Retrospective Analysis and Bayesian Model Averaging of CMIP6 Precipitation in the Nile River Basin

Journal Article · Mon Jan 11 00:00:00 EST 2021 · Journal of Hydrometeorology

DOI:https://doi.org/10.1175/jhm-d-20-0157.1· OSTI ID:1850277

Ombadi, Mohammed ^[1]; Nguyen, Phu ^[2]; Sorooshian, Soroosh ^[3]; Hsu, Kuo-lin ^[2]

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1. Univ. of California, Irvine, CA (United States). Center for Hydrometeorology and Remote Sensing. Dept. of Civil and Environmental Engineering; Univ. of California, Irvine, CA (United States)
2. Univ. of California, Irvine, CA (United States). Center for Hydrometeorology and Remote Sensing. Dept. of Civil and Environmental Engineering
3. Univ. of California, Irvine, CA (United States). Center for Hydrometeorology and Remote Sensing. Dept. of Civil and Environmental Engineering; Univ. of California, Irvine, CA (United States). Dept. of Earth System Science

The Nile River basin is one of the global hotspots vulnerable to climate change impacts because of a fast-growing population and geopolitical tensions. Previous studies demonstrated that general circulation models (GCMs) frequently show disagreement in the sign of change in annual precipitation projections. Here, we first evaluate the performance of 20 GCMs from phase six of the Coupled Model Intercomparison Project (CMIP6) benchmarked against a high-spatial-resolution precipitation dataset dating back to 1983 from Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR). Next, a Bayesian model averaging (BMA) approach is adopted to derive probability distributions of precipitation projections in the Nile basin. Retrospective analysis reveals that most GCMs exhibit considerable (up to 64% of mean annual precipitation) and spatially heterogenous bias in simulating annual precipitation. Moreover, it is shown that all GCMs underestimate interannual variability; thus, the ensemble range is underdispersive and is a poor indicator of uncertainty. The projected changes from the BMA model show that the value and sign of change vary considerably across the Nile basin. Specifically, it is found that projected changes in the two headwaters basins, namely, the Blue Nile and Upper White Nile, are 0.03% and -1.65%, respectively; both are statistically insignificant atα= 0.05. The uncertainty range estimated from the BMA model shows that the probability of a precipitation decrease is much higher in the Upper White Nile basin whereas projected change in the Blue Nile is highly uncertain both in magnitude and sign of change.

• Research Organization: Univ. of California, Oakland, CA (United States)
• Sponsoring Organization: USDOE Office of International Affairs (IA)
• Grant/Contract Number: IA0000018
• OSTI ID: 1850277
• Journal Information: Journal of Hydrometeorology, Journal Name: Journal of Hydrometeorology Journal Issue: 1 Vol. 22; ISSN 1525-755X
• Publisher: American Meteorological Society
• Country of Publication: United States
• Language: English

Related Subjects

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
54 ENVIRONMENTAL SCIENCES
Africa
Bayesian methods
Bias
Climate models
General circulation models
Meteorology & Atmospheric Sciences
Model evaluation/performance