Land-atmosphere Interaction

A uniqueness of the research is the study of land-atmosphere interaction embeded in the broader context of atmosphere-land-ocean interaction, as related to natural climate variability such as the El Nino/Southern Oscillation, as well as impact of anthropogenic effects such as tropical deforestation. One approach is to simplify the many processes in the atmosphere and the land-surface based on observations or theoretical/modeling results, so the interactions among the subsystems can be delineated. Our current workhorse tools include the Simple-Land (SLand) land-surface parameterization scheme and the Quasi-equilibrium Tropical Circulation Model (QTCM).

Research Areas


Downloadable Images

Sahel Decadal Rainfall

Sahel Rainfall Diff 1950-67 minus 1968-1987

Mechanisms of Sahel Multidecadal Rainfall Change

Research example 1: Amazon deforestation and climate

  • Local feedbacks as well as the large-scale responses in the atmosphere and ocean to the Amazon deforestation are studied through numerical modeling using models of intermediate complexity.
  • A land-atmosphere interaction theory is developed for the tropical deforestation problem. The theory emphasizes the energy and water balance. It highlights the interaction among processes of moist convection, cloud, radiation and surface hydrology while each individual process is simplified. The zero surface energy flux condition, due to the small heat capacity of land, makes land-atmosphere interaction distinctly different from ocean-atmosphere interaction. This imposes a constraint on the sensitivity to the details of surface energy partitioning. Consequently, land surface temperature is largely a response to the energy and water balance, rather than a forcing as in the case of sea surface temperature. The figure depicts the feedback loops in the local energy and water budget.
  • Observational data are analyzied, providing inspiration and checks for the theoretical and modeling work. The figure shows the Amazon basin hydrologic cycle based on observed rainfall, historical river discharge data and atmospheric reanalysis.
  • Individual processes are further scrutinized. Knowledge gained helps to develope better parameterizations for numerical models, which in turn help the modeling effort in predicting/understanding future climate change. The figure shows the results of a proposed parameterization of the reevaporation of the water lost through interception, taking into account of the spatial and temporal variability of rainfall, compared to the observation from the ARME experiment conducted near Manaus, Amazonia.

Research Example 2: Enhancement of Climate Interaction in the Sahel by Vegetation Interaction

The role of naturally varying vegetation in influencing the climate variability in the Sahel is explored in a coupled atmosphere-land-vegetation model. The Sahel rainfall variability is influenced by sea surface temperature variations in the oceans. Land-surface feedback is found to increase this variability both on interannual and interdecadal time scales. Interactive vegetation enhances the interdecadal variation significantly, but can reduce year to year variability due to a phase lag introduced by the relatively slow vegetation adjustment time. Variations in vegetation accompany the changes in rainfall, in particular, the multi-decadal drying trend from the 1950s to the 1980s.
  • Fig.2.1 Interannual Variability in the the Sahel Vegetation and Rainfall. Shown in the figure are the differences between 1989 (a wet year) and 1984 (a drought year). In the left panel is the Normalized Difference Vegetation Index, and on the right is rainfall.
  • Fig. 2.2 Annual rainfall anomaly in mm y$^{-1}$ (vertical bars) over the West African Sahel (13N--20N, 15W--20E) from 1950 to 1998: (A) observations from Hulme; (B) model with non-interactive land-surface hydrology (fixed soil moisture) and non-interactive vegetation (SST influence only, AO); smoothed line is a 9-year running mean showing the low-frequency variation; (C) model with interactive soil moisture but non-interactive vegetation (AOL); (D) model with interactive soil moisture and vegetation (AOLV). Also plotted (as connected circles; labeled on the right) are: (A) the Normalized Difference Vegetation Index (NDVI); (C) model simulated annual soil moisture anomaly (mm); (D) model simulated leaf area index (LAI) anomaly. All the anomalies are computed relative to the 1950--98 base period except that the NDVI data is relative to 1981.