Research Papers: Mahta Moghaddam

Characterizing permafrost active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska

By Yonghong Yi, John S. Kimball, Richard H. Chen, Mahta Moghaddam, Rolf H. Reichle, Umakant Mishra, Donatella Zona, Walter C. Oechel

The Cryosphere

2018

An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models and can lead to large uncertainties in predicting regional ecosystem responses and climate feedbacks. In this study, we developed a spatially integrated modeling and analysis framework combining field observations, local-scale ( ∼ 50m resolution) active layer thickness (ALT) and soil moisture maps derived from low-frequency (L+P-band) airborne radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Modeled ALT results show good correspondence with in situ measurements in higher-permafrost-probability (PP ≥ 70%) areas (n = 33; R = 0.60; mean bias = 1.58cm; RMSE = 20.32cm), but with larger uncertainty in sporadic and discontinuous permafrost areas. The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32±1.18cmyr−1) and much larger increases (> 3cmyr−1) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60±0.32). A spatially integrated analysis of the radar retrievals and model sensitivity simulations demonstrated that uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was the largest factor affecting modeled ALT accuracy, while soil moisture played a secondary role. Potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of active layer conditions and refinement of the modeling framework across a larger domain.


Characterization of vegetation and soil scattering mechanisms across different biomes using P-band SAR polarimetry

By Seyed Hamed Alemohammad, Alexandra G. Konings, Thomas Jagdhuber, Mahta Moghaddam, Dara Entekhabi

Remote Sensing of Environment

2018

Understanding the scattering mechanisms from the ground surface in the presence of different vegetation densities is necessary for the interpretation of P-band Synthetic Aperture Radar (SAR) observations and for the design of geophysical retrieval algorithms. In this study, a quantitative analysis of vegetation and soil scattering mechanisms estimated from the observations of an airborne P-band SAR instrument across nine different biomes in North America is presented. The goal is to apply a hybrid (model- and eigen-based) three component decomposition approach to separate the contributions of surface, double-bounce and vegetation volume scattering across a wide range of biome conditions. The decomposition makes no prior assumptions about vegetation structure. We characterize the dynamics of the decomposition across different North American biomes and assess their characteristic range. Impacts of vegetation coverseasonality and soil surface roughness on the contributions of each scattering mechanism are also investigated. Observations used here are part of the NASA Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission and data have been collected between 2013 and 2015.


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