基于亚齐纳甘拉亚县气候数据的热点评估

Abdurahman Abdurahman, N. Ismail, Faisal Abdullah, I. D. G. Arya Putra
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摘要

由于天气/气候因素,确定可能发生野火的热点地区需要进行更详细的研究,以考虑纳甘拉雅县(主要由泥炭地组成)相关机构采取的政策。有些地区的降雨观测资料不完整,需要卫星资料等替代资料进行估算。然而,卫星数据不一定与现场条件相匹配,因此需要进行验证。在本研究中,卫星数据与该地区现有的观测数据进行了验证,因此在没有野外数据的情况下,结果可以作为参考。数据采用GSMaP_GNRT6和Beutong、Cut Nyak Dien气象站、Darul Makmur、PT、Socfindo和Pulo Ie 5个降雨观测站2010-2019年的观测数据。用Pearson方法将卫星数据与观测数据进行相关,观察两者之间的关系。利用平均误差(ME)、均方根误差(RMSE)和平均绝对误差(MAE)公式计算各卫星数据与同一地点观测数据之间的差值。此外,还同时观察了几个地点的火灾事件和卫星热点数据的案例研究。此外,还利用验证后的降水数据计算了标准化降水指数(SPI)值。结果表明:GSMaP_GNRT6卫星降水资料与5个降水观测站的MAE值在101.3 ~ 195.12之间具有较好的相关性;结果还表明,火灾发生前10天的降雨量基数处于低水平(86%)。月SPI值为负、高气温和研究区土地类型也支持热点发生的数量。关键词:热点,降雨,气温,野火,泥炭地
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EVALUATION OF HOTSPOTS BASED ON CLIMATE DATA IN THE NAGAN RAYA REGENCY, ACEH
Identifying hotspots as a potential for wildfires due to weather/climate factors needs to be studied in more detail to consider the policies taken by relevant agencies in the Nagan Raya Regency, mainly consisting of peatlands. Rainfall observation data in some areas are incomplete, so alternative data are needed for rainfall estimation for those areas, such as satellite data. However, the satellite data does not necessarily match the conditions in the field, so validation is needed. In this study, satellite data were validated with available observational data in the area, so the results can be used as a reference when field data is unavailable. The data used are GSMaP_GNRT6 and observation data from 5 rainfall observation posts: Beutong, Cut Nyak Dien Meteorological Station, Darul Makmur, PT. Socfindo and Pulo Ie for the period 2010-2019. The satellite and the observation data were correlated with the Pearson method to see the relationship between the two data. The difference between each satellite data and observations at the same time and place is calculated using the formulas Mean Error (ME), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Furthermore, a case study of fire incidents and satellite hotspot data at several locations was also observed simultaneously. In addition, the validated rainfall data were also used to calculate the Standardized Precipitation Index (SPI) value. The result shows the validation of rainfall data with GSMaP_GNRT6 satellite data has a moderate correlation with the MAE value ranging from 101.3 to 195.12 from the five rainfall observation posts. The results also show that a 10-day base of rainfall before the occurrence of the wildfires was in a low category (86%). The number of hotspot occurrences was also supported by the negative monthly SPI value, high air temperature, and the type of land in the study area. Keywords: Hotspot, Rainfall, Air Temperature, Wildfires, Peat Lands
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