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JUNE 2012 K U N K E L E T A L . 1131

Meteorological Causes of the Secular Variations in Observed Extreme Events for the Conterminous

,1,#,@ 1 # 1 KENNETH E. KUNKEL,* DAVID R. EASTERLING, DAVID A. R. KRISTOVICH, BYRON GLEASON, # #,& LESLIE STOECKER, AND REBECCA SMITH * Cooperative Institute for and Satellites , North Carolina State University, Asheville, North Carolina 1 National Oceanic and Atmospheric Administration/National Climatic Data Center, Asheville, North Carolina # Illinois State Water Survey, Prairie Research Institute, University of Illinois at Urbana–Champaign, Champaign, Illinois @ Division of Atmospheric Sciences, Desert Research Institute, Reno, Nevada

(Manuscript received 30 August 2011, in final form 2 December 2011)

ABSTRACT

Daily extreme precipitation events, exceeding a threshold for a 1-in-5-yr occurrence, were identified from a network of 935 Cooperative Observer stations for the period of 1908–2009. Each event was assigned a meteorological cause, categorized as extratropical near a front (FRT), extratropical cyclone near center of low (ETC), (TC), mesoscale convective system (MCS), (isolated) con- vection (AMC), North American (NAM), and upslope flow (USF). The percentage of events as- cribed to each cause were 54% for FRT, 24% for ETC, 13% for TC, 5% for MCS, 3% for NAM, 1% for AMC, and 0.1% for USF. On a national scale, there are upward trends in events associated with fronts and tropical , but no trends for other meteorological causes. On a regional scale, statistically significant upward trends in the frontal category are found in five of the nine regions. For ETCs, there are statistically significant upward trends in the Northeast and east north central. For the NAM category, the trend in the West is upward. The central region has seen an upward trend in events caused by TCs.

1. Introduction causes of the remaining extreme precipitation events have not been identified. This paper describes the results Numerous studies have documented increases in U.S. of a comprehensive analysis of the meteorological cau- extreme precipitation during the latter part of the twen- ses of secular variations in extreme precipitation event tieth century (e.g., Groisman et al. 2004, 2005; Kunkel frequencies. et al. 2003, 2007). A recent paper examined the potential contribution of tropical cyclones (TCs) to the observed trends in the occurrence of daily extreme precipitation 2. Methods events, exceeding a threshold for a 1-in-5-yr occurrence A set of 935 long-term National Service (Kunkel et al. 2010). They found that an anomalously Cooperative Observer (COOP) stations used for a series high number of events caused by TCs accounted for over of recent studies was employed in this project. Daily one-third of the overall national annual anomaly during extreme precipitation events were identified for each the period of 1994–2008. Knight and Davis (2009) also station based on exceedance of the threshold amount for found increases in TC-caused events using another defi- a 1-in-5-yr recurrence interval over the period of 1895– nition of extreme precipitation. The meteorological 2009. The threshold varies widely across the United States from around 25 mm in parts of the interior west to around 200 mm along the Gulf Coast (Fig. 1; a larger set & Current affiliation: Department of Atmospheric Sciences, of 3646 stations, with records spanning the shorter pe- Colorado State University, Fort Collins, Colorado. riod of 1950–2010, was used in this figure to better il- lustrate the spatial variations). Because of large spatial Corresponding author address: Kenneth E. Kunkel, National variations in station density (see Kunkel et al. 2003, their Climatic Data Center, 151 Patton Avenue, Asheville, NC 28801. Fig. 1), the station data were used to create a 18318 E-mail: [email protected] gridded dataset of extreme precipitation events to

DOI: 10.1175/JHM-D-11-0108.1

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some extremes may be snowfall events. An analysis of snowfall data coincident with the precipitation reports indicated that just over 2% of the extreme station events were due wholly or partially to snowfall. Manual analysis as well as one automated process was used to determine the causes of the extreme precipitation events. It was decided at the beginning of the project that only data that are available through the entire study pe- riod would be used, so as to limit bias over time since more observation sites are available later in the time period. Because of these constraints, only pressure (from two reanalyses sources) and temperature data as well as the National Oceanic and Atmospheric Administration (NOAA) U.S. Daily Weather Map Series (http://docs.lib. noaa.gov/rescue/dwm/data_rescue_daily_weather_maps. html) were used to supplement the precipitation records. FIG. 1. Spatial distribution of the threshold value of the daily, For example, satellite data were not used to classify me- 1-in-5-yr precipitation amount for 3646 stations with less than 10% soscale convective systems (MCSs) since such data are missing data for the period of 1950–2010. only available from the 1960s onward. The first step was to identify spatially contiguous pre- achieve more even representation of areas. Grid ‘‘events’’ cipitation regions (CPR) for each day using the daily are defined as the number of events divided by the gridded dataset of precipitation values that was gener- number of stations in each grid box. If all stations in ated from all COOP data. The CPRs were defined by a grid box experienced a qualifying event on a particu- finding the grid box with the greatest precipitation for lar day, the assigned value for that grid box event was each day and then searching for adjacent grid boxes 1.0. Otherwise, the value is the fraction of stations ex- with daily precipitation values greater than 12.5 mm. periencing an event. Both the gridded and station da- This search was continued until the values were lower tasets were used for the following classification and than that threshold. The resulting region consists of analysis efforts. contiguous grid boxes with precipitation greater than The COOP dataset is a quite reliable source to eval- 12.5 mm, entirely surrounded by grid boxes with pre- uate trends in precipitation extremes. The observation cipitation less than 12.5 mm. All of the boxes greater equipment (8-in. gauge) and observational procedures than the 12.5 mm threshold are part of the CPR. This have remained constant since the late nineteenth cen- process was repeated until all the grid boxes with pre- tury. There are sources of errors, including recording cipitation greater than 12.5 mm were assigned to a CPR. or digitization errors. However, such errors tend to be The intent of this process was that CPRs represented random and thus are not a source of bias in trends. areas where the precipitation resulted from the same Furthermore, Kunkel et al. (2005) subjected the data to cause throughout the CPR and thus a single evaluation a number of quality control processes to detect and cor- would identify the cause for more than one station event. rect suspect values. There has been a shift over time in The somewhat arbitrary threshold was determined em- the relative number of stations taking their observations pirically by testing the results of the algorithm to identi- in the morning versus late afternoon. This is known to fy unique CPRs with a range of thresholds on a small have an effect on temperature trends, but it is not known number of days with widespread precipitation. Although whether the distribution of precipitation values is af- the extreme event threshold varies widely across the fected. Any such effects could alter daily values but are United States (Fig. 1), the selected fixed threshold of not likely to affect multiday distributions. In the Kunkel 12.5 mm resulted in CPRs similar to those identified by et al. (2003) study, they found that overall trends were experts. In climatologically drier regions, some CPRs similar whether looking at daily amounts or 5-day ac- may not be identified by use of a fixed threshold. How- cumulations. Thus, we do not expect that there are any ever, the only consequence of this is to increase the overall trend biases arising from this shift. number of evaluations; there is no impact on the final The ‘‘precipitation’’ reports from COOP stations in- results. clude liquid precipitation or liquid equivalent if all or All COOP sites exhibiting extreme precipitation for part of the precipitation is frozen. The identification of a given day were assigned to the CPR in which their grid extreme events used the precipitation reports and thus box resided. This allowed multiple extreme precipitation

Unauthenticated | Downloaded 10/01/21 11:08 PM UTC JUNE 2012 K U N K E L E T A L . 1133 events caused by a single meteorological system to be classified together. A few COOP sites with extreme events could not be assigned because the grid box containing the station had a grid-averaged precipitation value less than 12.5 mm. These events were compared to precipitation maps for that day. If it still did not appear to be connected to any other substantial precipitation, the cooperative station observer forms, the Climato- logical Data publication, and other nearby cooperative station observations were double checked to determine if the extreme event was in fact real. The coordinates of the CPRs and COOP sites were then used to plot precipitation maps (Fig. 2). From these, the shape, size, spatial orientation, and other surrounding CPRs aided in the classification of the events. The second step was to produce daily average surface FIG. 2. Example of the precipitation maps used during the classi- pressure and temperature maps for the days with the fication process. This shows locations of high-precipitation amounts (over 20 mm) that are within a CPR on 10 May 1981. The large dots extreme events. Surface pressure maps were computed indicate precipitation measurements greater than 20 mm and within from two different sources depending on the time pe- the CPR. Actual locations of the grid boxes within the CPR are given riod. One is a recent reanalysis effort that utilizes only in Fig. 3. surface pressure for input and thus is able to extend back into the nineteenth century (Compo et al. 2006, 2011; groups, and then the order of completion for the years Whitaker et al. 2004); this source was used for events was randomized to avoid trends due to any biases arising occurring prior to 1948. When the classification of events from changes over time in the expert judgment process. began, the reanalysis data only extended back to 1908 The CPRs needing classification were mainly divided and this year was chosen as the initial year of analysis. between two individuals, although unclear cases were For events occurring in 1948 and thereafter, NCEP– considered in conference calls with all the project team NCAR reanalysis data (Kalnay et al. 1996) were used; individuals (authors of this paper). A large amount of this reanalysis, which incorporates a much more exten- collaboration occurred between the two individuals to sive input dataset, was used so that future more in-depth help remove most of the bias due to differing decision analyses (e.g., upper-air patterns and thermodynamic processes. conditions) could be performed on post-1948 extreme The potential causes of the extreme precipitation events if desired. Since the surface pressure patterns events were classified into one of the following seven used in the classifications are constrained by surface categories: extratropical cyclones (ETCs), fronts (FRTs), pressure observations and both reanalyses use the same (NAM), isolated thunder- set of pressure observations, their patterns should be occurring in convectively unstable air masses very similar. Daily average surface pressure maps for the that will be denoted as air mass (AMC), day before, the day of, and the day after the CPR were MCSs, upslope flow precipitation (USF), and TCs. There plotted (Fig. 3). The grid boxes of the CPRs were also were certain characteristics that were needed for each overlaid on the maps. The temperature maps were made category. Fronts are usually associated with ETCs, so in the same format (Fig. 4), using the same COOP grid- these categories are connected. The CPRs caused by ded dataset as was used for the precipitation regions. fronts were one of the easiest to define. These required In addition to the pressure and temperature maps, a that aligned approximately per- NOAA U.S. Daily Weather Maps were included in the pendicular to the long axis of the CPR. Frontal cases classification process. were nearly always avail- were also determined by shifts, local minima in the able on these maps. In the 1940s, frontal systems were pressure fields, and changes in the dewpoint tempera- added which allowed an ‘‘agreement checking’’ mech- tures, if available, on the daily weather maps. ETC cases anism. Beyond this, cover and dewpoint temper- weredefinedassuchwhenaneventoccurredinclose ature observations were available for some years. proximity to the low center and was Using all these data, the extreme event CPRs were not aligned with a temperature gradient. Events such as classified by cause. For the 1908–2009 period analyzed, west coast storms and nor’easters usually fell there were 18 322 individual events that were aggregated into this category. Categorization as an NAM event was into 9746 CPRs. The CPRs were divided into yearly subject to several constraints. First, the event had to occur

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FIG. 3. Example of the surface pressure maps used in the classification of the contiguous precipitation regions. The pressure data comes from the NCEP–NCAR reanalysis dataset (Kalnay et al. 1996). The boxes indicate a CPR that occurred on 10 May 1981. in the southwestern part of the United States and be as- as being very small—one or two grid cells— and occur- sociated with widespread precipitation in that region. ring in warm areas and times of year. Station proximity Second, time of occurrence was generally limited to the to mountains and airflow toward these mountains were months of June–September. Additional indicators of an needed for a CPR to be classified as upslope. The MCS NAM event were low pressure near the Baja California category needed to be separated from frontal systems. peninsula or high pressure near Colorado or Utah. Air While many MCSs are initialized along frontal bound- mass convection (Brooks et al. 2003) events were defined aries (either surface or aloft), they frequently move away

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FIG. 4. Example of the surface temperature maps used during the classification of CPRs. The temperature data were derived from gridded COOP observations, and the boxes indicate the location of the CPR. The CPR occurred on 10 May 1981. Blue (red) colors indicate large negative (positive) anomalies and green indicates near-zero anomalies. as intensification occurs. In practice, the events that were available for the present study. To aid in learning how classified as MCSs were characterized by moderate-to- to identify MCCs, the MCCs observed and documented strong southerly winds but not always by anomalously in 1981 (Maddox et al. 1982), 1982 (Rodgers et al. 1983), warm temperatures. Because mesoscale convective com- 1983 (Rodgers et al. 1985), 1985 (Augustine and Howard plexes (MCCs) are a category of MCS, steps were taken 1988), 1986/87 (Augustine and Howard 1991), 1992/93 to understand and identify these events based on data (Anderson and Arritt 1998), and 1997/98 (Anderson and

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Arritt 2001) were examined in temperature anomaly and to the mountains in that area, the CPR was determined pressure maps as well as the daily weather maps. The to be USF. Convection, especially on a larger scale, is majority of the events identified in these studies did not a significant cause of heavy precipitation, but many times coincide with heavy precipitation events, so they could would not form without the influence of the other clas- not be used to make classifications of events used in the sification types. If no other classification was present and present study. Even with this learning process, it should convection looked reasonable, MCS was typically chosen be noted that an event was often classified as an MCS if as the final cause of the heavy event. no other category was appropriate. Once the classification was finished for all the CPRs, An automated process for determining many of the the cause associated with a specific CPR was assigned TC-caused extreme events was used. The National to all of the individual gridbox extreme precipitation Hurricane Center’s hurricane database archive (HURDAT; events in that CPR. Jarvinen et al. 1984; Neumann et al. 1999) was used in the automation. If the extreme event was 58 or less away from 3. Results the track of a documented tropical cyclone center in HURDAT for a given day, the event was classified as TC. The following results are all based on the ‘‘grid event’’ Over 1200 extreme precipitation events caused by At- data, which should minimize bias that would otherwise lantic or eastern Pacific TCs were categorized through arise because of the uneven spatial distribution of sta- this automated process. Some tropical cyclone events tions. The largest single cause of extreme precipitation were not captured by the automation but were found events in the United States was found to be frontal, ac- through the manual analysis. When tropical cyclones counting for about 54% of all grid events. ETCs are interacted with extratropical systems, the classification associated with 24% of the events, followed by tropical decision was based on location of the extreme event cyclones at 13% and MCSs at 5%. About 3% of the with regard to the tropical cyclone and the frontal system. events are associated with NAM and 1% with air mass A tropical cyclone was deemed extratropical when it convection. Only about 0.3% of the events were found developed frontal characteristics. to be caused primarily by upslope flow. Occasionally, multiple categories could be identified The spatial variability in causes is illustrated in Fig. 5a, as potential causes of a CPR. This could be due to either which shows the annual percentage breakdown for the insufficient data to fully determine the cause or could be primary causes in each of the nine climate regions de- due to multiple processes giving rise to an event. In these fined by Karl and Knight (1998). Generally only the cases, a single category was chosen, reflecting the most causes accounting for the highest percentages are listed; likely cause or the apparent primary cause. A hierarchy thus, the percentages do not add to 100%. In addition, was used in determining the primary causes. These de- in the case of those causes that are minor in a national cisions were typically based on the forcing mechanism context (USF, AMC, NAM, and TC), percentages are scale, with the largest scales identified as the primary given for those regions where they most frequently oc- causes. For example, frontal systems were normally given cur. In the Northwest (NW) and West (W) regions, priority when an event was also associated with another ETCs account for 80% or more of the events, with FRTs mechanism. Some CPRs that were classified as frontal accounting for most of the rest. The FRT category is the events appeared to have been affected by ETC, AMC, dominant cause in the remaining regions with the ex- USF, or MCS occurrence as well. The second priority ception of the Southeast (SE), where TCs are the most cause was ETC. It was usually easily determined if the frequent cause. In the continental interior regions of the heavy event was near the center of the low, and thus West North Central (WNC) and East North Central classified as an ETC event. A combination of NAM, (ENC), the combination of FRTs and ETCs account for USF, MCS, and AMC could have occurred to cause around 90% or more of the events, with MCSs the third heavy-event CPRs at certain times in the Southwest more frequent cause. TCs are a prominent cause in the (SW) United States. If a heavy precipitation event in Northeast (NE; 36%) and South (S; 17%) and also the SW United States was within widespread rainfall contribute in the Central (C, 9%) and SW (3%). The accompanied by an appropriate flow and pressure fields, NAM is responsible for 21% of the events in the SW. it was classified as NAM even though the other classifi- The minor categories of AMC and USF occur primarily cations could have played a role. When the criteria for in the SE (2%) and SW (2%), respectively. NAM events were not present, the forcing factors present It should be noted that the percentages for FRT, ETC, were evaluated based on the other classification types. and TC are somewhat inflated, since the largest-scale When small-scale isolated CPRs occurred, AMC was cause was chosen for events with multiple possible causes. chosen. On the other hand, if the flow was perpendicular However, these events with multiple apparent causes

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FIG. 5. Maps of regional and seasonal contributions of major extreme event causes for (a) annual, (b) winter [December–February (DJF)], (c) [March–May (MAM)], (d) [June–August (JJA)], and (e) [September–November (SON)]. In the seasonal maps, the underlined values are the percentages of total events occurring in that ; the values next to the causes are the percentages of total seasonal number of events. were infrequent. The effect of this hierarchical process, complex topography and limited over- observations. therefore, is thought to be minimal in most locations. Events associated with ETCs and associated frontal sys- However, a few regions may be significantly influenced. tems were generally classified as ETCs in these regions. For example, clear frontal signatures were often not The seasonal progression of the regional results is present in the W and NW regions—due in part to the shown in Figs. 5b–e. The total percentage of events

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FIG. 6. Annual time series of the number of extreme events per FIG. 7. Annual time series of the number of extreme events per station caused by ETCs (blue), fronts (red), and tropical cyclones station caused by NAM (blue), convectively unstable air masses (green). (red), MCSs (orange), and USF (green). occurring in the winter (Fig. 5b) is high in the W and The daily gridbox events were first summed for each NW; quite low in the SW, S, C, NE, and SE; and in- grid box for each year (the result representing the num- significant in the interior regions of WNC and ENC. ber of events per station for each year in each grid box), ETCs are the dominant cause in the western regions then arithmetically averaged for each cause for each year, (W, NW, and SW) and FRTs are the primary cause for the United States as a whole and for each region. elsewhere. In the spring (Fig. 5c), the total percentages Figures 6 and 7 show time series of the annual averages of events increase, relative to winter, in all regions ex- for each cause. It should be noted that the vertical scales cept the NW and W. The most frequently occurring are different between these two figures, illustrating the causes remain the same except in the SW, where the differing relative frequencies of the causes. There is a FRT category replaces ETCs. MCSs make contribu- sizeable upward trend in the number of events caused by tions in the S (14%), C (4%), and SE (8%). AMCs fronts (Fig. 6). There is also an upward trend in the events make a minor contribution in the SE (3%). The sum- caused by tropical cyclones, as was discussed in Kunkel mer percentages (Fig. 5d) are the highest of the four et al. (2010) and section 2. For the five other causes, there in the WNC (61%), ENC (66%), C (44%), SW is not an overall trend. (43%), and the NE (46%); the lowest in the NW (16%) Table 1 gives the magnitude and statistical signifi- and the W (4%); and the causes are the most varied in cance of the trends for each meteorological cause and all regions except the NW. FRTs remain the dominant nine regions defined by Karl and Knight (1998). Figure 8 category in the SW (44%), WNC (70%), ENC (79%), shows the time series for the frontal category for the C (73%), S (51%), and NE (49%). TCs are the domi- nine regions. Statistically significant upward trends in nant cause in the SE (58%) and the second most fre- the frontal category are found in five of the nine regions quent cause in the S (26%) and NE (35%). NAM (Table 1): NE, ENC, C, WNC, and S. events are nearly as frequent (41%) as FRT events in the For the six causes other than frontal, regional trends SW. The MCS category is the second most frequent in are not statistically significant, with the following ex- the ENC (10%) and C (13%) and third most frequent ceptions (Table 1). For ETCs, there are statistically sig- in the WNC (3%), S (15%), and SE (9%). USF events nificant upward trends in the NE and ENC. For the NAM occur most frequently in the summer in the SW (3%). (monsoon) category, the trend in the West is upward. The The fall season (Fig. 5e) total percentages are highest of Central region has seen an upward trend in events caused the four seasons in the SE (46%)—where TCs are by far by tropical cyclones. the largest contributor (71%)—and the S (35%). Total Given the overall upward trend in total events and in percentages are second highest in the NE (44%), events caused by fronts and tropical cyclones, a question S (35%), SW (35%), C (29%), ENC (23%), NW (32%), arises whether there are more systems causing extreme and W (19%). TCs are also the dominant fall contributor events or whether there are more extreme events per in the NE (44%) and second highest in the S (22%) and system. Figure 9 shows a time series of the total annual C (18%). number of CPRs with at least one extreme event and

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TABLE 1. Trends (events per station per year) for extreme precipitation events associated with each meteorological cause for the nine National Climatic Data Center (NCDC) climate regions based on linear least squares regression. All values are 3 1024. Significance noted at p 5 0.10, 0.05, and 0.01 are shown with bold, italic, and bold italic, respectively. Blanks indicate there were no heavy events associated with that particular meteorological cause in that region.

Region ETC Frontal Monsoon Air mass MCS Upslope TC Northeast 0.420 0.395 — 0.009 20.006 — 0.594 East North Central 0.144 0.845 — 0.005 0.002 — 0.038 Central 0.036 0.897 — 20.006 20.010 — 0.304 Southeast 0.074 0.361 — 20.022 20.045 — 0.723 West North Central 20.247 1.11 0.002 20.036 0.028 20.022 — South 0.033 1.64 0.020 0.026 0.097 — 0.406 Southwest 20.303 20.038 0.225 0.020 0.007 0.003 20.644 Northwest 0.399 20.038 — — — 20.022 — West 0.123 0.327 0.063 ———— of the average annual number of events in each CPR. 4. Summary There is a statistically significant (at the p 5 0.01 level) The assignment of a meteorological cause to the thou- upward trend in each of these. The slope is 1.8% per sands of extreme events was a very large undertaking, but decade for the number of events per CPR and 2.4% per has now been completed for the period of 1908–2009. decade for the total number of CPRs with extreme These results are based on consistently applied defini- events. A closer examination indicates that the time tions of causes described earlier and the ability to identify seriesforthetotalnumberofCPRswithextremesis the causes from the available data. The following key characterized by a step increase around 1940 and, in points were identified: fact, the trend since 1940 is not statistically significant. However, the number of events per CPR, while ex- d The largest single cause of extreme precipitation hibiting substantial interannual variability, is quasi- events in the United States was found to be frontal, linear and the trend is statistically significant both for accounting for about 54% of all grid events. the entire period and the period after 1940. Although d ETCs are associated with 24% of the events, followed the above analysis examined the overall statistics for all by tropical cyclones at 13% and MCSs at 5%. About extremes, the results for the frontally caused events is 3% of the events are associated with NAM and 1% with similar (not shown). The number of events per CPR for air mass convection. Only about 0.3% of the events tropical cyclone events (Fig. 10) is approximately double were found to be caused primarily by upslope flow. that for all CPRs identified in this study, and also ex- d In the Northwest and West regions, ETCs account for hibits a statistically (at the p 5 0.01 level) significant 80% or more of the events. The FRT category is the increase.

FIG. 9. Time series of the (a) annual number of extreme events FIG. 8. Decadal time series of the number of extreme events per per CPR (black) and (b) the annual number of CPRs having at least station caused by fronts for the nine climate regions. one extreme event (red).

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REFERENCES

Anderson, C. J., and R. W. Arritt, 1998: Mesoscale convective complexes and persistent elongated convective systems over the United States during 1992 and 1993. Mon. Wea. Rev., 126, 578–599. ——, and ——, 2001: Mesoscale convective complexes over the United States during the 1997–98 El Nin˜ o. Mon. Wea. Rev., 129, 2443–2457. Augustine, J. A., and K. W. Howard, 1988: Mesoscale convective complexes over the United States during 1985. Mon. Wea. Rev., 116, 685–701. ——, and ——, 1991: Mesoscale convective complexes over the United States during 1986 and 1987. Mon. Wea. Rev., 119, 1575–1589. Brooks, H., and Coauthors, 2003: Severe and torna- does. Handbook of Weather, Climate, and Water: Dynamics, Climate, Physical , Weather Systems, and Mea- surements, T. D. Potter and B. R. Colman, Eds., John Wiley and FIG. 10. Time series of the annual number of extreme events per CPR associated with a tropical cyclone. Sons, 575–619. Compo, G. P., J. S. Whitaker, and P. D. Sardeshmukh, 2006: Fea- sibility of a 100-year reanalysis using only surface pressure dominant cause in the remaining regions with the data. Bull. Amer. Meteor. Soc., 87, 175–190. ——, and Coauthors, 2011: The Twentieth Century Reanalysis pro- exception of the Southeast, where TCs are the most ject. Quart. J. Roy. Meteor. Soc., 137, 1–28, doi:10.1002/qj.776. frequent cause. MCSs are the third most frequent cause in Groisman, P. Ya., R. W. Knight, T. R. Karl, D. R. Easterling, B. the West North Central and East North Central. TCs are Sun, and J. H. Lawrimore, 2004: Contemporary changes of the a prominent cause in the Northeast and South. The NAM hydrological cycle over the contiguous United States: Trends is responsible for 21% of the events in the Southwest. The derived from in situ observations. J. Hydrometeor., 5, 64–85. minor categories of AMC and USF occur primarily in ——, ——, D. R. Easterling, T. R. Karl, G. C. Hegerl, and V. N. Razuvaev, 2005: Trends in intense precipitation in the climate the Southeast (2%) and Southwest (2%), respectively. record. J. Climate, 18, 1326–1350. d The upward trends appear to be primarily driven by Jarvinen, B. R., C. J. Neumann, and M. A. S. Davis, 1984: A increasesineventscausedbyfrontsandtropical tropical cyclone data tape for the North Atlantic Basin, 1886- cyclones. Statistically significant upward trends in the 1983: Contents, limitations, and uses. NOAA Tech. Memo. frontal category are found in five of the nine regions, NWS NHC 22, 21 pp. Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Re- mainly in central and northern regions. analysis Project. Bull. Amer. Meteor. Soc., 77, 437–471. d For ETCs, there are statistically significant upward Karl, T. R., and R. W. Knight, 1998: Secular trends of precipitation trends in the Northeast and East North Central. For amount, frequency, and intensity in the United States. Bull. the NAM category, the trend in the West is upward. Amer. Meteor. Soc., 79, 1107–1119. d The Central region has seen an upward trend in events Knight, D. B., and R. E. Davis, 2009: Contribution of tropical cyclones caused by tropical cyclones. Landfalling tropical cy- to extreme rainfall events in the southeastern United States. J. Geophys. Res., 114, D23102, doi:10.1029/2009JD012511. clones have not increased (Kunkel et al. 2008, their Kunkel, K. E., D. R. Easterling, K. Redmond, and K. Hubbard, Fig. 2.17), while the number of events per contiguous 2003: Temporal variations of extreme precipitation events in precipitation region associated with TCs has increased. the United States: 1895–2000. Geophys. Res. Lett., 30, 1900, It is not known whether there is a trend in extratropical doi:10.1029/2003GL018052. cyclone frequency (and associated fronts), but is the ——, ——, K. Hubbard, K. Redmond, K. Andsager, M. Kruk, and M. Spinar, 2005: Quality control of pre-1948 cooperative ob- subject of a separate investigation. server network data. J. Atmos. Oceanic Technol., 22, 1691–1705. The potential role of water vapor trends is also being ——, T. R. Karl, and D. R. Easterling, 2007: A Monte Carlo as- sessment of uncertainties in heavy precipitation frequency investigated. variations. J. Hydrometeor., 8, 1152–1160. ——, and Coauthors, 2008: Observed changes in weather and cli- Acknowledgments. This work was partially supported mate extremes. Weather and climate extremes in a changing by National Oceanic and Atmospheric Administration climate: Regions of focus: North America, Hawaii, Caribbean, Climate Program Office award NA07OAR4310063. We and U.S. Pacific Islands, T. R. Karl et al., Eds., U.S. Climate thank Anthony Arguez for helpful discussions during Change Science Program and Subcommittee on Global Change Research Rep., Synthesis and Assessment Product project planning. Any opinions, findings, and conclusions 3.3, , DC, 35–80. are those of the authors and do not necessarily reflect the ——, D. R. Easterling, D. A. R. Kristovich, B. Gleason, L. Stoecker, views of NOAA or the institutions for which they work. and R. Smith, 2010: Recent increases in U.S. heavy precipitation

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associated with tropical cyclones. Geophys. Res. Lett., 37, Rodgers, D. M., K. W. Howard, and E. C. Johnson, 1983: Mesoscale L24706, doi:10.1029/2010GL045164. convective complexes over the United States during 1982. Mon. Maddox, R. A., D. M. Rodgers, and K. W. Howard, 1982: Meso- Wea. Rev., 111, 2363–2369. scale convective complexes over the United States during ——, M. J. Magnano, and J. H. Arns, 1985: Mesoscale convective 1981—Annual summary. Mon. Wea. Rev., 110, 1501–1514. complexes over the United States during 1983. Mon. Wea. Neumann, C. J., B. R. Jarvinen, C. J. McAdie, and G. R. Hammer, Rev., 113, 888–901. 1999: Tropical cyclones of the North Atlantic Ocean, 1871– Whitaker, J. S., G. P. Compo, X. Wei, and T. M. Hamill, 2004: 1999. NOAA/NWS/NESDIS Historical Climatology Series Reanalysis without radiosondes using ensemble data assimi- 6-2, 206 pp. lation. Mon. Wea. Rev., 132, 1190–1200.

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