Sentence examples for atmospheric forecasts from inspiring English sources

One of its goals was the long-term monthly average of atmospheric forecasts (model climatology), produced by the BRAMS model for the entire country.

This manuscript reports on results of an 18-day high-resolution atmospheric forecasting field project using the Weather Research and Forecasting (WRF) model.

The difference operation between seasonal forecast and the monthly average of atmospheric forecast over a set of years in the past (the "climatology") eliminates this tendency, using the same numerical model, region and period of integration.

The currents for the fate/transport modeling were taken from the daily forecasts generated by the CANOPA (CANada Ocean PArallelise) ocean circulation model based on daily atmospheric forecast from the Canadian Meteorological Centre and five tidal constituents (Brickman and Drozdowski 2012).

The overall analysis shows that freely available atmospheric forecasting products can provide additional information on upcoming rainfall and peak flow events in areas where only base-line forecasts such as no-rainfall or climatology are available.

As The Local Italy reports, Turin's atmospheric pollution forecasts for the end of this week were set to reach dangerously toxic levels – so the city offered residents free bus and metro rides over Thursday and Friday in a bid to get people out of their cars and on to public transport.

A frequent re-initialization of REMO's atmospheric fields (forecast mode) slightly improves the simulation of precipitation but can also lead to local inaccuracies.

Soil moisture memory (SMM) is not only important for atmospheric weather/climate forecasting, but may also be useful in flood and drought prediction.

The GEOS-5 merges a modified version of the National Centers for Environmental Predictions Gridpoint Statistical Interpolation analysis algorithm [e.g., Wu et al., 2002] with the NASA atmospheric global forecast model, as documented in Rienecker et al. [ 2008].

The tool merges atmospheric dispersal model forecasts with air traffic data in a map-based platform to produce tables and maps showing potentially affected airports, flights and airspace sectors.

Supercomputers, for instance, aren't good at forecasting atmospheric details in the center of storms.