Finding optimal Noah-MP parameterizations for the characterization of surface heat fluxes in the Iberian Peninsula

Abstract

Land surface models (LSMs) play a crucial role in the characterization of land-atmosphere interactions by providing boundary conditions to a regional climate model (RCM). This is particularly true over the Iberian Peninsula (IP), a region where a water-limited regime governs most of the territory. This work aims to optimize the Noah LSM with multiparameterization options (Noah-MP) configuration for characterizing heat fluxes in the IP when the Weather Research and Forecasting (WRF) model v3.9.1 is used as RCM. To do that, a set of 70 experiments with a 1-year length has been completed using 35 combinations of Noah-MP parameterizations, both for a year with dry conditions in the IP (2005 year) and for a year with wet conditions (2010 year). Land surface heat fluxes and soil moisture simulated with Noah-MP coupled to WRF (WRF/Noah-MP) have been evaluated using as reference the available FLUXNET station data and CERRA-Land reanalysis data. In general, the results indicate that WRF/Noah-MP accurately simulates soil moisture and surface heat fluxes over the IP, especially for wetter climate conditions. The clustering method has presented an optimal configuration from 10 groups (Clusters from A to J), which showed that the WRF/Noah-MP parameterizations with the greatest influence on the simulation of surface heat fluxes over the IP are canopy stomatal resistance (CRS), surface exchange coefficient for heat (SFC), soil moisture factor controlling stomatal resistance (BTR), runoff and groundwater (RUN), and surface resistance to evaporation/sublimation (RSF). In addition, dynamic vegetation (DVEG) seems to influence simulations. Although several clusters/configurations showed reasonable results, experiment s27I in Cluster I with Jarvis CRS, Chen97 SFC, CLM-Type BTR, BATS RUN, and Adjusted Sellers to decrease RSURF for wet soil for RSF seem to be more adequate to simulate surface heat fluxes in the IP.