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Séminaire

Titre : Diagnosing land-atmosphere coupling and its impact on climate variability in GFDL's climate models
Nom du conférencier : Alexis Berg
Son affiliation : Rutgers University / Geophysical Fluid Dynamics Laboratory
Laboratoire organisateur : LMD
Date et heure : 05-04-2013 10h30
Lieu : Salle de réunion du LMD/Jussieu (T45-55, 3e étage)
Résumé :

Land-atmosphere interactions occur when the response of the land surface (soil and vegetation) to atmospheric variations feeds back, positively or negatively, on these atmospheric variations. These feedbacks mainly originate from soil moisture anomalies, conveyed to the atmosphere primarily through their impact on surface heat fluxes. In some regions these interactions can lead to some degree of physical coupling between the land and the atmosphere, with thus the potential to affect regional mean climate, climate variability and extremes. Diagnosing these interactions in climate models is thus a crucial element of a process-based evaluation of these models. In this presentation we will show results from ongoing activities at GFDL aimed at investigating land-atmosphere coupling in some of GFDL's climate models.

In a first part, we evaluate the feedback between surface turbulent energy fluxes and precipitation, which is one of the key issues associated with land/atmosphere interactions. Using the NARR reanalysis data, Findell et al. (2011) recently provided an assessment of the impacts of morning surface latent and sensible heat fluxes on the frequency and intensity of afternoon convective rainfall over North America. Here, we apply the same metrics to AMIP-like simulations from GFDL’s atmospheric models AM2.1 and AM3. We show that these models perform differently in representing the impact of surface fluxes on convection. The sources of these differences are investigated.

In a second part, we analyze results from GLACE-CMIP5 simulations performed at GFDL : i.e., historical and climate change transient AMIP-like simulations, with and without interactive soil moisture. Here we compare in particular the two simulations over 1971-2000, isolating the effect of soil moisture dynamics on the simulated climate and placing the emphasis on near-surface hydroclimatic variability. We show that soil moisture dynamics strongly enhance the variability of temperature over apparent 'hotspots', at different time scales over different regions. Analysis of the daily distribution of the different variables involved (soil moisture, surface fluxes, temperature, precipitation) sheds light on the higher-order moments of variability that emerge as a result of soil moisture dynamics, including bimodality and skewness. In particular, soil moisture dynamics disproportionately impact the high side of the temperature distribution. In addition, soil moisture appears to be responsible for the coupling between temperature and precipitation seasonal variability in some regions. These results have implications for the diagnosis and attribution of extreme events such as heatwaves and droughts.

Contact :

MP Lefebvre 0144272799