Meteorological Causes of the Secular Variations in Observed Extreme PrecipitationEvents for the Conterminous United States

KENNETH E. KUNKEL,*,1,#,@ DAVID R. EASTERLING,1 DAVID A. R. KRISTOVICH,# BYRON GLEASON,1

LESLIE STOECKER,# AND REBECCA SMITH#,&

* Cooperative Institute for Climate and Satellites North Carolina, North Carolina State University, Asheville, North Carolina1 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 cyclone near a front (FRT), extratropical cyclone near

center of low (ETC), tropical cyclone (TC), mesoscale convective system (MCS), air mass (isolated) con-

vection (AMC), North American monsoon (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

cyclones, 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

Numerous studies have documented increases in U.S.

extreme precipitation during the latter part of the twen-

tieth century (e.g., Groisman et al. 2004, 2005; Kunkel

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

events, exceeding a threshold for a 1-in-5-yr occurrence

(Kunkel et al. 2010). They found that an anomalously

high number of events caused by TCs accounted for over

one-third of the overall national annual anomaly during

the period of 1994–2008. Knight and Davis (2009) also

found increases in TC-caused events using another defi-

nition of extreme precipitation. The meteorological

causes of the remaining extreme precipitation events

have not been identified. This paper describes the results

of a comprehensive analysis of the meteorological cau-

ses of secular variations in extreme precipitation event

frequencies.

2. Methods

A set of 935 long-term National Weather Service

Cooperative Observer (COOP) stations used for a series

of recent studies was employed in this project. Daily

extreme precipitation events were identified for each

station based on exceedance of the threshold amount for

a 1-in-5-yr recurrence interval over the period of 1895–

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

of 3646 stations, with records spanning the shorter pe-

riod of 1950–2010, was used in this figure to better il-

lustrate the spatial variations). Because of large spatial

variations in station density (see Kunkel et al. 2003, their

Fig. 1), the station data were used to create a 18 3 18

gridded dataset of extreme precipitation events to

& Current affiliation: Department of Atmospheric Sciences,

Colorado State University, Fort Collins, Colorado.

Corresponding author address: Kenneth E. Kunkel, National

Climatic Data Center, 151 Patton Avenue, Asheville, NC 28801.

E-mail: ken.kunkel@noaa.gov

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

DOI: 10.1175/JHM-D-11-0108.1

� 2012 American Meteorological Society

achieve more even representation of areas. Grid ‘‘events’’

are defined as the number of events divided by the

number of stations in each grid box. If all stations in

a grid box experienced a qualifying event on a particu-

lar day, the assigned value for that grid box event was

1.0. Otherwise, the value is the fraction of stations ex-

periencing an event. Both the gridded and station da-

tasets were used for the following classification and

analysis efforts.

The COOP dataset is a quite reliable source to eval-

uate trends in precipitation extremes. The observation

equipment (8-in. gauge) and observational procedures

have remained constant since the late nineteenth cen-

tury. There are sources of errors, including recording

or digitization errors. However, such errors tend to be

random and thus are not a source of bias in trends.

Furthermore, Kunkel et al. (2005) subjected the data to

a number of quality control processes to detect and cor-

rect suspect values. There has been a shift over time in

the relative number of stations taking their observations

in the morning versus late afternoon. This is known to

have an effect on temperature trends, but it is not known

whether the distribution of precipitation values is af-

fected. Any such effects could alter daily values but are

not likely to affect multiday distributions. In the Kunkel

et al. (2003) study, they found that overall trends were

similar whether looking at daily amounts or 5-day ac-

cumulations. Thus, we do not expect that there are any

overall trend biases arising from this shift.

The ‘‘precipitation’’ reports from COOP stations in-

clude liquid precipitation or liquid equivalent if all or

part of the precipitation is frozen. The identification of

extreme events used the precipitation reports and thus

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.

For example, satellite data were not used to classify me-

soscale convective systems (MCSs) since such data are

only available from the 1960s onward.

The first step was to identify spatially contiguous pre-

cipitation regions (CPR) for each day using the daily

gridded dataset of precipitation values that was gener-

ated from all COOP data. The CPRs were defined by

finding the grid box with the greatest precipitation for

each day and then searching for adjacent grid boxes

with daily precipitation values greater than 12.5 mm.

This search was continued until the values were lower

than that threshold. The resulting region consists of

contiguous grid boxes with precipitation greater than

12.5 mm, entirely surrounded by grid boxes with pre-

cipitation less than 12.5 mm. All of the boxes greater

than the 12.5 mm threshold are part of the CPR. This

process was repeated until all the grid boxes with pre-

cipitation greater than 12.5 mm were assigned to a CPR.

The intent of this process was that CPRs represented

areas where the precipitation resulted from the same

cause throughout the CPR and thus a single evaluation

would identify the cause for more than one station event.

The somewhat arbitrary threshold was determined em-

pirically by testing the results of the algorithm to identi-

fy unique CPRs with a range of thresholds on a small

number of days with widespread precipitation. Although

the extreme event threshold varies widely across the

United States (Fig. 1), the selected fixed threshold of

12.5 mm resulted in CPRs similar to those identified by

experts. In climatologically drier regions, some CPRs

may not be identified by use of a fixed threshold. How-

ever, the only consequence of this is to increase the

number of evaluations; there is no impact on the final

results.

All COOP sites exhibiting extreme precipitation for

a given day were assigned to the CPR in which their grid

box resided. This allowed multiple extreme precipitation

FIG. 1. Spatial distribution of the threshold value of the daily,

1-in-5-yr precipitation amount for 3646 stations with less than 10%

missing data for the period of 1950–2010.

1132 J O U R N A L O F H Y D R O M E T E O R O L O G Y VOLUME 13

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

pressure and temperature maps for the days with the

extreme events. Surface pressure maps were computed

from two different sources depending on the time pe-

riod. One is a recent reanalysis effort that utilizes only

surface pressure for input and thus is able to extend back

into the nineteenth century (Compo et al. 2006, 2011;

Whitaker et al. 2004); this source was used for events

occurring prior to 1948. When the classification of events

began, the reanalysis data only extended back to 1908

and this year was chosen as the initial year of analysis.

For events occurring in 1948 and thereafter, NCEP–

NCAR reanalysis data (Kalnay et al. 1996) were used;

this reanalysis, which incorporates a much more exten-

sive input dataset, was used so that future more in-depth

analyses (e.g., upper-air patterns and thermodynamic

conditions) could be performed on post-1948 extreme

events if desired. Since the surface pressure patterns

used in the classifications are constrained by surface

pressure observations and both reanalyses use the same

set of pressure observations, their patterns should be

very similar. Daily average surface pressure maps for the

day before, the day of, and the day after the CPR were

plotted (Fig. 3). The grid boxes of the CPRs were also

overlaid on the maps. The temperature maps were made

in the same format (Fig. 4), using the same COOP grid-

ded dataset as was used for the precipitation regions.

In addition to the pressure and temperature maps,

NOAA U.S. Daily Weather Maps were included in the

classification process. Winds were nearly always avail-

able on these maps. In the 1940s, frontal systems were

added which allowed an ‘‘agreement checking’’ mech-

anism. Beyond this, cloud cover and dewpoint temper-

ature observations were available for some years.

Using all these data, the extreme event CPRs were

classified by cause. For the 1908–2009 period analyzed,

there were 18 322 individual events that were aggregated

into 9746 CPRs. The CPRs were divided into yearly

groups, and then the order of completion for the years

was randomized to avoid trends due to any biases arising

from changes over time in the expert judgment process.

The CPRs needing classification were mainly divided

between two individuals, although unclear cases were

considered in conference calls with all the project team

individuals (authors of this paper). A large amount of

collaboration occurred between the two individuals to

help remove most of the bias due to differing decision

processes.

The potential causes of the extreme precipitation

events were classified into one of the following seven

categories: extratropical cyclones (ETCs), fronts (FRTs),

North American monsoon (NAM), isolated thunder-

storms occurring in convectively unstable air masses

that will be denoted as air mass convection (AMC),

MCSs, upslope flow precipitation (USF), and TCs. There

were certain characteristics that were needed for each

category. Fronts are usually associated with ETCs, so

these categories are connected. The CPRs caused by

fronts were one of the easiest to define. These required

a temperature gradient that aligned approximately per-

pendicular to the long axis of the CPR. Frontal cases

were also determined by wind shifts, local minima in the

pressure fields, and changes in the dewpoint tempera-

tures, if available, on the daily weather maps. ETC cases

were defined as such when an event occurred in close

proximity to the low pressure system center and was

not aligned with a temperature gradient. Events such as

winter west coast storms and nor’easters usually fell

into this category. Categorization as an NAM event was

subject to several constraints. First, the event had to occur

FIG. 2. Example of the precipitation maps used during the classi-

fication process. This shows locations of high-precipitation amounts

(over 20 mm) that are within a CPR on 10 May 1981. The large dots

indicate precipitation measurements greater than 20 mm and within

the CPR. Actual locations of the grid boxes within the CPR are given

in Fig. 3.

JUNE 2012 K U N K E L E T A L . 1133

in the southwestern part of the United States and be as-

sociated with widespread precipitation in that region.

Second, time of occurrence was generally limited to the

months of June–September. Additional indicators of an

NAM event were low pressure near the Baja California

peninsula or high pressure near Colorado or Utah. Air

mass convection (Brooks et al. 2003) events were defined

as being very small—one or two grid cells— and occur-

ring in warm areas and times of year. Station proximity

to mountains and airflow toward these mountains were

needed for a CPR to be classified as upslope. The MCS

category needed to be separated from frontal systems.

While many MCSs are initialized along frontal bound-

aries (either surface or aloft), they frequently move away

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.

1134 J O U R N A L O F H Y D R O M E T E O R O L O G Y VOLUME 13

as intensification occurs. In practice, the events that were

classified as MCSs were characterized by moderate-to-

strong southerly winds but not always by anomalously

warm temperatures. Because mesoscale convective com-

plexes (MCCs) are a category of MCS, steps were taken

to understand and identify these events based on data

available for the present study. To aid in learning how

to identify MCCs, the MCCs observed and documented

in 1981 (Maddox et al. 1982), 1982 (Rodgers et al. 1983),

1983 (Rodgers et al. 1985), 1985 (Augustine and Howard

1988), 1986/87 (Augustine and Howard 1991), 1992/93

(Anderson and Arritt 1998), and 1997/98 (Anderson and

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.

JUNE 2012 K U N K E L E T A L . 1135

Arritt 2001) were examined in temperature anomaly and

pressure maps as well as the daily weather maps. The

majority of the events identified in these studies did not

coincide with heavy precipitation events, so they could

not be used to make classifications of events used in the

present study. Even with this learning process, it should

be noted that an event was often classified as an MCS if

no other category was appropriate.

An automated process for determining many of the

TC-caused extreme events was used. The National

Hurricane Center’s hurricane database archive (HURDAT;

Jarvinen et al. 1984; Neumann et al. 1999) was used in the

automation. If the extreme event was 58 or less away from

the track of a documented tropical cyclone center in

HURDAT for a given day, the event was classified as TC.

Over 1200 extreme precipitation events caused by At-

lantic or eastern Pacific TCs were categorized through

this automated process. Some tropical cyclone events

were not captured by the automation but were found

through the manual analysis. When tropical cyclones

interacted with extratropical systems, the classification

decision was based on location of the extreme event

with regard to the tropical cyclone and the frontal system.

A tropical cyclone was deemed extratropical when it

developed frontal characteristics.

Occasionally, multiple categories could be identified

as potential causes of a CPR. This could be due to either

insufficient data to fully determine the cause or could be

due to multiple processes giving rise to an event. In these

cases, a single category was chosen, reflecting the most

likely cause or the apparent primary cause. A hierarchy

was used in determining the primary causes. These de-

cisions were typically based on the forcing mechanism

scale, with the largest scales identified as the primary

causes. For example, frontal systems were normally given

priority when an event was also associated with another

mechanism. Some CPRs that were classified as frontal

events appeared to have been affected by ETC, AMC,

USF, or MCS occurrence as well. The second priority

cause was ETC. It was usually easily determined if the

heavy event was near the center of the low, and thus

classified as an ETC event. A combination of NAM,

USF, MCS, and AMC could have occurred to cause

heavy-event CPRs at certain times in the Southwest

(SW) United States. If a heavy precipitation event in

the SW United States was within widespread rainfall

accompanied by an appropriate flow and pressure fields,

it was classified as NAM even though the other classifi-

cations could have played a role. When the criteria for

NAM events were not present, the forcing factors present

were evaluated based on the other classification types.

When small-scale isolated CPRs occurred, AMC was

chosen. On the other hand, if the flow was perpendicular

to the mountains in that area, the CPR was determined

to be USF. Convection, especially on a larger scale, is

a significant cause of heavy precipitation, but many times

would not form without the influence of the other clas-

sification types. If no other classification was present and

convection looked reasonable, MCS was typically chosen

as the final cause of the heavy event.

Once the classification was finished for all the CPRs,

the cause associated with a specific CPR was assigned

to all of the individual gridbox extreme precipitation

events in that CPR.

3. Results

The following results are all based on the ‘‘grid event’’

data, which should minimize bias that would otherwise

arise because of the uneven spatial distribution of sta-

tions. The largest single cause of extreme precipitation

events in the United States was found to be frontal, ac-

counting for about 54% of all grid events. ETCs are

associated with 24% of the events, followed by tropical

cyclones at 13% and MCSs at 5%. About 3% of the

events are associated with NAM and 1% with air mass

convection. Only about 0.3% of the events were found

to be caused primarily by upslope flow.

The spatial variability in causes is illustrated in Fig. 5a,

which shows the annual percentage breakdown for the

primary causes in each of the nine climate regions de-

fined by Karl and Knight (1998). Generally only the

causes accounting for the highest percentages are listed;

thus, the percentages do not add to 100%. In addition,

in the case of those causes that are minor in a national

context (USF, AMC, NAM, and TC), percentages are

given for those regions where they most frequently oc-

cur. In the Northwest (NW) and West (W) regions,

ETCs account for 80% or more of the events, with FRTs

accounting for most of the rest. The FRT category is the

dominant cause in the remaining regions with the ex-

ception of the Southeast (SE), where TCs are the most

frequent cause. In the continental interior regions of the

West North Central (WNC) and East North Central

(ENC), the combination of FRTs and ETCs account for

around 90% or more of the events, with MCSs the third

more frequent cause. TCs are a prominent cause in the

Northeast (NE; 36%) and South (S; 17%) and also

contribute in the Central (C, 9%) and SW (3%). The

NAM is responsible for 21% of the events in the SW.

The minor categories of AMC and USF occur primarily

in the SE (2%) and SW (2%), respectively.

It should be noted that the percentages for FRT, ETC,

and TC are somewhat inflated, since the largest-scale

cause was chosen for events with multiple possible causes.

However, these events with multiple apparent causes

1136 J O U R N A L O F H Y D R O M E T E O R O L O G Y VOLUME 13

were infrequent. The effect of this hierarchical process,

therefore, is thought to be minimal in most locations.

However, a few regions may be significantly influenced.

For example, clear frontal signatures were often not

present in the W and NW regions—due in part to the

complex topography and limited over-ocean observations.

Events associated with ETCs and associated frontal sys-

tems were generally classified as ETCs in these regions.

The seasonal progression of the regional results is

shown in Figs. 5b–e. The total percentage of events

FIG. 5. Maps of regional and seasonal contributions of major extreme event causes for (a) annual, (b) winter

[December–February (DJF)], (c) spring [March–May (MAM)], (d) summer [June–August (JJA)], and (e) autumn

[September–November (SON)]. In the seasonal maps, the underlined values are the percentages of total events

occurring in that season; the values next to the causes are the percentages of total seasonal number of events.

JUNE 2012 K U N K E L E T A L . 1137

occurring in the winter (Fig. 5b) is high in the W and

NW; quite low in the SW, S, C, NE, and SE; and in-

significant in the interior regions of WNC and ENC.

ETCs are the dominant cause in the western regions

(W, NW, and SW) and FRTs are the primary cause

elsewhere. In the spring (Fig. 5c), the total percentages

of events increase, relative to winter, in all regions ex-

cept the NW and W. The most frequently occurring

causes remain the same except in the SW, where the

FRT category replaces ETCs. MCSs make contribu-

tions in the S (14%), C (4%), and SE (8%). AMCs

make a minor contribution in the SE (3%). The sum-

mer percentages (Fig. 5d) are the highest of the four

seasons in the WNC (61%), ENC (66%), C (44%), SW

(43%), and the NE (46%); the lowest in the NW (16%)

and the W (4%); and the causes are the most varied in

all regions except the NW. FRTs remain the dominant

category in the SW (44%), WNC (70%), ENC (79%),

C (73%), S (51%), and NE (49%). TCs are the domi-

nant cause in the SE (58%) and the second most fre-

quent cause in the S (26%) and NE (35%). NAM

events are nearly as frequent (41%) as FRT events in the

SW. The MCS category is the second most frequent in

the ENC (10%) and C (13%) and third most frequent

in the WNC (3%), S (15%), and SE (9%). USF events

occur most frequently in the summer in the SW (3%).

The fall season (Fig. 5e) total percentages are highest of

the four seasons in the SE (46%)—where TCs are by far

the largest contributor (71%)—and the S (35%). Total

percentages are second highest in the NE (44%),

S (35%), SW (35%), C (29%), ENC (23%), NW (32%),

and W (19%). TCs are also the dominant fall contributor

in the NE (44%) and second highest in the S (22%) and

C (18%).

The daily gridbox events were first summed for each

grid box for each year (the result representing the num-

ber of events per station for each year in each grid box),

then arithmetically averaged for each cause for each year,

for the United States as a whole and for each region.

Figures 6 and 7 show time series of the annual averages

for each cause. It should be noted that the vertical scales

are different between these two figures, illustrating the

differing relative frequencies of the causes. There is a

sizeable upward trend in the number of events caused by

fronts (Fig. 6). There is also an upward trend in the events

caused by tropical cyclones, as was discussed in Kunkel

et al. (2010) and section 2. For the five other causes, there

is not an overall trend.

Table 1 gives the magnitude and statistical signifi-

cance of the trends for each meteorological cause and

nine regions defined by Karl and Knight (1998). Figure 8

shows the time series for the frontal category for the

nine regions. Statistically significant upward trends in

the frontal category are found in five of the nine regions

(Table 1): NE, ENC, C, WNC, and S.

For the six causes other than frontal, regional trends

are not statistically significant, with the following ex-

ceptions (Table 1). For ETCs, there are statistically sig-

nificant upward trends in the NE and ENC. For the NAM

(monsoon) category, the trend in the West is upward. The

Central region has seen an upward trend in events caused

by tropical cyclones.

Given the overall upward trend in total events and in

events caused by fronts and tropical cyclones, a question

arises whether there are more systems causing extreme

events or whether there are more extreme events per

system. Figure 9 shows a time series of the total annual

number of CPRs with at least one extreme event and

FIG. 6. Annual time series of the number of extreme events per

station caused by ETCs (blue), fronts (red), and tropical cyclones

(green).

FIG. 7. Annual time series of the number of extreme events per

station caused by NAM (blue), convectively unstable air masses

(red), MCSs (orange), and USF (green).

1138 J O U R N A L O F H Y D R O M E T E O R O L O G Y VOLUME 13

of the average annual number of events in each CPR.

There is a statistically significant (at the p 5 0.01 level)

upward trend in each of these. The slope is 1.8% per

decade for the number of events per CPR and 2.4% per

decade for the total number of CPRs with extreme

events. A closer examination indicates that the time

series for the total number of CPRs with extremes is

characterized by a step increase around 1940 and, in

fact, the trend since 1940 is not statistically significant.

However, the number of events per CPR, while ex-

hibiting substantial interannual variability, is quasi-

linear and the trend is statistically significant both for

the entire period and the period after 1940. Although

the above analysis examined the overall statistics for all

extremes, the results for the frontally caused events is

similar (not shown). The number of events per CPR for

tropical cyclone events (Fig. 10) is approximately double

that for all CPRs identified in this study, and also ex-

hibits a statistically (at the p 5 0.01 level) significant

increase.

4. Summary

The assignment of a meteorological cause to the thou-

sands of extreme events was a very large undertaking, but

has now been completed for the period of 1908–2009.

These results are based on consistently applied defini-

tions of causes described earlier and the ability to identify

the causes from the available data. The following key

points were identified:

d The largest single cause of extreme precipitation

events in the United States was found to be frontal,

accounting for about 54% of all grid events.d ETCs are associated with 24% of the events, followed

by tropical cyclones at 13% and MCSs at 5%. About

3% of the events are associated with NAM and 1% with

air mass convection. Only about 0.3% of the events

were found to be caused primarily by upslope flow.d In the Northwest and West regions, ETCs account for

80% or more of the events. The FRT category is the

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 — — — —

FIG. 8. Decadal time series of the number of extreme events per

station caused by fronts for the nine climate regions.

FIG. 9. Time series of the (a) annual number of extreme events

per CPR (black) and (b) the annual number of CPRs having at least

one extreme event (red).

JUNE 2012 K U N K E L E T A L . 1139

dominant cause in the remaining regions with the

exception of the Southeast, where TCs are the most

frequent cause. MCSs are the third most frequent cause in

the West North Central and East North Central. TCs are

a prominent cause in the Northeast and South. The NAM

is responsible for 21% of the events in the Southwest. The

minor categories of AMC and USF occur primarily in

the Southeast (2%) and Southwest (2%), respectively.d The upward trends appear to be primarily driven by

increases in events caused by fronts and tropical

cyclones. Statistically significant upward trends in the

frontal category are found in five of the nine regions,

mainly in central and northern regions.d 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.d The Central region has seen an upward trend in events

caused by tropical cyclones. Landfalling tropical cy-

clones have not increased (Kunkel et al. 2008, their

Fig. 2.17), while the number of events per contiguous

precipitation region associated with TCs has increased.

It is not known whether there is a trend in extratropical

cyclone frequency (and associated fronts), but is the

subject of a separate investigation.

The potential role of water vapor trends is also being

investigated.

Acknowledgments. This work was partially supported

by National Oceanic and Atmospheric Administration

Climate Program Office award NA07OAR4310063. We

thank Anthony Arguez for helpful discussions during

project planning. Any opinions, findings, and conclusions

are those of the authors and do not necessarily reflect the

views of NOAA or the institutions for which they work.

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