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This project is funded by NSF
To examine four high-resolution hemispheric-scale gridded sets of monthly temperature and precipitation that have been constructed using different interpolation routines and reanalysis of data from a large number of weather stations
Tingjun Zhang is the PI and Roger G. Barry is Co-Investigator.
Quantitative estimates of the environmental and socioeconomic impacts of changing climate in the northern regions require robust permafrost projections. These estimates are also critically dependent on the availability of models and the forcing data that are needed for predictive calculations. In this project, we examined four high-resolution hemispheric-scale gridded sets of monthly temperature and precipitation that have been constructed using different interpolation routines and reanalysis of data from a large number of weather stations. Four data sets differ in mean annual air temperatures averaged over the 15-year period by one to two degrees Celsius and in degree-days of thawing by more 200 degree Celsius days from observations at more than one half of the 156 stations in Russian permafrost regions. A permafrost model forced with the gridded climatic data sets was used to calculate the maximum depth of seasonal thawing (active layer thickness) over permafrost, which we compared with the observations. We developed a comprehensive procedure for the evaluation of the permafrost model, which is based on the statistical ensemble approach and accounts for the natural small-scale variability of active layer thickness. At any given site, the model is forced with prescribed climatic data and run repeatedly with combinations of the varying snow, vegetation, and soil parameters to generate the statistics of calculated results, and the results are compared with the observation statistics.
Our evaluations, using data from selected Russian permafrost monitoring sites, indicated good correspondence between the calculated and observed active layer thickness in both the mean values and the standard deviations. To estimate the effect of uncertainties in forcing climatic data on permafrost projections, we compared the broadscale characteristics of the frozen ground calculated using four different data sets. We analyzed the zonal mean air and ground temperatures, active layer thickness, and the area occupied by the near-surface permafrost in the Eurasian latitudinal zone to the north of 45 degrees North. Results were noticeably different and largely consistent with the differences in the zonal mean air temperatures. The 0.5 to 1.0 degree Celsius difference in the zonal mean air temperature between the data sets led to a 10 to 20 percent range of uncertainty in the estimates of the zonal near-surface permafrost area, which is comparable to the changes projected for the following several decades. Our ultimate conclusion is that more observations and theoretical studies are needed to improve the characterization of the baseline climatic conditions and to narrow the range of uncertainties in model-based permafrost projections.
For more information, see the Freezing and Thawing Cycle of Soils at Local, Regional, and Global Scales Web page.
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