Work

Time Series Consistency of Passive Microwave Sensors (1978–2023) Brightness Temperature Data for Snow Depth Estimation

Year: 2025

Type: article

Abstract: Passive microwave remote sensing offers all-weather, all-day observations, but sensor inconsistencies hinder long-term continuity and multi-sensor integration for surface parameters estimation. This study proposed methods to improve brightness temperature (TB) consistency across seven major multifrequency, dual-polarized sensors from 1978 to 2023 via cross-calibration, including the Scanning Multi-channel Microwave Radiometer (SMMR), the Special Sensor Microwave/Imager (SSM/I), Special Sensor Microwave Imager/Sounder (SSMI/S), the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), the Advanced Microwave Scanning Radiometer-2 (AMSR2), the Microwave Radiation Imager (FY-3/MWRI), and the Scanning Microwave Radiometer (HY-2/SMR). To address temporal and spatial gaps, we grouped nine sensor pairs by overpass-time similarity or simultaneous operation. A two-point regression was applied using cold and warm scenes to calibrate brightness temperatures. Despite initial correlations above 0.9, substantial TB biases remained, particularly across generations and in vertical polarization. Calibration reduced these discrepancies, achieving R2> 0.998 with lower RMSE and MAE, most notably for low-frequency vertical channels. Spatial heterogeneity was further examined via pixel-wise regression between AMSR2 and FY-3D/MWRI, revealing regional biases and larger residuals in tropical forests, polar margins, and urban areas at higher frequencies. Validation using the Chang algorithm with Grody's snow cover detection confirmed improved inter-sensor snow depth consistency, with pixel-wise calibration offering higher local accuracy. This scalable cross-platform calibration framework supports TB harmonization for climate studies and multi-sensor hydrological and cryospheric applications.

Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

DOI: 10.1109/jstars.2025.3640871

Authors: Min Wu, Lingmei Jiang, Jianwei Yang, Shengli Wu, Guangjin Liu, Cheng Zhang

Institutions: Beijing Normal University, China Meteorological Administration

Language: English

Topic: Calibration and Measurement Techniques

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Climate action

Open Access status: gold

Estimated APC paid: $1,800