我们通过ee.ImageCollection方法定义一个影像集合,在我这里就是ECMWF/ERA5_LAND/DAILY_AGGR这个逐日的ERA5数据集,并选择其中的volumetric_soil_water_layer_1波段,即第一层土壤体积含水量;随后,用region定义研究区域,在我这里我需要全球的数据,所以就定义了全球的空间范围。 随后,设置时间范围。startDate和endD...
2. 使用FAO/GAUL_SIMPLIFIED_500m/2015/level0数据集,过滤出包含上述几何点的区域roi,并将该区域添加到地图中。 3. 使用ECMWF/ERA5_LAND/DAILY_AGGR数据集,选择了温度变量temperature_2m,并进行了一系列筛选条件:选择2015年到2018年的数据,以及3月到6月的数据。然后对每个图像进行了处理,将温度转换为摄氏度,并...
使用的气温数据为 ERA5-Land Daily Aggregated 下载自GEE https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5_LAND_DAILY_RAW 下面是代码 #清空变量 rm(list = ls()) gc() #安装包 #install.packages("terra") #install.packages("heatwaveR") #install.packages("magrittr") #install...
Daily Mean')Map.addLayer(era5_heat_i.select('utci_mean').selfMask().subtract(273.15),{min:...
Results reveal a general underestimation of TMAX and overestimation of TMIN in both operational forecasts and ERA5, highlighting the limitation of the ECMWF model in estimating the amplitude of the diurnal cycle of air temperature. ERA5′s accuracy has improved over the past decade, due to ...
Details can be found at the following link: https://cds.climate.copernicus.eu/how-to-api * cdsapirc Needed to authenticate with ECMWF CDS data servers to allow download. This is a dot-file in my your home directory (~/.cdsapirc). Key is specific to a CDS account. ~/.cdsapirc ...
To better analyze the spatial and temporal changes in the FG, two 30-year periods (1951–1980 and 1991–2020) were extracted, and the annual PFG, SFG, IFG and NFG were aggregated into 30-year values (PFG30, SFG30, IFG30, and NFG30), determined as follows:(2)Land{PFG30NPFG=30SFG...
ERA5 and ERA5-Land datasets, available at hourly timesteps, were aggregated to obtain daily time step values matching the observed gridded products time observations (07 h UTC to 07 h UTC). In addition, to enable a consistent comparison, AEMET dataset was resampled to 0.1° (0.25°) grid...
However, such spatial resolutions are rather coarse for physically based distributed hydrologic simulations, since the aggregated precipitation fields incorporate substantial biases, especially for low probability events; such as heavy precipitation (see e.g., Langousis & Kaleris, 2014; Mamalakis et al...
ERA5-HEAT is freely available from the Copernicus Climate Data Store (https://doi.org/10.24381/cds.553b7518), which has been developed as part of the Copernicus Climate Change Service implemented by ECMWF (https://cds.climate.copernicus.eu/). The gridded datasets of T and the UTCI were ...