TY - JOUR
T1 - Shifts in Precipitation Accumulation Extremes During the Warm Season Over the United States
AU - Martinez-Villalobos, Cristian
AU - Neelin, J. David
N1 - Funding Information:
This research was supported by National Science Foundation grant AGS-1540518 and National Oceanic and Atmospheric Administration grants NA15OAR4310097 and NA14OAR4310274. U.S. hourly precipitation data are courtesy of the NOAA-NCEI Climate Data Online system https://www.ncdc.noaa.gov/cdo-web/search?datasetid=PRECIP_HLY\#. CPC US Unified Precipitation Data (Chen et al.,; Xie et al.,) provided by the NOAA/OAR?ESRL PSD, Boulder, Colorado, USA. We thank J. Meyerson for data management assistance. A portion of this work has previously been presented at an American Geophysical Union meeting (Martinez-Villalobos & Neelin,).
Funding Information:
This research was supported by National Science Foundation grant AGS-1540518 and National Oceanic and Atmospheric Administration grants NA15OAR4310097 and NA14OAR4310274. U.S. hourly precipitation data are courtesy of the NOAA-NCEI Climate Data Online system https://www.ncdc.noaa.gov/ cdo-web/search?datasetid=PRECIP_HLY\#. CPC US Unified Precipitation Data (Chen et al., 2008; Xie et al., 2007) provided by the NOAA/OAR?ESRL PSD, Boulder, Colorado, USA. We thank J. Meyerson for data management assistance. A portion of this work has previously been presented at an American Geophysical Union meeting (Martinez-Villalobos & Neelin, 2017).
Publisher Copyright:
©2018. The Authors.
PY - 2018/8/28
Y1 - 2018/8/28
N2 - Precipitation accumulations, integrated over precipitation events in hourly data, are examined from 1979 to 2013 over the contiguous United States during the warm season (May–October). As expected from theory, accumulation distributions have a characteristic shape, with an approximate power law decrease with event size followed by an exponential drop at a characteristic cutoff scale sL for each location. This cutoff is a predictor of the highest accumulation percentiles and of a similarly defined daily precipitation cutoff PL. Comparing 1997–2013 and 1979–1995 periods, there are significant regional increases in sL in several regions. This yields distribution changes that are weighted disproportionately toward extreme accumulations. In the Northeast, for example, risk ratio (conditioned on occurrence) for accumulations larger than 109 mm increases by a factor of 2–4 (5th–95th). These changes in risk ratio as a function of size, and connection to underlying theory, have counterparts in the observed daily precipitation trends.
AB - Precipitation accumulations, integrated over precipitation events in hourly data, are examined from 1979 to 2013 over the contiguous United States during the warm season (May–October). As expected from theory, accumulation distributions have a characteristic shape, with an approximate power law decrease with event size followed by an exponential drop at a characteristic cutoff scale sL for each location. This cutoff is a predictor of the highest accumulation percentiles and of a similarly defined daily precipitation cutoff PL. Comparing 1997–2013 and 1979–1995 periods, there are significant regional increases in sL in several regions. This yields distribution changes that are weighted disproportionately toward extreme accumulations. In the Northeast, for example, risk ratio (conditioned on occurrence) for accumulations larger than 109 mm increases by a factor of 2–4 (5th–95th). These changes in risk ratio as a function of size, and connection to underlying theory, have counterparts in the observed daily precipitation trends.
KW - United States
KW - daily precipitation
KW - extreme events
KW - global warming
KW - precipitation accumulations
KW - risk
UR - http://www.scopus.com/inward/record.url?scp=85053245803&partnerID=8YFLogxK
U2 - 10.1029/2018GL078465
DO - 10.1029/2018GL078465
M3 - Article
AN - SCOPUS:85053245803
SN - 0094-8276
VL - 45
SP - 8586
EP - 8595
JO - Geophysical Research Letters
JF - Geophysical Research Letters
IS - 16
ER -