DAILY THAW DEPTH AND FROZEN GROUND DEPTH (Serreze, Oelke)

Summary

Daily thaw depth and frozen ground depth are calculated using a frozen ground model. Oelke et al. [2003] provide details.

The data is presented in 24 sub-datasets of different spatial and temporal aggregations (see aggregation description below).

Data Access

ORDER data for delivery by FTP.

* - This Dataset was submitted to or acquired by ArcticRIMS from a third party Research Institution.

Data Aggregation

There are two distinct methods to produce data aggregation along the "time" axis of the cube. These are -

1. Mean. Monthly or yearly values for each grid cell in the dataset has been produced as simple mean (average) over the indicated time period. An example is temperature datasets.

2. Sum. Monthly or yearly values for each grid cell in the dataset has been produced as arithmetic total over the indicated time period. An example is precipitation datasets.

3. Vector. Monthly or yearly values for each grid cell in the dataset has been produced as product vector (vector average) over the indicated time period. An example is wind direction datasets.

4. Class. Monthly or yearly values for each grid cell in the dataset has been produced as prevailing (most frequent) qualitative class over the indicated time period. An example is freeze-thaw datasets.

Each aggregated data file in a dataset has a notation of a method (mean or sum) used to produce the file. The notation included in the first (top) line of the file. Please, pay attention to that.

Aggregation along the "spatial scale" axis of the cube is done using simple mean (average) over all grid cells of each basin (river, sea basin, or continent) from an appropriate grid cell file.

 

Additional Information

Temporal Coverage

Spatial Coverage

Point of Contact