Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes
Lead Research Organisation:
Durham University
Department Name: Biological and Biomedical Sciences
Abstract
See lead proposal
Organisations
Publications
Hancock S
(2014)
Characterising forest gap fraction with terrestrial lidar and photography: An examination of relative limitations
in Agricultural and Forest Meteorology
Hancock S
(2013)
Evaluating global snow water equivalent products for testing land surface models
in Remote Sensing of Environment
Hancock S
(2014)
Biases in Reanalysis Snowfall Found by Comparing the JULES Land Surface Model to GlobSnow
in Journal of Climate
Hartley IP
(2015)
Quantifying landscape-level methane fluxes in subarctic Finland using a multiscale approach.
in Global change biology
Poyatos R
(2013)
Environmental and Vegetation Drivers of Seasonal CO2 Fluxes in a Sub-arctic Forest-Mire Ecotone
in Ecosystems
Reid T
(2014)
Spatial quantification of leafless canopy structure in a boreal birch forest
in Agricultural and Forest Meteorology
Roberts S
(2015)
Diatom response to mid-Holocene climate in three small Arctic lakes in northernmost Finnmark
in The Holocene
Rutter N
(2023)
Canopy Structure and Air Temperature Inversions Impact Simulation of Sub-Canopy Longwave Radiation in Snow-Covered Boreal Forests
in Journal of Geophysical Research: Atmospheres
| Description | An innovative application of terrestrial laser scanning to quantify forest canopies has been developed, allowing the canopy to be quantified in ways that allow improvements in the modelling of energy balance and hence snow dynamics. Field data have been collected in a range of sub-Arctic and Boreal forest types, demonstrating the applicability of the approach to both deciduous and evergreen canopies. |
| Exploitation Route | Our results will be of value to meteorologists and climate modelers seeking to improve the representation of canopy influences upon snow melt processes on forested landscapes in the land-surface sub-models of climate and numerical weather forecasting models. |
| Sectors | Environment |