Sentences with phrase «weather prediction model forecasts»

This study examines the horizontal distribution of cirrus clouds by means of satellite imagery analyses and numerical weather prediction model forecasts.

Not exact matches

Regardless of what climate models find, investigating these long - distance links in weather could also pay off by improving risk prediction and forecasts.

Shelby signaled potential increased spending for NOAA's satellite programs used to prepare weather prediction models and advance weather forecasting capabilities.

Comparing five state - of - the - art weather prediction models, researchers found current models can forecast both where and how much rainfall a tropical cyclone will produce up to two days in advance.

Apart from ground stations, weather forecasts are heavily dependent on weather satellites for information to start or «initialize» the numerical weather prediction models that are the foundation of modern weather prediction.

EWeLiNE cannnot simply use the NCAR system because weather models and the algorithms that convert weather predictions into power forecasts differ between the United States and Germany.

When compared to standard weather prediction modeling, Roebber's evolutionary methodology performs particularly well on longer - range forecasts and extreme events, when an accurate forecast is needed the most.

I was working for the Omani Meteorological Department when the implementation of a numerical weather forecasting model prompted the need for some local knowledge in numerical weather predictions.

Jerome Fast led the multi-agency forecasting and modeling team that provided predictions of the weather conditions, the location of the particulate plume downwind of Mexico City, and the extent of plumes from agricultural burning.

A few climate models have been tested for (and shown) capability in initial value predictions, on time scales from weather forecasting (a few days) to seasonal forecasting (annual).

This is quite subtle though — weather forecast models obviously do better if they have initial conditions that are closer to the observations, and one might argue that for particular climate model predictions that are strongly dependent on the base climatology (such as for Arctic sea ice) tuning to the climatology will be worthwhile.

The researchers compared predictions of 22 widely used climate «models» — elaborate schematics that try to forecast how the global weather system will behave — with actual readings gathered by surface stations, weather balloons and orbiting satellites over the past three decades.

We strive to translate scientific discoveries into improved models for weather forecasting and climate prediction.

This suggests that ongoing improvements in model formulation driven primarily by the needs of weather forecasting may lead also to more reliable climate predictions.

Sea surface temperature (SST) measured from Earth Observation Satellites in considerable spatial detail and at high frequency, is increasingly required for use in the context of operational monitoring and forecasting of the ocean, for assimilation into coupled ocean - atmosphere model systems and for applications in short - term numerical weather prediction and longer term climate change detection.

The GCM models referred to as climate models are actually weather models only capable of predicting weather about two weeks into the future and as we are aware from our weather forecasts temperature predictions...

Many numerical weather prediction centers now use coupled ocean - atmosphere models to produce ensemble forecasts on the subseasonal time scale.

This capability would enable a model to continuously update and improve parameterization approaches on the fly, with the potential to improve climate predictions and short - term weather forecasts.

Mikhail Tolstykh is an expert for global numerical weather prediction models to develop medium - range and seasonal forecasts.

Different models are used for weather prediction versus climate forecasts.

Their prediction is based on the quantity of incoming solar radiation and uses 16 - day forecasts from a numerical weather prediction model (WRF).

Traditionally numerical weather prediction has advanced progressively by improving single, «deterministic» forecasts with an increasing model accuracy and decreasing initial condition errors.

The fourth question «How robust are the models used by the Met Office for weather forecasting, climate predictions, atmospheric dispersion and other activities?»

ERA - Interim combines information from meteorological observations with background information from a forecast model, using the data assimilation approach developed for numerical weather prediction.

Meteorological observations from radiosondes are also applied to benchmark the numerical weather prediction models used to forecast day - to - day weather.

This information was then fed into the weather prediction model to forecast summer - to - summer temperature variability in the eastern United States during the 2080s.

Lindzen's fifth paragraph: «Many of the most alarming studies rely on long - range predictions using inherently untrustworthy climate models, similar to those that can not accurately forecast the weather a week from now.

The ECMWF provides its supercomputer - run Integrated Forecasting System, a world - renowned numerical weather prediction model, as a basis for some Copernicus services, such as atmospheric forecasts and reanalysis data.

Until recently, even the most sophisticated dynamical weather prediction models were unable to provide skillful forecasts of changes to a hurricane's intensity.

Much of this progress is due to advances in numerical weather prediction, that is, the use of computer models which approximate the fluid motions of the atmosphere to create forecasts of the weather at some time in the future.

Linearity can be a useful approximation for short - term effects when changes are small as in some weather forecasting, but certainly not for the long - term predictions from climate models.

This idea of a «statistically indistinguishable» ensemble is common in the field of weather forecasting and other ensemble prediction fields, and under this paradigm the reliability of model ensembles can be evaluated through the rank histogram approach (Anderson 1996) whereby the distribution of the observed occurrence of an event in the prediction ensembles is evaluated.

GFDL scientists focus on model - building relevant for society, such as hurricane research, weather and ocean prediction, seasonal forecasting, and understanding global and regional climate change.

Finally, there's consensus that we can not look at climate forecasts — in particular, probabilistic forecasts — the same way we view weather predictions, and none of us would sell climate - model output, either at face value or after statistical analysis, as a reliable representation of the complete range of possible futures.

It is worth noting that some high - resolution operational numerical weather prediction models have demonstrated reasonable ability in forecasting tropical cyclones.