TY - JOUR
T1 - Multi Model Calibration of Rainfall Forecasts in East Nusa Tenggara Using Ensemble Model Output Statistics
AU - Kuswanto, Heri
AU - Rahadiyuza, Dimas
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2018/6/14
Y1 - 2018/6/14
N2 - The current weather changes uncertainly, marked by significant rise in surface temperatures and reduced rainfall in the tropics. The impact of this uncertainty often leads to a misprediction which may causes lack of anticipation for the upcoming extreme weather events. Statistical approach is required to reduce the error prediction. In 2015, Indonesia experienced the drought-related threat induced by the impact of El Nino storms in the Asia Pacific region. It affected the agricultural sector where almost 21 thousand hectares of agricultural land along Java, Bali and Nusa Tenggara were experiencing drought. This research calibrates ensemble forecasts to take into account the uncertainty and reduce the bias. The calibration of ensemble forecast is carried out by Ensemble Model Output Statistics (EMOS), which is applied to rainfall forecast in East Nusa Tenggara. The results show that calibration using EMOS is capable to produce a reliable forecats, in which the optimum forecast is obtained by training window of 24 months.
AB - The current weather changes uncertainly, marked by significant rise in surface temperatures and reduced rainfall in the tropics. The impact of this uncertainty often leads to a misprediction which may causes lack of anticipation for the upcoming extreme weather events. Statistical approach is required to reduce the error prediction. In 2015, Indonesia experienced the drought-related threat induced by the impact of El Nino storms in the Asia Pacific region. It affected the agricultural sector where almost 21 thousand hectares of agricultural land along Java, Bali and Nusa Tenggara were experiencing drought. This research calibrates ensemble forecasts to take into account the uncertainty and reduce the bias. The calibration of ensemble forecast is carried out by Ensemble Model Output Statistics (EMOS), which is applied to rainfall forecast in East Nusa Tenggara. The results show that calibration using EMOS is capable to produce a reliable forecats, in which the optimum forecast is obtained by training window of 24 months.
UR - http://www.scopus.com/inward/record.url?scp=85048886053&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1028/1/012231
DO - 10.1088/1742-6596/1028/1/012231
M3 - Conference article
AN - SCOPUS:85048886053
SN - 1742-6588
VL - 1028
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012231
T2 - 2nd International Conference on Statistics, Mathematics, Teaching, and Research 2017, ICSMTR 2017
Y2 - 9 October 2017 through 10 October 2017
ER -
