ASCAT Surface State Flag (SSF): Extracting Information on Surface Freeze/Thaw Conditions From Backscatter Data Using an Empirical Threshold-Analysis Algorithm

• Published in: IEEE Transactions on Geoscience and Remote Sensing
• Main Authors: Naeimi, Vahid, Paulik, Christoph, Bartsch, Annett, Wagner, Wolfgang, Kidd, Richard, Park, Sang-Eun, Elger, Kirsten, Boike, Julia
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: 2011
• Subjects: permafrost
• Online Access: https://epic.awi.de/id/eprint/25807/; https://doi.org/10.1109/TGRS.2011.2177667; https://hdl.handle.net/10013/epic.39268

Information on soil surface state is valuable for many applications such as climate studies and monitoring of permafrost regions. C-band scatterometer data indicate good potential to deliver information on surface freeze/thaw. Variation in state or amount of water contained in the soil causes significant alteration of dielectric properties of the soil which is markedly observ- able in scatterometer backscattered signal. A threshold-analysis method is developed to derive a set of parameters to be used in evaluating the normalized backscatter measurements through decision trees and anomaly detection modules for determination of freeze/thaw conditions. The model parameters are extracted from two years (2007 132008) backscatter data from ASCAT scatterome- ter onboard Metop satellite collocated with ECMWF ReAnalysis (ERA-Interim) soil temperature. Backscatter measurements are flagged as indicator of frozen/unfrozen surface, and snowmelt or existing water on the surface. The output product, so-called sur- face state flag (SSF), compares well with two modeled soil temper- ature data sets as well as the air temperature measurements from synoptic meteorological stations across the northern hemisphere. The SSF time series are also validated with soil temperature data available at three in situ observation sites in Siberian region showing the overall accuracy of about 80% to 90%.