Renewable Energy Products

FINECAST® Nowcasting System: High Resolution AnalysisImproving Nowcasting via Data Assimilation

Fine-Scale Analysis and Nowcast System (FINECAST®) is used by the research community to study... more


Accurate wind forecasts are crucial for power-grid integration and load balancing. Current wind-forecasting methods, which are primarily based on statistical algorithms that use wind-farm... more

Wind Energy Prediction System

As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this renewable resource. NCAR and a team of researchers from public... more

Solar Energy Prediction System
Advanced Wind Prediction SystemFig. 1 Diagram of the WRF domains used in the wind energy prediction system. The grid spacings are as follows: D1=30km, D2=10km, and D3=3.3km.

In late December 2008,... more

Empirical Wind-to-Energy Conversion Algorithm
WRF Model Output

The Weather Research and Forecasting (WRF) Model is a next-generation mesoscale numerical weather prediction system designed to serve both atmospheric research and operational... more

WRF model output showing simulated radar reflectivity (dBZ) for Typhoon Mawar at 3.3-km (2.1-mi) grid spacing. Time period is from 0000 UTC 22 August 2005 to 0000 UTC 24 August 2005.

The Dynamic Integrated foreCast (DICast®) system is tasked with ingesting meteorological data (observations, models, statistical data, climate data, etc.) and producing meteorological forecasts at... more

DICast® System
Gridded ForecastingSample image of the surface air temperature generated by GRAFS at 21 UTC on April 8, 2009.

GRAFS (GRidded Atmospheric Forecast System) is a software system that is designed to... more

LOGICast™ software system

Two new postprocessing methods are proposed to reduce numerical weather prediction’s systematic and random errors. The first method consists of running a postprocessing algorithm inspired by the... more

Analog Kalman Filter (AnKF)

Although there has been a substantial, long-term effort by the weather research community to improve precipitation prediction, little attention has been paid to the prediction of clouds and... more

Distributed Solar Energy Prediction

Improved weather prediction and precise spatial analysis of small-scale weather events are crucial for energy management, as is the need to further develop and implement advanced... more

Load Prediction System

Real-time ensemble RTFDDA forecasting system combines real-time WRF-based FDDA technologies and a probabilistic forecast calibration technology for producing reliable real-time probabilistic wind/... more


RTFDDA-LES extends real-world numerical weather prediction to large-eddy-simulation (LES) scales, with grid sizes down to ~30m. The NCAR WRF-based RTFDDA system is formulated for simultaneously... more


As part of NASA and NREL funded projects, a new method has been proposed and demonstrated for the long-term estimate of the wind speeds at a target site, a key step in wind resource assessments (... more

Analog ensemble (AnEn)

FastEddy limited area domain simulation with the cell perturbation method for resolved turbulence instigation (top) versus a periodic domain reference simulation (bottom). This feature allows... more

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WRF-Solar® is the first numerical weather prediction model specifically designed to meet the growing demand for specialized... more


NCAR’s Renewable Energy Forecasting for Kuwait project, a 3-year, $5.1M project sponsored by the Kuwait Institute for Scientific Research (KISR) ( more

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A solar irradiance nowcasting system to support the Group on Earth Observations (GEO) Vision for Energy

A GEO Vision for Energy (GEO-VENER)... more

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NCAR developed an enhanced version of the Weather Research and Forecasting model – WRF-Solar® model to improve forecasting of solar... more

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The WRF-Solar® model (Jimenez et al. 2016) is a specific configuration and augmentation of the Weather Research and Forecasting (WRF) model.... more

VDRAS relies on data assimilation, a technique for combining real-world observations and computer model output to create a more accurate forecast.

VDRAS has a very fast update cycle,... more