Using InSAR Data to Improve the Water Vapor Distribution Downstream of the Core of the South American Low‐Level Jet. Issue 7 (8th April 2022)

• Record Type: Journal Article
• Authors: Mateus, P.; Miranda, P. M. A.
• Is Part Of: Journal of geophysical research. Volume 127:Issue 7(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-04-08
• Subjects: precipitation water vapor (PWV) -- data assimilation -- Weather Research and Forecast model (WRF) -- interferometry synthetic aperture radar (InSAR) -- Sentinel‐1 mission -- South American Low‐Level Jet (SALLJ); Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2021JD036111
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: Two and half years of Interferometric Synthetic Aperture Radar (InSAR) images obtained by Sentinel‐1 near Santa Cruz de la Sierra, Bolivia, before August 2019 are here analyzed and assimilated in the Weather Research and Forecast model (WRF) to assess the quality of the water vapor field at the core of the South American Low‐level Jet, and the downstream propagation of the implied water vapor anomalies into a large sector of South America. Due to the topographic locking of the Jet near the edge of the Andes cordillera at Santa Cruz, this experiment allows an assessment of the extension of the spatial impact of InSAR data assimilation in varying circulation conditions. That data improves the model skill at varying locations thousands of kilometers downstream, in both the distribution of water vapor assessed at a large number of well‐distributed GNSS observations and precipitation assessed against the Global Precipitation dataset and ERA5 reanalysis. Gains in the precipitation forecast skill are found to have a larger impact on the forecast of light rain, and lead to an almost cancellation of forecasts of no rain in cases with moderate to heavy rain. Because the distribution of water vapor is a main driver of weather, and InSAR is one of the few sources of data that can look down to mesoscale resolution regardless of daytime or weather, it is suggested that it may have a significant positive impact on short‐range weather forecasting and, maybe more importantly, on the quality of the climate of the forecast model. Key Points: Moisture anomalies can travel thousands of kilometers, leading to more skillful forecasts Gains in skill mostly translate into better forecasts of light rain and elimination of no rain forecasts in cases of heavy rainfall InSAR may constrain systematic biases in water vapor analyses