N: 90 S: -90 E: 180 W: -180
Description
The MOD09CMG Version 6.1 product provides an estimate of the surface spectral reflectance of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Bands 1 through 7, resampled to 5600 meter (m) pixel resolution and corrected for atmospheric conditions such as gasses, aerosols, and Rayleigh scattering. The MOD09CMG data product provides 25 layers including MODIS bands 1 through 7; Brightness Temperature data from thermal bands 20, 21, 31, and 32; along with Quality Assurance (QA) and observation bands. This product is based on a Climate Modeling Grid (CMG) for use in climate simulation models.
Known Issues
- For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.
Version Description
Product Summary
Citation
Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.
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File Naming Convention
The file name begins with the Product Short Name (MOD09CMG) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2025219), the Version of the data collection (061), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2025221032122), and the Data Format (hdf).
Documents
USER'S GUIDE
ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)
PRODUCT QUALITY ASSESSMENT
SCIENCE DATA PRODUCT VALIDATION
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| CY-Bench: a comprehensive benchmark dataset for sub-national crop yield forecasting | Kallenberg, Michiel, Paudel, Dilli, Ofori-Ampofo, Stella, Baja, Hilmy, van Bree, Ron, Potze, Aike, Poudel, Pratishtha, Saleh, Abdelrahman, Anderson, Weston, von Bloh, Malte, Castellano, Andres, Ennaji, Oumnia, Hamed, Raed, Laudien, Rahel, Lee, Donghoon, Luna, Inti, Masiliunas, Dainius, Meroni, Michele, Mutuku, Janet Mumo, Mkuhlani, Siyabusa, Richetti, Jonathan, Ruane, Alex C., Sahajpal, Ritvik, Shuai, Guanyuan, Sitokonstantinou, Vasileios, Noia-Junior, Rogerio de S., Srivastava, Amit Kumar, Strong, Robert, Sweet, Lily-belle, Vojnovic, Petar, de Wit, Allard, Zachow, Maximilian, Athanasiadis, Ioannis N. | Reflectance | |
| Estimates of Transboundary Transfer and Balance of Atmospheric Carbon Dioxide Fluxes in Sverdlovsk Region Using the Machine Learning Model | Rozanov, A. P., Gribanov, K. G., Zadvornykh, I. V., Sukhikh, G. A., Valdaiskikh, V. V., Zakharov, V. I. | Land Use/Land Cover Classification, Reflectance | |
| Enhanced MODIS-derived ice physical properties within the Common Land Model (CoLM) revealing bare-icesnow albedo feedback over Greenland | Guo, Shuyang, Dai, Yongjiu, Yuan, Hua, Liang, Hongbin | Albedo, Anisotropy, Reflectance, Snow Cover | |
| Advanced vegetation green-up onset in regions with cooling air | Jiang, Nan, Shen, Miaogen, Yang, Zhiyong | Reflectance, Land Use/Land Cover Classification | |
| Area of land degradation in arid regions from 2000 to 2023 | KIMURA, Reiji, MORIYAMA, Masao | Land Use/Land Cover Classification, Reflectance, Emissivity, Land Surface Temperature | |
| Estimates of Carbon Dioxide Flux into the Forest Ecosystem Based on Results of Ground-Based Hyperspectral Sounding of the Atmosphere and an Artificial Neural ... | Rozanov, A. P., Zadvornykh, I. V., Gribanov, K. G., Zakharov, V. I. | Land Use/Land Cover Classification, Reflectance | |
| A 20012022 global gross primary productivity dataset using an ensemble model based on the random forest method | Chen, Xin, Chen, Tiexi, Li, Xiaodong, Chai, Yuanfang, Zhou, Shengjie, Guo, Renjie, Dai, Jie | Albedo, Anisotropy, Reflectance, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Land Use/Land Cover Classification | |
| Differential phenological responses to temperature among various stages of spring vegetation green-up | Jiang, Nan, Shen, Miaogen, Yang, Zhiyong | Land Use/Land Cover Classification, Reflectance, Plant Phenology, Enhanced Vegetation Index (EVI) | |
| A novel retrieval model for soil salinity from CYGNSS: Algorithm and test in the Yellow River Delta | Wang, Jundong, Yang, Ting, Zhu, Kangying, Shao, Changxiu, Zhu, Wanxue, Hou, Guanqun, Sun, Zhigang | Reflectance, Emissivity, Land Surface Temperature | |
| Monitoring of recent aridification in Turkiye using MODIS satellite data from 2000 to 2021 | Kimura, Reiji, Moriyama, Masao, Saylan, Levent | Reflectance, Emissivity, Land Surface Temperature | |
| Warming does not delay the start of autumnal leaf coloration but slows its progress rate | Jiang, Nan, Shen, Miaogen, Ciais, Philippe, Campioli, Matteo, Penuelas, Josep, Korner, Christian, Cao, Ruyin, Piao, Shilong, Liu, Licong, Wang, Shiping, Liang, Eryuan, Delpierre, Nicolas, Soudani, Kamel, Rao, Yuhan, Montagnani, Leonardo, Hortnagl, Lukas, PaulLimoges, Eugenie, Myneni, Ranga, Wohlfahrt, Georg, Fu, Yongshuo, Sigut, Ladislav, Varlagin, Andrej, Chen, Jin, Tang, Yanhong, Zhao, Wenwu | Land Use/Land Cover Classification, Reflectance, Plant Characteristics, Plant Phenology, Vegetation Cover, Vegetation Index | |
| Evaluation of BRDF information retrieved from time-series multiangle data of the Himawari-8 AHI | Zhang, Xiaoning, Jiao, Ziti, Zhao, Changsen, Guo, Jing, Zhu, Zidong, Liu, Zhigang, Dong, Yadong, Yin, Siyang, Zhang, Hu, Cui, Lei, Li, Sijie, Tong, Yidong, Wang, Chenxia | Canopy Characteristics, Evergreen Vegetation, Crown, Deciduous Vegetation, Leaf Characteristics, Vegetation Cover, Land Use/Land Cover Classification, Reflectance | |
| A global land aerosol fine-mode fraction dataset (2001-2020) retrieved from MODIS using hybrid physical and deep learning approaches | Yan, Xing, Zang, Zhou, Li, Zhanqing, Luo, Nana, Zuo, Chen, Jiang, Yize, Li, Dan, Guo, Yushan, Zhao, Wenji, Shi, Wenzhong, Cribb, Maureen | Reflectance | |
| Assessment of spatial and temporal ecological environment quality under | Airiken, Muhadaisi, Zhang, Fei, Chan, Ngai Weng, Kung, Hsiang-te | Land Surface Temperature, Emissivity, Reflectance, Land Use/Land Cover Classification | |
| The added-value of remotely-sensed soil moisture data for agricultural drought detection in Argentina | Salvia, Mercedes, Sanchez, Nilda, Piles, Maria, Ruscica, Romina, Gonzalez-Zamora, Angel, Roitberg, Esteban, Martinez-Fernandez, Jose | Reflectance, Emissivity, Land Surface Temperature | |
| Revisiting daily MODIS evapotranspiration algorithm using flux tower measurements in China | Huang, Lei, Steenhuis, Tammo S., Luo, Yong, Tang, Qiuhong, Tang, Ronglin, Zheng, Junqing, Shi, Wen, Qiao, Chen | Reflectance, Emissivity, Land Surface Temperature, Land Use/Land Cover Classification, Albedo, Anisotropy, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | |
| Use of A MODIS Satellite-Based Aridity Index to Monitor Drought | Kimura, Reiji, Moriyama, Masao | Reflectance, Emissivity, Land Surface Temperature | |
| Trends in land surface phenology across the conterminous United States (1982-2016) analyzed by NEON domains | Liang, Liang, Henebry, Geoffrey M., Liu, Lingling, Zhang, Xiaoyang, Hsu, LiChih | Land Use/Land Cover Classification, Reflectance, Vegetation Cover, Vegetation Index | |
| 8-day and daily maximum and minimum air temperature estimation via machine learning method on a climate zone to global scale | Zeng, Linglin, Hu, Yuchao, Wang, Rui, Zhang, Xiang, Peng, Guozhang, Huang, Zhenyu, Zhou, Guoqing, Xiang, Daxiang, Meng, Ran, Wu, Weixiong, Hu, Shun | Emissivity, Land Surface Temperature, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Albedo, Anisotropy, Reflectance, RADAR IMAGERY, Terrain Elevation, Digital Elevation/Terrain Model (DEM) | |
| Comparing in situ spring phenology and satellite-derived start of season at rural and urban sites in Ireland | Donnelly, Alison, Yu, Rong, Liu, Lingling | Land Use/Land Cover Classification, Reflectance, Emissivity, Land Surface Temperature | |
| Early growing season anomalies in vegetation activity determine the largescale climatevegetation coupling in Europe | Wu, Minchao, Vico, Giulia, Manzoni, Stefano, Cai, Zhanzhang, Bassiouni, Maoya, Tian, Feng, Zhang, Jie, Ye, Kunhui, Messori, Gabriele | Land Use/Land Cover Classification, Reflectance, Vegetation Index, Plant Phenology, Plant Phenological Changes, Enhanced Vegetation Index (EVI) | |
| Long-term variations in actual evapotranspiration over the Tibetan Plateau | Han, Cunbo, Ma, Yaoming, Wang, Binbin, Zhong, Lei, Ma, Weiqiang, Chen, Xuelong, Su, Zhongbo | Terrain Elevation, Digital Elevation/Terrain Model (DEM), Topographical Relief Maps, Reflectance, Emissivity, Land Surface Temperature, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | |
| Near Real-Time Processing Chain for MSG SEVIRI Data for Free and Immediate Earth Monitoring Capabilities | Sobrino, Jose A., Julien, Yves | Reflectance | |
| Reconstruction of spatiotemporally continuous MODIS-band reflectance in east and south Asia from 2012 to 2015 | Gao, Bo, Gong, Huili, Zhou, Jie, Wang, Tianxing, Liu, Yuanyuan, Cui, Yaokui | Land Use/Land Cover Classification, Reflectance, Albedo, Anisotropy | |
| Urbanization and climate change jointly shift land surface phenology in the northern mid-latitude large cities | Qiu, Tong, Song, Conghe, Zhang, Yulong, Liu, Hongsheng, Vose, James M. | Population Size, Reflectance |
Variables
The table below lists the variables contained within a single granule for this dataset. Variables often contain observed or derived geophysical measurements collected from a variety of sources, including remote sensing instruments on satellite and airborne platforms, field campaigns, in situ measurements, and model outputs. The terms variable, parameter, scientific data set, layer, and band have been used across NASA’s Earth science disciplines; however, variable is the designated nomenclature in NASA’s Common Metadata Repository (CMR). Variable metadata attributes such as Name, Description, Units, Data Type, Fill Value, Valid Range, and Scale Factor allow users to efficiently process and analyze the data. The full range of attributes may not be applicable to all variables. Additional information on variable attributes is typically available in the data, user guide, and/or other product documentation.
For questions on a specific variable, please use the Earthdata Forum.
| Name Sort descending | Description | Units | Data Type | Fill Value | Valid Range | Scale Factor | Offset |
|---|---|---|---|---|---|---|---|
| Coarse Resolution Band 3 Path Radiance | Band 3 Radiance | N/A | int16 | -28672 | -100 to 16000 | 0.0001 | N/A |
| Coarse Resolution Brightness Temperature Band 20 | Band 20 Brightness Temperature (3.360-3.840 μm) | Kelvin | uint16 | 0 | 1 to 40000 | 0.01 | N/A |
| Coarse Resolution Brightness Temperature Band 21 | Band 21 Brightness Temperature (3.929-3.989 μm) | Kelvin | uint16 | 0 | 1 to 40000 | 0.01 | N/A |
| Coarse Resolution Brightness Temperature Band 31 | Band 31 Brightness Temperature (10.780-11.280 μm) | Kelvin | uint16 | 0 | 1 to 40000 | 0.01 | N/A |
| Coarse Resolution Brightness Temperature Band 32 | Band 32 Brightness Temperature (11.770-12.270 μm) | Kelvin | uint16 | 0 | 1 to 40000 | 0.01 | N/A |
| Coarse Resolution Granule Time | Granule time of day | Hours | int16 | 0 | 1 to 2355 | N/A | N/A |
| Coarse Resolution Internal CM | Internal Cloud Mask | Bit Field | uint16 | 0 | 1 to 8191 | N/A | N/A |
| Coarse Resolution Number Mapping | Number Mapping Cloud/Snow | Bit Field | uint32 | 0 | 1 to 2097151 | N/A | N/A |
| Coarse Resolution Ozone | Ozone Resolution | cm atm | uint8 | 0 | 1 to 255 | 0.0025 | N/A |
| Coarse Resolution QA | Quality Assurance | Bit Field | uint32 | 0 | 1 to 1073741824 | N/A | N/A |
| Coarse Resolution Relative Azimuth Angle | Relative Azimuth Angle | Degree | int16 | 0 | -18000 to 18000 | 0.01 | N/A |
| Coarse Resolution Solar Zenith Angle | Solar Zenith Angle | Degree | int16 | 0 | 1 to 18000 | 0.01 | N/A |
| Coarse Resolution State QA | State Quality Assurance | Bit Field | uint16 | 0 | 1 to 65535 | N/A | N/A |
| Coarse Resolution Surface Reflectance Band 1 | Surface Reflectance Band 1 (620-670 nm) | N/A | int16 | -28672 | -100 to 16000 | 0.0001 | N/A |
| Coarse Resolution Surface Reflectance Band 2 | Surface Reflectance Band 2 (841-876 nm) | N/A | int16 | -28672 | -100 to 16000 | 0.0001 | N/A |
| Coarse Resolution Surface Reflectance Band 3 | Surface Reflectance Band 3 (459-479 nm) | N/A | int16 | -28672 | -100 to 16000 | 0.0001 | N/A |
| Coarse Resolution Surface Reflectance Band 4 | Surface Reflectance Band 4 (545-565 nm) | N/A | int16 | -28672 | -100 to 16000 | 0.0001 | N/A |
| Coarse Resolution Surface Reflectance Band 5 | Surface Reflectance Band 5 (1230-1250 nm) | N/A | int16 | -28672 | -100 to 16000 | 0.0001 | N/A |
| Coarse Resolution Surface Reflectance Band 6 | Surface Reflectance Band 6 (1628-1652 nm) | N/A | int16 | -28672 | -100 to 16000 | 0.0001 | N/A |
| Coarse Resolution Surface Reflectance Band 7 | Surface Reflectance Band 7 (2105-2155 nm) | N/A | int16 | -28672 | -100 to 16000 | 0.0001 | N/A |
| Coarse Resolution View Zenith Angle | View Zenith Angle | Degree | int16 | 0 | 1 to 18000 | 0.01 | N/A |
| n pixels averaged | Number of pixels used in average | N/A | uint8 | 0 | 1 to 40 | N/A | N/A |
| number of 250m pixels averaged b1-2 | Number of 250m pixels used in b1-2 average | N/A | uint16 | 0 | 1 to 640 | N/A | N/A |
| number of 500m pixels averaged b3-7 | Number of 500m pixels used in average | N/A | uint16 | 0 | 1 to 200 | N/A | N/A |
| number of 500m rej. detector | Number of 500m pixels rejected for use | N/A | uint8 | 0 | 1 to 100 | N/A | N/A |