Abstract
Abstract. An improved representation of 3-D air motion and precipitation structure through forecast models and assimilation of observations is vital for improvements in weather forecasting capabilities. However, there are few independent data to properly validate a model forecast of precipitation structure when the underlying dynamics are evolving on short convective timescales. Using data from the JPL Ku/Ka-band Airborne Precipitation Radar (APR-2) and the 2 µm Doppler Aerosol Wind (DAWN) lidar collected during the 2017 Convective Processes Experiment (CPEX), the NASA Unified Weather Research and Forecasting (WRF) Ensemble Data Assimilation System (EDAS) modeling system was used to quantify the impact of high-resolution sparsely sampled DAWN measurements on the analyzed variables and on the forecast when the DAWN winds were assimilated. Overall, the assimilation of the DAWN wind profiles had a discernible impact on the wind field as well as the evolution and timing of the 3-D precipitation structure. Analysis of individual variables revealed that the assimilation of the DAWN winds resulted in important and coherent modifications of the environment. It led to an increase in the near-surface convergence, temperature, and water vapor, creating more favorable conditions for the development of convection exactly where it was observed (but not present in the control run). Comparison to APR-2 and observations by the Global Precipitation Measurement (GPM) satellite shows a much-improved forecast after the assimilation of the DAWN winds – development of precipitation where there was none, more organized precipitation where there was some, and a much more intense and organized cold pool, similar to the analysis of the dropsonde data. The onset of the vertical evolution of the precipitation showed similar radar-derived cloud-top heights, but delayed in time. While this investigation was limited to a single CPEX flight date, the investigation design is appropriate for further investigation of the impact of airborne Doppler wind lidar observations upon short-term convective precipitation forecasts.
Highlights
Atmospheric convection plays a major role in both weather and climate
This paper presented the results of the impact on the forecasted precipitation structure that resulted when Doppler Aerosol Wind (DAWN) wind vector profiles were assimilated by the NASA NASA Unified Weather Research and Forecasting (NUWRF) Ensemble Data Assimilation System (EDAS)
This study is a direct follow-on to the recently published paper by the authors (Turk et al, 2020), which describes in detail the DAWN observations during each of the 1 h periods used in the assimilation and the APR-2 data for the 10 June 2017 flight used for this impact study
Summary
Atmospheric convection plays a major role in both weather and climate. the initiation of convection and the mechanisms through which it organizes and grows upscale, from isolated convective cells to organized mesoscale convective systems, still remain largely unknown (Houze, 2018). Large-scale and mesoscale convergence and the presence of atmospheric boundaries (in moisture and heat) can play the role of these triggers of convection These individual storms organize and grow upscale, forming MCSs. But what factors lead to MCS development in the first place? The model environmental state fields are compared between the control run and the analysis to determine how the model state (wind, temperature, moisture) changed in the model as a result of the assimilation of DAWN wind profiles While this investigation and its conclusions are limited to a single CPEX flight date, the investigation design is appropriate for further investigation of the impact of airborne Doppler wind lidar observations upon short-term convective precipitation forecasts. The term T2020 is used to cite that paper
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