Page 188 - 《高原气象》2025年第3期

高 原 气 象 44 卷
746

A Precipitation Forecast Score Based on Potential Impact

PAN Liujie ， ZHANG Hongfang ， QI Chunjuan ， LU Shan ， DU Lili 1， 2
2， 3
1， 2
2， 3
1， 2
（1. Shaanxi Meteorological Observatory， Xi'an 710014， Shannxi， China；
2. Key Laboratory of Eco-Environment and Meteorology for the Qinling Mountains and
Loess Plateau， Xi'an 710014， Shannxi， China；
3. Shaanxi Meteorological Service Centre， Xi'an 710014， Shannxi， China）
Abstract： In traditional contingency tables， the hit and false alarm events are given equal weights when calculat‐
ing the precipitation TS score. The weight of missed precipitation events with different amounts that satisfy the
threshold conditions is also the same. At the same time， the frequency calculation method for hit events of differ‐
ent precipitation amounts within the threshold range is also the same. However， these methods lack precision in
the verification of high-resolution grid precipitation forecasts. In fact， the impact of differences in observed pre‐
cipitation values， even when predictions hit the threshold， may be completely different. Additionally， the impact
of differences in the forecasting and observation of precipitation values in missed precipitation events may also
vary greatly. The article proposes a precipitation impact forecast score based on the comprehensive consideration
of precipitation hit rate， missed alarm ratio， and precipitation amount. "Impact" is defined as the characterization
of potential consequences that may result from forecast hits or misses on actual precipitation occurrences. For hit
and missed events， impact factors are defined by taking the logarithm of observed precipitation and the logarithm
of the difference between observed and forecasted precipitation. Based on this， equivalent impacts （A and C） of
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hit and missed events are accumulated at the spatiotemporal scale. The scoring solely considering the impact of C
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is defined as a sub-item of the Impact Threat Scoring （ITS）. The precipitation scoring that takes into account the
combined effects of A and C is defined as the ITS score. Analysis shows that ITS assigns dynamic weights
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based on the degree of difference in missed precipitation， allowing for a clear distinction of the impact level of
missed events. On the other hand， ITS rewards the accurate prediction of heavy precipitation. The larger the hit
precipitation values and the smaller the difference between the forecasted and observed values in missed events，
the larger the ITS score. These factors result in a better ability to depict the potential consequences on actual pre‐
cipitation.
Key words： forecast verification； precipitation impact； TS score； ITS ； ITS score
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