6. Discussion and conclusionThe projected warming in South America is more pronounced along the eastern Amazon basin, relatively close to the mouth of the Amazon river, where a temperature increase of more than 7ºC is projected in the A2 scenario. Warming is more widespread during JJA than DJF, and the simulated warming in the Andes fluctuates between 2ºC and 7ºC, being especially high in the Cordillera Blanca and the Altiplano region. When comparing A2 and B2 projections, it is apparent that mainly the magnitude changes, with up to approximately 3ºC warmer temperature in A2, but the spatial pattern is very similar. In the A2 scenario no grid cells with temperature below freezing remain during DJF, indicative of the significant rise of the freezing levels. This rise has significant ramifications for glacier mass balance as the tropical glacier equilibrium line altitude (ELA) is closely tied to the 0°C isotherm.Predicted changes in precipitation indicate an overall decrease in northeastern South America, following a similar pattern as the observed increase in temperature in that area. This is consistent with the observed changes in relative humidity (RH), which also closely follow the pattern observed for temperature. Clearly changes in relative humidity reflect a temperature increase, rather than changes in specific humidity, indicating that changes in specific humidity are insufficient to keep relative humidity constant under strong warming scenarios. Precipitation changes in the Andes, do not present a clear pattern, but the Monsoon System appears to be stronger in the future with increased summer precipitation and an enhanced seasonality in the South American outer tropics.The PDFs indicate a stronger warming along the eastern slopes of the Andes, although temperature remains higher on the western slopes. Changes in the standard deviation are also larger on the eastern slopes. The annual mean projected temperature is about 1ºC higher in A2 than in B2 for both slopes. The standard deviation changes little in the B2 scenario, while A2 shows a pronounced change with a significant increase in year-to-year temperature variability.Changes in free tropospheric temperature indicate an increased warming with altitude for both scenarios, but less pronounced in the B2, consistent with results based on IPCC AR4 GCMs (Bradley et al., 2006)Changes in zonal and vertical wind indicate a strengthening of the westerly component and a weakening of the easterly upper-level flow, which would suggest drier conditions in the Altiplano at the end of the 21st century (Garreaud et al., 2003).In summary, these results reveal that predicted climate change is characterized by a general increase in surface and free tropospheric temperature, a decrease in relative humidity and, in the case of the Altiplano, a decrease in precipitation, all of which will adversely affect the glacier mass and energy balance of the remaining tropical glaciers along the Andes Cordillera.

GC41A-0110

Assessment of 21st Century Climate Change Projections in the Tropical AndesRocio Urrutia & Mathias Vuille

rurrutia@geo.umass.edu, mathias@geo.umass.eduClimate System Research Center, Department of Geosciences,University of Massachusetts Amherst, 611 North Pleasant Street, Amherst, MA

01003-9297, United States

1.IntroductionThe tropical Andes are one of the regions where recent climate change has been most evident (Vuille et al., submitted). This is consistent with the notion that high-elevation tropical mountains, extending to the mid-troposphere, will be more affected by warming (Bradley et al., 2006). One of the main impacts of this warming in the Andes is the retreat of glaciers, a process that may affect the availability of water for human consumption, irrigation, mining and power generation (Vergara et al., 2007).Climate models are an important tool to determine future changes and potential impacts of climate change. Since general circulation models (GCM) make projections at a relatively coarse resolution, they do not adequately capture the regional-scale changes, and they are not very well suited in regions with complex topography or diverse land cover (Jones et al., 2004; Solman et al., 2007). Regional climate models (RCM) on the other hand are comprehensive physical models that frequently incorporate atmosphere and land surface components, and the representation of important processes within the climate system (Jones et al., 2004). These models have the ability of solving meso-scale features that are not evident in global models, and are especially useful in places with complex topography, such as the Andes.

2. ObjectivesThe main objective of this study is to provide an assessment of predicted changes in climate in tropical South America and especially in the Andes region, by comparing output from a regional climate model (PRECIS) from the end of the 21st century (2071-2100) with a control run from the end of the 20th century (1961-1990).This simulation provides a baseline for estimating future climate change impacts in a medium-high (A2) emission scenario. In addition, mainly for temperature change assessments, a medium-low (B2) scenario is also considered for comparison.

3. Methods3.1 Study areaThe study area corresponds to tropical South America between approximately13º N-30º S and 89º W-41º W (Figure 1). This corresponds to the completeRCM domain, but after removing the grid cells where adjustments

between the GCM and the regional model take place, the actual study areais reduced to approximately 10º N-27º S and 86º W-44º W. The analysishas been mainly focused on the Andes region to detect and assess climaticchanges that could potentially have an impact on tropical glaciers in that area.

Figure 1. Study area3.2 Climate model In this study the Hadley Centre Regional Climate Modeling System, called PRECIS, was used to assess changes in climate between today and the end of the 21st century. The model was run in 0.44º lat. x 0.44º lon. (~50 x 50 km) resolution. Three simulations are analyzed here. The first simulation (RCM 61-90) involves a thirty year (1961-1990) period that serves as a control run and provides the base-line for comparison with the projected greenhouse gas emission scenarios. The second simulation (RCM SRES-A2) is based on a medium-high emission and high population-growth scenario run for the 2071-2100 period. In the third simulation (RCM SRES- B2), the projected greenhouse scenario corresponds to a lower emission and population growth, and it is also a run for the 2071-2100 period.

4. AnalysesOur analyses concentrate on variables known to affect glacier energy and mass balance. Analyses on surface variables focused on determining the differences between the A2 and control run in terms of temperature, precipitation and relative humidity. Dynamic analyses of monsoon behavior were investigated by means of time-latitude diagrams (Hovermuller diagrams). Probability Density Functions of mean annual temperature were established for all scenarios along the eastern and western slopes of the Andes to assess changes in the width and amplitude of the distribution. Latitudinal transects of free tropospheric temperature changes were developed for both A2 and B2 scenarios. Of special relevance for climate and precipitation in the Andes is the upper-tropospheric zonal flow aloft (Garreaud et al., 2003). This study therefore also includes an analysis of changes in zonal wind and vertical velocity along a latitudinal cross-section from the Pacific to the Amazon basin across the central Andes.

Figure 4. a) Difference in mean annual temperature between the A2 and control scenario. b) As in a), but for B2 scenario.

Figure 2.a) Difference in mean annual temperature for 30 years between A2 and control scenario. b) As in a), but for austral summer temperature (DJF) c) As in a), but for austral winter temperature (JJA).

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Figure 3.Difference in mean annual temperature between the A2 and control scenario for the Andes region.

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82,50055,000285,000JJA5,000022,500DJF

10,0005,00095,000AnnualB2A2Control

Table 1. Area in km2 with temperature below 0ºC

5.2 Predicted changes in surface precipitation and relative humidity

Figure 5. a) Absolute difference (in mm) in mean annual precipitation for 30 years between A2 and control scenario, b) Map indicating significant changes between the two scenarios. Areas in dark red are significantly different with 95% confidence c) As in a), but for relative difference (in percentage).

Figure 7. a) Changes in mean annual relative humidity between the A2 and control run for the 30 year period (in percent) b) Map indicating significant differences between the two scenarios. Areas in dark red are significantly different with 95% confidence.

Figure 6. a) Time-latitude diagram of the seasonal cycle of precipitation (in mm/day) averaged over longitude 50º-70ºW for the control scenario b) As in a), but for the A2 scenario.

b)a)

Figure 8. a) PDF of mean annual temperature for the control (blue line) and A2 (red line) scenario, considering grid cells >100 m along the western slope of the Andes. b) As in a) but for control and B2 scenario. c) As in a) but considering only grid cells >400 m, and for the eastern slope of the Andes. d) as in c) but for control and B2 scenario. In all cases black bars represent the individual years for each distribution.

5.4 Predicted changes in free tropospheric temperature

Figure 9. a) Difference in annual mean free tropospheric temperature between the A2 and control scenario. b) as in a) but for difference between the B2 and control scenario.

5.5 Predicted changes in zonal and vertical winds for summer in a longitudinal transect at 16º S

a)

Figure 10. a) Pressure-longitude cross section of zonal and vertical winds at 16ºS for DJF in the control scenario. b) as in a) but for the A2 scenario. c).as in a) but for difference between the A2 and control scenarios.

7. ReferencesBradley, R.S., Vuille, M., Diaz, H.F., & Vergara, W. 2006. Threats to water supplies in the Tropical Andes. Science 312, 5781: 1755-1756.Garreaud, R., Vuille, M., & Clement, A. 2003. The climate of the Altiplano: Observed current conditions and mechanisms of past changes. Palaeogeography, Palaeoclimatology, Palaeoecology 194: 5-22. Jones, R.G., M. Noguer, D. Hassell, D. Hudson, S. Wilson, G. Jenkins & J. Mitchell. 2004. Generating high resolution climate change scenarios using PRECIS. Met Office Hadley Centre, Exeter, UK. 40 pp. April 2004.Solman, S., Nunez, M., & Cabre, M. Regional climate change experiments over southern South America I: present climate. Climate dynamics doi 10.1007/s00382-007-0304-3.Vergara, W, Deeb, A., Valencia, A., Bradley, R., Francou, B., Zarzar, A., Grünwaldt, A. & Haeussling, S. 2007. Economic impacts of rapid glacier retreat in the Andes. Eos, Transactions, American Geophysical Union 88: 25, 19 June 2007.Vuille, M., B. Francou, P. Wagnon, I. Juen, G. Kaser, B.G. Mark & R.S. Bradley, Climate change and tropical Andean glaciers – Past, present and future. Earth Science. Reviews., (submitted).8. AcknowledgementsThis study was funded by NSF (EAR-0519415 awarded to MV) and by a Fulbright Fellowship to RU.

5.3 Probability Density Functions (PDF) for temperature along the western and eastern slope of the Andes5. Results5.1 Predicted changes in surface temperature

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0.44288.60.72289.70.33285.5Eastern slope0.43291.40.73292.40.41288.5Western slopeσ (º)μ (º)σ (º)μ (º)σ (º)μ (º)

B2A2ControlTable 2. Average temperature (µ) and standard deviation (σ ) in each PDF for each scenario and slope of the Andes

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