Assimilation of Ground-Based Microwave Radiometer on Heavy Rainfall Forecast in Beijing

Ground-based microwave radiometers (MWRPS) can provide continuous atmospheric temperature and relative humidity profiles for a weather prediction model. We investigated the impact of assimilation of ground-based microwave radiometers based on the rapid-refresh multiscale analysis and prediction syst...
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Autor*in:	Yajie Qi [verfasserIn] Shuiyong Fan [verfasserIn] Bai Li [verfasserIn] Jiajia Mao [verfasserIn] Dawei Lin [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	heavy rainfall ground-based microwave radiometer heat island effect

Übergeordnetes Werk:	In: Atmosphere - MDPI AG, 2011, 13(2021), 1, p 74
Übergeordnetes Werk:	volume:13 ; year:2021 ; number:1, p 74

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/atmos13010074

Katalog-ID:	DOAJ087057115

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520			\|a Ground-based microwave radiometers (MWRPS) can provide continuous atmospheric temperature and relative humidity profiles for a weather prediction model. We investigated the impact of assimilation of ground-based microwave radiometers based on the rapid-refresh multiscale analysis and prediction system-short term (RMAPS-ST). In this study, five MWRP-retrieved profiles were assimilated for the precipitation enhancement that occurred in Beijing on 21 May 2020. To evaluate the influence of their assimilation, two experiments with and without the MWRPS assimilation were set. Compared to the control experiment, which only assimilated conventional observations and radar data, the MWRPS experiment, which assimilated conventional observations, the ground-based microwave radiometer profiles and the radar data, had a positive impact on the forecasts of the RMAPS-ST. The results show that in comparison with the control test, the MWRPS experiment reproduced the heat island phenomenon in the observation better. The MWRPS assimilation reduced the bias and RMSE of two-meter temperature and two-meter specific humidity forecasting in the 0–12 h of the forecast range. Furthermore, assimilating the MWRPS improved both the distribution and the intensity of the hourly rainfall forecast, as compared with that of the control experiment, with observations that predicted the process of the precipitation enhancement in the urban area of Beijing.
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allfieldsSound	10.3390/atmos13010074 doi (DE-627)DOAJ087057115 (DE-599)DOAJa5d8dac6aade4a1cb695b04b5d1b5141 DE-627 ger DE-627 rakwb eng QC851-999 Yajie Qi verfasserin aut Assimilation of Ground-Based Microwave Radiometer on Heavy Rainfall Forecast in Beijing 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Ground-based microwave radiometers (MWRPS) can provide continuous atmospheric temperature and relative humidity profiles for a weather prediction model. We investigated the impact of assimilation of ground-based microwave radiometers based on the rapid-refresh multiscale analysis and prediction system-short term (RMAPS-ST). In this study, five MWRP-retrieved profiles were assimilated for the precipitation enhancement that occurred in Beijing on 21 May 2020. To evaluate the influence of their assimilation, two experiments with and without the MWRPS assimilation were set. Compared to the control experiment, which only assimilated conventional observations and radar data, the MWRPS experiment, which assimilated conventional observations, the ground-based microwave radiometer profiles and the radar data, had a positive impact on the forecasts of the RMAPS-ST. The results show that in comparison with the control test, the MWRPS experiment reproduced the heat island phenomenon in the observation better. The MWRPS assimilation reduced the bias and RMSE of two-meter temperature and two-meter specific humidity forecasting in the 0–12 h of the forecast range. Furthermore, assimilating the MWRPS improved both the distribution and the intensity of the hourly rainfall forecast, as compared with that of the control experiment, with observations that predicted the process of the precipitation enhancement in the urban area of Beijing. heavy rainfall ground-based microwave radiometer heat island effect Meteorology. Climatology Shuiyong Fan verfasserin aut Bai Li verfasserin aut Jiajia Mao verfasserin aut Dawei Lin verfasserin aut In Atmosphere MDPI AG, 2011 13(2021), 1, p 74 (DE-627)657584010 (DE-600)2605928-9 20734433 nnns volume:13 year:2021 number:1, p 74 https://doi.org/10.3390/atmos13010074 kostenfrei https://doaj.org/article/a5d8dac6aade4a1cb695b04b5d1b5141 kostenfrei https://www.mdpi.com/2073-4433/13/1/74 kostenfrei https://doaj.org/toc/2073-4433 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2021 1, p 74
language	English
source	In Atmosphere 13(2021), 1, p 74 volume:13 year:2021 number:1, p 74
sourceStr	In Atmosphere 13(2021), 1, p 74 volume:13 year:2021 number:1, p 74
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	heavy rainfall ground-based microwave radiometer heat island effect Meteorology. Climatology
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container_title	Atmosphere
authorswithroles_txt_mv	Yajie Qi @@aut@@ Shuiyong Fan @@aut@@ Bai Li @@aut@@ Jiajia Mao @@aut@@ Dawei Lin @@aut@@
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callnumber-first	Q - Science
author	Yajie Qi
spellingShingle	Yajie Qi misc QC851-999 misc heavy rainfall misc ground-based microwave radiometer misc heat island effect misc Meteorology. Climatology Assimilation of Ground-Based Microwave Radiometer on Heavy Rainfall Forecast in Beijing
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topic_title	QC851-999 Assimilation of Ground-Based Microwave Radiometer on Heavy Rainfall Forecast in Beijing heavy rainfall ground-based microwave radiometer heat island effect
topic	misc QC851-999 misc heavy rainfall misc ground-based microwave radiometer misc heat island effect misc Meteorology. Climatology
topic_unstemmed	misc QC851-999 misc heavy rainfall misc ground-based microwave radiometer misc heat island effect misc Meteorology. Climatology
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title	Assimilation of Ground-Based Microwave Radiometer on Heavy Rainfall Forecast in Beijing
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title_full	Assimilation of Ground-Based Microwave Radiometer on Heavy Rainfall Forecast in Beijing
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author_browse	Yajie Qi Shuiyong Fan Bai Li Jiajia Mao Dawei Lin
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title_sort	assimilation of ground-based microwave radiometer on heavy rainfall forecast in beijing
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title_auth	Assimilation of Ground-Based Microwave Radiometer on Heavy Rainfall Forecast in Beijing
abstract	Ground-based microwave radiometers (MWRPS) can provide continuous atmospheric temperature and relative humidity profiles for a weather prediction model. We investigated the impact of assimilation of ground-based microwave radiometers based on the rapid-refresh multiscale analysis and prediction system-short term (RMAPS-ST). In this study, five MWRP-retrieved profiles were assimilated for the precipitation enhancement that occurred in Beijing on 21 May 2020. To evaluate the influence of their assimilation, two experiments with and without the MWRPS assimilation were set. Compared to the control experiment, which only assimilated conventional observations and radar data, the MWRPS experiment, which assimilated conventional observations, the ground-based microwave radiometer profiles and the radar data, had a positive impact on the forecasts of the RMAPS-ST. The results show that in comparison with the control test, the MWRPS experiment reproduced the heat island phenomenon in the observation better. The MWRPS assimilation reduced the bias and RMSE of two-meter temperature and two-meter specific humidity forecasting in the 0–12 h of the forecast range. Furthermore, assimilating the MWRPS improved both the distribution and the intensity of the hourly rainfall forecast, as compared with that of the control experiment, with observations that predicted the process of the precipitation enhancement in the urban area of Beijing.
abstractGer	Ground-based microwave radiometers (MWRPS) can provide continuous atmospheric temperature and relative humidity profiles for a weather prediction model. We investigated the impact of assimilation of ground-based microwave radiometers based on the rapid-refresh multiscale analysis and prediction system-short term (RMAPS-ST). In this study, five MWRP-retrieved profiles were assimilated for the precipitation enhancement that occurred in Beijing on 21 May 2020. To evaluate the influence of their assimilation, two experiments with and without the MWRPS assimilation were set. Compared to the control experiment, which only assimilated conventional observations and radar data, the MWRPS experiment, which assimilated conventional observations, the ground-based microwave radiometer profiles and the radar data, had a positive impact on the forecasts of the RMAPS-ST. The results show that in comparison with the control test, the MWRPS experiment reproduced the heat island phenomenon in the observation better. The MWRPS assimilation reduced the bias and RMSE of two-meter temperature and two-meter specific humidity forecasting in the 0–12 h of the forecast range. Furthermore, assimilating the MWRPS improved both the distribution and the intensity of the hourly rainfall forecast, as compared with that of the control experiment, with observations that predicted the process of the precipitation enhancement in the urban area of Beijing.
abstract_unstemmed	Ground-based microwave radiometers (MWRPS) can provide continuous atmospheric temperature and relative humidity profiles for a weather prediction model. We investigated the impact of assimilation of ground-based microwave radiometers based on the rapid-refresh multiscale analysis and prediction system-short term (RMAPS-ST). In this study, five MWRP-retrieved profiles were assimilated for the precipitation enhancement that occurred in Beijing on 21 May 2020. To evaluate the influence of their assimilation, two experiments with and without the MWRPS assimilation were set. Compared to the control experiment, which only assimilated conventional observations and radar data, the MWRPS experiment, which assimilated conventional observations, the ground-based microwave radiometer profiles and the radar data, had a positive impact on the forecasts of the RMAPS-ST. The results show that in comparison with the control test, the MWRPS experiment reproduced the heat island phenomenon in the observation better. The MWRPS assimilation reduced the bias and RMSE of two-meter temperature and two-meter specific humidity forecasting in the 0–12 h of the forecast range. Furthermore, assimilating the MWRPS improved both the distribution and the intensity of the hourly rainfall forecast, as compared with that of the control experiment, with observations that predicted the process of the precipitation enhancement in the urban area of Beijing.
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container_issue	1, p 74
title_short	Assimilation of Ground-Based Microwave Radiometer on Heavy Rainfall Forecast in Beijing
url	https://doi.org/10.3390/atmos13010074 https://doaj.org/article/a5d8dac6aade4a1cb695b04b5d1b5141 https://www.mdpi.com/2073-4433/13/1/74 https://doaj.org/toc/2073-4433
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up_date	2024-07-04T00:03:48.438Z
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