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引用內容
參考資料：
Keller, C. A.、Knowland, K. E.、Duncan, B. N. Liu, J.、Anderson, D. C.、
Das, S.、... & Pawson, S. (2021 年)。NASA GEOS 組成預報模型系統 GEOS-CF v1 的說明。0：Journal of Advances in Modeling
Earth Systems, 13(4), e2020MS002413.
doi:10.1029/2020MS002413
[null,null,[],[[["\u003cp\u003eThe NASA GEOS-CF dataset provides high-resolution (0.25°) global atmospheric composition forecasts, including pollutants like O3, CO, NO2, SO2, and PM2.5.\u003c/p\u003e\n"],["\u003cp\u003eIt's a replay dataset covering the period from 2018-01-01 to 2024-12-11, with a temporal resolution of 3 hours and spatial resolution of 27750 meters.\u003c/p\u003e\n"],["\u003cp\u003eDeveloped by NASA's Global Modeling and Assimilation Office (GMAO), it's intended to supplement NASA's observational data for atmospheric chemistry research.\u003c/p\u003e\n"],["\u003cp\u003eGEOS-CF forecasts have demonstrated skill comparable to hindcasts, and their accuracy can be further enhanced through bias-correction techniques.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is freely available for research, education, and non-profit use through Google Earth Engine.\u003c/p\u003e\n"]]],["The dataset provides high-temporal frequency meteorological replay data from NASA's GEOS-CF, a global constituent prediction system. It offers hindcasts and 5-day forecasts of atmospheric constituents like ozone, carbon monoxide, nitrogen dioxide, sulfur dioxide, and fine particulate matter. Data, ranging from 2018-01-01T00:00:00Z to 2025-02-21T12:00:00Z, is available through the Earth Engine platform, accessible via provided snippets and a code editor. The model's performance has been evaluated against observations, demonstrating realistic simulations of several constituents.\n"],null,["Dataset Availability\n: 2018-01-01T00:00:00Z--2025-08-31T12:00:00Z\n\nDataset Provider\n:\n\n\n [NASA / GMAO](https://gmao.gsfc.nasa.gov/weather_prediction/GEOS-CF/)\n\nTags\n:\n[atmosphere](/earth-engine/datasets/tags/atmosphere) [composition](/earth-engine/datasets/tags/composition) [forecast](/earth-engine/datasets/tags/forecast) [geos](/earth-engine/datasets/tags/geos) [gmao](/earth-engine/datasets/tags/gmao) [nasa](/earth-engine/datasets/tags/nasa) \n\nDescription \nThis dataset contains meteorological replay (rpl) of high-temporal\nfrequency data (htf).\nThe Goddard Earth Observing System Composition Forecast (GEOS-CF) system is\na high-resolution (0.25°) global constituent prediction system from\nNASA's [Global Modeling and Assimilation Office(GMAO)](https://gmao.gsfc.nasa.gov/).\n\nGEOS-CF offers a new tool for atmospheric chemistry research, with the goal\nto supplement NASA's broad range of space-based and in-situ observations.\nGEOS-CF expands on the GEOS weather and aerosol modeling system by\nintroducing the [GEOS-Chem](http://wiki.seas.harvard.edu/geos-chem/)\nchemistry module to provide hindcasts and 5-days forecasts of atmospheric\nconstituents including ozone (O3), carbon monoxide (CO), nitrogen dioxide\n(NO2), sulfur dioxide (SO2), and fine particulate matter (PM2.5). The\nchemistry module integrated in GEOS-CF is identical to the offline GEOS-Chem\nmodel and readily benefits from the innovations provided by the GEOS-Chem\ncommunity.\n\nEvaluation of GEOS-CF against satellite, ozonesonde, and surface\nobservations for years 2018--2019 shows realistic simulated\nconcentrations of O3, NO2, and CO, with normalized mean biases of −0.1\nto 0.3, normalized root mean square errors between 0.1--0.4, and\ncorrelations between 0.3--0.8. Comparisons against surface observations\nhighlight the successful representation of air pollutants in many regions of\nthe world and during all seasons, yet also highlight current limitations,\nsuch as a global high bias in SO2 and an overprediction of summertime O3\nover the Southeast United States.\n\nGEOS-CF v1.0 generally overestimates aerosols by 20%--50% due to known\nissues in GEOS-Chem v12.0.1 that have been addressed in later versions. The\n5-days forecasts have skill scores comparable to the 1-day hindcast. Model\nskills can be improved significantly by applying a bias-correction to the\nsurface model output using a machine-learning approach.\n\nBands\n\n\n**Pixel Size**\n\n27750 meters\n\n**Bands**\n\n| Name | Units | Pixel Size | Description |\n|--------------------|---------------|------------|------------------------------------------------------------------------|\n| `CO` | Mol fraction | meters | Carbon monoxide (CO, MW = 28.00 g mol-1) volume mixing ratio dry air |\n| `NO2` | Mol fraction | meters | Nitrogen dioxide (NO2, MW = 46.00 g mol-1) volume mixing ratio dry air |\n| `O3` | Mol fraction | meters | Ozone (O3, MW = 48.00 g mol-1) volume mixing ratio dry air |\n| `PM25_RH35_GCC` | ug m-3 | meters | Particulate matter with diameter below 2.5 um RH 35 |\n| `PM25_RH35_GOCART` | kg/m\\^3 | meters | Total reconstructed PM2.5 RH 35 |\n| `Q` | Mass fraction | meters | Specific humidity |\n| `RH` | | meters | Relative humidity after moist |\n| `SLP` | Pa | meters | Sea level pressure |\n| `SO2` | Mol fraction | meters | Sulfur dioxide (SO2, MW = 64.00 g mol-1) volume mixing ratio dry air |\n| `T` | K | meters | Air temperature |\n| `U` | m/s | meters | Eastward wind |\n| `V` | m/s | meters | Northward wind |\n\nTerms of Use\n\n**Terms of Use**\n\nUnless otherwise noted, all NASA-produced data may be used for any purpose\nwithout prior permission. For more information and exceptions visit the\n[NASA Data \\& Information Policy page](https://earthdata.nasa.gov/collaborate/open-data-services-and-software/data-information-policy).\n\nCitations \nCitations:\n\n- Keller, C. A., Knowland, K. E., Duncan, B. N., Liu, J., Anderson, D. C.,\n Das, S., ... \\& Pawson, S. (2021). Description of the NASA GEOS composition\n forecast modeling system GEOS-CF v1. 0. Journal of Advances in Modeling\n Earth Systems, 13(4), e2020MS002413.\n [doi:10.1029/2020MS002413](https://doi.org/10.1029/2020MS002413)\n\nDOIs\n\n- \u003chttps://doi.org/10.1029/2020MS002413\u003e\n\nExplore with Earth Engine **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\nCode Editor (JavaScript) \n\n```javascript\nvar imageVisParamNO2 = {\n 'bands': ['NO2'],\n 'min': 6.96e-11,\n 'max': 4.42e-8,\n};\n\nvar imageVisParamT = {\n 'bands': ['T'],\n 'min': 220,\n 'max': 320,\n 'palette': ['d7191c', 'fdae61', 'ffffbf', 'abd9e9', '2c7bb6'],\n};\n\nvar geosCf = ee.ImageCollection('NASA/GEOS-CF/v1/rpl/htf');\n\nMap.setCenter(100, 20, 3);\n\nvar weeklyT =\n geosCf.select('T').filterDate('2019-06-01', '2019-06-08').median();\nMap.addLayer(weeklyT, imageVisParamT, 'Weekly T', false, 1);\n\nvar NO2 = ee.Image('NASA/GEOS-CF/v1/rpl/htf/20190601_0000z');\nMap.addLayer(NO2, imageVisParamNO2, 'NO2', true, 1);\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/NASA/NASA_GEOS-CF_v1_rpl_htf) \n[GEOS-CF rpl htf v1: Goddard Earth Observing System Composition Forecast](/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_rpl_htf) \nThis dataset contains meteorological replay (rpl) of high-temporal frequency data (htf). The Goddard Earth Observing System Composition Forecast (GEOS-CF) system is a high-resolution (0.25°) global constituent prediction system from NASA's Global Modeling and Assimilation Office(GMAO). GEOS-CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA's ... \nNASA/GEOS-CF/v1/rpl/htf, atmosphere,composition,forecast,geos,gmao,nasa \n2018-01-01T00:00:00Z/2025-08-31T12:00:00Z \n-90 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.1029/2020MS002413](https://doi.org/https://gmao.gsfc.nasa.gov/weather_prediction/GEOS-CF/)\n- [https://doi.org/10.1029/2020MS002413](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_rpl_htf)"]]
