Data Information Page from ArcticRIMS (http://RIMS.unh.edu) Title: DAILY THAW DEPTH AND FROZEN GROUND DEPTH , Aggregated by Administrative Regions (Serreze, Oelke) Description: Daily thaw depth and frozen ground depth are calculated using a frozen ground model. Oelke et al. [2003] provide details. Classification: Land Based, Climate, Political Divisions Author/PI: Richard Lammers, Mark Serreze and Christoph Oelke Contact Information for original gridded daily time step data: Mark Serreze Senior Research Scientist 449 UCB, RL-2, #223 National Snow and Ice Data Center University of Colorado Boulder, CO 80309-0449 E-mail: serreze@kryos.colorado.edu Tel: 303-492-2963 Web: http://nsidc.org/research/bios/serreze.html Christoph Oelke National Snow and Ice Data Center University of Colorado Boulder Colorado 80309-0449 USA Contact Information for all spatially and temporally aggregated data in RIMS: Richard Lammers Water Systems Analysis Group Institute for the Study of Earth, Oceans, and Space Morse Hall, Room 211 8 College Road University of New Hampshire Durham, NH 03824-3525 USA Email: Richard.Lammers@unh.edu Tel: (603) 862-4699 Web: http://www.wsag.unh.edu/ Temporal Coverage Begin Date (year-month-day): 1980-01-01 End Date (year-month-day): 2001-12-31 Spatial Coverage: Corner coordinates in Ease Projection (Units: Meters form N.P.) (Description at http://nsidc.org/data/ease/ease_grid.html) Minimum X: -4875633.612 m Minimum Y: -4875633.612 m Maximum X: 4875633.612 m Maximum Y: 4875633.612 m Corner coordinates in Geographical projection (Units: Degrees) (Description at http://en.wikipedia.org/wiki/Equirectangular_projection) Minimum latitude: 45.0 Minimum longitude: -180.0 Maximum latitude: 90.0 Maximum longitude: 180.0 Units: mm Aggregation Method: average General Methods: Thaw depth and frozen ground are calculated using different initial model settings. In the first case, all soil down to the lower model boundary is 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 according model grid cell values 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). Again, the according grid cell values are coded as missing (-9999.0). Both thaw depth and frozen ground depth are simulated for the regions of discontinuous permafrost and for sporadic permafrost. For regions of continuous permafrost we only show simulated thaw depths whereas for seasonally frozen ground there is only frozen ground depth. 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. The model is applied to the entire Arctic drainage area on the 25 km EASE grid with a daily time step. Soil is divided into three major layers (0-30 cm, 30-80 cm, and 80-1500 cm) with distinct thermal properties of frozen and thawed soil, respectively. Calculations are performed on 54 model nodes ranging from a thickness of 10 cm near the surface to 1 m at 15 m depth. Thermal properties of mineral soils are determined from soil dry bulk density and water content according to Kersten [1949] and Lunardini [1988] for peat. Initial temperatures are chosen according to the grid cell's permafrost classification based on the IPA map. The model is then spun up for 50 years in order to obtain more realistic start conditions for temperatures for all model layers. Comments: Frozen Ground Model - Details Active Layer Depth (ALD) in [cm], C. Oelke, NSIDC, August 2002 Settings as in Oelke et al. (2002), subm. to JGR-Atm. 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 1980-01-01, ending 1999-12-31 (7305 days), run in 4-year tiles with 1-year spinup for 1980-83 and from a startup-file therafter. Missing values (-9999.0) apply for grid cells in seasonally-frozen areas. Layers: 0-30 cm, 30-80 cm, 80-1500 cm. Temperature: Topography-corrected NCEP sigma-.995 on EASE grid. Snow: modified Chang algorithm and climatology, 7-day maxima, no snow above 8 deg C. Snow density: Annual cycle for each of Sturm et al. (1995) snow classes (tundra, taiga, maritime, prairie, alpine): areas defined Sturm. Snow conductivity: Logarithmic fit to data of "others" in Sturm et al. (1997). Soil bulk density: From IGBP-DIS Soil Data System. Upper 2 soil layers (dens., cond.) modified with peat characteristics: density 500 kg/m**3, Peat conductivity for frozen and thawed cases from Lunardini (1988). Peat 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 3 permafrost classes; frozen. Climatological 20-year geothermal heat flux into lowest model layer. Temperature The model is driven by surface air temperatures from the NCEP/NCAR reanalysis [Kalnay et al, 1996] at the lowest signal level (0.995) with modifications. The reanalysis data are provided at a horizontal resolution of 2.5 deg x 2.5 deg. A topography adjustment is performed based on NCEP/NCAR tropospheric lapse rates, the 0.995 sigma level temperature and topography from a digital elevation model on the 25 km EASE grid. Elevation is a first-order determinant of the spatial variation in surface air temperature. The topography adjustments effectively improve the resolution of the NCEP/NCAR data, making it more compatible with the snow cover data also used for model forcing. Details are given in Oelke et al. [2003]. Snow Cover Snow water equivalent (SWE) is derived from satellite passive microwave data. For the period 1978-1987, we use 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 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 of Canadian snow data (1955-1999) [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, we also use the EASE-Grid version of the 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, we 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. Soil Properties Soil bulk density for the three major model layers is derived from the SoilData System of IGBP [Global Soil Data Task, 2000] that can generate maps of a number of soil parameters at user-selected depths and spatial resolution from their pedon data base. Since the SoilData System accounts only for mineral soil types, we 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 a) fine grained soils (clay and silt), and b) coarse grained soils (sand and gravel), calculated for frozen and thawed states [Kersten, 1949]. We input daily soil water content obtained from a 20-year model climatology (1981-2000) of the UNH Permafrost/Water Balance Model. Remarks 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 of 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. References: 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. 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. Int. J. 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]. Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woolen, Y. Zhu, M. Chelliah, W. Ebisuzaki, W. Higgens, J. Janowiak, K.C. Mo, C. Ropelewski, J. Wang, A. Leetma, R. Reynolds, R. Jenne, and D. Joseph, 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteorol. Soc., 77, 437-471. 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 CD-ROM. CRYSYS Project, Climate Processes and Earth Observation Division, Meteorological Service of Canada, Downsview, Ontario, January 2000. Oelke, C., T. Zhang, M. Serreze, and R. Armstrong, 2003: Regional-scale modeling of soil freeze/thaw over the Arctic drainage basin. J. Geophys. Res. (In press). Sturm, M., J. Holmgren, and G.E. Liston, 1995: A seasonal snow cover classification system for local to global applications. J. Climate, 8, 1261-1283. Arctic RIMS Contact: Richard Lammers Water Systems Analysis Group Institute for the Study of Earth, Oceans, and Space Morse Hall University of New Hampshire Durham, NH 03824 Phone: (603) 862-4699 Fax: (603) 862-0587 Email: Richard.Lammers@unh.edu Web: http://wsag.unh.edu Data Archiving: This ArcticRIMS data set has been permanently stored to the ARCSS Data Archive at NCAR/EOL (http://www.eol.ucar.edu/projects/arcss) with the support of National Science Foundation grants (NSF) OPP-0230243 and Humans and Hydrology at High Latitudes (NSF) ARC-0531354 Note: Data represents only the portion of administrative units within the Pan-Arctic drainage domain.