Geospatial Coherence and Modelling of Land-Surface Fluxes
Abstract
Land-atmosphere fluxes are known to vary at multiple time scales, but uncertainty is higher as to how fluxes behave spatially within regions. With an increase in the number of eddy covariance towers, we are now able to examine the geospatial coherence of ecosystem fluxes. Eighteen sites from Michigan and Wisconsin were used in this study, ranging from 100 m to 600 km apart. Land-surface fluxes from a six-month period were used to quantify spatial coherence on a pair-wise basis. Using geospatial statistics, carbon cycling (NEE, GPP and Reco) and sensible heat fluxes were found to be 95% correlated directly outside of a flux footprint and 56% correlated out to a distance of ~35km. Water and momentum fluxes were less correlated, 83% directly outside of a flux footprint and 40% at a distance of ~130 km - albeit a much larger spatial distance than for the carbon and sensible heat fluxes. All fluxes showed strong spectral coherence at daily timescales, with 1-, 2- and 3-month frequencies being the next common mode of variability. A 9-year temporal flux record at a subsection of six sites was used to test flux modeling within the high coherence spatial zones. Results show that with as little as two years of data to build a neural network model with, 30-minute flux time-series can be modeled with +/- 10% accuracy when summed to the annual time-scale. This work demonstrates the potential of quantifying geospatial flux coherence across the Midwest, and the ability to predict fluxes beyond the spatial limit of a single flux tower footprint. Ultimately, this would allow better spatial scaling of terrestrial land-atmosphere fluxes between tower footprint and modeling or remote sensing scales.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.B41K2491R
- Keywords:
-
- 3315 Data assimilation;
- ATMOSPHERIC PROCESSES;
- 0414 Biogeochemical cycles;
- processes;
- and modeling;
- BIOGEOSCIENCES;
- 0426 Biosphere/atmosphere interactions;
- BIOGEOSCIENCES;
- 0430 Computational methods and data processing;
- BIOGEOSCIENCES