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Simultaneous Assimilation of Dual-Po...

Eure, Keenan C.,

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Simultaneous Assimilation of Dual-Polarization Radar and all-Sky Satellite Observations to Improve Convection Forecasts /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Simultaneous Assimilation of Dual-Polarization Radar and all-Sky Satellite Observations to Improve Convection Forecasts // Keenan C Eure.
Author:	Eure, Keenan C.,
Description:	1 electronic resource (79 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-05, Section: B.
Contained By:	Dissertations Abstracts International86-05B.
Subject:	Weather. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31631245
ISBN:	9798346376972

Simultaneous Assimilation of Dual-Polarization Radar and all-Sky Satellite Observations to Improve Convection Forecasts /
Eure, Keenan C.,

Simultaneous Assimilation of Dual-Polarization Radar and all-Sky Satellite Observations to Improve Convection Forecasts /Keenan C Eure. - 1 electronic resource (79 pages)

Source: Dissertations Abstracts International, Volume: 86-05, Section: B.

Accurate forecasts of severe weather are both a priority and a challenge for the National Oceanic and Atmospheric Administration (NOAA). Deep moist convection can become severe if it develops within a favorable environment, posing threats to public safety; issuing timely and accurate warnings of these threats is a NOAA responsibility conducted in. Yet, modeling internal structures of convection is difficult, as the details of these structures affect the storm mode, intensity, and longevity. Recent studies suggest that novel observations from the WSR-88Ds and GOES-16 have the potential to improve the convection forecasts in convection-allowing model (CAM) ensemble forecasting systems. Dual-polarization radar data from WSR-88Ds offer a wealth of information about the shape, size, and type of hydrometeors present in storms. Several distinct polarimetric signatures have been identified from the early stages of deep convection, such as the differential reflectivity (ZDR) column. These columns are vertical protrusions of positive ZDR values above the environmental melting level and can aid significantly in characterizing storm updrafts. Information on the updraft location and intensity has the potential to improve CAM representation of convection evolution. In addition, GOES-16 infrared (IR) all-sky brightness temperatures (BTs) provide complementary information and coverage on cloud structures that Doppler radars cannot directly measure. To explore the benefits of both types of observations, an ensemble data assimilation approach is applied to a severe weather event on 1 May 2018. The CAM selected for this study is the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model and observations are assimilated using an Ensemble Kalman Filter (EnKF). Conventional, WSR-88D ZDR, and GOES-16 all-sky BTs are assimilated separately and jointly over a 4-h period and results are compared to explore the influence of these observations on different aspects of the severe convective event. Results suggest that radar data alone provides modest improvements, and that satellite data adds great benefit to convection forecasts. Ultimately, simultaneous radar and satellite data assimilation provides the most accurate ensemble forecasts.

English

ISBN: 9798346376972Subjects--Topical Terms:

523974
Weather.

Simultaneous Assimilation of Dual-Polarization Radar and all-Sky Satellite Observations to Improve Convection Forecasts /
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520 $a Accurate forecasts of severe weather are both a priority and a challenge for the National Oceanic and Atmospheric Administration (NOAA). Deep moist convection can become severe if it develops within a favorable environment, posing threats to public safety; issuing timely and accurate warnings of these threats is a NOAA responsibility conducted in. Yet, modeling internal structures of convection is difficult, as the details of these structures affect the storm mode, intensity, and longevity. Recent studies suggest that novel observations from the WSR-88Ds and GOES-16 have the potential to improve the convection forecasts in convection-allowing model (CAM) ensemble forecasting systems. Dual-polarization radar data from WSR-88Ds offer a wealth of information about the shape, size, and type of hydrometeors present in storms. Several distinct polarimetric signatures have been identified from the early stages of deep convection, such as the differential reflectivity (ZDR) column. These columns are vertical protrusions of positive ZDR values above the environmental melting level and can aid significantly in characterizing storm updrafts. Information on the updraft location and intensity has the potential to improve CAM representation of convection evolution. In addition, GOES-16 infrared (IR) all-sky brightness temperatures (BTs) provide complementary information and coverage on cloud structures that Doppler radars cannot directly measure. To explore the benefits of both types of observations, an ensemble data assimilation approach is applied to a severe weather event on 1 May 2018. The CAM selected for this study is the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model and observations are assimilated using an Ensemble Kalman Filter (EnKF). Conventional, WSR-88D ZDR, and GOES-16 all-sky BTs are assimilated separately and jointly over a 4-h period and results are compared to explore the influence of these observations on different aspects of the severe convective event. Results suggest that radar data alone provides modest improvements, and that satellite data adds great benefit to convection forecasts. Ultimately, simultaneous radar and satellite data assimilation provides the most accurate ensemble forecasts.
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