Assessing the performance of CLM5 to simulate forest snow processes using multi-sensor datasets

Abstract:

Seasonal snow is an important part of the land surface energy budget due to its high reflectivity that can substantially increase Land Surface Albedo (LSA). Where seasonal snow overlaps with forested environments, land surface reflectivity is dampened by the presence of trees, further complicating LSA calculations. These snow-vegetation interactions show a high degree of heterogeneity in space and time, and are poorly represented by land surface models. Furthermore, it remains challenging to validate model performance due to the contrasting spatial scales of model resolutions and in-situ observations.

We present solar transmission and LSA estimates from CLM5, the land component of the NCAR Community Earth System Model, which we run in point-mode to mitigate model validation challenges. We set up site scale simulations at alpine and boreal sites, capturing a large range in forest structure and species found in seasonally snow covered environments. UAV-based observations of LSA and spatially distributed sub-canopy radiation measurements from a mobile radiometer platform are used to assess the ability of CLM5 to represent a) solar radiation transmission to the snow surface and b) the resulting LSA at each of those sites.

In CLM5, Leaf Area Index (LAI) is the main descriptor of canopy structure. We find that this descriptor is insufficient to reproduce the observed spatial and temporal variability in solar transmission at all measurement sites, with poorest model performance in sparsely forested sites. Our model experiments show that both solar transmission and LSA can be more accurately simulated if LAI is replaced by local canopy descriptors. This study emphasizes the need to improve the representation of canopy structural heterogeneity in land surface models, since the large impact this has on LSA may have far reaching implications for simulations of the snow albedo feedback strength over the entire Northern Hemisphere Extratropics.