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社区首页 >专栏 >Google Earth Engine ——GLDAS-2.0是用更新的普林斯顿全球气象强迫数据集基于MODIS的地表参数数据集

Google Earth Engine ——GLDAS-2.0是用更新的普林斯顿全球气象强迫数据集基于MODIS的地表参数数据集

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发布2024-02-02 11:31:31
2020
发布2024-02-02 11:31:31
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Global Land Data Assimilation System (GLDAS) ingests satellite and ground-based observational data products. Using advanced land surface modeling and data assimilation techniques, it generates optimal fields of land surface states and fluxes.

GLDAS-2.0 is one of two components of the GLDAS Version 2 (GLDAS-2) dataset, the second being GLDAS-2.1. GLDAS-2.0 is reprocessed with the updated Princeton Global Meteorological Forcing Dataset (Sheffield et al., 2006) and upgraded Land Information System Version 7 (LIS-7). It covers the period 1948-2010, and will be extended to more recent years as corresponding forcing data become available.

The model simulation was initialized on January 1, 1948, using soil moisture and other state fields from the LSM climatology for that day of the year. The simulation used the common GLDAS datasets for land cover (MCD12Q1: Friedl et al., 2010), land water mask (MOD44W: Carroll et al., 2009), soil texture (Reynolds, 1999), and elevation (GTOPO30). The MODIS based land surface parameters are used in the current GLDAS-2.x products while the AVHRR base parameters were used in GLDAS-1 and previous GLDAS-2 products (prior to October 2012).

Documentation:

  • Readme
  • How-to
  • 全球陆地数据同化系统(GLDAS)摄取了卫星和地面观测数据产品。它使用先进的陆地表面建模和数据同化技术,生成陆地表面状态和通量的最佳领域。 GLDAS-2.0是GLDAS第二版(GLDAS-2)数据集的两个组成部分之一,第二个是GLDAS-2.1。GLDAS-2.0是用更新的普林斯顿全球气象强迫数据集(Sheffield等人,2006)和升级的土地信息系统第7版(LIS-7)重新处理的。它涵盖了1948-2010年,并将随着相应的强迫数据的获得而扩展到更近的年份。 模型模拟在1948年1月1日初始化,使用当年LSM气候学中的土壤水分和其他状态场。模拟使用了通用的GLDAS数据集,用于土地覆盖(MCD12Q1:Friedl等人,2010)、土地水分掩蔽(MOD44W:Carroll等人,2009)、土壤纹理(Reynolds,1999)和海拔(GTOPO30)。目前的GLDAS-2.x产品使用的是基于MODIS的地表参数,而GLDAS-1和之前的GLDAS-2产品(2012年10月之前)使用的是AVHRR基础参数。 提供者注:扩展名为_tavg的是过去3小时的平均变量,扩展名为'_acc'的是过去3小时的累积变量,扩展名为'_inst'的是瞬时变量,扩展名为_f的是强制变量。 GES DISC Hydrology Documentation

Provider's Note: the names with extension _tavg are variables averaged over the past 3-hours, the names with extension '_acc' are variables accumulated over the past 3-hours, the names with extension '_inst' are instantaneous variables, and the names with '_f' are forcing variables.

Dataset Availability

1948-01-01T00:00:00 - 2010-12-31T00:00:00

Dataset Provider

NASA GES DISC at NASA Goddard Space Flight Center

Collection Snippet

ee.ImageCollection("NASA/GLDAS/V20/NOAH/G025/T3H")

Resolution

27830 meters

Bands Table

Name

Description

Min*

Max*

Units

Albedo_inst

Albedo

4.99

82.25

%

AvgSurfT_inst

Average surface skin temperature

194.55

351.63

K

CanopInt_inst

Plant canopy surface water

0

0.5

kg/m^2

ECanop_tavg

Canopy water evaporation

0

671.88

W/m^2

ESoil_tavg

Direct evaporation from bare soil

0

592.64

W/m^2

Evap_tavg

Evapotranspiration

0

0.0002

kg/m^2/s

LWdown_f_tavg

Downward long-wave radiation flux

44.62

561.46

W/m^2

Lwnet_tavg

Net long-wave radiation flux

-359.07

130.59

W/m^2

PotEvap_tavg

Potential evaporation rate

-241.88

1513.78

W/m^2

Psurf_f_inst

Pressure

47824.13

109036.41

Pa

Qair_f_inst

Specific humidity

0

0.06

kg/kg

Qg_tavg

Heat flux

-517.58

485.13

W/m^2

Qh_tavg

Sensible heat net flux

-872.46

797.71

W/m^2

Qle_tavg

Latent heat net flux

-243.71

716.69

W/m^2

Qs_acc

Storm surface runoff

0

131.39

kg/m^2

Qsb_acc

Baseflow-groundwater runoff

0

42.3

kg/m^2

Qsm_acc

Snow melt

0

27.58

kg/m^2

Rainf_f_tavg

Total precipitation rate

0

0.01

kg/m^2/s

Rainf_tavg

Rain precipitation rate

0

0.01

kg/m^2/s

RootMoist_inst

Root zone soil moisture

2

943.52

kg/m^2

SWE_inst

Snow depth water equivalent

0

117283.5

kg/m^2

SWdown_f_tavg

Downward short-wave radiation flux

0

1329.22

W/m^2

SnowDepth_inst

Snow depth

0

293.2

m

Snowf_tavg

Snow precipitation rate

0

0.004

kg/m^2/s

SoilMoi0_10cm_inst

Soil moisture

1.99

47.59

kg/m^2

SoilMoi10_40cm_inst

Soil moisture

5.99

142.8

kg/m^2

SoilMoi40_100cm_inst

Soil moisture

11.99

285.6

kg/m^2

SoilMoi100_200cm_inst

Soil moisture

20

476

kg/m^2

SoilTMP0_10cm_inst

Soil temperature

218.75

329.55

K

SoilTMP10_40cm_inst

Soil temperature

227.3

317.08

K

SoilTMP40_100cm_inst

Soil temperature

232.59

313.47

K

SoilTMP100_200cm_inst

Soil temperature

234.5

311.86

K

Swnet_tavg

Net short wave radiation flux

0

1128.86

W/m^2

Tair_f_inst

Air temperature

197.03

326.2

K

Tveg_tavg

Transpiration

0

611.89

W/m^2

Wind_f_inst

Wind speed

0.06

30.31

m/s

* = Values are estimated数据引用:

影像属性

Name

Type

Description

end_hour

Double

End hour

start_hour

Double

Start hour

引用:

Rodell, M., P.R. Houser, U. Jambor, J. Gottschalck, K. Mitchell, C.-J. Meng, K. Arsenault, B. Cosgrove, J. Radakovich, M. Bosilovich, J.K. Entin, J.P. Walker, D. Lohmann, and D. Toll, The Global Land Data Assimilation System, Bull. Amer. Meteor. Soc., 85(3), 381-394, 2004.

代码:

代码语言:javascript
复制
var dataset = ee.ImageCollection('NASA/GLDAS/V20/NOAH/G025/T3H')
                  .filter(ee.Filter.date('2010-06-01', '2010-06-02'));
var averageSurfaceSkinTemperatureK = dataset.select('AvgSurfT_inst');
var averageSurfaceSkinTemperatureKVis = {
  min: 250.0,
  max: 300.0,
  palette: ['1303ff', '42fff6', 'f3ff40', 'ff5d0f'],
};
Map.setCenter(71.72, 52.48, 3.0);
Map.addLayer(
    averageSurfaceSkinTemperatureK, averageSurfaceSkinTemperatureKVis,
    'Average Surface Skin Temperature [K]');
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