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Schaefer, Kevin M.

Publications and source records attributed to Schaefer, Kevin M..

The Terrestrial Biosphere Model Farm

Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901–2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges.

54 ENVIRONMENTAL SCIENCES↗

Joint retrieval of soil moisture and permafrost active layer thickness using L-band InSAR and P-band PolSAR

Seasonal subsidence measured by repeat-pass interferometric synthetic aperture radar (InSAR) can be used to infer the active layer thickness (ALT) in permafrost regions. The differential volume of soil water undergoing the phase change over the thaw season is one of the factors impacting the seasonal subsidence and is a function of both soil moisture profile and thaw depth. Without the information about soil moisture, this InSAR approach can have large biases in the ALT estimates when soil moisture profile is below saturation. Soil moisture and ALT can also be estimated from polarimetric synthetic aperture radar (PolSAR) backscatter observations but the sensing depth of the PolSAR approach is limited when deep ALT is present. In this paper, we integrated these two approaches and applied a joint retrieval method to estimate the soil moisture profiles and ALT from the L-band InSAR and P-band PolSAR data acquired over the Arctic-boreal region during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign.

Schaefer, Kevin M.↗