14 0.276 -0.12 70.40 Average Temperature 0.26 0.00 0.05 56.08 0.18 0.01 0.05 56.43 0.12 0.16 0.04 56.85 -0.17 0.199 -0.10 57.60 Min Temperature 0.37 0.00 0.08 43.80 0.20 0.00 0.06 44.50 0.11 0.18 0.04 44.70 -0.17 0.180 -0.10 45.55 May Precipitation -0.08 0.18 -0.29 0.27 -0.06 0.41 -0.23 0.24 -0.02 0.82 0.00 0.21 -0.10 0.431 -1.36 0.32 Max Temperature 0.24 0.00 0.05 75.10 0.13 0.07 0.04 76.10 0.19 0.03 0.07 76.40 0.18 0.153 0.18 76.75 Average Temperature 0.34 0.00 0.07 61.00 0.20 0.00 0.05 62.10 0.22 0.01 0.08 62.20 0.19 0.143 0.14 63.13 Min Temperature 0.41 0.00 0.09 47.80 0.28 0.00 0.07 48.30 0.21 0.02 0.07 49.00 0.11 0.382 0.08 49.05 June Precipitation 0.04 0.55 0.00 0.01 0.03 0.71 0.00 0.01 0.00 0.96 0.00 0.03 -0.09 0.509 0.00 0.05 Max Temperature 0.21 0.00 0.04 81.65 0.14 0.05 0.03 82.00 0.19 0.03 0.07 82.00 0.15 0.261 0.10 83.25 Average Temperature 0.35 0.00 0.05 66.78 0.25 0.00 0.04 67.50 0.21 0.01 0.05 67.70 0.12 0.372 0.05 68.03 Min Temperature 0.46 0.00 0.08 51.80 0.35 0.00 0.07 52.55 0.16 0.05 0.05 52.90 0.02 0.858 0.01 53.15 July Precipitation 0.07 0.31 0.00 0.00 -0.01 0.87 0.00 0.00 -0.09 0.36 0.00 0.00 -0.29 0.062 0.00 0.00 Max Temperature 0.15 0.01 0.02 87.50 0.08 0.29 0.01 87.85 0.04 0.61 0.01 88.20 0.12 0.344 0.04 88.55 Average Temperature 0.34 0.00 0.05 70.95 0.22 0.00 0.04 71.48 0.12 0.17 0.03 71.90 0.12 0.353 0.06 71.98 Min Temperature 0.54 0.00 0.09 54.00 0.40 0.00 0.08 54.75 0.27 0.00 0.07 55.60 0.13 0.317 0.08 56.15 August Precipitation 0.07 0.32 0.00 0.00 0.04 0.67 0.00 0.00 -0.09 0.38 0.00 0.00 -0.17 0.258 0.00 0.00 Max Temperature 0.26 0.00 0.03 86.90 0.17 0.02 0.03 87.40 0.09 0.29 0.02 87.70 0.14 0.276 0.06 88.15 Average Temperature 0.45 0.00 0.05 70.30 0.35 0.00 0.05 71.18 0.22 0.01 0.04 71.65 0.22 0.086 0.07 71.95 Min Temperature 0.57 0.00 0.09 53.90 0.49 0.00 0.09 54.55 0.30 0.00 0.07 55.40 0.11 0.391 0.04 55.80 September Precipitation -0.01 0.86 0.00 0.03 0.13 0.08 0.00 0.02 -0.02 0.84 0.00 0.04 0.08 0.584 0.00 0.03 Max Temperature 0.24 0.00 0.04 84.20 0.13 0.07 0.03 84.80 0.07 0.38 0.02 84.80 0.25 0.056 0.15 85.35 Average Temperature 0.41 0.00 0.06 68.45 0.27 0.00 0.05 69.05 0.10 0.23 0.02 69.15 0.29 0.025 0.13 69.53 Min Temperature 0.50 0.00 0.09 52.60 0.39 0.00 0.08 53.15 0.12 0.17 0.03 53.80 0.33 0.011 0.15 53.85 October Precipitation 0.02 0.70 0.02 0.50 0.06 0.43 0.20 0.50 0.05 0.57 0.34 0.43 -0.03 0.816 -0.33 0.46 Max Temperature 0.16 0.01 0.03 75.60 0.03 0.69 0.01 76.40 0.03 0.76 0.01 76.40 -0.07 0.592 -0.07 76.65 Average Temperature 0.30 0.00 0.04 61.55 0.16 0.03 0.03 62.10 0.06 0.49 0.01 62.60 -0.05 0.724 -0.03 62.98 Min Temperature 0.39 0.00 0.08 47.60 0.30 0.00 0.07 48.35 0.10 0.22 0.03 48.80 -0.01 0.929 0.00 48.90 November Precipitation 0.07 0.25 0.26 1.34 0.06 0.40 0.30 1.34 -0.05 0.56 -0.44 1.41 0.01 0.915 0.21 1.35 Max Temperature -0.06 0.37 -0.01 64.70 -0.08 0.27 -0.02 64.45 0.04 0.64 0.01 64.10 0.09 0.464 0.09 64.80 Average Temperature 0.16 0.01 0.03 52.78 0.08 0.27 0.02 53.00 0.05 0.52 0.02 53.10 0.17 0.199 0.13 53.70 Min Temperature 0.32 0.00 0.09 41.05 0.23 0.00 0.09 41.75 0.04 0.61 0.02 42.20 0.19 0.148 0.18 42.30 December Precipitation 0.02 0.75 0.06 2.04 0.03 0.71 0.14 2.05 0.00 0.98 0.02 2.05 0.12 0.335 2.06 2.03 Max Temperature 0.06 0.35 0.01 56.05 0.02 0.81 0.00 56.30 0.15 0.07 0.07 56.00 0.31 0.017 0.18 56.55 Average Temperature 0.16 0.01 0.04 46.55 0.06 0.40 0.02 46.95 0.05 0.58 0.02 46.95 0.28 0.031 0.27 46.85 Min Temperature 0.21 0.00 0.07 37.10 0.08 0.29 0.04 37.40 -0.06 0.52 -0.03 37.50 0.21 0.101 0.38 37.25 Key: p-Value = probability level; tau = Kendall's tau Notes: Precipitation is measured in inches, temperature is measured in degrees Fahrenheit Results shaded in blue are statistically significant wetter/cooler trends (upward trends in precipitation and downward trends in temperature) at a p-value of 0.05 Results shaded in red are statistically significant warmer/drier trends (downward trends in precipitation and upward trends in temperature) at a p-value of 0.05