CNRM GAME Andndash
Nabat P.,CNRM GAME Andndash |
Solmon F.,Abdus Salam International Center For Theoretical Physics |
Mallet M.,CNRS Laboratory for Aerology |
Kok J.F.,U.S. National Center for Atmospheric Research |
Somot S.,CNRM GAME Andndash
Atmospheric Chemistry and Physics | Year: 2012
The present study investigates the dust emission and load over the Mediterranean basin using the coupled chemistry-aerosol-regional climate model RegCM-4. The first step of this work focuses on dust particle emission size distribution modeling. We compare a parameterization in which the emission is based on the individual kinetic energy of the aggregates striking the surface to a recent parameterization based on an analogy with the fragmentation of brittle materials. The main difference between the two dust schemes concerns the mass proportion of fine aerosol that is reduced in the case of the new dust parameterization, with consequences for optical properties. At the episodic scale, comparisons between RegCM-4 simulations, satellite and ground-based data show a clear improvement using the new dust distribution in terms of aerosol optical depth (AOD) values and geographic gradients. These results are confirmed at the seasonal scale for the investigated year 2008. This change of dust distribution has sensitive impacts on the simulated regional dust budget, notably dry dust deposition and the regional direct aerosol radiative forcing over the Mediterranean basin. In particular, we find that the new size distribution produces a higher dust deposition flux, and smaller top of atmosphere (TOA) dust radiative cooling. A multi-annual simulation is finally carried out using the new dust distribution over the period 2000-2009. The average SW radiative forcing over the Mediterranean Sea reaches -13.6 W m -2 at the surface, and -5.5 W m-2 at TOA. The LW radiative forcing is positive over the basin: 1.7 W m-2 on average over the Mediterranean Sea at the surface, and 0.6 W m-2 at TOA. © Author(s) 2012. CC Attribution 3.0 License.
Parrens M.,CNRM GAME Andndash |
Mahfouf J.-F.,CNRM GAME Andndash |
Barbu A.L.,CNRM GAME Andndash |
Calvet J.-C.,CNRM GAME Andndash
Hydrology and Earth System Sciences | Year: 2014
Land surface models (LSM) have improved considerably in the last two decades. In this study, the Interactions between Surface, Biosphere, and Atmosphere (ISBA) LSM soil diffusion scheme is used (with 11 soil layers represented). A simplified extended Kalman filter (SEKF) allows ground observations of surface soil moisture (SSM) to be assimilated in the multilayer LSM in order to constrain deep soil moisture. In parallel, the same simulations are performed using the ISBA LSM with 2 soil layers (a thin surface layer and a bulk reservoir). Simulations are performed over a 3 yr period (2003-2005) for a bare soil field in southwestern France, at the SMOSREX (Surface Monitoring Of the Soil Reservoir Experiment) site. Analyzed soil moisture values correlate better with soil moisture observations when the ISBA LSM soil diffusion scheme is used. The Kalman gain is greater from the surface to 45 cm than below this limit. For dry periods, corrections introduced by the assimilation scheme mainly affect the first 15 cm of soil whereas weaker corrections impact the total soil column for wet periods. Such seasonal corrections cannot be described by the two-layer ISBA LSM. Sensitivity studies performed with the multilayer LSM show improved results when SSM (0-6 cm) is assimilated into the second layer (1-5 cm) than into the first layer (0-1 cm). The introduction of vertical correlations in the background error covariance matrix is also encouraging. Using a yearly cumulative distribution function (CDF)-matching scheme for bias correction instead of matching over the three years permits the seasonal variability of the soil moisture content to be better transcribed. An assimilation experiment has also been performed by forcing ISBA-DF (diffusion scheme) with a local forcing, setting precipitation to zero. This experiment shows the benefit of the SSM assimilation for correcting inaccurate atmospheric forcing.©Author(s) 2014. CC Attribution 3.0 License.