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Title: Assessing impacts of PBL and surface layer schemes in simulating the surface–atmosphere interactions and precipitation over the tropical ocean using observations from AMIE/DYNAMO

Journal Article · · Journal of Climate
 [1];  [2];  [1];  [1];  [1];  [3];  [1]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Lanzhou Univ., Lanzhou (China); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  3. Nanjing Univ., Nanjing (China); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
+ Show Author Affiliations

Accuracy of turbulence parameterization in representing Planetary Boundary Layer (PBL) processes in climate models is critical for predicting the initiation and development of clouds, air quality issues, and underlying surface-atmosphere-cloud interactions. In this study, we 1) evaluate WRF model-simulated spatial patterns of precipitation and surface fluxes, as well as vertical profiles of potential temperature, humidity, moist static energy and moisture tendency terms as simulated by WRF at various spatial resolutions and with PBL, surface layer and shallow convection schemes against measurements, 2) identify model biases by examining the moisture tendency terms contributed by PBL and convection processes through nudging experiments, and 3) evaluate the dependence of modeled surface latent heat (LH) fluxes onPBL and surface layer schemes over the tropical ocean. The results show that PBL and surface parameterizations have surprisingly large impacts on precipitation, convection initiation and surface moisture fluxes over tropical oceans. All of the parameterizations tested tend to overpredict moisture in PBL and free atmosphere, and consequently result in larger moist static energy and precipitation. Moisture nudging tends to suppress the initiation of convection and reduces the excess precipitation. The reduction in precipitation bias in turn reduces the surface wind and LH flux biases, which suggests that the model drifts at least partly because of a positive feedback between precipitation and surface fluxes. The updated shallow convection scheme KF-CuP tends to suppress the initiation and development of deep convection, consequently decreasing precipitation. The Eta surface layer scheme predicts more reasonable LH fluxes and the LH-Wind Speed relationship than the MM5 scheme, especially when coupled with the MYJ scheme. By examining various parameterization schemes in WRF, we identify sources of biases and weaknesses of current PBL, surface layer and shallow convection schemes in reproducing PBL processes, the initiation of convection and intra-seasonal variability of precipitation.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC05-76RL01830
OSTI ID:
1339861
Report Number(s):
PNNL-SA-114620; KP1701000
Journal Information:
Journal of Climate, Vol. 29, Issue 22; ISSN 0894-8755
Publisher:
American Meteorological SocietyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 16 works
Citation information provided by
Web of Science

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Cited By (5)

Modeling Impacts of Urbanization and Urban Heat Island Mitigation on Boundary Layer Meteorology and Air Quality in Beijing Under Different Weather Conditions journal April 2018
Hindcasting the Madden-Julian Oscillation With a New Parameterization of Surface Heat Fluxes: MJO HINDCAST IN THE WRF-MEP MODEL journal November 2017
Performance Analysis of Planetary Boundary Layer Parameterization Schemes in WRF Modeling Set Up over Southern Italy journal July 2018
Assessing the formation and evolution mechanisms of severe haze pollution in the Beijing–Tianjin–Hebei region using process analysis journal January 2019
Combinatorial Optimization for WRF Physical Parameterization Schemes: A Case Study of Three-Day Typhoon Simulations over the Northwest Pacific Ocean journal May 2019

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Related Subjects

54 ENVIRONMENTAL SCIENCES
PBL
surface layer
shallow convection
precipitation
AMIE/DYNAMO
clouds
boundary conditions
mesoscale models
model evaluation/performance
parameterization