N: 90 S: -90 E: 180 W: -180
Description
The MOD16A2 Version 6.1 Evapotranspiration/Latent Heat Flux product is an 8-day composite dataset produced at 500 meter (m) pixel resolution. The algorithm used for the MOD16 data product collection is based on the logic of the Penman-Monteith equation, which includes inputs of daily meteorological reanalysis data along with Moderate Resolution Imaging Spectroradiometer (MODIS) remotely sensed data products such as vegetation property dynamics, albedo, and land cover.
Provided in the MOD16A2 product are layers for composited Evapotranspiration (ET), Latent Heat Flux (LE), Potential ET (PET) and Potential LE (PLE) along with a quality control layer. Two low resolution browse images, ET and LE, are also available for each MOD16A2 granule.
The pixel values for the two Evapotranspiration layers (ET and PET) are the sum of all eight days within the composite period and the pixel values for the two Latent Heat layers (LE and PLE) are the average of all eight days within the composite period. Note that the last acquisition period of each year is a 5 or 6-day composite period, depending on the year.
Known Issues
- Operational and uncertainty issues are provided under Section 3 in the User Guide.
- 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 (MOD16A2) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2025201), the Tile Identifier which is horizontal tile and vertical tile provided as hXXvYY (h07v05), the Version of the data collection (061), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2025217003056), and the Data Format (hdf).
Documents
USER'S GUIDE
ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)
PRODUCT QUALITY ASSESSMENT
SCIENCE DATA PRODUCT VALIDATION
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Advancing point-to-grid scale ET mapping: comparative assessment of ECOSTRESS and MODIS LST and ET across heterogeneous landscapes | Park, Kijin, Baik, Jongjin, Kim, Kiyoung, Park, Jongmin | Evapotranspiration, Latent Heat Flux, Geolocation, Land Use/Land Cover Classification, Land Surface Temperature, Emissivity, Clouds | |
| Active Fire Dynamics in Venezuela | Correia Filho, Washington Luiz Felix, Freire, Felipe Machado, de Oliveira-Junior, Jose Francisco, Santiago, Dimas de Barros, Paredes-Trejo, Franklin, Pereira, Carlos Rodrigues, Abdo, Hazem Ghassan | Land Use/Land Cover Classification, Land Surface Temperature, Emissivity, Evapotranspiration, Latent Heat Flux, Photosynthesis, Primary Production | |
| A review of satellite-derived terrestrial evapotranspiration: theories, methods and products | Yao, Yunjun, Chen, Jiquan, Fisher, Joshua B., Shao, Changliang, Liu, Yuanbo | Evapotranspiration, Latent Heat Flux | |
| Bedrock controls vegetation resilience: Dominant role of lithology in | Li, Qian, Yue, Yuemin, Wang, Lu, Qi, Xiangkun, Wang, Kelin | Photosynthesis, Primary Production, VEGETATION PRODUCTIVITY, Evapotranspiration, Latent Heat Flux | |
| Environmental Degradation in Iraq: Attribution of Climatic Change and | Alqaraghuli, Akram, North, Peter, Bye, Iain, Rosette, Jacqueline, Los, Sietse | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Evapotranspiration, Latent Heat Flux, Land Surface Temperature, Emissivity | |
| High-Resolution Downscaling of GRACE-Derived Groundwater Storage Anomalies using Stacking Ensemble Machine Learning in the Data-Scarce Tropical Catchments | Karunarathna, S., Dissanayake, B. C., Gunawardhana, L., Rajapakse, L. | Evapotranspiration, Latent Heat Flux | |
| Impact of land-use change on ecosystem services in Africa's Great Green | Wang, Yizhuo, Scott, Catherine E., Dallimer, Martin | Land Use/Land Cover Classification, Plant Phenology, Enhanced Vegetation Index (EVI), Vegetation Index, Normalized Difference Vegetation Index (NDVI), Evapotranspiration, Latent Heat Flux, Topographical Relief Maps, Terrain Elevation, Digital Elevation/Terrain Model (DEM) | |
| On the Prediction and Evaluation of Terrestrial and Remote Sensing-Aided Groundwater Level in Tropical Peatlands | Utomo, Waluyo Yogo, Anwar, Syaiful, Tarigan, Suria Darma, Barus, Baba | Evapotranspiration, Latent Heat Flux | |
| Response of Vegetation Phenology to Hydrothermal Variables on the QTP Using EVI and MSAVI | Zhao, Zhijian, Lin, Hui, Wang, Li, Huang, Min, Wu, Lei, Tang, Linling, Yang, Tao, Xiao, Xin | Albedo, Anisotropy, Evapotranspiration, Latent Heat Flux, Land Use/Land Cover Classification, Land Surface Temperature, Emissivity, Reflectance | |
| PhysicsInformed, Differentiable Hydrologic Models for Capturing Unseen Extreme Events | Song, Yalan, Sawadekar, Kamlesh, Frame, Jonathan M., Pan, Ming, Clark, Martyn P., Knoben, Wouter J. M., Wood, Andrew W., Lawson, Kathryn E., Patel, Trupesh, Shen, Chaopeng | Evapotranspiration, Latent Heat Flux | |
| Sustainable grazing strategies for balancing soil conservation and | Liu, Le, Chen, Yunming, Peng, Shouzhang, Han, Qinggong, Wu, Yang | Evapotranspiration, Latent Heat Flux, Photosynthesis, Primary Production, VEGETATION PRODUCTIVITY, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar) | |
| Transition to transpiration-dominated evapotranspiration on the Loess | Xu, Yongkang, Zuo, Depeng, Ma, Zhijin, Liu, Jifeng, Wang, Guoqing, Xu, Zongxue, Han, Yuna, Abbaspour, Karim C., Yang, Hong | Evapotranspiration, Latent Heat Flux | |
| Variation of bioenergy efficiency of Arundo donax L. growing in northern and middle Egypt | Kassem, Hesham M., Ali, Hamada E., Arnous, Mohamed O., Zaghloul, Mohamed S. | Evapotranspiration, Latent Heat Flux | |
| A comparison of drought indices for crop yield loss detection: The role | Holwerda, Friso, Salazar-Martinez, Diego, Holmes, Thomas R.H., Hain, Christopher R., Anderson, Martha C. | Evapotranspiration, Latent Heat Flux, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Plant Phenology, Land Use/Land Cover Classification | |
| A GEE TSEB workflow for daily high-resolution fully remote sensing | El Hazdour, Ikram, Le Page, Michel, Hanich, Lahoucine, Chakir, Adnane, Lopez, Oliver, Jarlan, Lionel | Evapotranspiration, Latent Heat Flux | |
| A Multi-Scale Comprehensive Evaluation for Nine Evapotranspiration Products Across Mainland China Under Extreme Climatic Conditions | Qian, Long, Wu, Lifeng, Dong, Ning, Dai, Tianjin, Yu, Xingjiao, Bai, Xuqian, Yang, Qiliang, Liu, Xiaogang, Chen, Junying, Zhang, Zhitao | Surface Pressure, Heat Flux, Longwave Radiation, Shortwave Radiation, Air Temperature, Specific Humidity, Evapotranspiration, Wind Speed, Rain, Snow, Soil Moisture/Water Content, Soil Temperature, Land Surface Temperature, Snow Cover, Snow Depth, Snow Water Equivalent, Runoff, Surface Temperature, Humidity, Surface Winds, Precipitation Rate, Ground Water, Latent Heat Flux | |
| Comprehensive Evaluation of Water-Retention and Cooling Capacities of | Wu, Jianping, Xiao, Zhenzhen, Zhang, Chaoqun, Yan, Wenting, Ren, Jiashun, Liao, Ziyin, Lafortezza, Raffaele, Li, Xueyan, Su, Yongxian | Evapotranspiration, Latent Heat Flux | |
| Comparison of Artificial Intelligence Algorithms and Remote Sensing for | Orellana, Omar, Sandoval, Marco, Zagal, Erick, Hidalgo, Marcela, Suazo-Hernandez, Jonathan, Paulino, Leandro, Duarte, Efrain | Reflectance, Evapotranspiration, Latent Heat Flux | |
| Analyzing the dihedral scattering component of P-band SAR signals for trunk permittivity estimation a concept study | Fluhrer, Anke, Alemohammad, Hamed, Jagdhuber, Thomas | Vegetation Water Content, Soil Moisture/Water Content, Skin Temperature, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Evapotranspiration, Latent Heat Flux | |
| An LSTM approach to deciphering irrigation operations from remote | Wei, Shiqi, Xu, Tianfang | Evapotranspiration, Latent Heat Flux | |
| Assessing the impact of extreme climate events on European gross primary | Zhang, Huihui, Loaiciga, Hugo A, Okujeni, Akpona, Liu, Ji, Tan, Min, Sauter, Tobias | Land Use/Land Cover Classification, Photosynthesis, Primary Production, VEGETATION PRODUCTIVITY, Evapotranspiration, Latent Heat Flux | |
| Assessing evapotranspiration dynamics across central Europe in the context of landatmosphere drivers | Fluhrer, Anke, Baur, Martin J., Piles, Maria, Bayat, Bagher, Rahmati, Mehdi, Chaparro, David, Dubois, Clemence, Hellwig, Florian M., Montzka, Carsten, Kubert, Angelika, Mueller, Marlin M., Augscheller, Isabel, Jonard, Francois, Schellenberg, Konstantin, Jagdhuber, Thomas | Surface Pressure, Heat Flux, Longwave Radiation, Shortwave Radiation, Surface Temperature, Humidity, Evapotranspiration, Surface Winds, Rain, Precipitation Rate, Snow, Soil Moisture/Water Content, Soil Temperature, Land Surface Temperature, Snow Water Equivalent, Runoff, Latent Heat Flux | |
| Biophysical impact of forest age changes on land surface temperature in China | Zhang, Zhijiang, Wang, Lunche, Chen, Chao, Zhang, Xiang, Ding, Chao, Yuan, Moxi, Shen, Lixing, Li, Xinxin | Evapotranspiration, Latent Heat Flux | |
| Estimates of Irrigation Water Volume by Assimilation of Satellite Land | Corbari, C., Paciolla, N., Sheffield, J., Labbassi, K., Dos Santos Araujo, D. C., Berendsen, S., Szantoi, Z. | Evapotranspiration, Latent Heat Flux, Runoff, Soil Texture, Brightness Temperature, SIGMA NAUGHT, Surface Soil Moisture | |
| Estimating Reference Evapotranspiration Using Reanalysis Data from the | JimenezJimenez, Sergio Ivan, de Jesus MarcialPablo, Mariana, SanchezCohen, Ignacio, OjedaBustamante, Waldo, InzunzaIbarra, Marco Antonio, UrrietaVelazquez, Jose Alberto | Evapotranspiration, Latent Heat Flux |
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 |
|---|---|---|---|---|---|---|---|
| ET_500m | Total Evapotranspiration | kg/m²/8day | int16 | 32761 | -32767 to 32700 | 0.1 | N/A |
| ET_QC_500m | Evapotranspiration Quality Control flags | Bit Field | uint8 | 255 | 0 to 254 | N/A | N/A |
| LE_500m | Average Latent Heat Flux | J/m²/day | int16 | 32761 | -32767 to 32700 | 10000 | N/A |
| PET_500m | Total Potential Evapotranspiration | kg/m²/8day | int16 | 32761 | -32767 to 32700 | 0.1 | N/A |
| PLE_500m | Average Potential Latent Heat Flux | J/m²/day | int16 | 32761 | -32767 to 32700 | 10000 | N/A |