Location: Hydrology and Remote Sensing LaboratoryTitle: Surface energy flux estimation in two boreal settings in Alaska using a thermal-based remote sensing mode
|CRISTOBAL, J. - University Of Alaska|
|PRAKASH, A. - University Of Alaska|
|Kustas, William - Bill|
|GENS, R. - University Of Alaska|
Submitted to: Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/14/2020
Publication Date: 12/16/2020
Citation: Cristobal, J., Prakash, A., Anderson, M.C., Kustas, W.P., Alfieri, J.G., Gens, R. 2020. Surface energy flux estimation in two boreal settings in Alaska using a thermal-based remote sensing mode. Remote Sensing. 12(24):4108. https://doi.org/10.3390/rs12244108.
Interpretive Summary: The impact of climate change on the energy and hydrologic balance of the boreal forest is not well understood, with ramifications to ecosystem health, fire potential, and species migration. The remoteness of these northern regions is not conducive to extensive ground based observation; therefore, remote sensing approaches for mapping vegetation health, water use, and energy partitioning will be of value in monitoring response of boreal systems to climate change. This paper investigates the accuracy of a remotely sensed two-source energy balance (TSEB) model over representative flux sites in Alaska over birch and black spruce stands. Comparison of modeled and measured evapotranspiration (ET) and surface energy fluxes suggested important modifications to the TSEB model to improve performance over these important boreal landcover types – most critically, a down-adjustment of a parameter controlling vegetation transpiration. These modifications will be implemented in a regional version of the TSEB model that runs operationally over North America, used to monitor drought and water use in response to climate, land use, and land cover change.
Technical Abstract: Recent Arctic warming has led to changes in the hydrological cycle. Circum-Arctic and circumboreal ecosystems are showing evidence of “greening” and “browning” due to temperature warming leading to shrub encroachment, tree mortality and deciduousness. Increases in latent heat flux from increased evapotranspiration rates associated with deciduous-dominated ecosystems may be significant, because deciduous vegetation has extremely high-water use and water storage capacity compared to coniferous and herbaceous plant species. Thus, the impact of vegetation change in boreal ecosystems on regional surface energy balance is a significant knowledge gap that must be addressed to better understand observed trends in water use/availability and tree mortality. To this end, output from a two-source energy balance model (TSEB) with modifications for high latitude boreal ecosystems was evaluated using flux tower measurements and Terra/Aqua MODIS remote sensing data collected over the two largest boreal forest types in Alaska (birch and black spruce). Data under clear and overcast days and from leaf-out to senescence from 2012 to 2016 were used for validation. Using flux tower observations and local model inputs, modifications to the model formulation for soil heat flux, net radiation partitioning, and canopy transpiration were required for the boreal forest. These improvements resulted in a mean absolute percent difference of around 23% for turbulent daytime fluxes when surface temperature from the flux towers was used, similar to errors reported in other studies conducted in warmer climates. Results when surface temperature from Terra/Aqua MODIS estimates were used as model input suggested that these model improvements are pertinent for regional scale applications. Vegetation indices and LAI time-series from the Terra/Aqua MODIS products were confirmed to be appropriate for energy flux estimation in the boreal forest to describe vegetation properties (LAI and green fraction) when field observations are not available. Model improvements for boreal settings identified in this study will be implemented operationally over North America to map surface energy fluxes at regional scales using long time series of remote sensing estimates as part of NOAA’s GOES Evapotranspiration and Drought Information System.