Das NASA Global Land Data Assimilation System Version 2 (GLDAS-2) besteht aus drei Komponenten: GLDAS-2.0, GLDAS-2.1 und GLDAS-2.2. GLDAS-2.0 wird vollständig mit den meteorologischen Eingabedaten von Princeton betrieben und bietet eine zeitlich konsistente Reihe von 1948 bis 2014. GLDAS-2.1 wird mit einer Kombination aus Modell- und Beobachtungsdaten von 2000 bis heute erzwungen. Für die GLDAS-2.2-Produktsuiten wird die Datenassimilation (DA) verwendet, während die GLDAS-2.0- und GLDAS-2.1-Produkte „Open-Loop“ sind (d.h. keine Datenassimilation). Die Auswahl der Forcing-Daten sowie der DA-Beobachtungsquelle, der Variablen und des Schemas variiert für die verschiedenen GLDAS-2.2-Produkte.GLDAS-2.2 ist neu im GES DISC-Archiv und umfasst derzeit ein Hauptprodukt von CLSM-F2.5 mit Datenassimilation für das Gravity Recovery and Climate Experiment (GRACE-DA) von Februar 2003 bis heute. Die GLDAS-2.2-Daten sind in zwei Produktionsstreams verfügbar: „main“ und „Early“. Nur der Hauptstream wird aufgenommen.
Das GLDAS-2.2 GRACE-DA-Produkt wurde mit Catchment-F2.5 in Land Information System (LIS) Version 7 simuliert. Das Datenprodukt enthält 24 Felder für die Landoberfläche vom 1. Februar 2003 bis heute.
Die Simulation begann am 1. Februar 2003 unter Verwendung der Bedingungen aus der GLDAS-2.0-Tagesmodellsimulation für Einzugsgebiete, die mit den meteorologischen Analysefeldern des operativen integrierten Vorhersagesystems des Europäischen Zentrums für mittelfristige Wettervorhersage (EZMW) durchgeführt wurde. Die gesamte Beobachtung der Anomalie des terrestrischen Wassers vom GRACE-Satelliten wurde assimiliert (Li et al., 2019). Aufgrund der Datenvereinbarung mit dem ECMWF enthält dieses tägliche GLDAS-2.2-Produkt keine meteorologischen Forcing-Felder.
Hinweis des Anbieters: Die Namen mit der Erweiterung „_tavg“ sind Variablen, die über die letzten drei Stunden gemittelt wurden. Die Namen mit der Erweiterung „_acc“ sind Variablen, die über die letzten drei Stunden akkumuliert wurden. Die Namen mit der Erweiterung „_inst“ sind Momentanvariablen und die Namen mit „_f“ sind Forcing-Variablen.
Bänder
Pixelgröße 27.830 Meter
Bänder
Name
Einheiten
Min.
Max.
Pixelgröße
Beschreibung
ACond_tavg
m/s
0,000379*
5,99291*
Meter
Aerodynamische Leitfähigkeit
AvgSurfT_tavg
K
179,818*
324.265*
Meter
Durchschnittliche Hautoberflächentemperatur
CanopInt_tavg
kg/m²
0*
1.57295*
Meter
Oberflächenwasser auf Pflanzen
ECanop_tavg
kg/m²/s
–0,021881*
5,3e-05*
Meter
Verdunstung von Wasser aus dem Blätterdach
ESoil_tavg
kg/m²/s
–0,003637*
0,001172*
Meter
Direkte Verdunstung von unbedecktem Boden
EvapSnow_tavg
kg/m²/s
–0,021057*
0,000728*
Meter
Schnee-Evaporation
Evap_tavg
kg/m²/s
–0,02737*
0,00121*
Meter
Evapotranspiration
GWS_tavg
mm
77.0153*
3599.01*
Meter
Grundwasserspeicher
Lwnet_tavg
W/m^2
–221.308*
490.842*
Meter
Nettofluss der langwelligen Strahlung
Qg_tavg
W/m^2
–344.072*
174.036*
Meter
Wärmestrom
Qh_tavg
W/m^2
–2851,75*
54076,7*
Meter
Nettofluss an fühlbarer Wärme
Qle_tavg
W/m^2
–53.856,6*
2983,65*
Meter
Nettofluss latenter Wärme
Qsb_tavg
kg/m²/s
0*
0,000416*
Meter
Grundwasserabfluss
Qsm_tavg
kg/m²/s
0*
0,018311*
Meter
Schneeschmelze
Qs_tavg
kg/m²/s
0*
0,020244*
Meter
Oberflächenabfluss bei Sturm
SnowDepth_tavg
m
0*
8,57951*
Meter
Schneehöhe
SnowT_tavg
K
179,818*
324.265*
Meter
Schneeoberflächentemperatur
SoilMoist_P_tavg
kg/m²
109.394*
4049.02*
Meter
Bodenfeuchteprofil
SoilMoist_RZ_tavg
kg/m²
32,3665*
478.397*
Meter
Bodenfeuchte in der Wurzelzone
SoilMoist_S_tavg
kg/m²
0,001389*
9,56*
Meter
Bodenfeuchte an der Oberfläche
SWE_tavg
kg/m²
0*
3.688,07*
Meter
Wasseräquivalent der Schneehöhe
Swnet_tavg
W/m^2
0*
421.784*
Meter
Netto-Kurzwellenstrahlung
TVeg_tavg
kg/m²/s
-0.000371*
0,001654*
Meter
Transpiration
TWS_tavg
mm
109.394*
5084,16*
Meter
Terrestrischer Wasserspeicher
* geschätzter Mindest- oder Höchstwert
Bildattribute
Bildattribute
Name
Typ
Beschreibung
end_hour
DOUBLE
Startzeit (Stunde)
start_hour
DOUBLE
Startzeit (Stunde)
Nutzungsbedingungen
Nutzungsbedingungen
Die Verteilung von Daten des Goddard Earth Sciences Data and Information Services Center (GES DISC) wird vom Science Mission Directorate (SMD) der NASA finanziert. Gemäß der NASA Earth Science Data and Information Policy sind Daten aus dem GES DISC-Archiv für die Nutzer-Community kostenlos verfügbar.
Weitere Informationen finden Sie auf der GES DISC-Seite Data Policy (Datenrichtlinie).
Zitate
Quellenangaben:
Li, B., M. Rodell, S. Kumar, H. Beaudoing, A. Getirana, B. F. Zaitchik et al. (2019) Global GRACE data assimilation for groundwater and drought monitoring: Advances and challenges. Water Resources Research, 55,
7564–7586.
Das NASA Global Land Data Assimilation System Version 2 (GLDAS-2) besteht aus drei Komponenten: GLDAS-2.0, GLDAS-2.1 und GLDAS-2.2. GLDAS-2.0 wird vollständig mit den meteorologischen Eingabedaten von Princeton betrieben und bietet eine zeitlich konsistente Reihe von 1948 bis 2014. GLDAS-2.1 wird mit einer Kombination aus Modell- und Beobachtungsdaten aus dem Jahr 2000 …
[null,null,[],[[["\u003cp\u003eThe NASA Global Land Data Assimilation System (GLDAS-2.2) dataset provides 3-hourly land surface fields, including soil moisture, temperature, and evapotranspiration, from February 2003 to present.\u003c/p\u003e\n"],["\u003cp\u003eGLDAS-2.2 uses data assimilation, incorporating observations from the Gravity Recovery and Climate Experiment (GRACE) satellite, to estimate terrestrial water storage and related variables.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is available at a spatial resolution of 27830 meters and includes variables averaged, accumulated, and instantaneous over 3-hour intervals.\u003c/p\u003e\n"],["\u003cp\u003eGLDAS-2.2 is freely available through NASA's GES DISC and can be accessed and analyzed using Google Earth Engine.\u003c/p\u003e\n"],["\u003cp\u003eThis product is a component of the broader GLDAS-2 system, which also includes open-loop simulations (GLDAS-2.0 and GLDAS-2.1) covering earlier time periods.\u003c/p\u003e\n"]]],["The NASA GLDAS-2.2 dataset, provided by NASA GES DISC, offers daily land surface data from 2003-01-01 to 2024-11-30, simulated using the Catchment-F2.5 model with data assimilation. Key data includes 24 land surface fields, such as soil moisture, temperature, evaporation, and radiation, available with a 27830-meter pixel size. Data can be accessed via the Earth Engine using the provided code snippet. Data is free for research, education, and non-profit use.\n"],null,["# GLDAS-2.2: Global Land Data Assimilation System\n\nDataset Availability\n: 2003-01-01T03:00:00Z--2025-05-31T00:00:00Z\n\nDataset Provider\n:\n\n\n [NASA GES DISC at NASA Goddard Earth Sciences Data and Information Services Center](https://doi.org/10.5067/TXBMLX370XX8)\n\nCadence\n: 1 Day\n\nTags\n:\n[3-hourly](/earth-engine/datasets/tags/3-hourly) [climate](/earth-engine/datasets/tags/climate) [cryosphere](/earth-engine/datasets/tags/cryosphere) [evaporation](/earth-engine/datasets/tags/evaporation) [forcing](/earth-engine/datasets/tags/forcing) [geophysical](/earth-engine/datasets/tags/geophysical) [gldas](/earth-engine/datasets/tags/gldas) [humidity](/earth-engine/datasets/tags/humidity) [ldas](/earth-engine/datasets/tags/ldas) [nasa](/earth-engine/datasets/tags/nasa) [precipitation](/earth-engine/datasets/tags/precipitation) [pressure](/earth-engine/datasets/tags/pressure) [radiation](/earth-engine/datasets/tags/radiation) [soil](/earth-engine/datasets/tags/soil) [soil-moisture](/earth-engine/datasets/tags/soil-moisture) [surface](/earth-engine/datasets/tags/surface) [temperature](/earth-engine/datasets/tags/temperature) [water-vapor](/earth-engine/datasets/tags/water-vapor) [wind](/earth-engine/datasets/tags/wind) \n\n#### Description\n\nNASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three\ncomponents: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely\nwith the Princeton meteorological forcing input data and provides a temporally\nconsistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination\nof model and observation data from 2000 to present. GLDAS-2.2 product suites use\ndata assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are\n\"open-loop\" (i.e., no data assimilation). The choice of forcing data, as well as\nDA observation source, variable, and scheme, vary for different GLDAS-2.2\nproducts.GLDAS-2.2 is new to the GES DISC archive and currently includes a main\nproduct from CLSM-F2.5 with Data Assimilation for the Gravity Recovery and\nClimate Experiment (GRACE-DA) from February 2003 to present. The GLDAS-2.2\ndata are available in two production streams: main and Early, only main one\nis ingested.\n\nThe GLDAS-2.2 GRACE-DA product was simulated with Catchment-F2.5 in Land\nInformation System (LIS) Version 7. The data product contains 24 land\nsurface fields from February 1, 2003 to present.\n\nThe simulation started on February 1, 2003 using the conditions from the\nGLDAS-2.0 Daily Catchment model simulation, forced with the meteorological\nanalysis fields from the operational European Centre for Medium-Range\nWeather Forecasts (ECMWF) Integrated Forecasting System. The total\nterrestrial water anomaly observation from GRACE satellite was assimilated\n(Li et al, 2019). Due to the data agreement with ECMWF, this GLDAS-2.2 daily\nproduct does not include the meteorological forcing fields.\n\nDocumentation:\n\n- [Readme](https://hydro1.gesdisc.eosdis.nasa.gov/data/GLDAS/GLDAS_CLSM025_DA1_D.2.2/doc/README_GLDAS2.pdf)\n\n- [How-to](https://disc.gsfc.nasa.gov/information/howto?tags=hydrology)\n\n- [GES DISC Hydrology Documentation](https://disc.gsfc.nasa.gov/information/documents?title=Hydrology%20Documentation)\n\nProvider's Note: the names with extension _tavg are variables\naveraged over the past 3-hours, the names with extension '_acc' are\nvariables accumulated over the past 3-hours, the names with extension\n'_inst' are instantaneous variables, and the names with '_f' are\nforcing variables.\n\n### Bands\n\n\n**Pixel Size**\n\n27830 meters\n\n**Bands**\n\n| Name | Units | Min | Max | Pixel Size | Description |\n|---------------------|-----------|-------------|------------|------------|-----------------------------------|\n| `ACond_tavg` | m/s | 0.000379\\* | 5.99291\\* | meters | Aerodynamic conductance |\n| `AvgSurfT_tavg` | K | 179.818\\* | 324.265\\* | meters | Average surface skin temperature |\n| `CanopInt_tavg` | kg/m\\^2 | 0\\* | 1.57295\\* | meters | Plant canopy surface water |\n| `ECanop_tavg` | kg/m\\^2/s | -0.021881\\* | 5.3e-05\\* | meters | Canopy water evaporation |\n| `ESoil_tavg` | kg/m\\^2/s | -0.003637\\* | 0.001172\\* | meters | Direct evaporation from bare soil |\n| `EvapSnow_tavg` | kg/m\\^2/s | -0.021057\\* | 0.000728\\* | meters | Snow Evaporation |\n| `Evap_tavg` | kg/m\\^2/s | -0.02737\\* | 0.00121\\* | meters | Evapotranspiration |\n| `GWS_tavg` | mm | 77.0153\\* | 3599.01\\* | meters | Ground water storage |\n| `Lwnet_tavg` | W/m\\^2 | -221.308\\* | 490.842\\* | meters | Net long-wave radiation flux |\n| `Qg_tavg` | W/m\\^2 | -344.072\\* | 174.036\\* | meters | Heat flux |\n| `Qh_tavg` | W/m\\^2 | -2851.75\\* | 54076.7\\* | meters | Sensible heat net flux |\n| `Qle_tavg` | W/m\\^2 | -53856.6\\* | 2983.65\\* | meters | Latent heat net flux |\n| `Qsb_tavg` | kg/m\\^2/s | 0\\* | 0.000416\\* | meters | Baseflow-groundwater runoff |\n| `Qsm_tavg` | kg/m\\^2/s | 0\\* | 0.018311\\* | meters | Snow melt |\n| `Qs_tavg` | kg/m\\^2/s | 0\\* | 0.020244\\* | meters | Storm surface runoff |\n| `SnowDepth_tavg` | m | 0\\* | 8.57951\\* | meters | Snow depth |\n| `SnowT_tavg` | K | 179.818\\* | 324.265\\* | meters | Snow Surface temperature |\n| `SoilMoist_P_tavg` | kg/m\\^2 | 109.394\\* | 4049.02\\* | meters | Profile Soil moisture |\n| `SoilMoist_RZ_tavg` | kg/m\\^2 | 32.3665\\* | 478.397\\* | meters | Root Zone Soil moisture |\n| `SoilMoist_S_tavg` | kg/m\\^2 | 0.001389\\* | 9.56\\* | meters | Surface Soil moisture |\n| `SWE_tavg` | kg/m\\^2 | 0\\* | 3688.07\\* | meters | Snow depth water equivalent |\n| `Swnet_tavg` | W/m\\^2 | 0\\* | 421.784\\* | meters | Net short wave radiation flux |\n| `TVeg_tavg` | kg/m\\^2/s | -0.000371\\* | 0.001654\\* | meters | Transpiration |\n| `TWS_tavg` | mm | 109.394\\* | 5084.16\\* | meters | Terrestrial water storage |\n\n\\* estimated min or max value\n\n### Image Properties\n\n**Image Properties**\n\n| Name | Type | Description |\n|------------|--------|-------------|\n| end_hour | DOUBLE | End hour |\n| start_hour | DOUBLE | Start hour |\n\n### Terms of Use\n\n**Terms of Use**\n\nDistribution of data from the Goddard Earth Sciences\nData and Information Services Center (GES DISC) is funded by NASA's\nScience Mission Directorate (SMD). Consistent with NASA [Earth\nScience Data and Information Policy](https://www.earthdata.nasa.gov/engage/open-data-services-and-software/data-and-information-policy/),\ndata from the GES DISC archive are available free to the user community.\nFor more information visit the GES DISC [Data Policy](https://disc.sci.gsfc.nasa.gov/citing)\npage.\n\n### Citations\n\nCitations:\n\n- Li, B., M. Rodell, S. Kumar, H. Beaudoing, A. Getirana, B. F. Zaitchik, et\n al. (2019) Global GRACE data assimilation for groundwater and drought\n monitoring: Advances and challenges. Water Resources Research, 55,\n 7564-7586.\n- [Additional references](https://ldas.gsfc.nasa.gov/gldas/GLDASpublications.php)\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.ImageCollection('NASA/GLDAS/V022/CLSM/G025/DA1D')\n .filter(ee.Filter.date('2010-06-01', '2010-06-02'));\nvar averageSurfaceSkinTemperatureK = dataset.select('AvgSurfT_tavg');\nvar averageSurfaceSkinTemperatureKVis = {\n min: 258,\n max: 316,\n palette: ['1303ff', '42fff6', 'f3ff40', 'ff5d0f'],\n};\nMap.setCenter(71.72, 52.48, 3.0);\nMap.addLayer(\n averageSurfaceSkinTemperatureK, averageSurfaceSkinTemperatureKVis,\n 'Average Surface Skin Temperature [K]');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/NASA/NASA_GLDAS_V022_CLSM_G025_DA1D) \n[GLDAS-2.2: Global Land Data Assimilation System](/earth-engine/datasets/catalog/NASA_GLDAS_V022_CLSM_G025_DA1D) \nNASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination of model and observation data from 2000 ... \nNASA/GLDAS/V022/CLSM/G025/DA1D, 3-hourly,climate,cryosphere,evaporation,forcing,geophysical,gldas,humidity,ldas,nasa,precipitation,pressure,radiation,soil,soil-moisture,surface,temperature,water-vapor,wind \n2003-01-01T03:00:00Z/2025-05-31T00:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://doi.org/10.5067/TXBMLX370XX8)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/NASA_GLDAS_V022_CLSM_G025_DA1D)"]]
