Daily time series of spatially enhanced relative humidity for Europe at 30 arc seconds resolution (Set 4: 2015 - 2019) derived from ERA5-Land data
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Overview:<br> ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past. Processing steps:<br> The original hourly ERA5-Land air temperature 2 m above ground and dewpoint temperature 2 m data has been spatially enhanced from 0.1 degree to 30 arc seconds (approx. 1000 m) spatial resolution by image fusion with CHELSA data (V1.2) (https://chelsa-climate.org/). For each day we used the corresponding monthly long-term average of CHELSA. The aim was to use the fine spatial detail of CHELSA and at the same time preserve the general regional pattern and fine temporal detail of ERA5-Land. The steps included aggregation and enhancement, specifically:<br> 1. spatially aggregate CHELSA to the resolution of ERA5-Land<br> 2. calculate difference of ERA5-Land - aggregated CHELSA<br> 3. interpolate differences with a Gaussian filter to 30 arc seconds<br> 4. add the interpolated differences to CHELSA Subsequently, the temperature time series have been aggregated on a daily basis. From these, daily relative humidity has been calculated for the time period 01/2000 - 07/2021. Relative humidity (rh2m) has been calculated from air temperature 2 m above ground (Ta) and dewpoint temperature 2 m above ground (Td) using the formula for saturated water pressure from Wright (1997): <code>maximum water pressure = 611.21 * exp(17.502 * Ta / (240.97 + Ta))</code> <code>actual water pressure = 611.21 * exp(17.502 * Td / (240.97 + Td))</code> <code>relative humidity = actual water pressure / maximum water pressure</code> Data provided is the daily averages of relative humidity. This set provides data for the years 2000 - 2004. For other time periods, please see further linked data sets. Resultant values have been converted to represent percent * 10, thus covering a theoretical range of [0, 1000]. File naming scheme (YYYY = year; MM = month; DD = day):<br> <code>ERA5_land_rh2m_avg_daily_YYYYMMDD.tif</code> Projection + EPSG code:<br> Latitude-Longitude/WGS84 (EPSG: 4326) Spatial extent:<br> north: 82:00:30N<br> south: 18N<br> west: 32:00:30W<br> east: 70E Spatial resolution:<br> 30 arc seconds (approx. 1000 m) Temporal resolution:<br> Daily Pixel values:<br> Percent * 10 (scaled to Integer; example: value 738 = 73.8 %) Software used:<br> GDAL 3.2.2 and GRASS GIS 8.0.0 Original ERA5-Land dataset license:<br> https://apps.ecmwf.int/datasets/licences/copernicus/ CHELSA climatologies (V1.2):<br> Data used: Karger D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E, Linder, H.P., Kessler, M. (2018): Data from: Climatologies at high resolution for the earth's land surface areas. Dryad digital repository. http://dx.doi.org/doi:10.5061/dryad.kd1d4<br> Original peer-reviewed publication: Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. https://doi.org/10.1038/sdata.2017.122 Processed by:<br> mundialis GmbH & Co. KG, Germany (https://www.mundialis.de/) Reference: Wright, J.M. (1997): Federal meteorological handbook no. 3 (FCM-H3-1997). Office of Federal Coordinator for Meteorological Services and Supporting Research. Washington, DC Data is also available in EU LAEA (EPSG: 3035) projection: https://zenodo.org/record/7434447
概述： ERA5-Land是一款再分析数据集，相较于ERA5，它以更高的分辨率提供了数十年来陆地变量演变的一致性观测视角。该数据集通过重演欧洲中期天气预报中心（ECMWF）ERA5气候再分析的陆地分量生成。再分析技术结合全球观测数据与模式数据，依据物理定律构建出全球完整且一致的数据集。这类再分析数据可追溯至数十年前，能够精准刻画过去的气候状况。 处理流程： 原始的逐小时ERA5-Land地面2米气温与露点温度数据，已通过与CHELSA气候数据集（V1.2，https://chelsa-climate.org/）进行图像融合，将空间分辨率从0.1度提升至30角秒（约1000米）。本次处理每日采用CHELSA对应的长期月平均数据，目标是在保留ERA5-Land的区域整体格局与精细时间细节的同时，利用CHELSA的高空间分辨率特性。具体处理步骤包括聚合与增强操作，详情如下： 1. 将CHELSA数据空间聚合至ERA5-Land的分辨率 2. 计算ERA5-Land与聚合后CHELSA数据的差值 3. 使用高斯滤波器将差值插值至30角秒分辨率 4. 将插值后的差值添加至CHELSA数据 随后，将气温时间序列聚合为日尺度数据，并基于2000年1月至2021年7月的时段计算每日相对湿度。相对湿度（rh2m）通过地面2米气温（Ta）与地面2米露点温度（Td），依据Wright（1997）提出的饱和水汽压公式计算得出： <code>maximum water pressure = 611.21 * exp(17.502 * Ta / (240.97 + Ta))</code> <code>actual water pressure = 611.21 * exp(17.502 * Td / (240.97 + Td))</code> <code>relative humidity = actual water pressure / maximum water pressure</code> 本数据集提供的为每日平均相对湿度，覆盖2000年至2004年时段。其他时段的数据请参阅相关链接数据集。 最终结果值已按百分比×10进行缩放，理论取值范围为[0, 1000]。示例：数值738对应73.8%。 文件命名格式（YYYY=年；MM=月；DD=日）： <code>ERA5_land_rh2m_avg_daily_YYYYMMDD.tif</code> 投影与EPSG代码： 纬度-经度/WGS84（EPSG: 4326） 空间范围： 北：82°00′30″N 南：18°N 西：32°00′30″W 东：70°E 空间分辨率： 30角秒（约1000米） 时间分辨率： 逐日 像素值： 百分比×10（缩放为整数；示例：数值738对应73.8%） 所用软件： GDAL 3.2.2与GRASS GIS 8.0.0 原始ERA5-Land数据集许可： https://apps.ecmwf.int/datasets/licences/copernicus/ CHELSA气候数据集（V1.2）： 所用数据来源：Karger D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E, Linder, H.P., Kessler, M. (2018): 地球陆地表面区域高分辨率气候数据集。Dryad数字仓储。http://dx.doi.org/doi:10.5061/dryad.kd1d4 原始同行评议论文：Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): 地球陆地表面区域高分辨率气候数据集。《科学数据》（Scientific Data）4 170122. https://doi.org/10.1038/sdata.2017.122 处理方： 德国mundialis GmbH & Co. KG（https://www.mundialis.de/） 参考文献：Wright, J.M. (1997): 联邦气象手册第3号（FCM-H3-1997）。联邦气象服务协调员办公室及配套研究项目，华盛顿特区。 本数据集同时提供EU LAEA（EPSG: 3035）投影版本：https://zenodo.org/record/7434447
