Gapfilled Daytime and Nighttime Land Surface Temperature from MODIS MOD11A2 v6.1 products.
Daytime and Nighttime Land Surface Temperature (LST) are derived from the ~1km MODIS MOD11A2 v6.1 products. The 8-daily composites are converted to degrees Celsius and then gap-filled using the approach outlined in Weiss et al (2014) to eliminate missing data caused by factors such as cloud cover.
The gap-filled 8-daily ~1km outputs are then aggregated temporally and spatially to produce monthly and annual ~5km products.
Directories are structured in the following way: {VariableName}/{Resolution}/{TemporalSummary}
And under that, filenames are structured by:
8-daily: {VariableName}.{Year}.{JulianDay}.Data.{Resolution}.{SpatialSummary}.tif
Monthly: {VariableName}.{Year}.{Month}.{TemporalSummary}.{Resolution}.{SpatialSummary}.tif
Annual: {VariableName}.{Year}.Annual.{TemporalSummary}.{Resolution}.{SpatialSummary}.tif
Synoptic: {VariableName}.Synoptic.{Month-or-Overall}.{TemporalSummary}.{Resolution}.{SpatialSummary}.tif
VariableName options in this dataset are:
LST_Day_v061: daytime Land Surface TemperatureLST_Night_v061: nighttime Land Surface TemperatureLST_DiurnalDifference_v061: difference between daytime and nighttime LSTsResolution in this dataset is either 1km or 5km
Standard values for TemporalSummary are: min, max, range, mean, SD, count. In addition there are:
Data: this indicated that no temporal aggregation has occurredBalanced-mean: This is specific to overall synoptic data, it represents the mean of the 12 monthly synoptic mean datasets as opposed to the overall mean of the (e.g. daily) data. This gives a weighting to help correct for seasonal bias that could otherwise be present in areas where data are more often missing at certain times of year.Standard values for SpatialSummary are: min, max, range, sum, mean, SD, count. In addition:
Data: this indicates that no spatial aggregation has occurred