The monthly climatology dataset contains a series of land surface parameters simulated from the Noah 3.6.1 model in the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS). The dataset comprises of 12 monthly files, each representing the monthly data averaged over 35 years from 1982 to 2016, based on the FLDAS Noah Land Surface Model L4 Global Monthly 0.1 x 0.1 degree (MERRA-2 and CHIRPS) V001 (FLDAS_NOAH01_C_GL_M_001) monthly data. The data are in 0.10 degree resolution and the spatial coverage is global (60S, 180W, 90N, 180E). The FLDAS regional monthly climatology datasets will no longer be available and have been superseded by the global monthly climatology dataset. More information about the monthly FLDAS can be found from the dataset landing page for FLDAS_NOAH01_C_GL_M_001 and the FLDAS README document. In November 2020, all FLDAS data were post-processed with the MOD44W MODIS land mask. Previously, some grid boxes over inland water were considered as over land and, thus, had non-missing values. The post-processing corrected this issue and masked out all model output data over inland water; the post-processing did not affect the meteorological forcing variables. More information on this can be found in the FLDAS README document, and the MOD44W MODIS land mask is available on the FLDAS Project site. If you had downloaded any FLDAS data prior to November 2020, please download the data again to receive the post-processed data.

The Prediction of Worldwide Energy Resource (POWER) Project is funded through the NASA Applied Sciences Program within the Earth Science Mission Directorate. The POWER Project supports three user communities with solar and/or meteorological data: 1) Renewable Energy (RE), 2) Sustainable Buildings (SB), and 3) Agroclimatology (AG)POWER Data Sources:The POWER project provides access to community-based Analysis Ready Data (ARD) for meteorology and solar-related parameters, specifically formulated for assessing and designing renewable energy systems.The data is available on at the source models’ native latitude and longitude global grid.Temporal levels include Hourly, Daily, Monthly, Annual, and Climatology. Download options include single point, regional, and global data.Formats include NetCDF, CSV, ASCII, geoJSON, ICASA, & EPW.Meteorological parameters are derived from:NASA's GMAO MERRA-2 archive (Jan. 1, 1981 – 3 Months Behind Near Real Time)NASA's GEOS 5.12.4 FP-IT archive (End of MERRA2 – Near Real Time)Solar parameters are derived from:NASA's GEWEX/SRB release 4.0 archive (Jan. 1, 1984 – Dec. 31, 2000) NASA's CERES SYN1deg (Jan. 1, 2001 – 3 Months Behind Near Real Time)NASA's FLASHFlux (3 Months Behind Near Real Time – Near Real Time)If you have any comments or questions, please do not hesitate to contact us at larc-power-project@mail.nasa.gov

The Essential thermaL Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn). This dataset is the Global ELITE Landsat LST dataset generated by the radiative transfer method (Cheng et al., 2021). Firstly, a new scheme was used to determine the real-time Landsat 5/7/8 narrowband emissivity . Then, the MERRA2 reanalysis product was used for thermal infrared data atmospheric correction (Meng and Cheng, 2018). Finally, an LST product with 30m spatial resolution was generated using the radiative transfer equation method. This is the ELITE Landsat LST dataset for Landsat 8 from January 6, 2020 to January 10, 2020. Please click here to download the ELITE Landsat LST for Landsat 8 from January 1, 2020 to January 5, 2020 and click here to download the ELITE Landsat LST for Landsat 8 from January 11, 2020 to January 15, 2020. Dataset Characteristics: Spatial Coverage: Global landmsss Temporal Coverage: 2020.1.6-2020.1.10 Spatial Resolution: 30m Temporal Resolution: 16 days Data Format: Geotiff Scale: 0.01 Citation (Please cite these papers when using the data): Cheng, J., Meng, X., Dong, S., & Liang, S. (2021). Generating the 30-m land surface temperature product over continental China and USA from landsat 5/7/8 data. Science of Remote Sensing, 4, 100032 Meng, X., & Cheng, J. (2018). Evaluating Eight Global Reanalysis Products for Atmospheric Correction of Thermal Infrared Sensor—Application to Landsat 8 TIRS10 Data. Remote Sensing, 10, 474 If you have any questions, please contact Prof. Jie Cheng (eliteqrs@126.com).

The Essential thermaL Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

This dataset is the Global ELITE Landsat LST dataset generated by the radiative transfer method (Cheng et al., 2021). Firstly, a new scheme was used to determine the real-time Landsat 5/7/8 narrowband emissivity . Then, the MERRA2 reanalysis product was used for thermal infrared data atmospheric correction (Meng and Cheng, 2018). Finally, an LST product with 30m spatial resolution was generated using the radiative transfer equation method.

This is the ELITE Landsat LST dataset for Landsat 8 from January 21, 2020 to January 25, 2020. Please click here to download the ELITE Landsat LST for Landsat 8 from January 16, 2020 to January 20, 2020 and click here to download the ELITE Landsat LST for Landsat 8 from January 26, 2020 to January 30, 2020.

Dataset Characteristics:

• Spatial Coverage: Global landmsss
• Temporal Coverage: 2020.1.21-2020.1.25
• Spatial Resolution: 30m
• Temporal Resolution: 16 days
• Data Format: Geotiff
• Scale: 0.01

Citation (Please cite these papers when using the data):

1. Cheng, J., Meng, X., Dong, S., & Liang, S. (2021). Generating the 30-m land surface temperature product over continental China and USA from landsat 5/7/8 data. Science of Remote Sensing, 4, 100032

2. Meng, X., & Cheng, J. (2018). Evaluating Eight Global Reanalysis Products for Atmospheric Correction of Thermal Infrared Sensor—Application to Landsat 8 TIRS10 Data. Remote Sensing, 10, 474

If you have any questions, please contact Prof. Jie Cheng (eliteqrs@126.com).