Abstract
In the Arctic, weather forecasting is one element of risk mitigation, helping operators to have knowledge on weather-related risk in advance through forecasting capabilities at time ranges from a few hours to days ahead. The operational numerical weather prediction is an initial value problem where the forecast quality depends both on the quality of the forecast model itself and on the quality of the specified initial state. The initial states are regularly updated using environmental observations through data assimilation. This paper assesses the impact of observations, which are accessible through the global telecommunication and the EUMETCast dissemination systems on analyses and forecasts of an Arctic limited area AROME (Application of Research to Operations at Mesoscale) model (AROME-Arctic). An assessment through the computation of degrees of freedom for signals on the analysis, the utilization of an energy norm-based approach applied to the forecasts, verifications against observations, and a case study showed similar impacts of the studied observations on the AROME-Arctic analysis and forecast systems. The AROME-Arctic assimilation system showed a relatively high sensitivity to the humidity or humidity-sensitive observations. The more radiance data were assimilated, the lower was the estimated relative sensitivity of the assimilation system to different conventional observations. Data assimilation, at least for surface parameters, is needed to produce accurate forecasts from a few hours up to days ahead over the studied Arctic region. Upper-air conventional observations are not enough to improve the forecasting capability over the AROME-Arctic domain compared to those already produced by the ECMWF (European Centre for Medium-range Weather Forecast). Each added radiance data showed a relatively positive impact on the analyses and forecasts of the AROME-Arctic. The humidity-sensitive microwave (AMSU-B/MHS) radiances, assimilated together with the conventional observations and the Infrared Atmospheric Sounding Interferometer (IASI)-assimilated on top of conventional and microwave radiances produced enough accurate one-day-ahead forecasts of polar low.
Highlights
Good knowledge of the Arctic environment is becoming more and more important due to the increasing activities such as ship traffic and resource exploitation in the region
The degrees of freedom for signal (DFS) are computed with analyses well distant in time from each other to reduce the influence of interdependency between weather conditions prescribed in the model initial state
We observed that the H-A without data assimilation has less accurate forecasts at surface and low tropospheric levels in verification against conventional observations
Summary
Good knowledge of the Arctic environment is becoming more and more important due to the increasing activities such as ship traffic and resource exploitation in the region. In the frame of the Arctic Climate Change, Economy and Society (ACCESS) project (Gascard et al [4]), the Norwegian Meteorological Institute (MET Norway), among other scientific tasks, dealt with (1) describing the short-range monitoring and forecasting capabilities in the Arctic and (2) identifying the key factors limiting the monitoring and forecasting capabilities, and providing recommendations for key areas to improve the forecasting capabilities in the Arctic. These studies were conducted with the operational NWP model at MET Norway.
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