Hurricane Warm‐Core Retrievals from AMSU‐A and Remapped ATMS Measurements with Rain Contamination Eliminated

Abstract

Due to a shorter effective integration time for each field of view of the Advanced Microwave Temperature Sounder (ATMS) onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite than that for the Advanced Microwave Sounding Unit-A (AMSU-A) onboard previous National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellites NOAA-15 to NOAA-19, ATMS temperature-sounding channels have higher observational resolutions and larger noise equivalent differential temperatures than the corresponding AMSU-A channels. The high resolution of the ATMS allows hurricane rainband features that are not resolvable by AMSU-A to be captured. But the larger noise equivalent differential temperature of ATMS weakens this capability through the significant impact of observational noise on warm-core retrievals. In this study, a remapping algorithm is applied to obtain AMSU-A-like ATMS fields of view to suppress this noise. A modified warm-core retrieval algorithm, which consists of two sets of training coefficients for clear-sky and cloudy conditions, is applied to limb-corrected ATMS and AMSU-A measurements using collocated Global Positioning System radio occultation observations in the previous month of the targeted hurricanes as training data sets. ATMS channels 5, 6, and 7 (AMSU-A channels 4, 5, and 6) are excluded when training the coefficients for cloudy conditions to avoid cloud/rain contamination. As a result, the abnormal cold core in the low and middle troposphere and the banded warm structures in phase with rainbands are both successfully removed. The warm-core evolution of Hurricane Matthew (2016) during its entire life span is temporally consistent on intensity as obtained from NOAA-15, NOAA-18, and MetOp-B AMSU-A observations and S-NPP ATMS observations. ZOU AND TIAN 10,815

Studies of FY-3 Observations over the Past 10 Years: A Review

“…Therefore, atmospheric temperatures can be retrieved from MWTS observations by expressing the atmospheric temperature at a specified pressure level ( ( ) T p ) as a weighted sum of different MWTS channels' brightness temperature observations. Therefore, TC warm cores can be directly retrieved from microwave temperature sounding channels [50,51]. Since the FOV sizes of MWTS and ATMS sounding channels are nearly twice smaller than those of AMSU-A, a remapping algorithm could be applied to make MWTS and ATMS observations of the same FOVs as AMSU-A so that the MWTS and ATMS retrieved warm cores are consistent to those obtained from AMSU-A onboard NOAA-15, NOAA-18, MetOp-A and MetOp-B [51].…”

“…Therefore, TC warm cores can be directly retrieved from microwave temperature sounding channels [50,51]. Since the FOV sizes of MWTS and ATMS sounding channels are nearly twice smaller than those of AMSU-A, a remapping algorithm could be applied to make MWTS and ATMS observations of the same FOVs as AMSU-A so that the MWTS and ATMS retrieved warm cores are consistent to those obtained from AMSU-A onboard NOAA-15, NOAA-18, MetOp-A and MetOp-B [51]. By doing so, the impact of ATMS's large observational noise on warm-core retrievals can also be reduced.…”

A comprehensive 4D-Var vortex initialization using a nonhydrostatic axisymmetric TC model with convection accounted for

“…Ninety-six ATMS scene resolution cells, symmetrically distributed on both sides of the sub-satellite path, are sampled. Since neighbouring ATMS FOVs overlap significantly, a remap algorithm is applied to convert ATMS FOVs at the original 2.2 beam width to a new 3.3 beam width (Zou and Tian, 2018).…”

“…In this study, we propose to replace the MM5 by the RE87 model and the bogus SLP by satellite-derived warm-core temperature anomalies and total precipitable water (TPW) fields. The novelty of this work involves developing a new 4D-Var VI system, making use of satellite retrieval products of warm core and TPW generated by the authors based on their past research Zou, 2016a, 2016b;Zou and Tian, 2018), and demonstrating of a promising, improved TC intensity prediction. The article is arranged as follows.…”

Comparison of the Remapping Algorithms for the Advanced Technology Microwave Sounder (ATMS)

“…However, the application of these spaceborne, multispectral measurements from multiple sensors is often plagued with the problem of nonuniform spatial resolution caused by the limited size of the satellite instrument antenna and the frequency-dependent microwave emission from the earth-atmosphere system. The mismatch in resolution becomes a critical issue when observations from different frequencies and different sensors are combined to retrieve geophysical parameters like wind speed, cloud liquid water, total precipitation water, and snow depth [3][4][5][6]. It could also lead to uncertainty in the cross-calibration between similar satellite radiometer instruments [2,4,7,8].…”