Impacts of a priori databases using six WRF microphysics schemes on passive microwave rainfall retrievals

Ju Hye Kim, Dong Bin Shin, Christian Kummerow

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

Physically based rainfall retrievals from passive microwave sensors often make use of cloud-resolving models (CRMs) to build a priori databases of potential rain structures. Each CRM, however, has its own cloud microphysics assumptions. Hence, approximated microphysics may cause uncertainties in the a priori information resulting in inaccurate rainfall estimates. This study first builds a priori databases by combining the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) observations and simulations from the Weather Research and Forecasting (WRF) model with six different cloud microphysics schemes. The microphysics schemes include the Purdue-Lin (LIN), WRF Single-Moment 6 (WSM6), Goddard Cumulus Ensemble (GCE), Thompson (THOM), WRF Double-Moment 6 (WDM6), and Morrison (MORR) schemes. As expected, the characteristics of the a priori databases are inherited from the individual cloud microphysics schemes. There are several distinct differences in the databases. Particularly, excessive graupel and snow exist with the LIN and THOM schemes, while more rainwater is incorporated into the a priori information with WDM6 than with any of the other schemes. Major results show that convective rainfall regions are not well captured by the LIN and THOM schemes-based retrievals. Rainfall distributions and their quantities retrieved from the WSM6 and WDM6 schemes-based estimations, however, show relatively better agreement with the PR observations. Based on the comparisons of the various microphysics schemes in the retrievals, it appears that differences in the a priori databases considerably affect the properties of rainfall estimations.

Original languageEnglish
Pages (from-to)2367-2381
Number of pages15
JournalJournal of Atmospheric and Oceanic Technology
Volume30
Issue number10
DOIs
Publication statusPublished - 2013 Oct 1

Fingerprint

Rain
cloud microphysics
Microwaves
weather
rainfall
radar
Radar
TRMM
cumulus
rainwater
Microwave sensors
Precipitation (meteorology)
snow
Snow
microwave
sensor
simulation

All Science Journal Classification (ASJC) codes

  • Ocean Engineering
  • Atmospheric Science

Cite this

@article{fd9a6e5d550e488f945a28a3a30b6053,
title = "Impacts of a priori databases using six WRF microphysics schemes on passive microwave rainfall retrievals",
abstract = "Physically based rainfall retrievals from passive microwave sensors often make use of cloud-resolving models (CRMs) to build a priori databases of potential rain structures. Each CRM, however, has its own cloud microphysics assumptions. Hence, approximated microphysics may cause uncertainties in the a priori information resulting in inaccurate rainfall estimates. This study first builds a priori databases by combining the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) observations and simulations from the Weather Research and Forecasting (WRF) model with six different cloud microphysics schemes. The microphysics schemes include the Purdue-Lin (LIN), WRF Single-Moment 6 (WSM6), Goddard Cumulus Ensemble (GCE), Thompson (THOM), WRF Double-Moment 6 (WDM6), and Morrison (MORR) schemes. As expected, the characteristics of the a priori databases are inherited from the individual cloud microphysics schemes. There are several distinct differences in the databases. Particularly, excessive graupel and snow exist with the LIN and THOM schemes, while more rainwater is incorporated into the a priori information with WDM6 than with any of the other schemes. Major results show that convective rainfall regions are not well captured by the LIN and THOM schemes-based retrievals. Rainfall distributions and their quantities retrieved from the WSM6 and WDM6 schemes-based estimations, however, show relatively better agreement with the PR observations. Based on the comparisons of the various microphysics schemes in the retrievals, it appears that differences in the a priori databases considerably affect the properties of rainfall estimations.",
author = "Kim, {Ju Hye} and Shin, {Dong Bin} and Christian Kummerow",
year = "2013",
month = "10",
day = "1",
doi = "10.1175/JTECH-D-12-00261.1",
language = "English",
volume = "30",
pages = "2367--2381",
journal = "Journal of Atmospheric and Oceanic Technology",
issn = "0739-0572",
publisher = "American Meteorological Society",
number = "10",

}

Impacts of a priori databases using six WRF microphysics schemes on passive microwave rainfall retrievals. / Kim, Ju Hye; Shin, Dong Bin; Kummerow, Christian.

In: Journal of Atmospheric and Oceanic Technology, Vol. 30, No. 10, 01.10.2013, p. 2367-2381.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Impacts of a priori databases using six WRF microphysics schemes on passive microwave rainfall retrievals

AU - Kim, Ju Hye

AU - Shin, Dong Bin

AU - Kummerow, Christian

PY - 2013/10/1

Y1 - 2013/10/1

N2 - Physically based rainfall retrievals from passive microwave sensors often make use of cloud-resolving models (CRMs) to build a priori databases of potential rain structures. Each CRM, however, has its own cloud microphysics assumptions. Hence, approximated microphysics may cause uncertainties in the a priori information resulting in inaccurate rainfall estimates. This study first builds a priori databases by combining the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) observations and simulations from the Weather Research and Forecasting (WRF) model with six different cloud microphysics schemes. The microphysics schemes include the Purdue-Lin (LIN), WRF Single-Moment 6 (WSM6), Goddard Cumulus Ensemble (GCE), Thompson (THOM), WRF Double-Moment 6 (WDM6), and Morrison (MORR) schemes. As expected, the characteristics of the a priori databases are inherited from the individual cloud microphysics schemes. There are several distinct differences in the databases. Particularly, excessive graupel and snow exist with the LIN and THOM schemes, while more rainwater is incorporated into the a priori information with WDM6 than with any of the other schemes. Major results show that convective rainfall regions are not well captured by the LIN and THOM schemes-based retrievals. Rainfall distributions and their quantities retrieved from the WSM6 and WDM6 schemes-based estimations, however, show relatively better agreement with the PR observations. Based on the comparisons of the various microphysics schemes in the retrievals, it appears that differences in the a priori databases considerably affect the properties of rainfall estimations.

AB - Physically based rainfall retrievals from passive microwave sensors often make use of cloud-resolving models (CRMs) to build a priori databases of potential rain structures. Each CRM, however, has its own cloud microphysics assumptions. Hence, approximated microphysics may cause uncertainties in the a priori information resulting in inaccurate rainfall estimates. This study first builds a priori databases by combining the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) observations and simulations from the Weather Research and Forecasting (WRF) model with six different cloud microphysics schemes. The microphysics schemes include the Purdue-Lin (LIN), WRF Single-Moment 6 (WSM6), Goddard Cumulus Ensemble (GCE), Thompson (THOM), WRF Double-Moment 6 (WDM6), and Morrison (MORR) schemes. As expected, the characteristics of the a priori databases are inherited from the individual cloud microphysics schemes. There are several distinct differences in the databases. Particularly, excessive graupel and snow exist with the LIN and THOM schemes, while more rainwater is incorporated into the a priori information with WDM6 than with any of the other schemes. Major results show that convective rainfall regions are not well captured by the LIN and THOM schemes-based retrievals. Rainfall distributions and their quantities retrieved from the WSM6 and WDM6 schemes-based estimations, however, show relatively better agreement with the PR observations. Based on the comparisons of the various microphysics schemes in the retrievals, it appears that differences in the a priori databases considerably affect the properties of rainfall estimations.

UR - http://www.scopus.com/inward/record.url?scp=84886620263&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84886620263&partnerID=8YFLogxK

U2 - 10.1175/JTECH-D-12-00261.1

DO - 10.1175/JTECH-D-12-00261.1

M3 - Article

AN - SCOPUS:84886620263

VL - 30

SP - 2367

EP - 2381

JO - Journal of Atmospheric and Oceanic Technology

JF - Journal of Atmospheric and Oceanic Technology

SN - 0739-0572

IS - 10

ER -