Evaluating Aeolus HLOS Winds and Characterizing the Low-Level Jet (LLJ) and Tropical Easterly Jet (TEJ) over the Indian Summer Monsoon: An Intercomparison with Radiosonde and Reanalysis Datasets

Reliable prediction of the Indian Summer Monsoon (ISM) requires accurate representation of large-scale circulation features such as the Low-Level Jet (LLJ) and Tropical Easterly Jet (TEJ), yet sparse observational coverage over the Indian Ocean region continues to limit model validation and improvement. This study validated horizontal line-of-sight (HLOS) winds from the ESA Aeolus satellite, carrying the first spaceborne Doppler wind lidar (ALADIN), against high-resolution radiosonde observations at Gadanki (13.5°N, 79.2°E) during 2019–2021, with spatial intercomparisons against reanalysis datasets extended through 2022. Observation days were classified into clear-sky and cloudy-sky conditions using infrared brightness temperature to assess Aeolus retrievals under varying cloud regimes. Rayleigh-clear retrievals showed strong agreement with radiosondes (correlation coefficient = 0.95, bias = 0.11 m s−1), while Mie-cloudy retrievals performed notably weaker (correlation coefficient = 0.35, bias = 3.40 m s−1). Agreement improved with altitude, with the highest correlation (0.97) observed in the upper troposphere–lower stratosphere (UTLS). HLOS wind differences between Aeolus and radiosondes generally remained within ±2 m s−1. The vertical structure and intensity of the LLJ and TEJ derived from Aeolus agreed most closely with radiosonde observations, followed by ERA5, MERRA-2, and NCEP-2 reanalyses, in order of increasing deviation. Spatial deviations were small relative to ERA5 and MERRA-2 but substantially larger relative to NCEP-2. These findings demonstrate that Aeolus provides reliable HLOS wind measurements for characterizing the vertical structure and seasonal evolution of Indian Summer Monsoon circulation, while supporting the evaluation of atmospheric reanalysis datasets over observationally sparse regions.