TY - JOUR
T1 - Why do precipitation intensities tend to follow gamma distributions?
AU - Martinez-Villalobos, Cristian
AU - Neelin, J. David
N1 - Funding Information:
This research was supported by National Science Foundation Grant AGS-1540518 and by National Oceanic and Atmospheric Administration Grant NA18OAR4310280. Manus Island precipitation data are courtesy of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Climate Research Facility Tropical West Pacific field campaign. We thank K. Schiro for assistance with this dataset. Miami Airport, Hartford Airport and Fullerton Dam precipitation data are courtesy of the NOAA/NCEI Climate Data Online system (https://www.ncdc.noaa.gov/cdo-web/search?datasetid5PRECIP_HLY\#). We thank F. Zwiers for a postseminar question that helped motivate
Funding Information:
Acknowledgments. This research was supported by National Science Foundation Grant AGS-1540518 and by National Oceanic and Atmospheric Administration Grant NA18OAR4310280. Manus Island precipitation data are courtesy of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Climate Research Facility Tropical West Pacific field campaign. We thank K. Schiro for assistance with this dataset. Miami Airport, Hartford Airport and Fullerton Dam precipitation data are courtesy of the NOAA/NCEI Climate Data Online system (https://www.ncdc.noaa.gov/ cdo-web/search?datasetid5PRECIP_HLY\#). We thank F. Zwiers for a postseminar question that helped motivate this work and J. Meyerson for graphical assistance. A portion of this work has previously been presented at an American Physical Society meeting (Martinez-Villalobos and Neelin 2018a) and at an American Geophysical Union meeting (Martinez-Villalobos and Neelin 2018c).
Publisher Copyright:
© 2019 American Meteorological Society.
PY - 2019
Y1 - 2019
N2 - The probability distribution of daily precipitation intensities, especially the probability of extremes, impacts a wide range of applications. In most regions this distribution decays slowly with size at first, approximately as a power law with an exponent between 0 and 21, and then more sharply, for values larger than a characteristic cutoff scale. This cutoff is important because it limits the probability of extreme daily precipitation occurrences in current climate. There is a long history of representing daily precipitation using a gamma distribution—here we present theory for how daily precipitation distributions get their shape. Processes shaping daily precipitation distributions can be separated into nonprecipitating and precipitating regime effects, the former partially controlling how many times in a day it rains, and the latter set by single-storm accumulations. Using previously developed theory for precipitation accumulation distributions—which follow a sharper power-law range (exponent < 21) with a physically derived cutoff for large sizes—analytical expressions for daily precipitation distribution power-law exponent and cutoff are calculated as a function of key physical parameters. Precipitating and nonprecipitating regime processes both contribute to reducing the power-law range exponent for the daily precipitation distribution relative to the fundamental exponent set by accumulations. The daily precipitation distribution cutoff is set by the precipitating regime and scales with moisture availability, with important consequences for future distribution shifts under global warming. Similar results extend to different averaging periods, providing insight into how the precipitation intensity distribution evolves as a function of both underlying physical climate conditions and averaging time.
AB - The probability distribution of daily precipitation intensities, especially the probability of extremes, impacts a wide range of applications. In most regions this distribution decays slowly with size at first, approximately as a power law with an exponent between 0 and 21, and then more sharply, for values larger than a characteristic cutoff scale. This cutoff is important because it limits the probability of extreme daily precipitation occurrences in current climate. There is a long history of representing daily precipitation using a gamma distribution—here we present theory for how daily precipitation distributions get their shape. Processes shaping daily precipitation distributions can be separated into nonprecipitating and precipitating regime effects, the former partially controlling how many times in a day it rains, and the latter set by single-storm accumulations. Using previously developed theory for precipitation accumulation distributions—which follow a sharper power-law range (exponent < 21) with a physically derived cutoff for large sizes—analytical expressions for daily precipitation distribution power-law exponent and cutoff are calculated as a function of key physical parameters. Precipitating and nonprecipitating regime processes both contribute to reducing the power-law range exponent for the daily precipitation distribution relative to the fundamental exponent set by accumulations. The daily precipitation distribution cutoff is set by the precipitating regime and scales with moisture availability, with important consequences for future distribution shifts under global warming. Similar results extend to different averaging periods, providing insight into how the precipitation intensity distribution evolves as a function of both underlying physical climate conditions and averaging time.
UR - http://www.scopus.com/inward/record.url?scp=85075562671&partnerID=8YFLogxK
U2 - 10.1175/JAS-D-18-0343.1
DO - 10.1175/JAS-D-18-0343.1
M3 - Article
AN - SCOPUS:85075562671
SN - 0022-4928
VL - 76
SP - 3611
EP - 3631
JO - Journal of the Atmospheric Sciences
JF - Journal of the Atmospheric Sciences
IS - 11
ER -