Data Products  › Product & Algorithm › Caveats of AMSR-E Integrated Cloud Liquid Water product (Version 2.0)
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Caveats for the standard products

Caveats of AMSR-E Integrated Cloud Liquid Water product (Version 2.0)

Algorithm development PI : Dr. Frank J. Wentz (Remote Sensing Systems)


This document briefly describes some caveats for the AMSR-E Level 2 standard products (Version 2.0) of integrated cloud liquid water.
Revision from Version 1.0
This is the first release of AMSR-E integrated cloud liquid water products. Therefore, we do not have the Version 1.0 product for integrated cloud liquid water.
Retrieval areas
This product retrieves integrated cloud liquid water over global oceans. Retrievals are done in the vicinity of sea ice, but are not reliable over sea ice. The user must look at the possible sea-ice flag and decide if the retrievals are usable. Land areas are masked out by using land-ocean flag information provided by JAXA. In addition, cloud water is not retrieved in regions where the input brightness temperatures are out of bounds. Cloud water may be retrieved over large lakes.
Retrieval range and error
There is no explicit retrieval range for cloud water. The rms retrieval error is estimated to be 0.02 mm based on theoretical simulations.
Categories
Quality flags included are for proximity to land and sea-ice. Retrieval accuracy near land or sea-ice may be degraded. Therefore, users must select the data depending on their purpose.
Estimates in rain

When there is rain in the field of view, the estimate of cloud water may not be a good indicator of the true cloud water because of the difficulty in separating cloud water from rain water. As a general rule of thumb, when the cloud water exceeds 0.18 mm, it is likely that there is some rain in the field of view.
Ancillary data used in retrieval
During retrieval, the surface air temperatures, as provided by JAXA, is used as ancillary input data.
Algorithm consistency with AMSR (Version 1.0)
The algorithm is identical to that of AMSR (Version 1.0). However, a brightness temperature conversion table was prepared and used to optimize for each instrument.

 

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