Myriam Khodri

Irregular tropical glacier retreat over the Holocene epoch driven by progressive warming

The causes and timing of tropical glacier fluctuations during the Holocene epoch (10,000 years ago to present) are poorly understood. Yet constraining their sensitivity to changes in climate is important, as these glaciers are both sensitive indicators of climate change and serve as water reservoirs for highland regions. Studies have so far documented extra-tropical glacier fluctuations, but in the tropics, glacier–climate relationships are insufficiently understood. Here we present a 10Be chronology for the past 11,000 years (11 kyr), using 57 moraines from the Bolivian Telata glacier (in the Cordillera Real mountain range). This chronology indicates that Telata glacier retreated irregularly. A rapid and strong melting from the maximum extent occurred from 10.8 ± 0.9 to 8.5 ± 0.4 kyr ago, followed by a slower retreat until the Little Ice Age, about 200 years ago. A dramatic increase in the rate of retreat occurred over the twentieth century. A glacier–climate model indicates that, relative to modern climate, annual mean temperature for the Telata glacier region was −3.3 ± 0.8 °C cooler at 11 kyr ago and remained −2.1 ± 0.8 °C cooler until the end of the Little Ice Age. We suggest that long-term warming of the eastern tropical Pacific and increased atmospheric temperature in response to enhanced austral summer insolation were the main drivers for the long-term Holocene retreat of glaciers in the southern tropics.

Past Climate Variability in South America and Surrounding Regions

derstand permafrost dynamics and the relationship with atmospheric methane concentrations over longer timescales. It is clear from paleorecords that peatland permafrost has expanded and contracted over the Holocene at differenttimes in differentplaces (e.g., Vardy et al., 2005; Oksanen, 2006). Although the impacts of Holocene peatland expansion on atmo-spheric methane are now being explored (Smith et al., 2004; Korhola et al., 2010; Beilman et al., this issue), the implications of Holocene permafrost variability on past global methane concentrations have not yet been assessed. The sparse data on contemporary methane emissions show that peatlands with and without perma-frost differsignificantly in their function-ing. More continuous measurements are required to document ongoing changes. Modern process models of carbon dy-namics linked to paleoreconstructions of permafrost could produce critical insights into Walter, K.M., Edwards, M.E., Grosse, G., Zimov, S.A. and Chapin, F.S., long-term role and functioning of northern peatlands in the global carbon cycle.

Reconstruction of the South Atlantic Subtropical Dipole index for the past 12,000 years from surface temperature proxy

Climate indices based on sea surface temperature (SST) can synthesize information related to physical processes that describe change and variability in continental precipitation from floods to droughts. The South Atlantic Subtropical Dipole index (SASD) is based on the distribution of SST in the South Atlantic and fits these criteria. It represents the dominant mode of variability of SST in the South Atlantic, which is modulated by changes in the position and intensity of the South Atlantic Subtropical High. Here we reconstructed an index of the South Atlantic Ocean SST (SASD-like) for the past twelve thousand years (the Holocene period) based on proxy-data. This has great scientific implications and important socio-economic ramifications because of its ability to infer variability of precipitation and moisture over South America where past climate data is limited. For the first time a reconstructed index based on proxy data on opposite sides of the SASD-like mode is able to capture, in the South Atlantic, the significant cold events in the Northern Hemisphere at 12.9−11.6 kyr BP and 8.6−8.0 ky BP. These events are related, using a transient model simulation, to precipitation changes over South America.

Coupling statistically downscaled GCM outputs with a basin-lake hydrological model in subtropical South America: evaluation of the influence of large-scale precipitation changes on regional hydroclimate variability

We explore the reliability of large-scale climate variables, namely precipitation and temperature, as inputs for a basin-lake hydrological model in central Argentina. We used data from two regions in NCEP/NCAR reanalyses and three regions from LMDZ model simulations forced with observed sea surface temperature (HadISST) for the last 50 years. Reanalyses data cover part of the geographical area of the Sali-Dulce Basin (region A) and a zone at lower latitudes (region B). The LMDZ selected regions represent the geographical area of the Sali-Dulce Basin (box A), and two areas outside of the basin at lower latitudes (boxes B and C). A statistical downscaling method is used to connect the large-scale climate variables inferred from LMDZ and the reanalyses, with the hydrological Soil Water Assessment Tool (SWAT) model in order to simulate the Rio Sali-Dulce discharge during 1950-2005. The SWAT simulations are then used to force the water balance of Laguna Mar Chiquita, which experienced an abrupt level rise in the 1970s attributed to the increase in Rio Sali-Dulce discharge. Despite that the lowstand in the 1970s is not well reproduced in either simulation, the key hydrological cycles in the lake level are accurately captured. Even though satisfying results are obtained with the SWAT simulations using downscaled reanalyses, the lake level are more realistically simulated with the SWAT simulations using downscaled LMDZ data in boxes B and C, showing a strong climate influence from the tropics on lake level fluctuations. Our results highlight the ability of downscaled climatic data to reproduce regional climate features. Laguna Mar Chiquita can therefore be considered as an integrator of large-scale climate changes since the forcing scenarios giving best results are those relying on global climate simulations forced with observed sea surface temperature. This climate-basin-lake model is a promising approach for understanding and simulating long-term lake level variations.