The Impact of Dropsonde Data on the Performance of the NCEP Global Forecast System during the 2020 Atmospheric Rivers Observing Campaign. Part I: Precipitation

Abstract

The impact of assimilating dropsonde data from the 2020 Atmospheric River (AR) Reconnaissance (ARR) field campaign on operational numerical precipitation forecasts was assessed. Two experiments were executed for the period from 24 January to 18 March 2020 using the NCEP Global Forecast System version 15 (GFSv15) with a four-dimensional hybrid ensemble-variational (4DEnVar) data assimilation system. The control run (CTRL) used all the routinely assimilated data and included ARR dropsonde data, whereas the denial run (DENY) excluded the dropsonde data. There were 17 Intensive Observing Periods (IOPs) totaling 46 Air Force C-130 and 16 NOAA G-IV missions to deploy dropsondes over targeted regions with potential for downstream high-impact weather associated with the ARs. Data from a total of 628 dropsondes were assimilated in the CTRL. The dropsonde data impact on precipitation forecasts over U.S. West Coast domains is largely positive, especially for day 5 lead time, and appears driven by different model variables on a case-by-case basis. These results suggest that data gaps associated with ARs can be addressed with targeted ARR field campaigns providing vital observations needed for improving U.S. West Coast precipitation forecasts.

Impacts of Dropsonde Observations on Forecasts of Atmospheric Rivers and Associated Precipitation in the NCEP GFS and ECMWF IFS Models

“…modeling system forced by the NCEP GFS analysis and forecast products. In addition, the NCEP model has most precipitation skill improvements at the higher thresholds, in agreement with Lord et al (2023a), while the ECMWF precipitation results were less sensitive to thresholds. For the ECMWF model, the control forecasts have less skill than the denial at a 24-h lead time but show consistent and generally significant improvement at longer lead times.…”

Atmospheric River Reconnaissance 2021: A Review

“…Several studies have shown the positive impact of AR Recon data on AR forecasts (e.g., Stone et al 2020;Lord et al 2022;Zheng et al 2021b), and data denial experiments that systematically assess data impact of the AR Recon 2021 targeted observations are beyond the scope of this paper but are underway. We can, however, illustrate the impact of all available observations (including AR Recon data and conventional data) on the analysis in the ECMWF IFS during AR Recon IOPs and at AR Recon dropsonde locations.…”

“…Although most observations assimilated in NWP systems are from satellites, the positive impact of dropsonde data on AR forecast skill has been demonstrated in several studies (e.g., Stone et al 2020;Lord et al 2022;Zheng et al 2021b), using forecast sensitivity observation impact (FSOI) diagnostics and full data denial experiments. Drifting buoys equipped with barometers make accurate measurements of sea level pressure and have been shown to contribute to weather forecast improvement (Centurioni et al 2017;Ingleby and Isaksen 2018).…”