DAILY PRECIPITATION, FROM MONTHLY STATION RECORDS AND DISAGGREGATION (Serreze)

Summary

This data set, spanning the period 1980-2008, is assembled from (1) interpolation of observed monthly totals from available station records with bias adjustments (2) disaggregation of the monthly totals to daily totals, making use of daily precipitation forecasts from the NCEP/NCAR reanalysis [Kalnay et al., 1996]. Station records from 1990 onwards are considered to be too sparse to assemble gridded products using this approach. A daily product from 1980 through the present is described separately (DAILY PRECIPITATION FROM STATISTICAL RECONSTRUCTIONS). This latter product, which is continually updated, makes use of a suite of variables from the NCEP/NCAR reanalysis.

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