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5

Most likely, climatology means there was no retrieval at all. Bayesian retrievals combine information from an a priori with information from measurements. When the retrieval fails for whatever reason, or the measurement contains insufficient information, instead of reporting no measurement at all, they copy over information from the a priori and use the ...


3

You could fill the gaps with the analysis products of numerical weather prediction. NCAR for example (RDA UCAR) hosts the NCEP North American Regional Reanalysis (NARR) with data from 1979 to 2018 including snow cover (NARR) in 3-hourly intervals. But I would guess it depends on your goal: You can make an educated guess (bayesian approach, combining ...


2

Gerrit is correct, the climatological setting indicates that the value is filled in (not an actual retrieval). If you see the MODIS Vegetation Index User’s Guide, it is discussed a few times: Cloud-free global coverage is achieved by replacing clouds with the historical MODIS time series climatology record (Fig. 5) and In the Climatology Fill case, ...


1

Technically, this is a mathematical modelling problem. You just happen to be using earth science data - satellite LIDAR readings. Ore reserve geologists constantly deal with this, but in three dimensions when they are required to create a block models of a geological deposit from drill hole data. Scientific fields that use 2D data would include: forestry, ...


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