A Brief Assessment of the Impact of Nearly 40 Years of Assimilated Observations Over the Amazon Basin. Issue 3 (12th March 2020) - Diniz, F. L. R.; Todling, R.; Herdies, D. L.
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. Plain Language Summary: Observations of atmospheric variables are of fundamental importance to allow for reliable weather predictions and to enable scientists to improve their modeling of the atmosphere. Conventional observing systems measure temperature, winds, humidity, and pressure directly. These amount to a small fraction of the global observing system, which is dominated by indirect satellite observations. Objective evaluation for how different components of the observing systems contribute to improving weather predictions have become essential to help scientists understand how best to build future observing systems. The present study provides an evaluation of nearly 40 years of observations used in the context of a procedure called reanalysis, which essentially blends observations and model predictions in a carefully designed manner. Our particular work examines the impact of observations over the Amazon basin. In this region, conventional observations are found to still contribute most to reducing forecast errors, especially in the later years of the reanalysis, while satellite‐derived winds are found to contribute most in the wet season. The work suggests that improving the treatment of other satellite observations allowing their use over cloudy and precipitating regions might change their ranking in comparison to conventional observations. Key Points: Pre‐EOS satellite radiances contribute most to FSOI over the Amazon basin In the EOS era, radiosonde observations are the largest contributors to forecast error reduction in the region Satellite winds are large contributors to forecast error reduction, but mainly during wet periods