Temperature and precipitation gridded data for global and regional domains derived from in-situ and satellite observations

This dataset provides high-resolution gridded temperature and precipitation observations from a selection of sources. Additionally the dataset contains daily global average near-surface temperature anomalies. All fields are defined on either daily or monthly frequency. The datasets are regularly updated to incorporate recent observations. The included data sources are commonly known as GISTEMP, Berkeley Earth, CPC and CPC-CONUS, CHIRPS, IMERG, CMORPH, GPCC and CRU, where the abbreviations are explained below.
These data have been constructed from high-quality analyses of meteorological station series and rain gauges around the world, and as such provide a reliable source for the analysis of weather extremes and climate trends. The regular update cycle makes these data suitable for a rapid study of recently occurred phenomena or events.
The NASA Goddard Institute for Space Studies temperature analysis dataset (GISTEMP-v4) combines station data of the Global Historical Climatology Network (GHCN) with the Extended Reconstructed Sea Surface Temperature (ERSST) to construct a global temperature change estimate.
The Berkeley Earth Foundation dataset (BERKEARTH) merges temperature records from 16 archives into a single coherent dataset.
The NOAA Climate Prediction Center datasets (CPC and CPC-CONUS) define a suite of unified precipitation products with consistent quantity and improved quality by combining all information sources available at CPC and by taking advantage of the optimal interpolation (OI) objective analysis technique.
The Climate Hazards Group InfraRed Precipitation with Station dataset (CHIRPS-v2) incorporates 0.05° resolution satellite imagery and in-situ station data to create gridded rainfall time series over the African continent, suitable for trend analysis and seasonal drought monitoring.
The Integrated Multi-satellitE Retrievals dataset (IMERG) by NASA uses an algorithm to intercalibrate, merge, and interpolate “all'' satellite microwave precipitation estimates, together with microwave-calibrated infrared (IR) satellite estimates, precipitation gauge analyses, and potentially other precipitation estimators over the entire globe at fine time and space scales for the Tropical Rainfall Measuring Mission (TRMM) and its successor, Global Precipitation Measurement (GPM) satellite-based precipitation products.
The Climate Prediction Center morphing technique dataset (CMORPH) by NOAA has been created using precipitation estimates that have been derived from low orbiter satellite microwave observations exclusively. Then, geostationary IR data are used as a means to transport the microwave-derived precipitation features during periods when microwave data are not available at a location.
The Global Precipitation Climatology Centre dataset (GPCC) is a centennial product of monthly global land-surface precipitation based on the ~80,000 stations world-wide that feature record durations of 10 years or longer. The data coverage per month varies from ~6,000 (before 1900) to more than 50,000 stations.
The Climatic Research Unit dataset (CRU v4) features an improved interpolation process, which delivers full traceability back to station measurements. The station measurements of temperature and precipitation are public, as well as the gridded dataset and national averages for each country. Cross-validation was performed at a station level, and the results have been published as a guide to the accuracy of the interpolation.
This catalogue entry complements the E-OBS record in many aspects, as it intends to provide high-resolution gridded meteorological observations at a global rather than continental scale.
These data may be suitable as a baseline for model comparisons or extreme event analysis in the CMIP5 and CMIP6 dataset.

本数据集汇聚了来自多个来源的高分辨率网格化温度和降水量观测数据。此外，该数据集还包含了每日全球近地表平均温度异常值。所有字段均以每日或每月的频率定义。数据集定期更新，以整合最新的观测数据。包含的数据来源包括广为人知的 GISTEMP、Berkeley Earth、CPC 及 CPC-CONUS、CHIRPS、IMERG、CMORPH、GPCC 和 CRU，其缩写解释如下。

这些数据基于对全球气象站序列和雨量计的高质量分析构建而成，因此为分析极端天气现象和气候趋势提供了可靠的资料来源。定期的更新周期使得这些数据适用于对近期发生现象或事件的快速研究。

NASA 戈达德太空研究所温度分析数据集（GISTEMP-v4）将全球历史气候网络（GHCN）的站点数据与扩展重建的海表温度（ERSST）相结合，以构建全球温度变化估计。

伯克利地球基金会数据集（BERKEARTH）将来自16个档案馆的温度记录合并为一个单一且连贯的数据集。

NOAA 气候预测中心数据集（CPC 和 CPC-CONUS）通过整合 CPC 可用的所有信息来源，并利用最优内插（OI）客观分析技术，定义了一系列统一的降水量产品，以实现数量一致和质量提升。

气候灾害小组红外降水与站点数据集（CHIRPS-v2）通过融合0.05°分辨率的卫星影像和地面站点数据，在非洲大陆上创建网格化降雨时间序列，适用于趋势分析和季节性干旱监测。

NASA 集成多卫星检索数据集（IMERG）利用算法对“所有”卫星微波降水量估计进行校准、合并和插值，同时结合微波校准的红外（IR）卫星估计、降水量计分析和可能的其它降水量估计，在全球范围内以精细的时间和空间尺度，为热带降雨测量任务（TRMM）及其继任者全球降水量测量（GPM）卫星降雨产品提供数据。

NOAA 气候预测中心形态变换技术数据集（CMORPH）使用仅来自低轨道卫星的微波观测数据推导出的降水量估计，然后利用地球同步红外数据作为在微波数据不可用时的微波推导降水量特征传输手段。

全球降水量气候中心数据集（GPCC）是基于约 80,000 个具有 10 年或更长时间记录的全球陆地表面月降水量数据，每月的数据覆盖范围从 1900 年前的约 6,000 个站点增加到超过 50,000 个站点。

气候研究单位数据集（CRU v4）具有改进的内插过程，能够完整追溯至站点测量值。温度和降水量测量值以及网格化数据集和每个国家的国家平均值均公开，并在站点级别进行了交叉验证，结果已作为插值准确度指南发表。

本目录条目在多个方面补充了 E-OBS 记录，因为它旨在提供全球而非大陆尺度的分辨率较高的网格化气象观测数据。

这些数据可能适合作为 CMIP5 和 CMIP6 数据集模型比较或极端事件分析的基础。