Ninth International Conference on Permafrost ... - IARC Research

Interannual Variability of the Near-Surface Soil Freeze-Thaw Cycle Detected fromPassive Microwave Remote Sensing Data in the Northern HemisphereTingjun ZhangNational Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences,University of Colorado at BoulderRichard ArmstrongNational Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences,University of Colorado at BoulderIntroductionBetter knowledge and understanding of the near-surfacefreeze-thaw cycle of soils are prerequisite for evaluatingthe impact of cold season/cold region processes on surfaceand subsurface hydrology, regional and global climate,carbon exchange between the atmosphere and the land, andthe terrestrial ecosystem as a whole. The challenge is todevelop new techniques and methodologies to obtain dataand information of the near-surface soil freeze-thaw cycle.A combined frozen soil algorithm using passive microwavesatellite remote sensing data and numerical modeling wasdeveloped and validated to detect the near-surface soilfreeze-thaw cycle over snow-free and snow-covered landareas. In this study, we use the NSIDC Frozen Soil Algorithm(Zhang & Armstrong 2001, Zhang et al. 2003) to investigatethe interannual variability of the near-surface soil freezethawcycle over the period from 1988 through 2006 in theNorthern Hemisphere.Data and MethodsThe NSIDC Frozen Soil Algorithm consists of two parts:(1) Over snow-free land surface, passive microwave satelliteremote sensing algorithm was used to detect the near-surfacesoil freeze-thaw cycle; (2) Over snow-covered land surface,a one-dimensional heat transfer numerical model with phasechange was used to detect soil freeze-thaw status undersnow cover (Zhang & Armstrong 2001, Zhang et al. 2003).Using the Defense Meteorological Satellite Program’sSpecial Sensor Microwave Imager (SSM/I) data, the passivemicrowave algorithm uses a negative spectral gradientbetween 19 GHz and 37 GHz, vertically polarized brightnesstemperatures, and a cut-off brightness temperature at 37GHz with vertical polarization (T B[37V]). SSM/I data andsoil temperature data from 26 stations over the contiguousUnited States from the two-year period July 1, 1997, throughJune 30, 1999, were used to calibrate the algorithm (year1), to validate the algorithm (year 2), and to demonstratefreeze/thaw classification (both years). A cut-off brightnesstemperature of 258.2 K was obtained based on a linearcorrelation (r 2 = 0.84) between the soil temperature at 5 cmdepth and the T B(37V). The NSIDC Frozen Soil Algorithmprovides accuracy for frozen soil detection of about 76%and accuracy for the correct classification of both frozen andunfrozen soils of approximately 83% with a percent errorof about 17%. We used the validated NSIDC Frozen SoilFigure 1. Distribution of the near-surface soil freeze on December15, 1998, in the Northern Hemisphere.Algorithm to investigate the interannual and interdecadalvariability of the timing, frequency, duration and number ofdays, and daily area extent of the near-surface soil freezethawcycle over the period from 1988 through 2006 in theNorthern Hemisphere.ResultsIn the Northern Hemisphere, the near-surface soil starts tofreeze in September, expanding southwards and reaching tomaximum extent by January or February, then decreasing inarea extent, disappearing in late May or early June. Figure1 is a snapshot of area extent of snow cover and the nearsurfacesoil freeze on December 15, 1998, detected fromthe NSIDC Frozen Soil Algorithm. Area extent of the nearsurfacesoil freeze (Fig. 1, dark blue) is larger than that ofsnow cover (Fig. 1, light blue). Generally speaking, thenear-surface soil freeze-thaw or seasonally frozen groundis the largest in extent among all cryospheric components.The timing of snow on ground is very critical for soil freeze/thaw status under snow cover. Snow may not be accumulatedwhen the ground surface temperature is above 0°C, sincesnow will be melted when it reaches the ground. Soil maybe thawed under thick snow cover (Fig. 1, yellow) this isbecause of the combined impact of geothermal heat flux andsnow insulation effect.361