Effects of soot-induced snow albedo change on snowpack and hydrological cycle in western United States based on Weather Research and Forecasting chemistry and regional climate simulations

AbstractUnderstanding future precipitation changes is critical for water supply and flood risk applications in the western United States. The North American COordinated Regional Downscaling EXperiment (NA-CORDEX) matrix of global and regional climate models at multiple resolutions (~ 50-km and 25-km grid spacings) is used to evaluate mean monthly precipitation, extreme daily precipitation, and snow water equivalent (SWE) over the western United States, with a sub-regional focus on California. Results indicate significant model spread in mean monthly precipitation in several key water-sensitive areas in both historical and future projections, but suggest model agreement on increasing daily extreme precipitation magnitudes, decreasing seasonal snowpack, and a shortening of the wet season in California in particular. While the beginning and end of the California cool season are projected to dry according to most models, the core of the cool season (December, January, February) shows an overall wetter projected change pattern. Daily cool-season precipitation extremes generally increase for most models, particularly in California in the mid-winter months. Finally, a marked projected decrease in future seasonal SWE is found across all models, accompanied by earlier dates of maximum seasonal SWE, and thus a shortening of the period of snow cover as well. Results are discussed in the context of how the diverse model membership and variable resolutions offered by the NA-CORDEX ensemble can be best leveraged by stakeholders faced with future water planning challenges.

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CORDEX-WRF v1.3: development of a module for the Weather Research and Forecasting (WRF) model to support the CORDEX community

Geoscientific Model Development ◽

10.5194/gmd-12-1029-2019 ◽

2019 ◽

Vol 12 (3) ◽

pp. 1029-1066 ◽

Cited By ~ 2

Author(s):

Lluís Fita ◽

Jan Polcher ◽

Theodore M. Giannaros ◽

Torge Lorenz ◽

Josipa Milovac ◽

...

Keyword(s):

Regional Climate ◽

Regional Scale ◽

Wrf Model ◽

Data Access ◽

Quality Data ◽

Weather Research And Forecasting ◽

Time Step ◽

Mitigation And Adaptation ◽

Data Requirements ◽

Weather Research

Abstract. The Coordinated Regional Climate Downscaling Experiment (CORDEX) is a scientific effort of the World Climate Research Program (WRCP) for the coordination of regional climate initiatives. In order to accept an experiment, CORDEX provides experiment guidelines, specifications of regional domains, and data access and archiving. CORDEX experiments are important to study climate at the regional scale, and at the same time, they also have a very prominent role in providing regional climate data of high quality. Data requirements are intended to cover all the possible needs of stakeholders and scientists working on climate change mitigation and adaptation policies in various scientific communities. The required data and diagnostics are grouped into different levels of frequency and priority, and some of them even have to be provided as statistics (minimum, maximum, mean) over different time periods. Most commonly, scientists need to post-process the raw output of regional climate models, since the latter was not originally designed to meet the specific CORDEX data requirements. This post-processing procedure includes the computation of diagnostics, statistics, and final homogenization of the data, which is often computationally costly and time-consuming. Therefore, the development of specialized software and/or code is required. The current paper presents the development of a specialized module (version 1.3) for the Weather Research and Forecasting (WRF) model capable of outputting the required CORDEX variables. Additional diagnostic variables not required by CORDEX, but of potential interest to the regional climate modeling community, are also included in the module. “Generic” definitions of variables are adopted in order to overcome the model and/or physics parameterization dependence of certain diagnostics and variables, thus facilitating a robust comparison among simulations. The module is computationally optimized, and the output is divided into different priority levels following CORDEX specifications (Core, Tier 1, and additional) by selecting pre-compilation flags. This implementation of the module does not add a significant extra cost when running the model; for example, the addition of the Core variables slows the model time step by less than a 5 %. The use of the module reduces the requirements of disk storage by about a 50 %. The module performs neither additional statistics over different periods of time nor homogenization of the output data.

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Hydroclimate of the Western United States Based on Observations and Regional Climate Simulation of 1981–2000. Part II: Mesoscale ENSO Anomalies

Journal of Climate ◽

10.1175/1520-0442(2003)016<1912:hotwus>2.0.co;2 ◽

2003 ◽

Vol 16 (12) ◽

pp. 1912-1928 ◽

Cited By ~ 56

Author(s):

L. Ruby Leung ◽

Yun Qian ◽

Xindi Bian ◽

Allen Hunt

Keyword(s):

United States ◽

Regional Climate ◽

Western United States ◽

Climate Simulation ◽

Regional Climate Simulation

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CO2 Sensitivity of Extreme Climate Events in the Western United States

Earth Interactions ◽

10.1175/ei181.1 ◽

2006 ◽

Vol 10 (15) ◽

pp. 1-17 ◽

Cited By ~ 8

Author(s):

Jason L. Bell ◽

Lisa C. Sloan

Keyword(s):

United States ◽

Extreme Events ◽

Climate Model ◽

Heat Waves ◽

Regional Climate ◽

Western United States ◽

Climate Extreme ◽

Climate Model Simulations ◽

Atmospheric Co2 Concentrations ◽

High Elevations

Abstract Based upon trends in observed climate, extreme events are thought to be increasing in frequency and/or magnitude. This change in extreme events is attributed to enhancement of the hydrologic cycle caused by increased greenhouse gas concentrations. Results are presented of relatively long (50 yr) regional climate model simulations of the western United States examining the sensitivity of climate and extreme events to a doubling of preindustrial atmospheric CO2 concentrations. These results indicate a shift in the temperature distribution, resulting in fewer cold days and more hot days; the largest changes occur at high elevations. The rainfall distribution is also affected; total rain increases as a result of increases in rainfall during the spring season and at higher elevations. The risk of flooding is generally increased, as is the severity of droughts and heat waves. These results, combined with results of decreased snowpack and increased evaporation, could further stress the water supply of the western United States.

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Will Future Climate Favor More Erratic Wildfires in the Western United States?

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-12-0317.1 ◽

2013 ◽

Vol 52 (11) ◽

pp. 2410-2417 ◽

Cited By ~ 22

Author(s):

Lifeng Luo ◽

Ying Tang ◽

Shiyuan Zhong ◽

Xindi Bian ◽

Warren E. Heilman

Keyword(s):

United States ◽

Climate Models ◽

Regional Climate ◽

Fire Behavior ◽

Regional Climate Models ◽

Future Climate ◽

Lower Atmosphere ◽

Western United States ◽

Mountainous Regions ◽

Increased Risk

AbstractWildfires that occurred over the western United States during August 2012 were fewer in number but larger in size when compared with all other Augusts in the twenty-first century. This unique characteristic, along with the tremendous property damage and potential loss of life that occur with large wildfires with erratic behavior, raised the question of whether future climate will favor rapid wildfire growth so that similar wildfire activity may become more frequent as climate changes. This study addresses this question by examining differences in the climatological distribution of the Haines index (HI) between the current and projected future climate over the western United States. The HI, ranging from 2 to 6, was designed to characterize dry, unstable air in the lower atmosphere that may contribute to erratic or extreme fire behavior. A shift in HI distribution from low values (2 and 3) to higher values (5 and 6) would indicate an increased risk for rapid wildfire growth and spread. Distributions of Haines index are calculated from simulations of current (1971–2000) and future (2041–70) climate using multiple regional climate models in the North American Regional Climate Change Assessment Program. Despite some differences among the projections, the simulations indicate that there may be not only more days but also more consecutive days with HI ≥ 5 during August in the future. This result suggests that future atmospheric environments will be more conducive to erratic wildfires in the mountainous regions of the western United States.

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Regional Climate–Weather Research and Forecasting Model

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-11-00180.1 ◽

2012 ◽

Vol 93 (9) ◽

pp. 1363-1387 ◽

Cited By ~ 84

Author(s):

Xin-Zhong Liang ◽

Min Xu ◽

Xing Yuan ◽

Tiejun Ling ◽

Hyun I. Choi ◽

...

Keyword(s):

Weather Prediction ◽

Regional Climate ◽

Weather Forecast ◽

Ecosystem Model ◽

Climate Prediction ◽

Weather Research And Forecasting ◽

Forecasting Model ◽

Physical Processes ◽

Terrestrial Hydrology ◽

Weather Research

The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979– 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.

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