A Brief Assessment of the Impact of Nearly 40 Years of Assimilated Observations Over the Amazon Basin

Abstract

Adding a Forecast Sensitivity‐based Observation Impact component to Version 2 of the Modern Era Retrospective‐analysis for Research and Applications, the present study provides an assessment of the impact of nearly 40 years of observations on short‐range (24‐hr) forecasts over the Amazon basin. Under self‐verification, forecast errors are found to slightly increase from the early data‐sparse days to the more recent years, when data dramatically increase. Throughout the reanalysis, satellite radiances dominate in volume, but only before 1999 they dominate the impacts. Beyond 1999, over 50% of forecast error reduction is associated with conventional observations (radiosondes). Atmospheric Motion Vectors are also found to be large contributors to error reduction, but their contribution reduces in dry periods. In opposition to Atmospheric Motion Vectors, satellite radiances tend to contribute more in the dry season. Results provide motivation for additional conventional observations and the use of all‐sky treatment of radiances.

The Impact of the Observation Data Assimilation on Atmospheric Reanalyses over Tibetan Plateau and Western Yunnan-Guizhou Plateau

“…This is an example showing that the differences in forecast models and data assimilation methods are minor in impact on the performance of reanalyses as compared to differences of assimilating only surface observations and of also assimilating upper-air observations. Moreover, 20CR exhibited a similar performance with the older generation reanalyses (prior to 2010) of the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) and the Japan Meteorological Agency Climate Data Assimilation System (JCDAS) in the Antarctic Peninsula region [37]. However, compared with the other new-generation reanalyses, 20CR has obviously larger biases and larger RMSE for temperature, specific humidity, and wind in the Antarctic Peninsula region [38].…”

“…The significant effect of conventional observations on a multi-year reanalysis (the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2)) was also noted in some recent studies which employed the forecast sensitivity-based observation impact (FSOI) technique [36,37]. Diniz and Todling [36] indicated that conventional observations played a major role in reducing forecast errors throughout the nearly 40-year reanalysis period.…”