Credibility of convection-permitting modeling to improve seasonal precipitation forecasting in the southwestern United States

Sujan Pal, Hsin I. Chang, Christopher Castro, Francina Dominguez

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Abstract

Sub-seasonal to seasonal (S2S) forecasts are critical for planning and management decisions in multiple sectors. This study shows results from dynamical downscaling using a regional climate model at a convection-permitting scale driven by boundary conditions from the global reanalysis of the Climate Forecast System Model (CFSR). Convection-permitting modeling (CPM) enhances the representation of regional climate by better resolving the regional forcings and processes, associated with topography and land cover, in response to variability in the large-scale atmospheric circulation. We performed dynamically downscaled simulations with the Weather Research and Forecasting (WRF) model over the Upper and Lower Colorado basin at 12 km and 3 km grid spacing from 2000 to 2010 to investigate the potential of dynamical downscaling to improved the modeled representation of precipitation the Southwestern United States. Employing a convection-permitting nested domain of 3 km resolution significantly reduces the bias in mean (∼2 mm/day) and extreme (∼4 mm/day) summer precipitation when compared to coarser domain of 12 km resolution and coarse resolution CFSR products. The convection-permitting modeling product also better represents eastward propagation of organized convection due to mesoscale convective systems at a sub-daily scale, which largely account for extreme summer rainfall during the North American monsoon. In the cool season both coarse and high-resolution simulations perform well with limited bias of ∼1 mm/day for the mean and ∼2 mm/day for the extreme precipitation. Significant correlation was found (∼0.85 for summer and ∼0.65 for winter) for both coarse and high-resolution model with observed regionally and seasonally averaged precipitation. Our findings suggest that the use of CPM is necessary in a dynamical modeling system for S2S prediction in this region, especially during the warm season when precipitation is mostly convectively driven.

Original languageEnglish (US)
Article number11
JournalFrontiers in Earth Science
Volume7
DOIs
StatePublished - Feb 26 2019

Fingerprint

convection
modeling
downscaling
regional climate
summer
convective system
atmospheric circulation
simulation
climate modeling
land cover
spacing
monsoon
boundary condition
topography
weather
rainfall
winter
climate
prediction
basin

Keywords

  • Downscaling
  • Extremes
  • Precipitation
  • Regional climate model
  • Seasonal forecasting

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

Cite this

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title = "Credibility of convection-permitting modeling to improve seasonal precipitation forecasting in the southwestern United States",
abstract = "Sub-seasonal to seasonal (S2S) forecasts are critical for planning and management decisions in multiple sectors. This study shows results from dynamical downscaling using a regional climate model at a convection-permitting scale driven by boundary conditions from the global reanalysis of the Climate Forecast System Model (CFSR). Convection-permitting modeling (CPM) enhances the representation of regional climate by better resolving the regional forcings and processes, associated with topography and land cover, in response to variability in the large-scale atmospheric circulation. We performed dynamically downscaled simulations with the Weather Research and Forecasting (WRF) model over the Upper and Lower Colorado basin at 12 km and 3 km grid spacing from 2000 to 2010 to investigate the potential of dynamical downscaling to improved the modeled representation of precipitation the Southwestern United States. Employing a convection-permitting nested domain of 3 km resolution significantly reduces the bias in mean (∼2 mm/day) and extreme (∼4 mm/day) summer precipitation when compared to coarser domain of 12 km resolution and coarse resolution CFSR products. The convection-permitting modeling product also better represents eastward propagation of organized convection due to mesoscale convective systems at a sub-daily scale, which largely account for extreme summer rainfall during the North American monsoon. In the cool season both coarse and high-resolution simulations perform well with limited bias of ∼1 mm/day for the mean and ∼2 mm/day for the extreme precipitation. Significant correlation was found (∼0.85 for summer and ∼0.65 for winter) for both coarse and high-resolution model with observed regionally and seasonally averaged precipitation. Our findings suggest that the use of CPM is necessary in a dynamical modeling system for S2S prediction in this region, especially during the warm season when precipitation is mostly convectively driven.",
keywords = "Downscaling, Extremes, Precipitation, Regional climate model, Seasonal forecasting",
author = "Sujan Pal and Chang, {Hsin I.} and Christopher Castro and Francina Dominguez",
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language = "English (US)",
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TY - JOUR

T1 - Credibility of convection-permitting modeling to improve seasonal precipitation forecasting in the southwestern United States

AU - Pal, Sujan

AU - Chang, Hsin I.

AU - Castro, Christopher

AU - Dominguez, Francina

PY - 2019/2/26

Y1 - 2019/2/26

N2 - Sub-seasonal to seasonal (S2S) forecasts are critical for planning and management decisions in multiple sectors. This study shows results from dynamical downscaling using a regional climate model at a convection-permitting scale driven by boundary conditions from the global reanalysis of the Climate Forecast System Model (CFSR). Convection-permitting modeling (CPM) enhances the representation of regional climate by better resolving the regional forcings and processes, associated with topography and land cover, in response to variability in the large-scale atmospheric circulation. We performed dynamically downscaled simulations with the Weather Research and Forecasting (WRF) model over the Upper and Lower Colorado basin at 12 km and 3 km grid spacing from 2000 to 2010 to investigate the potential of dynamical downscaling to improved the modeled representation of precipitation the Southwestern United States. Employing a convection-permitting nested domain of 3 km resolution significantly reduces the bias in mean (∼2 mm/day) and extreme (∼4 mm/day) summer precipitation when compared to coarser domain of 12 km resolution and coarse resolution CFSR products. The convection-permitting modeling product also better represents eastward propagation of organized convection due to mesoscale convective systems at a sub-daily scale, which largely account for extreme summer rainfall during the North American monsoon. In the cool season both coarse and high-resolution simulations perform well with limited bias of ∼1 mm/day for the mean and ∼2 mm/day for the extreme precipitation. Significant correlation was found (∼0.85 for summer and ∼0.65 for winter) for both coarse and high-resolution model with observed regionally and seasonally averaged precipitation. Our findings suggest that the use of CPM is necessary in a dynamical modeling system for S2S prediction in this region, especially during the warm season when precipitation is mostly convectively driven.

AB - Sub-seasonal to seasonal (S2S) forecasts are critical for planning and management decisions in multiple sectors. This study shows results from dynamical downscaling using a regional climate model at a convection-permitting scale driven by boundary conditions from the global reanalysis of the Climate Forecast System Model (CFSR). Convection-permitting modeling (CPM) enhances the representation of regional climate by better resolving the regional forcings and processes, associated with topography and land cover, in response to variability in the large-scale atmospheric circulation. We performed dynamically downscaled simulations with the Weather Research and Forecasting (WRF) model over the Upper and Lower Colorado basin at 12 km and 3 km grid spacing from 2000 to 2010 to investigate the potential of dynamical downscaling to improved the modeled representation of precipitation the Southwestern United States. Employing a convection-permitting nested domain of 3 km resolution significantly reduces the bias in mean (∼2 mm/day) and extreme (∼4 mm/day) summer precipitation when compared to coarser domain of 12 km resolution and coarse resolution CFSR products. The convection-permitting modeling product also better represents eastward propagation of organized convection due to mesoscale convective systems at a sub-daily scale, which largely account for extreme summer rainfall during the North American monsoon. In the cool season both coarse and high-resolution simulations perform well with limited bias of ∼1 mm/day for the mean and ∼2 mm/day for the extreme precipitation. Significant correlation was found (∼0.85 for summer and ∼0.65 for winter) for both coarse and high-resolution model with observed regionally and seasonally averaged precipitation. Our findings suggest that the use of CPM is necessary in a dynamical modeling system for S2S prediction in this region, especially during the warm season when precipitation is mostly convectively driven.

KW - Downscaling

KW - Extremes

KW - Precipitation

KW - Regional climate model

KW - Seasonal forecasting

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U2 - 10.3389/feart.2019.00011

DO - 10.3389/feart.2019.00011

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VL - 7

JO - Frontiers in Earth Science

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SN - 2296-6463

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