Retrieval of temperature profiles in tropical cyclone Nanmadol from resampled advanced technology microwave sounder observations

In the past, satellite microwave sounding data are often utilized for retrieving the thermal structure of tropical cyclones (TCs). However, the spatial resolutions and scan pattern of the instruments vary from one to another and can affect the retrievals of TC structures. In this study, Backus-Gilbe...

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Bibliographic Details
Published in:Remote sensing of environment Vol. 304; p. 114068
Main Authors: Li, Wenyu, Weng, Fuzhong
Format: Journal Article
Language:English
Published: Elsevier Inc 01.04.2024
Subjects:
air temperature
algorithms
environment
hurricanes
Microwave sounding
One-dimension variational (1DVAR) retrieval
Resampling
satellites
Tropical cyclone (TC)
Microwave sounding
One-dimension variational (1DVAR) retrieval
Resampling
Tropical cyclone (TC)
ISSN:0034-4257, 1879-0704
Online Access:Get full text
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Summary:In the past, satellite microwave sounding data are often utilized for retrieving the thermal structure of tropical cyclones (TCs). However, the spatial resolutions and scan pattern of the instruments vary from one to another and can affect the retrievals of TC structures. In this study, Backus-Gilbert Inversion (BGI), ATOVS and AVHRR Pre-processing Package (AAPP) filter and N × N field-of-views (FOVs) average algorithms are utilized to resample the Advanced Technology Microwave Sounder (ATMS) data and the impacts from different resampling algorithms on brightness temperature structures and retrieved atmospheric temperature are analyzed. It is shown that for ATMS channel 1 to 2, the larger differences between original and resampled brightness temperatures are found in cloudy areas and at the land-ocean boundary. When ATMS channels 1–16 data are resampled to the AMSU-like resolution, the brightness temperatures become less noisy at channel 3 to 16 and can lead to a higher convergence rate in the one-dimension variational (1DVAR) algorithm. Furthermore, the warm core intensity of a tropical storm of Nanmadol is reduced by about 2.5 K and its size becomes smaller after the ATMS data is resampled to the AMSU resolution. •Utilization of different algorithms for resampling ATMS data•Impact of resampling on brightness temperature structures•Effect of resampling on the retrieval of temperature profiles in tropical cyclones
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ISSN:0034-4257
1879-0704
DOI:10.1016/j.rse.2024.114068