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Dataset

 

European Space Agency (ESA) GlobSnow L3B mean STD of 7 day running mean Snow Water Equivalent (SWE) Estimates (1979-2013)

Update Frequency: Not Planned
Latest Data Update: 2015-10-19
Status: Completed
Online Status: ONLINE
Publication State: Published
Publication Date: 2015-11-21
Download Stats: last 12 months
Dataset Size: 8.41K Files | 49GB

Abstract

The ESA funded GlobSnow project produced snow water equivalent (SWE) 7-day estimates and standard errors for the Northern Hemisphere for the years 1979-2013.

SWE describes the amount of liquid water in the snow pack that would be formed if the snow pack was completely melted. Weekly Aggregated Snow Water Equivalent (Weekly L3B SWE) were calculated for each day based on a 7-day sliding time window aggregation of the daily SWE product.

The SWE product shall cover the Northern Hemisphere, excluding the mountainous areas, Greenland, the glaciers and snow on ice (lakes/seas/oceans)

The spatial resolution of the product is 25 km on EASE-grid projection.

Construction of the 30 years historical data set will be carried out using SMMR, SSM/I and SSMI/S data along with ground-based weather station data. The data are utilized for the different years as follows:

1979/09/11 - 1987/10/30 SMMR (Scanning Multichannel Microwave Radiometer onboard Nimbus-7 satellite)
1987/11/01 - 2008/12/31 SSM/I (Special Sensor Microwave/Imager onboard the DMSP satellite series F8/F11/F13)
2009/01/01 - present SSM/I(S) (Special Sensor Microwave/Imager (Sounder) onboard the DMSP satellite series F17/F18/)

These data may be redistributed and used without restriction.

Citable as:  Luojus, K. (2015): European Space Agency (ESA) GlobSnow L3B mean STD of 7 day running mean Snow Water Equivalent (SWE) Estimates (1979-2013). Finnish Meteorological Institute, date of citation. https://catalogue.ceda.ac.uk/uuid/48d69bd4dd89464fb1f32c3669bfaa94
Abbreviation: esa-globsnow-v2.0-SWE-weekly-estimates
Keywords: esa, globsnow, swe, snow, climate, northern hemisphere, monthly, error, estimate

Details

Previous Info:
No news update for this record
Previously used record identifiers:
No related previous identifiers.
Access rules:
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence: http://creativecommons.org/licenses/by/3.0/. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

SWE Data provided by the FMI as part of the CLIPC project in 2015.

File Format:
The SWE products are distributed in NetCDF-4 classic format, following the CF-1.6 convention: a single file contains the data for a single variable on the date given in the file name.

Process overview

This dataset was generated by a combination of instruments deployed on platforms and computations as detailed below.

Computation Element: 1

Title Computation for: GlobSnow L3B mean STD of 7 day running mean Snow Water Equivalent (SWE) Estimates
Abstract Statistical error is determined through an adaptive dynamic error propagation approach. For more details see accompanying documents on basic methodology in Pulliainen 2006 (link under docs tab).
Input Description None
Output Description None
Software Reference None
Output Description

None

  • units: degrees
  • var_id: lat
  • long_name: WGS84 latitude coordinates, center of pixel
  • units: degrees
  • var_id: lon
  • long_name: WGS84 longitude coordinates, center of pixel
  • var_id: lambert_azimuthal_equal_area
  • var_id: time_bnds
  • units: m
  • var_id: x
  • standard_name: projection_x_coordinate
  • long_name: x coordinate of projection
  • units: m
  • var_id: y
  • standard_name: projection_y_coordinate
  • long_name: y coordinate of projection

Co-ordinate Variables

  • long_name: time
  • standard_name: time
  • var_id: time
Coverage
Temporal Range
Start time:
1979-09-10T23:00:00
End time:
2013-05-30T22:59:59
Geographic Extent

 
90.0000°
 
-180.0000°
 
180.0000°
 
0.0000°
 
Related parties
Authors (1)
Principal Investigators (1)