This review summarizes the progress achieved on regional climate modeling activities over South America since the early efforts at the beginning of the 2000s until now. During the last 10 years, simulations with regional climate models (RCMs) have been performed for several purposes over the region. Early efforts were mainly focused on sensitivity studies to both physical mechanisms and technical aspects of RCMs. The last developments were focused mainly on providing high-resolution information on regional climate change. This paper describes the most outstanding contributions from the isolated efforts to the ongoing coordinated RCM activities in the framework of the CORDEX initiative, which represents a major endeavor to produce ensemble climate change projections at regional scales and allows exploring the associated range of uncertainties. The remaining challenges in modeling South American climate features are also discussed. 1. Introduction One of the main motivations for developing Regional Climate Models (RCMs) has been the need for producing climate information at the regional level to assess the impacts of climate change. It is a well-known fact that, to date, Atmosphere Ocean Global climate Models (AOGCMs) are the only tools available to predict the future evolution of the climate system in response to anthropogenic forcings, such as the increase in greenhouse gas (GHG) concentrations. During the last decades, coupled global models have been continuously improved, mostly due to the increasing computational capacity and the improved representation of different components of the climate system: the atmosphere, the oceans, and the land-surface. However, the most updated global models within the suit of the CMIP5 initiative [1] operate on horizontal resolutions of the order of hundreds of kilometers [2]. The lack of regional details in current AOGCMs limits their capability in capturing regional-scale processes forced by topographic features or other regional-scale forcings. These regional-scale forcings are responsible for modulating the large-scale circulation features that determine the regional climate. Moreover, coarse resolution also limits the applicability of global model outputs for impact studies that demand information on much finer spatial scales. Since the early 1990s, RCMs became the most widespread methodology to add further detail to global climate simulations. After the pioneering work by Giorgi and Mearns [3], the development of RCMs has led to increased resolution, longer model simulations, and developments towards regional
References
[1]
R. J. Stouffer, K. E. Taylor, and G. A. Meehl, “CMIP5 long-term experimental design,” CLIVAR Exchanges, vol. 16, no. 56, pp. 5–7, 2011.
[2]
K. E. Taylor, R. J. Stouffer, and G. A. Meehl, “An overview of CMIP5 and the experiment design,” Bulletin of the American Meteorological Society, vol. 93, pp. 485–498, 2012.
[3]
F. Giorgi and L. O. Mearns, “Approaches to the simulation of regional climate change: a review,” Reviews of Geophysics, vol. 29, no. 2, pp. 191–216, 1991.
[4]
F. Giorgi, C. Jones, and G. Asrar, “Addressing climate information needs at the regional level: the CORDEX framework,” World Meteorological Organization Buletin, vol. 58, no. 3, pp. 175–183, 2009.
[5]
C. Vera, W. Higgins, J. Amador et al., “Toward a unified view of the American monsoon systems,” Journal of Climate, vol. 19, no. 20, pp. 4977–5000, 2006.
[6]
R. D. Garreaud, M. Vuille, R. Compagnucci, and J. Marengo, “Pesent-day South American climate,” Palaeogeography Palaeoclimatology, Palaeoecology, vol. 281, no. 3-4, pp. 180–195, 2009.
[7]
J. P. Boulanger, S. Schlindwein, and E. Gentile, “CLARIS LPB WP1: metamorphosis of the CLARIS LPB European project: from a mechanistic to a systemic approach,” CLIVAR Exchanges, vol. 16, no. 57, pp. 7–10, 2011.
[8]
R. E. Dickinson, R. M. Errico, F. Giorgi, and G. T. Bates, “A regional climate model for the western United States,” Climatic Change, vol. 15, no. 3, pp. 383–422, 1989.
[9]
F. Giorgi, “On the simulation of regional climate using a limited area model nested in a general circulation model,” Journal of Climate, vol. 3, no. 9, pp. 941–963, 1990.
[10]
S. C. Chou, A. M. B. Nunes, and I. F. A. Cavalcanti, “Extended range forecasts over South America using regional eta model,” Journal of Geophysical Research, vol. 105, no. D8, pp. 147–110, 2000.
[11]
C. G. Menéndez, A. C. Saulo, and Z. X. Li, “Simulation of South American wintertime climate with a nesting system,” Climate Dynamics, vol. 17, pp. 219–231, 2001.
[12]
M. Nicolini, P. Salio, J. J. Katzfey, J. L. McGregor, and A. C. Saulo, “January and July regional climate simulation over South America,” Journal of Geophysical Research, vol. 107, no. D22, 2002.
[13]
P. Nobre, A. D. Moura, and L. Sun, “Dynamical downscaling of seasonal climate prediction over Nordeste Brazil with ECHAM3 and NCEP's regional spectral models at IRI,” Bulletin of the American Meteorological Society, vol. 82, no. 12, pp. 2787–2796, 2001.
[14]
V. Misra, P. A. Dirmeyer, B. P. Kirtman, H.-M. H. Juang, and M. Kanamitsu, “Regional simulation of interannual variability over South America,” Journal of Geophysical Research, vol. 107, no. D20, 2002.
[15]
V. Misra, P. A. Dirmeyer, and B. P. Kirtman, “Dynamic downscaling of seasonal simulations over South America,” Journal of Climate, vol. 16, no. 1, pp. 103–117, 2003.
[16]
V. Misra, P. A. Dirmeyer, and B. P. Kirtman, “A comparative study of two land surface schemes in regional climate integrations over South America,” Journal of Geophysical Research, vol. 107, no. D20, pp. 48–9, 2002.
[17]
A. Seth and M. Rojas, “Simulation and sensitivity in a nested modeling system for South America—part I: reanalysis boundary forcing,” Journal of Climate, vol. 16, pp. 2437–2453, 2003.
[18]
M. Rojas and A. Seth, “Simulation and sensitivity in a nested modeling system for South America—part II: GCM boundary forcing,” Journal of Climate, vol. 16, pp. 2454–2471, 2003.
[19]
A. Seth, M. Rojas, B. Liebmann, and J.-H. Qian, “Daily rainfall analysis for South America from a regional climate model and station observations,” Geophysical Research Letters, vol. 31, no. 7, Article ID L07213, 2004.
[20]
V. Misra and M. Kanamitsu, “Anomaly nesting: a methodology to downscale seasonal climate simulations from AGCMs,” Journal of Climate, vol. 17, no. 17, pp. 3249–3262, 2004.
[21]
M. Rojas, “Multiply nested regional climate simulation for southern South America: sensitivity to model resolution,” Monthly Weather Review, vol. 134, no. 8, pp. 2208–2223, 2006.
[22]
R. P. da Rocha, C. A. Morales, S. V. Cuadra, and T. Ambrizzi, “Precipitation diurnal cycle and summer climatology assessment over South America: an evaluation of Regional Climate Model version 3 simulations,” Journal of Geophysical Research, vol. 114, no. D10, Article ID D10108, pp. 1–19, 2009.
[23]
S. A. Solman and N. L. Pessacg, “Regional climate simulations over South America: sensitivity to model physics and to the treatment of lateral boundary conditions using the MM5 model,” Climate Dynamics, vol. 38, no. 1-2, pp. 281–300, 2012.
[24]
J. P. R. Fernandez, S. H. Franchito, and V. B. Rao, “Simulation of the summer circulation over South America by two regional climate models—part I: mean climatology,” Theoretical and Applied Climatology, vol. 86, no. 1–4, pp. 247–260, 2006.
[25]
F. Giorgi, X. Bi, and J. S. Pal, “Mean, interannual variability and trends in a regional climate change experiment over Europe. I. Present-day climate (1961–1990),” Climate Dynamics, vol. 22, no. 6-7, pp. 733–756, 2004.
[26]
L. R. Leung, Y. Qian, and X. Bian, “Hydroclimate of the western United States based on observations and regional climate simulation of 1981–2000—part I: seasonal statistics,” Journal of Climate, vol. 16, pp. 1892–1911, 2003.
[27]
X. Z. Liang, L. Li, and K. Kunkel, “Regional climate model simulation of US precipitation during 1982–2002—part I: annual cycle,” Journal of Climate, vol. 17, pp. 3510–3528, 2004.
[28]
F. Giorgi, X. Bi, and J. Pal, “Mean, interannual variability and trends in a regional climate change experiment over Europe. II: climate change scenarios (2071–2100),” Climate Dynamics, vol. 23, no. 7-8, pp. 839–858, 2004.
[29]
J. R？is？nen, M. Rummukainen, and A. Ullerstig, “Downscaling of greenhouse gas induced climate change in two GCMs with the Rossby Centre regional climate model for Northern Europe,” Tellus A, vol. 53, no. 2, pp. 168–191, 2001.
[30]
A. Seth, S. A. Rauscher, S. J. Camargo, J.-H. Qian, and J. S. Pal, “RegCM3 regional climatologies for South America using reanalysis and ECHAM global model driving fields,” Climate Dynamics, vol. 28, no. 5, pp. 461–480, 2007.
[31]
S. A. Rauscher, A. Seth, B. Liebmann, J.-H. Qian, and S. J. Camargo, “Regional climate model-simulated timing and character of seasonal rains in South America,” Monthly Weather Review, vol. 135, no. 7, pp. 2642–2657, 2007.
[32]
S. A. Solman, M. N. Nu？ez, and M. F. Cabré, “Regional climate change experiments over southern South America. I: present climate,” Climate Dynamics, vol. 30, no. 5, pp. 533–552, 2008.
[33]
M. S. Reboita, R. P. da Rocha, T. Ambrizzi, and S. Sugahara, “South Atlantic Ocean cyclogenesis climatology simulated by regional climate model (RegCM3),” Climate Dynamics, vol. 35, no. 7, pp. 1331–1347, 2010.
[34]
M. S. Reboita, R. P. da Rocha, T. Ambrizzi, and E. Caetano, “An assessment of the latent and sensible heat flux on the simulated regional climate over Southwestern South Atlantic Ocean,” Climate Dynamics, vol. 34, no. 6, pp. 873–889, 2010.
[35]
G. Silvestri, C. Vera, D. Jacob, S. Pfeifer, and C. Teichmann, “A high-resolution 43-year atmospheric hindcast for South America generated with the MPI regional model,” Climate Dynamics, vol. 32, no. 5, pp. 693–709, 2009.
[36]
J. F. Pesquero, S. C. Chou, C. A. Nobre, and J. A. Marengo, “Climate downscaling over South America for 1961–1970 using the Eta Model,” Theoretical and Applied Climatology, vol. 99, no. 1-2, pp. 75–93, 2010.
[37]
M. Nu？ez, S. A. Solman, and M. F. Cabré, “Regional climate change experiments over southern South America. II: climate change scenarios in the late twenty-first century,” Climate Dynamics, vol. 32, no. 7-8, pp. 1081–1095, 2009.
[38]
R. D. Garreaud and M. Falvey, “The coastal winds off western subtropical South America in future climate scenarios,” International Journal of Climatology, vol. 29, no. 4, pp. 543–554, 2009.
[39]
J. A. Marengo, R. Jones, L. M. Alves, and M. C. Valverde, “Future change of temperature and precipitation extremes in south america as derived from the precis regional climate modeling system,” International Journal of Climatology, vol. 29, no. 15, pp. 2241–2255, 2009.
[40]
J. A. Marengo, S. C. Chou, G. Kay et al., “Development of regional future climate change scenarios in South America using the Eta CPTEC/HadCM3 climate change projections: climatology and regional analyses for the Amazon, S？o Francisco and the Paraná River basins,” Climate Dynamics, vol. 38, no. 9-10, pp. 1829–1848, 2012.
[41]
R. Urrutia and M. Vuille, “Climate change projections for the tropical Andes using a regional climate model: temperature and precipitation simulations for the end of the 21st century,” Journal of Geophysical Research, vol. 114, no. D2, Article ID D02108, 2009.
[42]
A. A. S？rensson, C. G. Menéndez, R. Ruscica, P. Alexander, P. Samuelsson, and U. Willén, “Projected precipitation changes in South America: a dynamical downscaling within CLARIS,” Meteorologische Zeitschrift, vol. 19, no. 4, pp. 347–355, 2010.
[43]
R. Laprise, D. Kornic, M. Rapaic et al., “Considerations of domain size and large-scale driving for nested Regional Climate Models: impact on internal variability and skill at developing small-scale details,” in Climate Change: Inferences from Paleoclimate and Regional Aspects, Proceedings of the Milutin Milankovitch 130th Anniversary Symposium, A. Berger, F. Mesinger, and Dj. Sijacki, Eds., part 4, pp. 181–199, Springer, 2009.
[44]
S. A. Rauscher, A. Seth, J.-H. Qian, and S. J. Camargo, “Domain choice in an experimental nested modeling prediction system for South America,” Theoretical and Applied Climatology, vol. 86, no. 1–4, pp. 229–246, 2006.
[45]
J. H. Christensen, B. Hewitson, A. Busuioc et al., “Regional climate projections,” in Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, S. Solomon, D. Qin, M. Manning et al., Eds., pp. 847–940, Cambridge University Press, Cambridge, UK, 2007.
[46]
C. Vera, G. Silvestri, B. Liebmann, and P. González, “Climate change scenarios for seasonal precipitation in South America from IPCC-AR4 models,” Geophysical Research Letters, vol. 33, no. 13, Article ID L13707, 2006.
[47]
M. Déqué, D. P. Rowell, D. Lüthi et al., “An intercomparison of regional climate simulations for Europe: assessing uncertainties in model projections,” Climatic Change, vol. 81, no. 1, pp. 53–70, 2007.
[48]
S. A. Solman and N. L. Pessacg, “Evaluating uncertainties in regional climate simulations over South America at the seasonal scale,” Climate Dynamics, vol. 39, no. 1, pp. 59–76, 2012.
[49]
S. V. Cuadra and R. P. da Rocha, “Sensitivity of regional climatic simulation over Southeastern South America to SST specification during austral summer,” International Journal of Climatology, vol. 27, no. 6, pp. 793–804, 2007.
[50]
J. H. Christensen, T. R. Carter, M. Rummukainen, and G. Amanatidis, “Evaluating the performance and utility of regional climate models: the PRUDENCE project,” Climatic Change, vol. 81, no. 1, pp. 1–6, 2007.
[51]
C. D. Hewitt, “The ENSEMBLES project: providing ensemble based predictions of climate changes and their impacts,” EGGS Newsletter, vol. 13, pp. 22–25, 2005.
[52]
L. Mearns, W. J. Gutowski, R. Jones et al., “A regional climate change assessment program for North America,” EOS Transactions American Geophysical Union, vol. 90, no. 36, pp. 311–312, 2009.
[53]
J.-P. Boulanger, G. Brasseur, A. F. Carril et al., “A Europe-South America network for climate change assessment and impact studies,” Climatic Change, vol. 98, no. 3, pp. 307–329, 2010.
[54]
C. G. Menéndez, M. de Castro, J.-P. Boulanger et al., “Downscaling extreme month-long anomalies in southern South America,” Climatic Change, vol. 98, no. 3, pp. 379–403, 2010.
[55]
A. Carril, C. Menéndez, A. Remedio et al., “Assessment of a multi-RCM ensemble for South Eastern South America,” Climate Dynamics, vol. 39, pp. 2747–2768, 2012.
[56]
J. A. Marengo and T. Ambrizzi, “Use of regional climate models in impacts assessments and adaptations studies from continental to regional and local scales: the CREAS (Regional Climate Change Scenarios for South America) initiative in South America,” in Proceedings of the 8th International Conference on Southern Hemisphere Meteorology and Oceanography (ICSHMO '06), pp. 291–296, 2006.
[57]
J. A. Marengo, T. Ambrizzi, R. P. da Rocha et al., “Future change of climate in South America in the late twenty-first century: intercomparison of scenarios from three regional climate models,” Climate Dynamics, vol. 35, no. 6, pp. 1089–1113, 2010.
[58]
S. C. Chou, J. A. Marengo, A. A. Lyra et al., “Downscaling of South America present climate driven by 4-member HadCM3 runs,” Climate Dynamics, vol. 38, no. 3-4, pp. 635–653, 2012.
[59]
S. Uppala, D. Dee, S. Kobayashi, P. Berrisford, and A. Simmons, “Towards a climate adapt assimilation system: status update of ERAInterim,” ECMWF Newsletter, vol. 115, pp. 12–18, 2008.
[60]
S. Solman, E. Sanchez, P. Samuelsson et al., “Evaluation of an ensemble of regional climate model simulations over South America driven by the ERA-Interim reanalysis: model performance and uncertainties,” Climate Dynamics, 2013.
[61]
S. A. Rauscher, E. Coppola, C. Piani, and F. Giorgi, “Resolution effects on regional climate model simulations of seasonal precipitation over Europe,” Climate Dynamics, vol. 35, no. 4, pp. 685–711, 2010.
[62]
B. Tencer, M. Rusticucci, P. Jones, and D. Lister, “A southeastern south american daily gridded dataset of observed surface minimum and maximum temperature for 1961–2000,” Bulletin of the American Meteorological Society, vol. 92, no. 10, pp. 1339–1346, 2011.
