Forecast Impact of Targeted Observations: Sensitivity to Observation Error and Proximity to Steep Orography

Abstract

For a targeted observations case, the dependence of the size of the forecast impact on the targeted dropsonde observation error in the data assimilation is assessed. The targeted observations were made in the lee of Greenland; the dependence of the impact on the proximity of the observations to the Greenland coast is also investigated. Experiments were conducted using the Met Office Unified Model (MetUM), over a limited-area domain at 24-km grid spacing, with a four-dimensional variational data assimilation (4D-Var) scheme. Reducing the operational dropsonde observation errors by one-half increases the maximum forecast improvement from 5% to 7%-10%, measured in terms of total energy. However, the largest impact is seen by replacing two dropsondes on the Greenland coast with two farther from the steep orography; this increases the maximum forecast improvement from 5% to 18% for an 18-h forecast (using operational observation errors). Forecast degradation caused by two dropsonde observations on the Greenland coast is shown to arise from spreading of data by the background errors up the steep slope of Greenland. Removing boundary layer data from these dropsondes reduces the forecast degradation, but it is only a partial solution to this problem. Although only from one case study, these results suggest that observations positioned within a correlation length scale of steep orography may degrade the forecast through the anomalous upslope spreading of analysis increments along terrain-following model levels.

Evaluation of wind forecasts over Svalbard using the high-resolution Polar WRF with 3DVAR

“…Adaptive observations in the sensitivity region at the beginning of the polar low genesis would be beneficial for improving forecast accuracy (Jung et al 2016). Aspelien et al (2011) and Irvine, Gray, and Methven (2011) showed that the forecast accuracy of the polar low affecting the Scandinavian Peninsula increases as targeted dropsonde observations are added to the region with sparse observations. In addition, using appropriate physics schemes that consider the characteristics of the polar environment in the NWP model is important for enhancing the accuracy of forecasting polar lows.…”

Improving Winter Storm Forecasts With Observing System Simulation Experiments (OSSEs). Part 2: Evaluating a Satellite Gap With Idealized and Targeted Dropsondes

“…The goal of a targeted observation effort is to identify regions where a reduction in analysis error can improve forecasts over a specified verification region. OSEs with targeted observations have been employed for hurricanes and tropical storms (Aberson, 2008(Aberson, , 2010, polar storms (Irvine et al, 2009(Irvine et al, , 2011, and extratropical storms Langland, Toth, et al, 1999;Szunyogh et al, 2000Szunyogh et al, , 2002. These studies generally find small improvements to forecasts on average, but results are case dependent and sometimes forecasts are neutral or degraded.…”

Effect of Observation Network Design on Meteorological Forecasts of Asian Dust Events

“…The simulated observations were considered as the upper-air radiosonde observations and obtained by adding observational errors to the TRUE. The simulated wind speed, wind direction, and temperature at 850, 500, and 200 hPa were extracted from the TRUE at the targeting time (0 h), and the observational errors of the radiosonde (Irvine et al 2011) were added to these wind and temperature variables. New analysis fields were then generated at the targeting time by assimilating the simulated observations to the WRF 3DVAR.…”