Abstract:

Using CLDAS products, the European Centre for Medium-Range Weather Forecasts high resolution model (ECMWF_HR), Global/Regional assimilation and prediction system-Global Forecast System (GRAPES_ GFS) and the data of the national meteorological center forecast (SCMOC) were analyzed for identifying the occurrence and intensity of heat damage under the condition of 1-3d, 1-5d and 1-7d in advance during the early rice booting maturity period in the middle and lower reaches of the Yangtze river from 2021 to 2023. The results showed that: (1) for the identification effect on the occurrence of heat damage, SCMOC products had better identification effect, with the probability of detection (POD) greater than 0.6 for each prediction period. The TS score between 0.49 to 0.59. The POD of GRAPES_GFS product was also greater than 0.6, but the false alarm rate (FAR) was greater than 0.3, with the TS score of 0.45 to 0.52. The ECWMF_HR product had the worst discriminative effect, with POD less than 0.4 and TS score less than 0.3. (2) For the identification effect of heat damage intensity, the value of accumulated heat damage of SCMOC products and CLDAS products were the closest, with the correlation coefficient (Cor) greater than 0.6. The root mean square error (RMSE) increased the forecast period, with values of 1.57℃·d, 2.57℃·d, and 3.43℃·d, respectively. GRAPES_GFS product had a strong forecast for most of Hubei and northern Jiangxi, while the forecast for central and southern Hunan was significantly weak. The Cor of GRAPES_GFS product with the CLDAS product was about 0.06 lower than that of the SCMOC product, and the RMSE was about 0.4℃·d higher. The Cor of ECMWF_HR products and CLDAS products was less than 0.4 in each forecast period, and the RMSE was 0.5℃·d to 1.0℃·d higher than that of the SCMOC products. (3) For the heat damage in different years, SCMOC and GRAPES_GFS products had good identification effect in 2022 and 2023, but the former had better identification effect in 2021. The ECMWF_HR product showed a significant weak forecast for the occurrence and intensity of heat damage in the study area from 2021 to 2023. In summary, the SCMOC prediction product has better identification effect on the heat damage of early rice in the middle and lower reaches of the Yangtze River, which can provide reference to carry out disaster prevention and reduction work on the heat damage of early rice.

Key words: ECMWF_HR model, GRAPES_GFS model, SCMOC model, Heat damage of early rice, Forecast evaluation