Help Center

For example, the MASIE-NH coastline has slight differences with the Arctic coastline available from the Toolik-Arctic Geobotanical Atlas. The differences are most apparent on the north east coast of Greenland.

There are a few reasons that the soil moisture data values in SMAP Level-4 data products may vary from what you expect in a particular region. The first step a data user should take in investigating apparently anomalous values is to look at the rich quality information and other data flags contained in SMAP data files and associated QA files.

A typical AMSR-E swath width consists of approximately 2000 scans, with 243 pixels per scan for the 6.9 GHz to 36.5 GHz channels, and 486 pixels per scan for the 89.0 GHz channel.

The surface and root zone soil moisture estimates in the SMAP Level-4 soil moisture products are the outputs of a land surface model into which SMAP observations of brightness temperature have been assimilated. The coupling between the surface layer and the root zone layer is known to be very strong in this model (the Catchment model of Koster et al. [2000]), perhaps overly so, and this will indeed lead to similarity in the surface and root zone soil moisture time series.

While the standard SMAP Level-2 and -3 radiometer soil moisture products contain landcover_class and landcover_class_fraction in the data files, the enhanced soil moisture products do not. This is because the landcover class ancillary data are not available at the 9 km grid posting that the enhanced products are provided on. However, the lack of landcover class does not affect soil moisture retrieval as these data are included in the standard products for diagnostic purposes only. Standard SMAP Level-2 and -3 radiometer soil moisture products include:

If you plot the average daily change in sea ice extent in the northern hemisphere, based on the data from 'Sea_Ice_Index_Daily_Extent_G02135_v3.0.xlsx', you may notice that at the beginning of each month, particularly in the summer, the daily change is larger.

Given the choices of either shape distortion or areal distortion or both, the equal-area projections were chosen for the EASE Grids because they minimized the amount of distortion over the hemispheric and global areas being portrayed. One convenient side effect of this choice is that calculations of areal statistics are reduced to simply summing pixels and multiplying by a constant area per pixel, so the acronym, EASE takes on a secondary meaning, as in easy to use.