Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe

Solar Energy ◽  
2013 ◽  
Vol 94 ◽  
pp. 305-326 ◽  
Author(s):  
Richard Perez ◽  
Elke Lorenz ◽  
Sophie Pelland ◽  
Mark Beauharnois ◽  
Glenn Van Knowe ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Solar Irradiance ◽  
Weather Prediction ◽  
Numerical Weather ◽  
The Us

scholarly journals Verification of Forecast Weather Surface Variables over Vietnam Using the National Numerical Weather Prediction System

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Tien Du Duc ◽  
Lars Robert Hole ◽  
Duc Tran Anh ◽  
Cuong Hoang Duc ◽  
Thuy Nguyen Ba
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Model Performance ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Prediction System ◽  
Regional Models ◽  
Global Spectral Model ◽  
Numerical Weather ◽  
The Us

The national numerical weather prediction system of Vietnam is presented and evaluated. The system is based on three main models, namely, the Japanese Global Spectral Model, the US Global Forecast System, and the US Weather Research and Forecasting (WRF) model. The global forecast products have been received at 0.25- and 0.5-degree horizontal resolution, respectively, and the WRF model has been run locally with 16 km horizontal resolution at the National Center for Hydro-Meteorological Forecasting using lateral conditions from GSM and GFS. The model performance is evaluated by comparing model output against observations of precipitation, wind speed, and temperature at 168 weather stations, with daily data from 2010 to 2014. In general, the global models provide more accurate forecasts than the regional models, probably due to the low horizontal resolution in the regional model. Also, the model performance is poorer for stations with altitudes greater than 500 meters above sea level (masl). For tropical cyclone performance validations, the maximum wind surface forecast from global and regional models is also verified against the best track of Joint Typhoon Warning Center. Finally, the model forecast skill during a recent extreme rain event in northeast Vietnam is evaluated.

Impact of aerosols on the forecast accuracy of solar irradiance calculated by a numerical weather prediction model

2014 ◽  
Vol 223 (12) ◽  
pp. 2621-2630 ◽  
Author(s):  
Ken-ichi Shimose ◽  
Hideaki Ohtake ◽  
Joao Gari da Silva Fonseca ◽  
Takumi Takashima ◽  
Takashi Oozeki ◽  
...  
Keyword(s):  
Prediction Model ◽  
Numerical Weather Prediction ◽  
Solar Irradiance ◽  
Weather Prediction ◽  
Forecast Accuracy ◽  
Numerical Weather Prediction Model ◽  
Numerical Weather

scholarly journals Solar Irradiance Forecasts by Mesoscale Numerical Weather Prediction Models with Different Horizontal Resolutions

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1374
Author(s):  
Ohtake ◽  
Uno ◽  
Oozeki ◽  
Hayashi ◽  
Ito ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Solar Irradiance ◽  
Prediction Models ◽  
Weather Prediction ◽  
Longwave Radiation ◽  
Horizontal Resolution ◽  
Numerical Weather ◽  
Downward Longwave Radiation ◽  
Radiation Processes ◽  
Numerical Weather Prediction Models

This study examines the performance of radiation processes (shortwave and longwave radiations) using numerical weather prediction models (NWPs). NWP were calculated using four different horizontal resolutions (5, 2 and 1 km, and 500 m). Validation results on solar irradiance simulations with a horizontal resolution of 500 m indicated positive biases for direct normal irradiance dominate for the period from 09 JST (Japan Standard Time) to 15 JST. On the other hand, after 15 JST, negative biases were found. For diffused irradiance, weak negative biases were found. Validation results on upward longwave radiation found systematic negative biases of surface temperature (corresponding to approximately −2 K for summer and approximately −1 K for winter). Downward longwave radiation tended to be weak negative biases during both summer and winter. Frequency of solar irradiance suggested that the frequency of rapid variations of solar irradiance (ramp rates) from the NWP were less than those observed. Generally, GHI distributions between the four different horizontal resolutions resembled each other, although horizontal resolutions also became finer.

Twenty-Four Hour Solar Irradiance Forecast Based on Neural Networks and Numerical Weather Prediction

2015 ◽  
Vol 137 (3) ◽  
Author(s):  
C. Cornaro ◽  
F. Bucci ◽  
M. Pierro ◽  
F. Del Frate ◽  
S. Peronaci ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Solar Irradiance ◽  
Weather Prediction ◽  
Numerical Weather ◽  
The One ◽  
Model Output Statistics ◽  
Photovoltaic Plant ◽  
University Of Rome ◽  
The University ◽  
Persistence Model

In this paper, several models to forecast the hourly solar irradiance with a day in advance using artificial neural network techniques have been developed and analyzed. The forecast irradiance is the one incident on the plane of the modules array of a photovoltaic plant. Pure statistical (ST) models that use only local measured data and model output statistics (MOS) approaches to refine numerical weather prediction data are tested for the University of Rome “Tor Vergata” site. The performance of ST and MOS, together with the persistence model (PM), is compared. The ST models improve the performance of the PM of around 20%. The combination of ST and NWP in the MOS approach gives the best performance, improving the forecast of approximately 39% with respect to the PM.

Operational implementation of the smoke forecasting capability in the RAP/HRRR numerical weather prediction system

2021 ◽  
Author(s):  
Ravan Ahmadov ◽  
Eric James ◽  
Georg Grell ◽  
Curtis Alexander ◽  
Stuart McKeen
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Fire Plume ◽  
Numerical Weather ◽  
Modeling Systems ◽  
The Us ◽  
Radiative Power ◽  
Visibility Forecasting ◽  
Direct Feedback ◽  
The Impact

<p>Since December, 2020 NOAA’s operational Rapid Refresh and High-Resolution Rapid Refresh (RAP/HRRR) numerical weather prediction modeling systems include smoke forecasting capability. In RAP/HRRR-Smoke primary aerosols (smoke) emissions from wildland fires are simulated by ingesting the fire radiative power data from the VIIRS (onboard S-NPP and NOAA-20) and MODIS (Terra and Aqua) satellite instruments in real time. I will describe the development and applications of the RAP and HRRR-Smoke models, which cover 3 domains – North America (at 13.5 km spatial gridding), CONUS and Alaska (3km resolution). I will present the applications of these models to forecast smoke distributions on regional and continental scales, and how adding the smoke direct feedback capability can improve weather and visibility forecasting. The RAP/HRRR-Smoke models are the first operational weather models in the US, which include the impact of the smoke aerosols on weather and visibility forecasting. The verification of the HRRR-Smoke model for July-August 2018 over the CONUS domain using various meteorological and aerosol measurements will be presented. For verification of the fire plume injection height simulations in HRRR-Smoke, we use the aircraft lidar and in-situ measurements from the FIREX-AQ campaign during August 6-8, 2019. Finally, I will discuss the future plans for improving forecasting of smoke-weather interactions in coupled air quality models.</p>

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