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Title: Detected Changes in Precipitation Extremes at Their Native Scales Derived from In Situ Measurements

Abstract

The gridding of daily accumulated precipitation—especially extremes—from ground-based station observations is problematic due to the fractal nature of precipitation, and therefore estimates of long period return values and their changes based on such gridded daily datasets are generally underestimated. In this paper, we characterize high-resolution changes in observed extreme precipitation from 1950 to 2017 for the contiguous United States (CONUS) based on in situ measurements only. Our analysis utilizes spatial statistical methods that allow us to derive gridded estimates that do not smooth extreme daily measurements and are consistent with statistics from the original station data while increasing the resulting signal-to-noise ratio. Furthermore, we use a robust statistical technique to identify significant pointwise changes in the climatology of extreme precipitation while carefully controlling the rate of false positives. We present and discuss seasonal changes in the statistics of extreme precipitation: the largest and most spatially coherent pointwise changes are in fall (SON), with approximately 33% of CONUS exhibiting significant changes (in an absolute sense). Other seasons display very few meaningful pointwise changes (in either a relative or absolute sense), illustrating the difficulty in detecting pointwise changes in extreme precipitation based on in situ measurements. While our main result involves seasonalmore » changes, we also present and discuss annual changes in the statistics of extreme precipitation. In this paper we only seek to detect changes over time and leave attribution of the underlying causes of these changes for future work.« less

Authors:
 [1];  [2];  [1];  [1];  [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Univ. of California, Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1573098
Alternate Identifier(s):
OSTI ID: 1577831
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Published Article
Journal Name:
Journal of Climate
Additional Journal Information:
Journal Volume: 32; Journal Issue: 23; Journal ID: ISSN 0894-8755
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Meteorology & Atmospheric Sciences

Citation Formats

Risser, Mark D., Paciorek, Christopher J., O’Brien, Travis A., Wehner, Michael F., and Collins, William D. Detected Changes in Precipitation Extremes at Their Native Scales Derived from In Situ Measurements. United States: N. p., 2019. Web. doi:10.1175/jcli-d-19-0077.1.
Risser, Mark D., Paciorek, Christopher J., O’Brien, Travis A., Wehner, Michael F., & Collins, William D. Detected Changes in Precipitation Extremes at Their Native Scales Derived from In Situ Measurements. United States. https://doi.org/10.1175/jcli-d-19-0077.1
Risser, Mark D., Paciorek, Christopher J., O’Brien, Travis A., Wehner, Michael F., and Collins, William D. Mon . "Detected Changes in Precipitation Extremes at Their Native Scales Derived from In Situ Measurements". United States. https://doi.org/10.1175/jcli-d-19-0077.1.
@article{osti_1573098,
title = {Detected Changes in Precipitation Extremes at Their Native Scales Derived from In Situ Measurements},
author = {Risser, Mark D. and Paciorek, Christopher J. and O’Brien, Travis A. and Wehner, Michael F. and Collins, William D.},
abstractNote = {The gridding of daily accumulated precipitation—especially extremes—from ground-based station observations is problematic due to the fractal nature of precipitation, and therefore estimates of long period return values and their changes based on such gridded daily datasets are generally underestimated. In this paper, we characterize high-resolution changes in observed extreme precipitation from 1950 to 2017 for the contiguous United States (CONUS) based on in situ measurements only. Our analysis utilizes spatial statistical methods that allow us to derive gridded estimates that do not smooth extreme daily measurements and are consistent with statistics from the original station data while increasing the resulting signal-to-noise ratio. Furthermore, we use a robust statistical technique to identify significant pointwise changes in the climatology of extreme precipitation while carefully controlling the rate of false positives. We present and discuss seasonal changes in the statistics of extreme precipitation: the largest and most spatially coherent pointwise changes are in fall (SON), with approximately 33% of CONUS exhibiting significant changes (in an absolute sense). Other seasons display very few meaningful pointwise changes (in either a relative or absolute sense), illustrating the difficulty in detecting pointwise changes in extreme precipitation based on in situ measurements. While our main result involves seasonal changes, we also present and discuss annual changes in the statistics of extreme precipitation. In this paper we only seek to detect changes over time and leave attribution of the underlying causes of these changes for future work.},
doi = {10.1175/jcli-d-19-0077.1},
journal = {Journal of Climate},
number = 23,
volume = 32,
place = {United States},
year = {2019},
month = {11}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1175/jcli-d-19-0077.1

Citation Metrics:
Cited by: 8 works
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Works referenced in this record:

An Introduction to the Bootstrap
book, May 1994

  • Efron, Bradley; Tibshirani, R. J.
  • Monographs on Statistics and Applied Probability
  • DOI: 10.1201/9780429246593

Large-scale multiple testing under dependence
journal, April 2009

  • Sun, Wenguang; Tony Cai, T.
  • Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 71, Issue 2
  • DOI: 10.1111/j.1467-9868.2008.00694.x

Increased record-breaking precipitation events under global warming
journal, July 2015


A probabilistic gridded product for daily precipitation extremes over the United States
journal, February 2019

  • Risser, Mark D.; Paciorek, Christopher J.; Wehner, Michael F.
  • Climate Dynamics, Vol. 53, Issue 5-6
  • DOI: 10.1007/s00382-019-04636-0

Observations: Atmosphere and Surface
book, March 2014


The remarkable wide range spatial scaling of TRMM precipitation
journal, October 2008


The efficacy of using gridded data to examine extreme rainfall characteristics: a case study for Australia: GRIDDED RAINFALL EXTREMES IN AUSTRALIA
journal, September 2012

  • King, Andrew D.; Alexander, Lisa V.; Donat, Markus G.
  • International Journal of Climatology, Vol. 33, Issue 10
  • DOI: 10.1002/joc.3588

Monitoring and Understanding Trends in Extreme Storms: State of Knowledge
journal, April 2013

  • Kunkel, Kenneth E.; Karl, Thomas R.; Brooks, Harold
  • Bulletin of the American Meteorological Society, Vol. 94, Issue 4
  • DOI: 10.1175/BAMS-D-11-00262.1

Encoding daily rainfall records via adaptations of the fractal multifractal method
journal, December 2015

  • Maskey, M. L.; Puente, C. E.; Sivakumar, B.
  • Stochastic Environmental Research and Risk Assessment, Vol. 30, Issue 7
  • DOI: 10.1007/s00477-015-1201-7

Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: The HadEX2 dataset: HADEX2-GLOBAL GRIDDED CLIMATE EXTREMES
journal, March 2013

  • Donat, M. G.; Alexander, L. V.; Yang, H.
  • Journal of Geophysical Research: Atmospheres, Vol. 118, Issue 5
  • DOI: 10.1002/jgrd.50150

False Discovery Control for Random Fields
journal, December 2004

  • Perone Pacifico, M.; Genovese, C.; Verdinelli, I.
  • Journal of the American Statistical Association, Vol. 99, Issue 468
  • DOI: 10.1198/0162145000001655

Rapid attribution of the August 2016 flood-inducing extreme precipitation in south Louisiana to climate change
journal, January 2017

  • van der Wiel, Karin; Kapnick, Sarah B.; van Oldenborgh, Geert Jan
  • Hydrology and Earth System Sciences, Vol. 21, Issue 2
  • DOI: 10.5194/hess-21-897-2017

North American Trends in Extreme Precipitation
journal, June 2003


Spatially Dependent Multiple Testing Under Model Misspecification, With Application to Detection of Anthropogenic Influence on Extreme Climate Events
journal, June 2018

  • Risser, Mark D.; Paciorek, Christopher J.; Stone, Dáithí A.
  • Journal of the American Statistical Association, Vol. 114, Issue 525
  • DOI: 10.1080/01621459.2018.1451335

Representing Extremes in a Daily Gridded Precipitation Analysis over the United States: Impacts of Station Density, Resolution, and Gridding Methods
journal, July 2014


Spatial analysis of variations in precipitation intensity in the USA
journal, October 2010

  • Balling, Robert C.; Goodrich, Gregory B.
  • Theoretical and Applied Climatology, Vol. 104, Issue 3-4
  • DOI: 10.1007/s00704-010-0353-0

Observational- and model-based trends and projections of extreme precipitation over the contiguous United States: JANSSEN ET AL.
journal, February 2014

  • Janssen, Emily; Wuebbles, Donald J.; Kunkel, Kenneth E.
  • Earth's Future, Vol. 2, Issue 2
  • DOI: 10.1002/2013EF000185

An evaluation of the consistency of extremes in gridded precipitation data sets
journal, January 2019


A probabilistic gridded product for daily precipitation extremes over the United States
journal, February 2019

  • Risser, Mark D.; Paciorek, Christopher J.; Wehner, Michael F.
  • Climate Dynamics, Vol. 53, Issue 5-6
  • DOI: 10.1007/s00382-019-04636-0

An Overview of the Global Historical Climatology Network-Daily Database
journal, July 2012

  • Menne, Matthew J.; Durre, Imke; Vose, Russell S.
  • Journal of Atmospheric and Oceanic Technology, Vol. 29, Issue 7
  • DOI: 10.1175/JTECH-D-11-00103.1

False discovery control in large-scale spatial multiple testing
journal, April 2014

  • Sun, Wenguang; Reich, Brian J.; Tony Cai, T.
  • Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 77, Issue 1
  • DOI: 10.1111/rssb.12064

Statistics of Extremes
journal, April 2015


The Influence of Large-Scale Climate Variability on Winter Maximum Daily Precipitation over North America
journal, June 2010

  • Zhang, Xuebin; Wang, Jiafeng; Zwiers, Francis W.
  • Journal of Climate, Vol. 23, Issue 11
  • DOI: 10.1175/2010JCLI3249.1

The effect of correlation in false discovery rate estimation
journal, February 2011


Global Increasing Trends in Annual Maximum Daily Precipitation
journal, June 2013


Spatially-Dependent Multiple Testing Under Model Misspecification, with Application to Detection of Anthropogenic Influence on Extreme Climate Events [Supplemental Data]
fileset, April 2018

  • Risser, Mark D.; Paciorek, Christopher J.
  • figshare-Supplementary information for journal article at DOI: 10.1080/01621459.2018.1451335, 3 files
  • DOI: 10.6084/m9.figshare.6075758.v1

On the Verification and Comparison of Extreme Rainfall Indices from Climate Models
journal, April 2008


Trends in Intense Precipitation in the Climate Record
journal, May 2005

  • Groisman, Pavel Ya; Knight, Richard W.; Easterling, David R.
  • Journal of Climate, Vol. 18, Issue 9
  • DOI: 10.1175/JCLI3339.1

under dependency
journal, August 2001