The Surface Temperatures Measured at Multiple Angles Data Set was collected at two locations within the northwest quadrant of the FIFE study area during July and August 1989. The data set contains hemispherical surface temperature, surface temperatures measured at several view zenith angles, and surface temperatures and at-view azimuth increments of 45 degrees. These data were collected using the Everest multiplexed infrared thermometers (IRT) Model 4000 and an Eppley Precision Infrared Radiometer Model PIR. Periodically measurements of the surface emissivity and incoming longwave radiation were also made. The purpose of this study was to characterize bi-directional reflectance factor distributions, estimate surface albedo from bi-directional reflectance factor and radiance data, determine the variability of reflected and emitted fluxes in selected spectral wavebands as a function of topography, vegetative community and management practice, determine the influence of plant water status on surface reflectance factors, and determine sun angle affects on radiation fluxes.

The Surface Radiant Temperature Measured with a Helicopter-borne Infrared Thermometer Data Set were collected for six days during July and August of 1989 to provide the radiant temperature of the FIFE sites and as a check of the thermal band on the MMR. The average and standard deviation of radiant temperature were measured with an Everest infrared thermometer. The Everest Series 4000 Infrared Thermometer (IRT) was mounted on the NASA Bell UH-1B helicopter in conjunction with the Barnes Multiband Modular Radiometer (MMR) and the Spectron Engineering SE590 Spectroradiometer for the 1989 field campaign. The IRT collected radiant temperature data as the helicopter hovered over individual sites within the FIFE study area.

Surface temp. measured w/ Everest IRT, multiple angles & Eppley IR Radiometer

Surface temperatures collected w/ Everest Infrared Temperature Transducer

Canopy IR & air temperature, albedo, incoming and reflected shortwave, humidity

The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Temperature and Emissivity (LST&E) Climate Modeling Grid Version 2 product (VJ121C) is compiled daily from daytime Level 2 Gridded (L2G) intermediate products. The L2G process maps the daily [VJ121](https://doi.org/10.5067/VIIRS/VJ121.002) swath granules onto a sinusoidal MODIS grid and stores all observations overlapping a gridded cell for a given day. The VJ121C1 algorithm sorts through all these observations for each cell and estimates the final LST value as an average from all cloud-free observations that have good LST accuracies. The 0.05 degree (5,600 m) dataset is derived through resampling the native 750 meter VIIRS resolution in the input product. The overall objective for NASA VIIRS products is to ensure the algorithms and products are compatible with the MODIS Terra and Aqua algorithms to promote the continuity of the Earth Observation System (EOS) mission. Additional details regarding the method used to create this Level 3 (L3) product are available in the Algorithm Theoretical Basis Document (ATBD).The VJ121C1 product contains 25 Science Datasets (SDS): LST, quality control, view zenith angle, and time of observation for both day and night observations along with emissivity for bands M14, M15, and M16. Low-resolution browse images for day and night LST are also available for each VJ121C1 granule.Known Issues* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS) and the User Guide.Improvements/Changes from Previous Version* Improved calibration algorithm and coefficients for entire NOAA-20 mission.* Improved geolocation accuracy and applied updates to fix outliers around maneuver periods.* Corrected the aerosol quantity flag (low, average, high) mainly over brighter surfaces in the mid- to high-latitudes such as desert and tropical vegetation areas. This has an impact on the retrieval of other downstream data products such as VNP13 Vegetation Indices and VNP43 Bidirectional Reflectance Distribution Function (BRDF)/Albedo.* Improved cloud mask input product for corrections along coastlines and artifacts from use of coarse resolution climatology data. * Replaced the land/water mask input product with the eight-class land/water mask from the VNP03 geolocation product that better aligns with MODIS.* Replaced MERRA2 inputs with GEOS5.* Included inland water body pixels to allow for LST retrieval over these areas.* Introduced daily, 8-day, and monthly LST CMG products.* More details can be found in this [VIIRS Land V2 Changes document](https://landweb.modaps.eosdis.nasa.gov/data/userguide/VIIRS_Land_C2_Changes_09152022.pdf).

The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Temperature and Emissivity (LST&E) Climate Modeling Grid Version 2 product (VNP21C) is compiled daily from daytime Level 2 Gridded (L2G) intermediate products. The L2G process maps the daily [VNP21](https://doi.org/10.5067/VIIRS/VNP21.002) swath granules onto a sinusoidal MODIS grid and stores all observations overlapping a gridded cell for a given day. The VNP21A1 algorithm sorts through all these observations for each cell and estimates the final LST value as an average from all cloud-free observations that have good LST accuracies. The 0.05 degree (5600 m) dataset is derived through resampling the native 750 meter VIIRS resolution in the input product. The overall objective for NASA VIIRS products is to ensure the algorithms and products are compatible with the MODIS Terra and Aqua algorithms to promote the continuity of the Earth Observation System (EOS) mission. Additional details regarding the method used to create this Level 3 (L3) product are available in the Algorithm Theoretical Basis Document (ATBD).The VNP21C1 product contains 25 Science Datasets (SDS): LST, quality control, view zenith angle, and time of observation for both day and night observations along with emissivity for bands M14, M15, and M16. Low-resolution browse images for day and night LST are also available for each VNP21C1 granule.Known Issues* Users of VIIRS and MODIS LST products may notice an increase in occurrences of extreme high temperature outliers in the unfiltered VNP21 and MxD21 products compared to the heritage MxD11 LST products. This can occur especially over desert regions like the Sahara where undetected cloud and dust can negatively impact MxD11, MxD21, and VNP21 retrieval algorithms. * In the MxD11 LST products, these contaminated pixels are flagged in the algorithm and set to fill values in the output products based on differences in the band 32 and band 31 radiances used in the generalized split window algorithm. In the VNP21 and MxD21 LST products, values for the contaminated pixels are retained in the output products (and may result in overestimated temperatures), and users need to apply Quality Control (QC) filtering and other error analyses for filtering out bad values. High temperature outlier thresholds are not employed in VNP21 and MxD21 since it would potentially remove naturally occurring hot surface targets such as fires and lava flows.* High atmospheric aerosol optical depth (AOD) caused by vast dust outbreaks in the Sahara and other deserts highlighted in the example documentation are the primary reason for high outlier surface temperature values (and corresponding low emissivity values) in the VNP21 and MxD21 LST products. Future versions of the VNP21 and MxD21 products will include a dust flag from the MODIS aerosol product and/or brightness temperature look up tables to filter out contaminated dust pixels. It should be noted that in the MxD11B day/night algorithm products, more advanced cloud filtering is employed in the multi-day products based on a temporal analysis of historical LST over cloudy areas. This may result in more stringent filtering of dust contaminated pixels in these products. * To mitigate the impact of dust in the VNP21 and MxD21 products, the science team recommends using a combination of the existing QC bits, emissivity values, and estimated product errors, to confidently remove bad pixels from analysis.* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS).Improvements/Changes from Previous Versions* Improved calibration algorithm and coefficients for entire Suomi NPP mission.* Improved geolocation accuracy and applied updates to fix outliers around maneuver periods.* Corrected the aerosol quantity flag (low, average, high) mainly over brighter

Temperature data from Everest IR thermometer mounted on the helicopter