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Title: Evaluation of CMIP5 continental precipitation simulations relative to satellite-based gauge-adjusted observations

Journal Article · · Journal of Geophysical Research: Atmospheres
DOI:https://doi.org/10.1002/2013JD021152· OSTI ID:1227015
 [1];  [1];  [2]
  1. Univ. of California, Irvine, CA (United States). Dept. of Civil and Environmental Engineering
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
+ Show Author Affiliations

Numerous studies have emphasized that climate simulations are subject to various biases and uncertainties. The objective of this study is to cross-validate 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of precipitation against the Global Precipitation Climatology Project (GPCP) data, quantifying model pattern discrepancies and biases for both entire data distributions and their upper tails. The results of the Volumetric Hit Index (VHI) analysis of the total monthly precipitation amounts show that most CMIP5 simulations are in good agreement with GPCP patterns in many areas, but that their replication of observed precipitation over arid regions and certain sub-continental regions (e.g., northern Eurasia, eastern Russia, central Australia) is problematical. Overall, the VHI of the multi-model ensemble mean and median also are superior to that of the individual CMIP5 models. However, at high quantiles of reference data (e.g., the 75th and 90th percentiles), all climate models display low skill in simulating precipitation, except over North America, the Amazon, and central Africa. Analyses of total bias (B) in CMIP5 simulations reveal that most models overestimate precipitation over regions of complex topography (e.g. western North and South America and southern Africa and Asia), while underestimating it over arid regions. Also, while most climate model simulations show low biases over Europe, inter-model variations in bias over Australia and Amazonia are considerable. The Quantile Bias (QB) analyses indicate that CMIP5 simulations are even more biased at high quantiles of precipitation. Lastly, we found that a simple mean-field bias removal improves the overall B and VHI values, but does not make a significant improvement in these model performance metrics at high quantiles of precipitation.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE; United States Bureau of Reclamation (USBR); National Science Foundation (NSF)
Grant/Contract Number:
AC52-07NA27344; R11AP81451; OISE-1243543
OSTI ID:
1227015
Report Number(s):
LLNL-JRNL-635873
Journal Information:
Journal of Geophysical Research: Atmospheres, Vol. 119, Issue 4; ISSN 2169-897X
Publisher:
American Geophysical UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 162 works
Citation information provided by
Web of Science

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Influence of winter season climate variability on snow-precipitation ratio in the western United States: Influence of winter season climate variability on snow-fraction journal November 2015
Low-level circulation and precipitation simulated by CMIP5 GCMS over southeastern South America journal August 2018
Assessment of seven CMIP5 model precipitation extremes over Iran based on a satellite‐based climate data set
  • Katiraie‐Boroujerdy, Pari‐Sima; Akbari Asanjan, Ata; Chavoshian, Ali
  • International Journal of Climatology, Vol. 39, Issue 8 https://doi.org/10.1002/joc.6035
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Projected changes in modified Thornthwaite climate zones over Southwest Asia using a CMIP5 multi‐model ensemble journal April 2019
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Projected spatial patterns in precipitation and air temperature for China's northwest region derived from high‐resolution regional climate models journal December 2019
Precipitation in the Karakoram-Himalaya: a CMIP5 view journal October 2014
Impact of model resolution on simulating the water vapor transport through the central Himalayas: implication for models’ wet bias over the Tibetan Plateau journal January 2018
An evaluation of the consistency of extremes in gridded precipitation data sets journal January 2019
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Sensitivity of the projected hydroclimatic environment of the Delaware River basin to formulation of potential evapotranspiration journal September 2016
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The CAMS Climate System Model and a Basic Evaluation of Its Climatology and Climate Variability Simulation journal December 2018
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Climate change and vector-borne diseases: what are the implications for public health research and policy?
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Projected increases in magnitude and socioeconomic exposure of global droughts in 1.5 and 2 °C warmer climates journal January 2020

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54 ENVIRONMENTAL SCIENCES
58 GEOSCIENCES
precipitation
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