Understanding the Cascade: Removing GCM Biases Improves Dynamically Downscaled Climate Projections
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- Univ. of California, Los Angeles, CA (United States); Univ. of Wyoming, Laramie, WY (United States)
- Univ. of California, Los Angeles, CA (United States)
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Univ. of Oklahoma, Norman, OK (United States)
Polarization surrounding bias correction (BC) in creating climate projections arises from its lack of physicality. Here, we perform and analyze 18 dynamical downscaling simulations (with and without BC) to better understand the physical impacts of BC, applied before downscaling, on regional climate output across the western United States. Without BC, downscaled precipitation is systematically and unrealistically wet biased compared to a hierarchy of observationally based datasets over the 1980–2014 period due to cascading mean–state Global Climate Model (GCM) biases: (a) overly strong lower–tropospheric lapse rates (5 K/km), (b) overly cold (2 K) tropospheric temperatures, and (c) anomalous mid–tropospheric cyclonic vorticity advection. With BC, downscaled precipitation (snow) biases are virtually eliminated (halved). Identified GCM biases are common to the broader Coupled Model Intercomparison Project ensemble. Physical effects of BC on the quality of the regionalized projections, pending an evaluation of BC's distortion of the downscaled climate response, may motivate its broader application by dynamical downscalers.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- Grant/Contract Number:
- AC02-05CH11231
- OSTI ID:
- 2447709
- Journal Information:
- Geophysical Research Letters, Journal Name: Geophysical Research Letters Journal Issue: 9 Vol. 51; ISSN 0094-8276
- Publisher:
- American Geophysical Union (AGU)Copyright Statement
- Country of Publication:
- United States
- Language:
- English
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