Temperature and Humidity Profiles Retrieval in a Plain Area from Fengyun-3D/HIRAS Sensor Using a 1D-VAR Assimilation Scheme

In this study, a one-dimensional variational (1D-VAR) retrieval system is proposed to simultaneously retrieve temperature and humidity atmospheric profiles under clear-sky conditions. Our technique requires observations from the Fengyun-3D Hyperspectral Infrared Radiation Atmospheric Sounding (HIRAS...

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Main Authors: Liuhua Zhu, Yansong Bao, George P. Petropoulos, Peng Zhang, Feng Lu, Qifeng Lu, Ying Wu, Dan Xu
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/12/3/435
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spelling doaj-8a03a358bf0143c2ac35d2cdd7538d732020-11-25T03:33:08ZengMDPI AGRemote Sensing2072-42922020-01-0112343510.3390/rs12030435rs12030435Temperature and Humidity Profiles Retrieval in a Plain Area from Fengyun-3D/HIRAS Sensor Using a 1D-VAR Assimilation SchemeLiuhua Zhu0Yansong Bao1George P. Petropoulos2Peng Zhang3Feng Lu4Qifeng Lu5Ying Wu6Dan Xu7Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, CMA Key Laboratory for Aerosol-Cloud-Precipitation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, CMA Key Laboratory for Aerosol-Cloud-Precipitation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaSchool of Mineral Resources Engineering, Technical University of Crete, Kounoupidiana Campus, 73100 Crete, GreeceKey Laboratory of Radiometric Calibration and Validation for Environmental Satellites /National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, ChinaKey Laboratory of Radiometric Calibration and Validation for Environmental Satellites /National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, ChinaKey Laboratory of Radiometric Calibration and Validation for Environmental Satellites /National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, CMA Key Laboratory for Aerosol-Cloud-Precipitation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaCollaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, CMA Key Laboratory for Aerosol-Cloud-Precipitation, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaIn this study, a one-dimensional variational (1D-VAR) retrieval system is proposed to simultaneously retrieve temperature and humidity atmospheric profiles under clear-sky conditions. Our technique requires observations from the Fengyun-3D Hyperspectral Infrared Radiation Atmospheric Sounding (HIRAS) satellite combined with the Weather Research and Forecast (WRF) model. In the method, the radiative transfer for the TIROS Operational Vertical Sounder (TOVS (RTTOV) model is also used as a forward observation operator. The accuracy of our approach was evaluated using as a case study the region of Beijing in China. Predicted temperature and humidity profiles were compared against ERA-Interim data, which was used as reference. Mean bias (MB) of the temperature profiles varied between −0.8 K to 0.9 K, while the root-mean-square error (RMSE) ranged from 0.5 K to 2.6 K. In the boundary layer, the 1D-VAR algorithm performed better compared with the first guess. In the middle troposphere, the retrievals were more dependent on the first guess. With respect to relative humidity predictions, the accuracy of the evaluation of the whole troposphere was improved with the inclusion of the satellite observations, reporting an MB varying from −5.68% to 2.83%. Compared with Atmospheric Infrared Sounder’s (AIRS’) products, our predicted temperature profiles showed a very good consistency and the humidity predictions were also of an acceptable prediction accuracy. All in all, results clearly evidenced the promising potential of our proposed approach for retrieving temperature and humidity profiles under clear-sky conditions.https://www.mdpi.com/2072-4292/12/3/435temperature and humidity profilesone-dimensional variational (1d-var) assimilationhirasremote sensing
collection DOAJ
language English
format Article
sources DOAJ
author Liuhua Zhu
Yansong Bao
George P. Petropoulos
Peng Zhang
Feng Lu
Qifeng Lu
Ying Wu
Dan Xu
spellingShingle Liuhua Zhu
Yansong Bao
George P. Petropoulos
Peng Zhang
Feng Lu
Qifeng Lu
Ying Wu
Dan Xu
Temperature and Humidity Profiles Retrieval in a Plain Area from Fengyun-3D/HIRAS Sensor Using a 1D-VAR Assimilation Scheme
Remote Sensing
temperature and humidity profiles
one-dimensional variational (1d-var) assimilation
hiras
remote sensing
author_facet Liuhua Zhu
Yansong Bao
George P. Petropoulos
Peng Zhang
Feng Lu
Qifeng Lu
Ying Wu
Dan Xu
author_sort Liuhua Zhu
title Temperature and Humidity Profiles Retrieval in a Plain Area from Fengyun-3D/HIRAS Sensor Using a 1D-VAR Assimilation Scheme
title_short Temperature and Humidity Profiles Retrieval in a Plain Area from Fengyun-3D/HIRAS Sensor Using a 1D-VAR Assimilation Scheme
title_full Temperature and Humidity Profiles Retrieval in a Plain Area from Fengyun-3D/HIRAS Sensor Using a 1D-VAR Assimilation Scheme
title_fullStr Temperature and Humidity Profiles Retrieval in a Plain Area from Fengyun-3D/HIRAS Sensor Using a 1D-VAR Assimilation Scheme
title_full_unstemmed Temperature and Humidity Profiles Retrieval in a Plain Area from Fengyun-3D/HIRAS Sensor Using a 1D-VAR Assimilation Scheme
title_sort temperature and humidity profiles retrieval in a plain area from fengyun-3d/hiras sensor using a 1d-var assimilation scheme
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2020-01-01
description In this study, a one-dimensional variational (1D-VAR) retrieval system is proposed to simultaneously retrieve temperature and humidity atmospheric profiles under clear-sky conditions. Our technique requires observations from the Fengyun-3D Hyperspectral Infrared Radiation Atmospheric Sounding (HIRAS) satellite combined with the Weather Research and Forecast (WRF) model. In the method, the radiative transfer for the TIROS Operational Vertical Sounder (TOVS (RTTOV) model is also used as a forward observation operator. The accuracy of our approach was evaluated using as a case study the region of Beijing in China. Predicted temperature and humidity profiles were compared against ERA-Interim data, which was used as reference. Mean bias (MB) of the temperature profiles varied between −0.8 K to 0.9 K, while the root-mean-square error (RMSE) ranged from 0.5 K to 2.6 K. In the boundary layer, the 1D-VAR algorithm performed better compared with the first guess. In the middle troposphere, the retrievals were more dependent on the first guess. With respect to relative humidity predictions, the accuracy of the evaluation of the whole troposphere was improved with the inclusion of the satellite observations, reporting an MB varying from −5.68% to 2.83%. Compared with Atmospheric Infrared Sounder’s (AIRS’) products, our predicted temperature profiles showed a very good consistency and the humidity predictions were also of an acceptable prediction accuracy. All in all, results clearly evidenced the promising potential of our proposed approach for retrieving temperature and humidity profiles under clear-sky conditions.
topic temperature and humidity profiles
one-dimensional variational (1d-var) assimilation
hiras
remote sensing
url https://www.mdpi.com/2072-4292/12/3/435
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