Addressing the sensitivity of forecast impact to flight path design for targeted observations of extratropical winter storms: A demonstration in an OSSE framework

Abstract

Few studies have examined the forecast uncertainties brought about from varying aircraft flight track patterns in targeted observations for extratropical winter storms. To examine the degree of uncertainty in downstream forecasts caused by different aircraft flight patterns, a series of observing system simulation experiments (OSSEs) are performed and demonstrated for two extratropical winter storms identified in the European Centre for Medium‐Range Weather Forecasts (ECMWF) T511 Nature Run using the National Centers for Environmental Prediction Global Data Assimilation System and Global Forecast System (Q1FY15). Winter storms were chosen to support operational Pacific Ocean targeting strategies using unmanned aircraft. For these two storms, objective and composite flight tracks are generated as they could occur in an operational field mission to sample sensitive areas and meteorologically important regions, and then the changes in downstream forecasts across the various flight tracks are evaluated. The forecast impact downstream is sensitive to flight track orientation and shows case‐dependent results, with some flight patterns leading to significant improvements, while others result in neutral to degraded forecasts. The degree of downstream uncertainty in the verification region can vary up to 8% from the different flight paths, depending on the metric used and the atmospheric variables analysed. Although the study is a demonstration of the technique and is limited to only two case studies, it suggests that uncertainty in flight path design should not be neglected in future field missions. Some guidance for mitigating this uncertainty is also discussed.

Measurement report: Impact of African aerosol particles on cloud evolution in a tropical montane cloud forest in the Caribbean

“…A number of experiments have been carried out to compare the GDAS model with observations and have found that the GDAS output compares well with the actual meteorological data (e.g.,. Kleist and Ide, 2015;Kren et al, 2020;Rangsanseri et al, 2020). The overall accuracy of the backtrajectories' position depends on the wind fields taken from the meteorological model, the interpolation of wind velocity from the grid point to the actual trajectory position (Rolph and Draxler, 1990), and truncation errors and has been estimated to be about 15 %-20 % (Stohl et al, 2002).…”

Toward targeted observations of the meteorological initial state for improving the PM2.5forecast of a heavy haze event that occurred in the Beijing–Tianjin–Hebei region

“…These additional observations are assimilated by a data assimilation system to provide a more reliable initial state, which would be supplied to the model to obtain a more accurate prediction. Targeted observations have become a hot topic in atmospheric science due to their successful applications in improving the prediction skills of extreme weather events, such as typhoons (Wu et al, 2009;Mu et al, 2009) and winter storms (Kren et al, 2020) and high-impact climatic events, such as the El Niño-Southern Oscillation (ENSO; Kramer and Dijkstra, 2013;Duan et al, 2018) and Indian Ocean Dipole (IOD; Feng et al, 2017;Beal et al, 2020). As we stated above, the meteorological initial fields have great impacts on the PM 2.5 forecasts of the BTH region (Bei et al, 2017;Liu et al, 2018); meanwhile, our results also showed that the PM 2.5 forecasts are sensitive to the uncertainties of meteorological initial conditions (see Sect.…”