JpGU-AGU Joint Meeting 2017

講演情報

[JJ] 口頭発表

セッション記号 H (地球人間圏科学) » H-RE 応用地質学・資源エネルギー利用

[H-RE18] [JJ] 再生可能エネルギーの効果的な利用に向けた地球科学データの活用

2017年5月22日(月) 09:00 〜 10:30 202 (国際会議場 2F)

コンビーナ:大竹 秀明(国立研究開発法人 産業技術総合研究所 太陽光発電研究センター)、宇野 史睦(産業技術総合研究所)、島田 照久(弘前大学大学院理工学研究科)、野原 大輔(電力中央研究所)、座長:大竹 秀明(国立研究開発法人 産業技術総合研究所)

09:45 〜 10:00

[HRE18-04] 複数の予報機関のアンサンブルスプレッドを利用した日射量予測の大外しの予見可能性

*宇野 史睦1,4大竹 秀明1,4松枝 未遠2,3山田 芳則4 (1.産業技術総合研究所、2.筑波大学計算科学研究センター、3.オックスフォード大学、4.気象庁/気象研究所)

キーワード:アンサンブル予測、予測の大外し、TIGGE、地表面日射量

Energy management using weather forecast of numerical weather prediction (NWP) center is exposed to blackout risks and production of excessive surplus power owing to the large forecast errors (forecast busts) of NWP models. The detection of forecast busts is important for stable electricity provisions. Dispersion of ensemble forecast (ensemble spread: ES) relate to forecast skill. Multi-center grand ensemble (MCGE) has higher forecast skill than single-NWP center ensemble forecast. It is considered that the ES and ES of MCGE (ESg) can be used as the predictor of the forecast busts. We investigate the detectability of forecast busts on operational regional forecast predicted by Japan Meteorological Agency (JMA-MSM) using lognormal ES (LNES) and ES of MCGE (LNESg) in Kanto Plain, Japan. One- to six-day ahead global forecast at four leading NWP centers (European Centre for Medium-Range Weather Forecasts: ECMWF, Japan Meteorological Agency: JMA, National Centers for Environmental Prediction: NCEP, and Met Office, UKMO) were used to detect of daily surface solar radiation of regional forecast in 2015.
Root mean square error for the ensemble mean of MCGE (EMg) and 5km regional forecast of JMA-MSM are 27.6 and 28.6 Wm−2 for the one-day ahead forecast, respectively. The forecast skill of the EMg was found to be comparable with that of the JMA-MSM. In October 2015, the correlation between the absolute value of forecast error coefficient (|Fc|) on the operational regional forecast and LNESg for the one-, three-, and five-day ahead forecasts are 0.68, 0.63, and 0.45, respectively (see Figure). The correlation for one- and six-day ahead forecast was found to have statistical significance at ten and seven months, respectively. The LNESg can be, therefore, a valuable predictor for detection of forecast busts in the regional forecast.