Advances in Precipitation Retrieval and Applications from Low-Earth-Orbiting Satellite Information

Afzali Gorooh, Vesta; Hsu, Kuolin; Ferraro, Ralph; Turk, Joe; Meng, Huan; Nguyen, Phu; Jimenez Arellano, Claudia; Kalluri, Satya; Sorooshian, Soroosh

doi:10.1175/bams-d-23-0229.1

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…al., 2015). This would be valuable over open oceans where independent validation data from radars or rain gauges is practically nonexistent (Gorooh et. al., 2023).…”

Section: Furthering the Use Of Pro In Science And Applicationsmentioning

confidence: 99%

Advances in the Use of Global Navigation Satellite System Polarimetric Radio Occultation Measurements for NWP and Weather Applications

Turk,

Cardellach,

de la Torre-Juárez

et al. 2024

Bulletin of the American Meteorological Society

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Hybrid Meeting "2 nd GNSS Polarimetric Radio Occultations User Workshop"What: Over 80 people from 14 countries, 3 continents and over 40 different affiliations, from government agencies, research centers, universities and the commercial space sector discussed the status of the polarimetric radio occultation technique and applications being developed from current and future observations, with focus on its use for and in numerical weather prediction modeling.

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“…al., 2015). This would be valuable over open oceans where independent validation data from radars or rain gauges is practically nonexistent (Gorooh et. al., 2023).…”

Section: Furthering the Use Of Pro In Science And Applicationsmentioning

confidence: 99%

Advances in the Use of Global Navigation Satellite System Polarimetric Radio Occultation Measurements for NWP and Weather Applications

Turk,

Cardellach,

de la Torre-Juárez

et al. 2024

Bulletin of the American Meteorological Society

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Superiority of Dynamic Weights against Fixed Weights in Merging Multi-Satellite Precipitation Datasets over Pakistan

Ejaz,

Khan,

Shahid

et al. 2024

Water

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Satellite precipitation products (SPPs) are undeniably subject to uncertainty due to retrieval algorithms and sampling issues. Many research efforts have concentrated on merging SPPs to create high-quality merged precipitation datasets (MPDs) in order to reduce these uncertainties. This study investigates the efficacy of dynamically weighted MPDs in contrast to those using static weights. The analysis focuses on comparing MPDs generated using the “dynamic clustered Bayesian averaging (DCBA)” approach with those utilizing the “regional principal component analysis (RPCA)” under fixed-weight conditions. These MPDs were merged from SPPs and reanalysis precipitation data, including TRMM (Tropical Rainfall Measurement Mission) Multi-satellite Precipitation Analysis (TMPA) 3B42V7, PERSIANN-CDR, CMORPH, and the ERA-Interim reanalysis precipitation data. The performance of these datasets was evaluated in Pakistan’s diverse climatic zones—glacial, humid, arid, and hyper-arid—employing data from 102 rain gauge stations. The effectiveness of the DCBA model was quantified using Theil’s U statistic, demonstrating its superiority over the RPCA model and other individual merging methods in the study area The comparative performances of DCBA and RPCA in these regions, as measured by Theil’s U, are 0.49 to 0.53, 0.38 to 0.45, 0.37 to 0.42, and 0.36 to 0.43 in glacial, humid, arid, and hyper-arid zones, respectively. The evaluation of DCBA and RPCA compared with SPPs at different elevations showed poorer performance at high altitudes (>4000 m). The comparison of MPDs with the best performance of SPP (i.e., TMPA) showed significant improvement of DCBA even at altitudes above 4000 m. The improvements are reported as 49.83% for mean absolute error (MAE), 42.31% for root-mean-square error (RMSE), 27.94% for correlation coefficient (CC), 40.15% for standard deviation (SD), and 13.21% for Theil’s U. Relatively smaller improvements are observed for RPCA at 13.04%, 1.56%, 10.91%, 1.67%, and 5.66% in the above indices, respectively. Overall, this study demonstrated the superiority of DCBA over RPCA with static weight. Therefore, it is strongly recommended to use dynamic variation of weights in the development of MPDs.

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Advances in Precipitation Retrieval and Applications from Low-Earth-Orbiting Satellite Information

Cited by 2 publications

References 13 publications

Advances in the Use of Global Navigation Satellite System Polarimetric Radio Occultation Measurements for NWP and Weather Applications

Advances in the Use of Global Navigation Satellite System Polarimetric Radio Occultation Measurements for NWP and Weather Applications

Superiority of Dynamic Weights against Fixed Weights in Merging Multi-Satellite Precipitation Datasets over Pakistan

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