Model Output of Active Layer Depth in the Arctic Drainage Basin, 1979-2001

Summary

Investigators applied the Frozen Ground Model to the entire Arctic Drainage Basin to create this data set of active layer depth (ALD), recorded in centimeters. This model has been shown to provide excellent results for active layer depth and soil temperatures when driven with well-known boundary conditions and forcing parameters at specific locations. The model is driven by 2-meter air temperatures from the ERA-40 European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis. The reanalysis data are provided on a N80 reduced Gaussian grid, which is symmetric about the Equator with 80 latitudinal points in each hemisphere.

Data represent a subset of the entire 25 km Equal-Area Scalable Earth Grid (EASE-Grid) for the Northern Hemisphere (721 x 721 = 39,926 grid cells). There are monthly files for 23 years, 1979-2001, with a daily time step. Data are in space-delimited ASCII text format, and are available via FTP.

Citing These Data

Zhang, T., R. G. Barry, C. Oelke, and A. Etringer. 2006. Model output of active layer depth in the Arctic Drainage Basin, 1979-2001. Boulder, CO: National Center for Atmospheric Research. ARCSS Data Archive.

Overview Table

Table of Contents

1. Contacts and Acknowledgments
2. Detailed Data Description
3. Data Access and Tools
4. Data Acquisition and Processing
5. References and Related Publications
6. Document Information

1. Contacts and Acknowledgments

Investigators

Tingjun Zhang
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO, USA 80309-0449

Roger G. Barry
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO, USA 80309-0449

Christoph Oelke
University of Münster, Institute for Geophysics
Corrensstr. 24, D-48149
Münster, Germany

Andrew Etringer
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO, USA 80309-0449

Acknowledgements

This research was supported by the National Science Foundation (NSF) Office of Polar Programs (OPP) Arctic System Science (ARCSS) Program grant OPP-0229766.

2. Detailed Data Description

Format

Data are in space-delimited ASCII text format.

Files

Investigators have also provided the file readme_ald.txt, which contains much of the same information as this documentation.

File Naming Convention

File names follow the convention ALD.yyyy.mm.txt, where yyyy represents the year and mm represents the month of data collection.

File Size

Data files are 10.6 MB in size. The data are distributed as compressed (.zip) files.

Spatial Coverage

Southernmost Latitude: 45.3498° N
Northernmost Latitude: 83.6166° N
Westernmost Longitude: 180.0000° W
Easternmost Longitude: 180.0000° E

Grid Description

There are 39,926 grid cells representing the Arctic Drainage Basin. These 39,926 grid cells are a subset of the entire 25 km EASE-Grid for the Northern Hemisphere (721 x 721 grid cells).

Temporal Coverage

Data cover 23 years, 1979-2001.

Temporal Resolution

Data have a daily time step.

Parameter or Variable

Parameter Description

This data set includes modeled active layer depth (ALD) data. See Model Parameters for more information.

Sample Data Record

Each file contains 2 lines of header information, followed by 39,926 rows of data. Each data row has 34 columns.

* On days that data was not collected or days that do not exist (for example, there are only 30 days in April), missing values are given. Missing data are given a value of -9999.0.

These data are from April 1982, found in ALD.1982.04.txt.

Quality Assessment

Modeled thaw depths for sporadic permafrost areas, mainly in the southern parts of the Arctic drainage domain, are spuriously high. In these regions, the permafrost is very isolated and occurs at sub-grid scales. The forcing data sets (surface air temperature, snow cover, and soil bulk density) are likely not representative of the true forcing conditions for these small areas and produce an unrealistic increase in thaw depth with time. Frozen ground depths of small non-permafrost areas within discontinuous permafrost are likely too high, as forcing parameters are more representative of the colder permafrost climate condition at these grid cells.

ERA-40 2-meter air temperatures are used. There is no topographical correction.

3. Data Access and Tools

Data Access

Data are available for ordering through NCAR.

Volume

The total volume of the compressed (.zip) data files is approximately 451 MB.

Related Data Collections

• Time Series of Active Layer Thickness in the Russian Arctic, 1930-1990

4. Data Acquisition and Processing

Daily thaw depth and frozen ground depth were calculated using a frozen ground model with different initial model settings. In the first case, all soil down to the lower model boundary was set to sub-freezing initial temperatures. Thawing during the summer months caused the development of a thawed layer at the top with the thaw depth again decreasing during freeze-up of the thawed layer in fall. Frozen ground depth, on the other hand, is calculated with soil temperatures at all depths above freezing at the beginning. Here the frozen depth increased during winter, and spring thawing eventually decreases its value.

Thaw depth is calculated for areas identified from the International Permafrost Association (IPA) Circum-Arctic Map of Permafrost and Ground-Ice Conditions (IPA, 1998) as continuous permafrost, and for the frozen parts of discontinuous and sporadic permafrost. Thaw depth is not determined for non-permafrost (seasonally frozen ground) areas. The model grid cell values for which thaw depth is not determined are coded as missing (-9999.0). Frozen ground depth is calculated from the model for areas of seasonally frozen ground, and for the non-frozen parts of sporadic and discontinuous permafrost. No frozen ground depth is calculated for continuous permafrost areas (based on the IPA map). Both thaw depth and frozen ground depth are simulated for the regions of discontinuous permafrost and for sporadic permafrost. For regions of continuous permafrost, only simulated thaw depths are shown; whereas for seasonally frozen ground, only frozen ground depth is provided.

Frozen Ground Model

A finite-element model for one-dimensional heat conduction with phase change (Goodrich, 1982) is used. This model has been shown to provide excellent results for active layer depth and soil temperatures when driven with well-known boundary conditions and forcing parameters at specific locations. For this research, the model was applied to the entire Arctic drainage area (39,926 grid cells) on the 25 km EASE-Grid with a daily time step. Investigators divided soil into three major layers (0 cm to 30 cm, 30 cm to 80 cm, and 80 cm to 3000 cm) with distinct thermal properties of frozen and thawed soil, respectively. They also performed calculations on 63 model nodes ranging from a thickness of 10 cm near the surface to 2 m at 30 m depth. Thermal properties of mineral soils were determined from soil dry bulk density and water content according to Kersten [1949] and Lunardini [1988] for peat. Investigators chose initial temperatures according to the grid cell's permafrost classification based on the IPA map. They the model for a 50-year period on the same initial conditions in order to obtain more realistic start conditions for temperatures for all model layers.

Model Parameters

ALD is calculated for the IPA areas of continuous, discontinuous, or sporadic/isolated permafrost. It applies to the frozen parts for discontinuous and sporadic/isolated permafrost. This output is from a simulation starting 01 January 1979, ending 31 December 2001 (8401 days), and run in 4-year increments or tiles. The output of the simulation for the years 1979-1982 became the startup file for subsequent tiles. Missing values (-9999.0) apply for grid cells in seasonally-frozen areas. ALD is produced at 39,926 grid cells making up the entire Arctic drainage. The model parameters are as follows:

Layers: 0 cm to 30 cm, 30 cm to 80 cm, 80 cm to 3000 cm

Temperature: ERA-40 2-meter Air Temperature on EASE-Grid

Snow: Modified change algorithm and climatology, 7-day maxima, no snow above 8 °C

Snow density: Annual cycle for each of Sturm et al. (1995) snow classes (tundra, taiga, maritime, prairie, alpine)

Snow conductivity: Logarithmic fit to data of "others" in Sturm et al. (1997)

Soil bulk density: From the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) Soil Data System

Upper 2 soil layers modified with peat characteristics: Includes density (500 kg/m³) and conductivity for frozen and thawed cases from Lunardini (1988). Peat is included dependent on topography: below 1200 m for Layer 1, 1000 m for Layer 2.

Concentration of Clay+Silt and Sand+Gravel: From IGBP-DIS Soil Data System

Volumetric soil moisture: From UNH P/WBM climatology (1981-2000), redistributed from root and deep layers to the 3 model layers

Initialization: Temperature profiles dependent on the three permafrost classes; continuous permafrost, discontinuous permafrost, and sporadic or isolated permafrost, where continuous the permafrost class was used for initialization (climatological 20-year geothermal heat flux into lowest model layer)

Temperature

The model is driven by 2-meter air temperatures from the ERA-40 ECMWF Reanalysis (ECMWF, 2001). The reanalysis data are provided on a N80 reduced Gaussian grid, which is symmetric about the Equator with 80 latitudinal points in each hemisphere. The data was regridded to a 25km Northern Hemisphere EASE-Grid using a bilinear interpolation scheme (ECMWF, 2004).

Snow Cover

Snow water equivalent (SWE) is derived from satellite passive microwave data. For the period 1978-1987, investigators used the retrieval algorithm of Chang et al. (1987) developed for the Scanning Multichannel Microwave Imager (SMMR). For the period 1988 onwards, coverage is provided by the Special Sensor Microwave/Imager (SSM/I). For the SSM/I coverage period the retrieval algorithm was modified taking into account the different radiometer frequencies as compared to SMMR. Snow height is derived from SWE values by dividing by a climatological snow density at the given location and time of year. A 45-year time series (1955-1999) of Canadian snow data (MSC, 2000) is used to define the climatological seasonal cycles of snow density for tundra, taiga, prairie, alpine and maritime regions. These snow classes were defined by Sturm et al. (1995) based on climatological values of temperature, precipitation and wind speed.

Tundra and taiga snow account for more than 90% of the Arctic drainage area. Very thin snow cover often cannot be detected by passive microwave remote sensing because it does not provide a sufficiently strong scattering signal. Therefore, investigators also used the EASE-Grid version of the National Oceanic and Atmospheric Administration National Environmental Satellite, Data, and Information Service (NOAA-NESDIS) weekly snow charts (Armstrong and Brodzik, 2002) for snow identification. The NOAA charts are based on information from several visible-band satellites. For grid cells where the SSM/I does not detect snow but the NOAA charts do, investigators assume a snow thickness of 3 cm. The NOAA charts are most useful at the beginning of the winter season and for the southern margin of snow cover. Erroneous SSM/I depictions of snow, sometimes occurring in the middle of summer, are eliminated through comparison with the NOAA snow charts. The maximum snow depth allowed is 80 cm.

Soil Properties

Soil bulk density for the three major model layers is derived from the SoilData System of the International Geosphere-Biosphere Programme (IGBP) (Global Soil Data Task, 2000), which can generate maps of a number of soil parameters at user-selected depths and spatial resolutions from their database. Since the SoilData System accounts only for mineral soil types, investigators parameterize a percentage of organic soil (peat) for the top two major soil layers (Oelke et al., 2003). The relative compositions of clay, silt, sand and gravel for each grid cell are also extracted from the SoilData System. These concentrations are used to weight the different thermal conductivities for fine grained soils (clay and silt) and coarse grained soils (sand and gravel) calculated for frozen and thawed states (Kersten, 1949). Investigators input daily soil water content obtained from a 20-year model climatology (1981-2000) of the University of New Hampshire Permafrost/Water Balance Model.

5. References and Related Publications

Armstrong, R. L., and M. J. Brodzik. 2002. Northern Hemisphere EASE-Grid weekly snow cover and sea ice extent, Version 2. Boulder, CO. National Snow and Ice Data Center. CD-ROM.

Chang, A. T. C., J. L. Foster, and D. K. Hall. 1987. Nimbus-7 SMMR derived global snow cover parameters. Annals of Glaciology 9, 39-44.

European Centre for Medium-Range Weather Forecasts. 2002. ERA-40 Project Report Series 3. Workshop on Re-analysis, 5-9 November 2001. European Center for Medium Range Weather Forecasts 443 pp.

European Centre for Medium-Range Weather Forecasts. 21 January 2004. "2.3 Horizontal interpolation." Bilinear Interpolation Scheme. Available from http://www.ecmwf.int/research/ifsdocs/CY25r1/Technical/Technical-3-04.html#wp961293; [INTERNET]

Global Soil Data Task. 2000. Global Gridded Surfaces of Selected Soil Characteristics (IGBP-DIS). International Geosphere-Biosphere Programme - Data and Information Services. Available online at http://www.daac.ornl.gov from the ORNL Distributed Active Archive Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee, U.S.A.

Goodrich, L. E. 1982. Efficient numerical technique for one-dimensional thermal problems with phase change. International Journal of Heat and Mass Transfer 21, 615-621.

International Permafrost Association (IPA). 1998. Data and Information Working Group, Circumpolar Active-Layer Permafrost System (CAPS), version 1.0. Boulder, CO: National Snow and Ice Data Center/World Data Center for Glaciology. CD-ROM.

Kersten, M. S. 1949. Laboratory research for the determination of the thermal properties of soils. Final report. Engineering Experiment Station, University of Minnesota.

Lunardini, V. J. 1988. Heat conduction with freezing and thawing. US Army Corps of Engineers Cold Regions Research and Engineering Laboratory, Monograph, 88-1.

Meteorological Service of Canada (MSC). 2000. Canadian Snow Data. CRYSYS Project, Climate Processes and Earth Observation Division, Meteorological Service of Canada, Downsview, Ontario. CD-ROM.

Oelke, C., T. Zhang, M. Serreze, and R. Armstrong. 2003. Regional-scale modeling of soil freeze/thaw over the Arctic drainage basin. Journal of Geophysical Research 108 (D10): 4314.

Oelke, C. and T. Zhang. 2004. A model study of circum-arctic soil temperatures. Permafrost and Periglacial Processes 15: 103-121.

Sturm, M., J. Holmgren, and G. E. Liston. 1995. A seasonal snow cover classification system for local to global applications. Journal of Climate 8, 1261-1283.

6. Document Information

Acronyms and Abbreviations

The following acronyms and abbreviations are used in this document.

Document Creation Date

May 2006

Document URL

http://data.eol.ucar.edu/codiac/dss/id=106.ARCSS158