Skill and Skill Prediction of Cloud-Track Advection-Only Forecasting under a Cumulus-Dominated Regime

Skill and Skill Prediction of Cloud-Track Advection-Only Forecasting under a Cumulus-Dominated... AbstractThe intermittency of solar power production is dependent on the evolution and advection of the nearby cloud field. A key problem related to solar energy integration is the improvement of 1-h-ahead forecasts to reduce the impact of intermittency on power systems operations. Many solar forecasts explicitly or implicitly assume Taylor’s hypothesis. While such advection-only forecasts can be presumed to be valid across sufficiently short time scales, it is not clear how rapidly the skill of such a forecast decays with increased lead time. As the goal is to improve the quality of 1-h-ahead forecasts, this work focuses on quantifying the skill of cloud-track wind-based cumulus-dominated cloud field forecasts with respect to lead time. No explicit connection is drawn to the quality of solar forecasts because of the importance of separating two potential sources of error: cloud field forecasting and radiative transfer estimation. It is found that the cumulus field forecast skill begins to asymptotically approach a minimum at lead times of beyond 30 min, suggesting that advection-only forecasts in a cumulus-dominated environment should not be relied upon for 1-h-ahead point forecasts used by radiative transfer methods to estimate solar power production. A first attempt at forming a probabilistic forecast that can quantify this increasing uncertainty when using advection-only methods is presented. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Meteorology and Climatology American Meteorological Society

Skill and Skill Prediction of Cloud-Track Advection-Only Forecasting under a Cumulus-Dominated Regime

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1558-8432
eISSN
1558-8432
D.O.I.
10.1175/JAMC-D-16-0224.1
Publisher site
See Article on Publisher Site

Abstract

AbstractThe intermittency of solar power production is dependent on the evolution and advection of the nearby cloud field. A key problem related to solar energy integration is the improvement of 1-h-ahead forecasts to reduce the impact of intermittency on power systems operations. Many solar forecasts explicitly or implicitly assume Taylor’s hypothesis. While such advection-only forecasts can be presumed to be valid across sufficiently short time scales, it is not clear how rapidly the skill of such a forecast decays with increased lead time. As the goal is to improve the quality of 1-h-ahead forecasts, this work focuses on quantifying the skill of cloud-track wind-based cumulus-dominated cloud field forecasts with respect to lead time. No explicit connection is drawn to the quality of solar forecasts because of the importance of separating two potential sources of error: cloud field forecasting and radiative transfer estimation. It is found that the cumulus field forecast skill begins to asymptotically approach a minimum at lead times of beyond 30 min, suggesting that advection-only forecasts in a cumulus-dominated environment should not be relied upon for 1-h-ahead point forecasts used by radiative transfer methods to estimate solar power production. A first attempt at forming a probabilistic forecast that can quantify this increasing uncertainty when using advection-only methods is presented.

Journal

Journal of Applied Meteorology and ClimatologyAmerican Meteorological Society

Published: Mar 20, 2017

References

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