Claudio G. Menéndez

CLARIS Project : towards climate downscaling in South America

We explore the bias in monthly and seasonal mean precipitation simulated by ensembles of different regional climate models over South America within the context of the EU-FP6 CLARIS project (A Europe-South America Network for Climate Change Assessment and Impact Studies). We briefly described two series of coordinated simulations: (i) Case studies of anomalous months for south-eastern South America performed with an ensemble of six models, and (ii) A multiyear simulation of the period 1991―2000 performed by four models. The models have been forced with the European Centre for Medium Range Weather Forecasting Reanalysis (ERA-40) and are compared to observational data compiled by the Climatic Research Unit (CRU). The ensemble-mean bias can be large when simulating particular extreme periods in La Plata Basin. Our multi-model analysis suggests that even though the ten-year ensemble mean is able to capture the major regional characteristics of seasonal mean precipitation for South America, models individually display considerable precipitation biases especially in tropical areas. The relatively good performance of the multi-model annual average over La Plata Basin results from the cancelation of offsetting errors in the individual models.

Performance of a multi-RCM ensemble for South Eastern South America

The ability of four regional climate models to reproduce the present-day South American climate is examined with emphasis on La Plata Basin. Models were integrated for the period 1991–2000 with initial and lateral boundary conditions from ERA-40 Reanalysis. The ensemble sea level pressure, maximum and minimum temperatures and precipitation are evaluated in terms of seasonal means and extreme indices based on a percentile approach. Dispersion among the individual models and uncertainties when comparing the ensemble mean with different climatologies are also discussed. The ensemble mean is warmer than the observations in South Eastern South America (SESA), especially for minimum winter temperatures with errors increasing in magnitude towards the tails of the distributions. The ensemble mean reproduces the broad spatial pattern of precipitation, but overestimates the convective precipitation in the tropics and the orographic precipitation along the Andes and over the Brazilian Highlands, and underestimates the precipitation near the monsoon core region. The models overestimate the number of wet days and underestimate the daily intensity of rainfall for both seasons suggesting a premature triggering of convection. The skill of models to simulate the intensity of convective precipitation in summer in SESA and the variability associated with heavy precipitation events (the upper quartile daily precipitation) is far from satisfactory. Owing to the sparseness of the observing network, ensemble and observations uncertainties in seasonal means are comparable for some regions and seasons.

Climate change scenarios over the South American region: an intercomparison of coupled general atmosphere-ocean circulation models

Results of four different coupled atmosphere-ocean general circulation model runs for South America and surrounding oceans are examined. The mean response of the simulated climate system to a gradual increase of greenhouse gases is presented. The transient coupled experiment data provided for the Intergovernmental Panel on Climate Change (IPCC) were the most recent available to us at the time of this study, from the following research centres in Europe and USA: the UK Meteorological Office (UKMO), the Max-Planck Institute for Meteorology (MPI), the Geophysical Fluid Dynamic Laboratory (GFDL) and the National Center for Atmospheric Research (NCAR). The regional performance of the control simulations (with fixed CO2 concentration) is determined by comparing sealevel pressure, near-surface zonal wind, precipitation and surface air temperature from the models, against observed climatological fields. The response of the climate system to the enhanced emission scenarios is established comparing the control experiments with the respective transient experiments around the time of doubling CO2. To assist in estimating likely future climate change in the South American region, only the results of those model experiments with the best control simulation of current climate in the region are considered: the UKMO and MPI models. A maximum warming over the continent and a minimum warming in the extratropical oceans, a slight intensification and southward migration of the subtropical ridge, a deepening of the sub-Antarctic trough, an intensification of the westerly winds, and increasing precipitation in the tropics and in the mid-latitude oceans are the most important potential changes simulated by both models for the increased CO2 scenarios. # 1997 Royal Meteorological Society. Int. J. Climatol., Vol. 17, 1613‐1633

Summer soil–precipitation coupling in South America

The soil moisture memory contributes to atmospheric variability and seasonal predictability and could potentially affect the development of the South American Monsoon System. The relative importance of the local land surface feedbacks and the large-scale dynamical processes during the different phases of the monsoon are still largely unknown. We examine the impacts of land surface conditions during the mature monsoon phase with the Rossby Centre Atmospheric regional model through calculating the coupling strength between soil moisture, evapotranspiration and precipitation. Regions of high coupling strength (hotspots) are identified and analysed focusing on the link between soil moisture–evapotranspiration coupling and soil moisture–precipitation coupling, the relation between the coupling strength and seasonal predictability and the hotspots importance for extreme precipitation events. La Plata Basin and northeastern Brazil are identified as hotspots due to evapotranspiration recycling. A region within the South Atlantic Convergence Zone is identified as a hotspot of precipitation explained by moisture advection. Extreme precipitation events are repressed in parts of La Plata Basin when the link between precipitation and soil moisture is cut through using prescribed soil moisture.

Projected precipitation changes in South America: a dynamical downscaling within CLARIS

Responses of precipitation seasonal means and extremes over South America in a downscaling of a Climate change scenario are assessed with the Rossby Centre Regional Atmospheric Model (RCA). The anthropogenic warming under A1B scenario influences more on the likelihood of occurrence of severe extreme events like heavy precipitation and dry spells than on the mean seasonal precipitation. The risk of extreme precipitation increases in the La Plata Basin with a factor of 1.5-2.5 during all seasons and in the northwestern part of the continent with a factor 1.5-3 in summer, while it decreases in central and northeastern Brazil during winter and spring. The maximum amount of 5-days precipitation increases by up to 50% in La Plata Basin, indicating risks of flooding. Over central Brazil and the Bolivian lowland, where present 5-days precipitation is higher, the increases are similar in magnitude and could cause less impacts. In southern Amazonia, northeastern Brazil and the Amazon basin, the maximum number of consecutive dry days increases and mean winter and spring precipitation decreases, indicating a longer dry season. In the La Plata Basin, there is no clear pattern of change for the dry spell duration.

La Plata basin precipitation variability in spring: role of remote SST forcing as simulated by GCM experiments

An ensemble of nine experiments with the same interannually varying sea surface temperature (SST), as boundary forcing, and different initial conditions is used to investigate the role of tropical oceans in modulating precipitation variability in the region of La Plata Basin (LPB). The results from the ensemble are compared with a twentieth-century experiment performed with a coupled ocean-atmosphere model, sharing the same atmospheric component. A rotated empirical orthogonal functions analysis of South America precipitation shows that the dominant mode of variability in spring is realistically captured in both experiments. Its principal component (RPC1) correlated with global SST and atmospheric fields identifies the pattern related to El Niño Southern Oscillation and its large-scale teleconnections. Overall the pattern is well simulated in the tropical southern Pacific Ocean, mainly in the ensemble, but it is absent or too weak in other oceanic areas. The coupled model experiment shows a more realistic correlation in the subtropical South Atlantic where air-sea interactions contribute to the relationship between LPB precipitation and SST. The correspondence between model and data is much improved when the composite analysis of SST and atmospheric fields is done over the ensemble members having an RPC1 in agreement with the observations: the improvement relies on avoiding climate noise by averaging only over members that are statistically similar. Furthermore, the result suggests the presence of a high level of uncertainty due to internal atmospheric variability. The analysis of some individual years selected from the model and data RPC1 comparison reveals interesting differences among rainy springs in LPB. For example, 1982, which corresponds to a strong El Niño year, represents a clean case with a distinct wave train propagating from the central Pacific and merging with another one from the eastern tropical south Indian Ocean. The year 2003 is an example of a rainy spring in LPB not directly driven by remote SST forcing. In this case the internal variability has a dominant role, as the model is not able to reproduce the correct local precipitation pattern.

Future hydroclimatological changes in South America based on an ensemble of regional climate models

Changes between two time slices (1961–1990 and 2071–2100) in hydroclimatological conditions for South America have been examined using an ensemble of regional climate models. Annual mean precipitation (P), evapotranspiration (E) and potential evapotranspiration (EP) are jointly considered through the balances of land water and energy. Drying or wetting conditions, associated with changes in land water availability and atmospheric demand, are analysed in the Budyko space. The water supply limit (E limited by P) is exceeded at about 2% of the grid points, while the energy limit to evapotranspiration (E = EP) is overall valid. Most of the continent, except for the southeast and some coastal areas, presents a shift toward drier conditions related to a decrease in water availability (the evaporation rate E/P increases) and, mostly over much of Brazil, to an increase in the aridity index (Ф = EP/P). These changes suggest less humid conditions with decreasing surface runoff over Amazonia and the Brazilian Highlands. In contrast, Argentina and the coasts of Ecuador and Peru are characterized by a tendency toward wetter conditions associated with an increase of water availability and a decrease of aridity index, primarily due to P increasing faster than both E and EP. This trend towards wetter soil conditions suggest that the chances of having larger periods of flooding and enhanced river discharges would increase over parts of southeastern South America. Interannual variability increases with Ф (for a given time slice) and with climate change (for a given aridity regimen). There are opposite interannual variability responses to the cliamte change in Argentina and Brazil by which the variability increases over the Brazilian Highlands and decreases in central-eastern Argentina.

Assessment of CORDEX simulations over South America: added value on seasonal climatology and resolution considerations

A new set of CORDEX simulations over South America, together with their coarser-resolution driving Global Climate Models (GCMs) are used to investigate added value of Regional Climate Models (RCMs) in reproducing mean climate conditions over the continent. There are two types of simulations with different lateral boundary conditions: five hindcast simulations use re-analysis as boundary conditions, and five other historical simulations use GCMs outputs. Multi-model ensemble means and individual simulations are evaluated against two or three observation-based gridded datasets for 2-m surface air temperature and total precipitation. The analysis is performed for summer and winter, over a common period from 1990 to 2004. Results indicate that added value of RCMs is dependent on driving fields, surface properties of the area, season and variable considered. A robust added value for RCMs driven by ERA-Interim is obtained in reproducing the summer climatology of surface air temperature over tropical and subtropical latitudes. Mixed results can be seen, however, for summer precipitation climatology in both hindcast and historical experiments. For winter, there is no noticeable improvement by the RCMs for the large-scale precipitation and surface air temperature climatology. To further understand the added value of RCMs, models deviations from observation are decomposed according to different terms that reflect the observational uncertainty, the representativeness error, the interpolation error, and the actual performance of the model. Regions where these errors are not negligible, such as in complex terrain regions, among others, can be identified. There is a clear need for complementary assessment to understand better the real value added by RCMs.

Are we Observing Mountain Waves Above the Andes Range from GPS Occultation Profiles

GPS radio occultation temperature profiles retrieved from SAC-C and CHAMP exhibit a significant wave activity in the troposphere and lower stratosphere at midlatitudes (30°S to 40°S) above the Andes Range. Large amplitude structures, with long vertical wavelength, have been repeatedly reported in this region, as detected from other experimental devices and attributed to mountain waves. The possibility to associate the observed enhancements in wave activity to mountain forcing, or instead, to other significant sources in the region considered is discussed. The generation in the vicinity to a permanent jet situated above the mountains of inertio gravity waves by geostrophic adjustment, with longer horizontal and perhaps shorter vertical wavelengths than those expected from mountain waves, seems to be the main source. These waves could be more easily detected from GPS profiles than mountain waves. As it is known, inertio gravity waves are the means by which mass and momentum are redistributed so as to ultimately achieve geostrophic balance from an initially unbalanced state.

Assessment of a Regional Climate Change Scenario for Central Argentina: A Statistical Downscaling Approach

With the purpose of assessing the vulnerability of crop production in Argentina related to the impact of global warming, we estimated local changes of monthly mean precipitation for summer and winter months caused by CO2 doubling, at selected stations lying in central Argentina. A statistical downscaling approach was developed by means of empirical relationships between large-scale climatic variables from the NCEP re-analyses data set and local scale precipitation data. The method was tested against an independent set of observed data and subsequently applied to the Max Plank Institute (MPI) GCM control run. Despite the simplicity of the statistical approach developed, it was able to satisfactorily reproduce the spatial patterns of the regional precipitation field. The response of the climate system to the enhanced emission scenario simulated by the MPI model was used to infer the local climate change. A precipitation decrease over the region of interest is simulated by the MPI model for the increased CO2 scenario. Accordingly, with the GCM potential changes, the local precipitation decrease is higher in summer than in winter. This result has an important consequence for the rainfall regime over the region, namely that a higher decrease of rainfall is projected for the rainy season while a weaker decrease is projected for the dry season. Regional scenarios of climate change, including both rainfall and extreme temperatures were then used to assess the impact of climate change on crops (wheat, maize, sunflower and soybean) and pastures production in the Pampas region in order to evaluate the vulnerability of the system to global warming.