Methane Emissions in the North Slope: Identifying the Source of Model and Observation Disagreement
Abstract
As climate change causes temperatures to warm in high latitude regions, methane emissions are expected to increase as a result of thawing permafrost. There are numerous dynamic processes that influence the methane emissions from tundra soils, making it difficult for large scale models to accurately estimate methane fluxes. This research aims to assess the disparity between aircraft measurements of methane surface influence and model simulations in the North Slope of Alaska. One of the carbon cycle science goals of the Arctic Boreal Vulnerability Experiment (ABoVE) is to determine a methane budget within the ABoVE domain; however, current model simulations are inconsistent with observed measurements. Specifically, this research analyzes methane estimates from various Global Carbon Project (GCP) models, comparing them to aircraft data collected through the Atmospheric Radiation Measurement's Airborne Carbon Measurements (ARM-ACME V) during the 2015 field campaign in the North Slope. The disparities are then analyzed within the context of "footprint" products of a coupled WRF-STILT (Weather Research and Forecasting and Stochastic Time Inverted Lagrangian Transport) model in order to assess spatial trends of the model-data mismatch. The individual GCP models are also assessed by extracting monthly data profiles along two longitudinal cross-sections, revealing that some models estimate no methane emissions, while others display great seasonal variation. The goal of this project is to identify potential sources of model-data disparity through spatial analysis of variables, including inundation, active layer thickness, soil moisture, land cover heterogeneity, above-ground vegetation, and surface water extent. This work will inform the ABoVE team regarding possible sources of error in model assessments, and potentially identify either specific regions that are highly uncertain in the North Slope or processes that need to be incorporated to improve model accuracy.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMB080.0006R
- Keywords:
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- 0414 Biogeochemical cycles;
- processes;
- and modeling;
- BIOGEOSCIENCES;
- 0428 Carbon cycling;
- BIOGEOSCIENCES;
- 0439 Ecosystems;
- structure and dynamics;
- BIOGEOSCIENCES;
- 0475 Permafrost;
- cryosphere;
- and high-latitude processes;
- BIOGEOSCIENCES