Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Generation of Non-Linear Technique Based 6 Hourly Wind Reanalysis Products Using SCATSAT-1 and Numerical Weather Prediction Model Outputs

Version 1 : Received: 25 January 2023 / Approved: 28 January 2023 / Online: 28 January 2023 (03:03:19 CET)

A peer-reviewed article of this Preprint also exists.

Bhowmick, S.A.; Gupta, M.; Chakraborty, A.; Agarwal, N.; Sharma, R.; Ali, M.M. Generation of Non-Linear Technique Based 6 Hourly Wind Reanalysis Products Using SCATSAT-1 and Numerical Weather Prediction Model Outputs. Remote Sens. 2023, 15, 1040. Bhowmick, S.A.; Gupta, M.; Chakraborty, A.; Agarwal, N.; Sharma, R.; Ali, M.M. Generation of Non-Linear Technique Based 6 Hourly Wind Reanalysis Products Using SCATSAT-1 and Numerical Weather Prediction Model Outputs. Remote Sens. 2023, 15, 1040.

Abstract

Observations of ocean surface winds from Indian scatterometer SCATSAT-1 have been combined with background wind field from a numerical weather prediction (NWP) model available at National Centre for Medium Range Weather Prediction (NCMRWF) to generate a 6-hourly gridded hybrid wind product. A distinctive feature of the study is to produce a global gridded wind field from SCATSAT-1 scatterometer passes with spatio-temporal data gaps at regular synoptic hours relevant for forcing models and other NWP studies. This is done by making use of concepts from the modern particle filter technique, which does not represent the model probability density function (PDF) following the Gaussian technique. The 6 hourly hybrid wind is generated for the entire year of 2018 and is validated using the wind speed from daily gridded level-4 SCATSAT-1 winds (L4AW), Cross Calibrated Multi-Platform dataset (CCMP) and global buoy data from National Data Buoy Centre (NDBC). The results indicate potential of the technique to produce scatterometer winds at the desired temporal frequency with significantly less noise and along swath biases. The study shows the generated hybrid winds have very high quality with respect to the already existing daily product available from ISRO.

Keywords

Winds; SCATSAT-1; NCMRWF (National Center for Medium Range Weather Forecasting), CCMP (Cross Calibrated Mul-ti-Platform) and Particle filter

Subject

Environmental and Earth Sciences, Space and Planetary Science

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