Coupling a field-scale resolving land surface model to a global atmosphere model: Uncovering the role of sub-grid heterogeneity in land-atmosphere interactions
Abstract
Multi-scale spatial heterogeneity over land plays an important role in the coupling between the land surface and atmosphere over a range of temporal and spatial scales. However, until now, limited representation of land heterogeneity in coupled land-atmosphere models (e.g., numerical weather prediction) has continued to constrain our understanding of the role of heterogeneity in the Earth system. Recent advances at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) allow us to revisit this persistent limitation. By harnessing the existing petabytes of land information from satellite remote sensing, the GFDL LM4.2 land surface model is able to explicitly represent sub-grid heterogeneity over land at field scales. In this presentation, we leverage the advances in LM4.2 by coupling it to the GFDL AM4 atmosphere model to assess the sensitivity of land-atmosphere interactions to multi-scale spatial organization over land.
Through four different global model experiments we quantify how the different drivers of sub-grid spatial heterogeneity impact the surface states and fluxes (e.g., soil moisture, evaporation, precipitation, and CAPE) over the globe. Starting with the baseline experiment (no sub-grid heterogeneity), each subsequent experiment adds a new source of sub-grid heterogeneity: 1) soils, 2) topography, and 3) land cover. For each experiment, the water, energy, and carbon cycles over land are spun-up for around 200 years. These computed initial conditions are then used to initialize the land-atmosphere coupled model (LM4.2/AM4) that is run between 1979 and 2010. We will present results from the comparison of these simulations to uncover the role of each driver of heterogeneity both locally (i.e., hotspots) and globally. We will conclude by discussing existing weaknesses in the modeling framework, future directions, and the potential applications in numerical weather forecasting, seasonal prediction, and climate prediction.- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.H11B..08C
- Keywords:
-
- 3307 Boundary layer processes;
- ATMOSPHERIC PROCESSESDE: 3322 Land/atmosphere interactions;
- ATMOSPHERIC PROCESSESDE: 1843 Land/atmosphere interactions;
- HYDROLOGYDE: 1866 Soil moisture;
- HYDROLOGY