このデータセットには、高時間頻度データ（htf）の気象予報（fcst）が含まれています。creation_time プロパティと forecast_time プロパティを使用して、関心のあるデータを選択します。Goddard Earth Observing System Composition Forecast（GEOS-CF）システムは、NASA の Global Modeling and Assimilation Office（GMAO）による高解像度（0.25°）のグローバル構成要素予測システムです。
Keller, C. A.、Knowland, K. E., Duncan, B. N., Liu, J.、Anderson、D. C.、
Das, S.、... & Pawson, S. （2021 年）。NASA GEOS 構成予測モデリング システム GEOS-CF v1 の説明。0: Journal of Advances in Modeling
Earth Systems, 13(4), e2020MS002413.
doi:10.1029/2020MS002413
[null,null,[],[[["\u003cp\u003eThe NASA GEOS-CF v1 dataset provides high-resolution (0.25°) global meteorological forecasts, including atmospheric constituents like ozone, carbon monoxide, and particulate matter.\u003c/p\u003e\n"],["\u003cp\u003eIt offers a 5-day forecast and hindcast data, created by the Global Modeling and Assimilation Office (GMAO).\u003c/p\u003e\n"],["\u003cp\u003eUsers can select specific data using the 'creation_time' and 'forecast_time' properties.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is available from October 1, 2022, to December 11, 2024, and is accessible through Google Earth Engine.\u003c/p\u003e\n"],["\u003cp\u003eThough generally accurate, the dataset may overestimate aerosols and has some limitations in predicting specific constituents like SO2 and summertime O3 in certain regions.\u003c/p\u003e\n"]]],["The NASA GEOS-CF dataset, provided by NASA/GMAO, offers high-resolution meteorological forecasts from October 1, 2022, to February 21, 2025. This includes data on atmospheric constituents like ozone, carbon monoxide, nitrogen dioxide, sulfur dioxide, and particulate matter (PM2.5). The system uses the GEOS-Chem module to generate 5-day forecasts. Data can be selected using 'creation_time' and 'forecast_time' properties and accessed via Google Earth Engine with specified image properties, bands and code examples.\n"],null,["Dataset Availability\n: 2022-10-01T00:00:00Z--2025-09-04T12:00:00Z\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 forecast (fcst) of high-temporal\nfrequency data (htf). Use the 'creation_time' and 'forecast_time' properties\nto select data of interest.\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\nImage Properties\n\n**Image Properties**\n\n| Name | Type | Description |\n|---------------|--------|------------------|\n| creation_time | DOUBLE | Time of creation |\n| forecast_time | DOUBLE | Forecast time |\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/fcst/htf');\n\nMap.setCenter(100, 20, 3);\n\nvar weeklyT =\n geosCf.select('T').filterDate('2022-11-01', '2022-11-08').median();\nMap.addLayer(weeklyT, imageVisParamT, 'Weekly T', false, 1);\n\nvar NO2 = ee.Image('NASA/GEOS-CF/v1/fcst/htf/20221215_12z-20221216_1200z');\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_fcst_htf) \n[GEOS-CF fcst htf v1: Goddard Earth Observing System Composition Forecast](/earth-engine/datasets/catalog/NASA_GEOS-CF_v1_fcst_htf) \nThis dataset contains meteorological forecast (fcst) of high-temporal frequency data (htf). Use the 'creation_time' and 'forecast_time' properties to select data of interest. 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 ... \nNASA/GEOS-CF/v1/fcst/htf, atmosphere,composition,forecast,geos,gmao,nasa \n2022-10-01T00:00:00Z/2025-09-04T12:00:00Z \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_fcst_htf)"]]
