Google Earth Engine ——1958-2020年TerraClimate 全球陸地表面每月氣候和氣候水準衡的資料集

TerraClimate: Monthly Climate and Climatic Water Balance for Global Terrestrial Surfaces, University of Idaho

TerraClimate is a dataset of monthly climate and climatic water balance for global terrestrial surfaces. It uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser spatial resolution, but time-varying data from CRU Ts4.0 and the Japanese 55-year Reanalysis (JRA55). Conceptually, the procedure applies interpolated time-varying anomalies from CRU Ts4.0/JRA55 to the high-spatial resolution climatology of WorldClim to create a high-spatial resolution dataset that covers a broader temporal record.

Temporal information is inherited from CRU Ts4.0 for most global land surfaces for temperature, precipitation, and vapor pressure. However, JRA55 data is used for regions where CRU data had zero climate stations contributing (including all of Antarctica, and parts of Africa, South America, and scattered islands). For primary climate variables of temperature, vapor pressure, and precipitation, the University of Idaho provides additional data on the number of stations (between 0 and 8) that contributed to the CRU Ts4.0 data used by TerraClimate. JRA55 was used exclusively for solar radiation and wind speeds.

TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. A modified Thornthwaite-Mather climatic water-balance model and extractable soil water storage capacity data was used at a 0.5° grid from Wang-Erlandsson et al. (2016).

TerraClimate 是全球陸地表面每月氣候和氣候水準衡的資料集。它使用氣候輔助插值，将 WorldClim 資料集的高空間分辨率氣候法線與較粗的空間分辨率、但來自 CRU Ts4.0 和日本 55 年再分析 (JRA55) 的時變資料相結合。從概念上講，該過程将來自 CRU Ts4.0/JRA55 的内插時變異常應用于 WorldClim 的高空間分辨率氣候學，以建立涵蓋更廣泛時間記錄的高空間分辨率資料集。

大多數全球陸地表面的溫度、降水和蒸汽壓力的時間資訊繼承自 CRU Ts4.0。但是，JRA55 資料用于 CRU 資料具有零氣候站貢獻的地區（包括整個南極洲、非洲部分地區、南美洲和分散的島嶼）。對于溫度、蒸氣壓和降水等主要氣候變量，愛達荷大學提供了額外的資料，涉及對 TerraClimate 使用的 CRU Ts4.0 資料做出貢獻的站點數量（0 到 8 之間）。 JRA55 專門用于太陽輻射和風速。

TerraClimate 還使用水準衡模型生成月度地表水準衡資料集，該模型結合了參考蒸散量、降水、溫度和内插植物可提取土壤水容量。修改後的 Thornthwaite-Mather 氣候水準衡模型和可提取的土壤蓄水能力資料在 Wang-Erlandsson 等人的 0.5° 網格中使用。 (2016)。
      

Dataset Availability

1958-01-01T00:00:00 - 2020-12-01T00:00:00

Dataset Provider

University of California Merced

Collection Snippet

ee.ImageCollection("IDAHO_EPSCOR/TERRACLIMATE")

Resolution

2.5 arc minutes

Bands Table

Name	Description	Min*	Max*	Units	Scale
aet	Actual evapotranspiration, derived using a one-dimensional soil water balance model	3140	mm	0.1
def	Climate water deficit, derived using a one-dimensional soil water balance model	4548	mm	0.1
pdsi	Palmer Drought Severity Index	-4317	3418	0.01
pet	Reference evapotranspiration (ASCE Penman-Montieth)	4548	mm	0.1
pr	Precipitation accumulation	7245	mm
ro	Runoff, derived using a one-dimensional soil water balance model	12560	mm
soil	Soil moisture, derived using a one-dimensional soil water balance model	8882	mm	0.1
srad	Downward surface shortwave radiation	5477	W/m^2	0.1
swe	Snow water equivalent, derived using a one-dimensional soil water balance model	32767	mm
tmmn	Minimum temperature	-770	387	°C	0.1
tmmx	Maximum temperature	-670	576	°C	0.1
vap	Vapor pressure	14749	kPa	0.001
vpd	Vapor pressure deficit	1113	kPa	0.01
vs	Wind-speed at 10m	2923	m/s	0.01

* = Values are estimated

影像屬性：

Name	Type	Description
status	String	'provisional' or 'permanent'

資料說明：

The data set is in the public domain as licensed under the Creative Commons Public Domain (CC0) license. 

資料引用：

Abatzoglou, J.T., S.Z. Dobrowski, S.A. Parks, K.C. Hegewisch, 2018, Terraclimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015, Scientific Data 5:170191, doi:10.1038/sdata.2017.191

代碼：

var dataset = ee.ImageCollection('IDAHO_EPSCOR/TERRACLIMATE')
                  .filter(ee.Filter.date('2017-07-01', '2017-08-01'));
var maximumTemperature = dataset.select('tmmx');
var maximumTemperatureVis = {
  min: -300.0,
  max: 300.0,
  palette: [
    '1a3678', '2955bc', '5699ff', '8dbae9', 'acd1ff', 'caebff', 'e5f9ff',
    'fdffb4', 'ffe6a2', 'ffc969', 'ffa12d', 'ff7c1f', 'ca531a', 'ff0000',
    'ab0000'
  ],
};
Map.setCenter(71.72, 52.48, 3);
Map.addLayer(maximumTemperature, maximumTemperatureVis, 'Maximum Temperature');