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W. J. Gutowski Jr.
,
P. A. Ullrich
,
A. Hall
,
L. R. Leung
,
T. A. O’Brien
,
C. M. Patricola
,
R. W. Arritt
,
M. S. Bukovsky
,
K. V. Calvin
,
Z. Feng
,
A. D. Jones
,
G. J. Kooperman
,
E. Monier
,
M. S. Pritchard
,
S. C. Pryor
,
Y. Qian
,
A. M. Rhoades
,
A. F. Roberts
,
K. Sakaguchi
,
N. Urban
, and
C. Zarzycki
Full access
W. J. Gutowski Jr
,
P. A. Ullrich
,
A. Hall
,
L. R. Leung
,
T. A. O’Brien
,
C. M. Patricola
,
R. W. Arritt
,
M. S. Bukovsky
,
K. V. Calvin
,
Z. Feng
,
A. D. Jones
,
G. J. Kooperman
,
E. Monier
,
M. S. Pritchard
,
S. C. Pryor
,
Y. Qian
,
A. M. Rhoades
,
A. F. Roberts
,
K. Sakaguchi
,
N. Urban
, and
C. Zarzycki

ABSTRACT

Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions.

Free access
D. R. Feldman
,
A. C. Aiken
,
W. R. Boos
,
R. W. H. Carroll
,
V. Chandrasekar
,
S. Collis
,
J. M. Creamean
,
G. de Boer
,
J. Deems
,
P. J. DeMott
,
J. Fan
,
A. N. Flores
,
D. Gochis
,
M. Grover
,
T. C. J. Hill
,
A. Hodshire
,
E. Hulm
,
C. C. Hume
,
R. Jackson
,
F. Junyent
,
A. Kennedy
,
M. Kumjian
,
E. J. T. Levin
,
J. D. Lundquist
,
J. O’Brien
,
M. S. Raleigh
,
J. Reithel
,
A. Rhoades
,
K. Rittger
,
W. Rudisill
,
Z. Sherman
,
E. Siirila-Woodburn
,
S. M. Skiles
,
J. N. Smith
,
R. C. Sullivan
,
A. Theisen
,
M. Tuftedal
,
A. C. Varble
,
A. Wiedlea
,
S. Wielandt
,
K. Williams
, and
Z. Xu

Abstract

The science of mountainous hydrology spans the atmosphere through the bedrock and inherently crosses physical and disciplinary boundaries: land–atmosphere interactions in complex terrain enhance clouds and precipitation, while watersheds retain and release water over a large range of spatial and temporal scales. Limited observations in complex terrain challenge efforts to improve predictive models of the hydrology in the face of rapid changes. The Upper Colorado River exemplifies these challenges, especially with ongoing mismatches between precipitation, snowpack, and discharge. Consequently, the U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility has deployed an observatory to the East River Watershed near Crested Butte, Colorado, between September 2021 and June 2023 to measure the main atmospheric drivers of water resources, including precipitation, clouds, winds, aerosols, radiation, temperature, and humidity. This effort, called the Surface Atmosphere Integrated Field Laboratory (SAIL), is also working in tandem with DOE-sponsored surface and subsurface hydrologists and other federal, state, and local partners. SAIL data can be benchmarks for model development by producing a wide range of observational information on precipitation and its associated processes, including those processes that impact snowpack sublimation and redistribution, aerosol direct radiative effects in the atmosphere and in the snowpack, aerosol impacts on clouds and precipitation, and processes controlling surface fluxes of energy and mass. Preliminary data from SAIL’s first year showcase the rich information content in SAIL’s many datastreams and support testing hypotheses that will ultimately improve scientific understanding and predictability of Upper Colorado River hydrology in 2023 and beyond.

Open access