Understanding regional climate variability is necessary in order to assess the impacts of climate change. Until recently, the best methods for evaluating regional climate variability were via observation networks and coarse-gridded reanalysis datasets. However, the recent development of high-resolution reanalysis datasets offers an opportunity to better evaluate the climatologically diverse continent of South America. This study compares NCEP’s CFS reanalysis dataset with NCEP’s coarser-resolution reanalysis II dataset to determine if CFS reanalysis improves our ability to represent the regional climate of South America. Our results show several regional differences between the CFSR and Re2 data, especially in areas of large topographical gradients. A comparison with the University of Delaware and TRMM precipitation datasets lends credence to some of these differences, such as heavier precipitation associated with anomalous 925？hPa westerlies over northwestern Peru and Ecuador during El Ni？o. However, our results also stress that caution is advised when using reanalysis data to assess regional climate variability, especially in areas of large topographical gradient such as the Andes. Our results establish a baseline to better study climate change, especially given the release of IPCC AR5 model simulations. 1. Introduction Representing summer climatology in South America is complicated by the diversity of its topographical features. As noted by Garreaud et al. [1], the Andes act as a climatological barrier separating arid conditions to the west in the Peru-Bolivian Atacama Desert from wet conditions to the east in the Amazon Basin. The aridity in the Atacama Desert is related to the position of the southeastern Pacific subtropical high, which causes large-scale subsidence [2, 3]. The ability of the Andes to block tropospheric flow also results in a rain shadow in the Altiplano [4]. The precipitation that does occur in the area is confined mostly to austral summer (DJF) and is driven by diurnal convection and the westward transport of moisture from the interior of the continent [5–7]. With the recent implementation of high-resolution reanalysis datasets, it would be interesting to assess their ability to simulate South American climatology. This study compares the high-resolution CFSR data with coarse-grid reanalysis II (hereafter referred to as Re2) applied to South American climatology and interannual variability. The high-resolution reanalysis data will also allow us to detect features not seen in the coarse resolution data such as the climatological
References
[1]
R. D. Garreaud, M. Vuille, R. Compagnucci, and J. Marengo, “Present-day South American climate,” Palaeogeography, Palaeoclimatology, Palaeoecology, vol. 281, no. 3–4, pp. 180–195, 2009.
[2]
R. D. Garreaud, “The Andes climate and weather,” Advances in Geosciences, vol. 22, pp. 3–11, 2009.
[3]
M. J. Rodwell and B. J. Hoskins, “Subtropical anticyclones and summer monsoons,” Journal of Climate, vol. 14, no. 15, pp. 3192–3211, 2001.
[4]
J. Houston and A. J. Hartley, “The central andean west-slope rainshadow and its potential contribution to the origin of hyper-aridity in the Atacama Desert,” International Journal of Climatology, vol. 23, no. 12, pp. 1453–1464, 2003.
[5]
M. Vuille, R. S. Bradley, M. Werner, R. Healy, and F. Keimig, “Modeling precipitation over the tropical Americas: 1. Interann- ual variability and climatic controls,” Journal of Geophysical Research, vol. 108, no. D6, p. 4174, 2003.
[6]
R. Garreaud, M. Vuille, and A. C. Clement, “The climate of the Altiplano: observed current conditions and mechanisms of past changes,” Palaeogeography, Palaeoclimatology, Palaeoecology, vol. 194, no. 1–3, pp. 5–22, 2003.
[7]
M. Falvey and R. D. Garreaud, “Moisture variability over the South American Altiplano during the South American low level jet experiment (SALLJEX) observing season,” Journal of Geophysical Research D, vol. 110, no. D22, article 27, 2005.
[8]
C. F. Ropelewski and M. S. Halpert, “Global and regional scale precipitation patterns associated with the El Ni？o/Southern Oscillation (ENSO),” Monthly Weather Review, vol. 115, pp. 1606–1626, 1987.
[9]
P. Aceituno, “On the functioning of the Southern Oscillation in the South American sector. Part I: surface climate,” Monthly Weather Review, vol. 116, no. 3, pp. 505–524, 1988.
[10]
G. N. Kiladis and H. F. Diaz, “Global climatic anomalies associated with extremes in the Southern Oscillation,” Journal of Climate, vol. 2, pp. 1069–1090, 1989.
[11]
J. A. Marengo, “Interannual variability of surface climate in the Amazon Basin,” International Journal of Climatology, vol. 12, no. 8, pp. 853–863, 1992.
[12]
M. Vuille, R. S. Bradley, and F. Keimig, “Interannual climate variability in the Central Andes and its relation to tropical Pacific and Atlantic forcing,” Journal of Geophysical Research D, vol. 105, no. 10, pp. 12447–12460, 2000.
[13]
B. Rein, “How do the 1982/83 and 1997/98 El Ni？os rank in a geological record from Peru?” Quaternary International, vol. 161, no. 1, pp. 56–66, 2007.
[14]
L. E. Wells, “Holocene history of the El Nino phenomenon as recorded in flood sediments of northern coastal Peru,” Geology, vol. 18, no. 11, pp. 1134–1137, 1990.
[15]
E. Kalnay, M. Kanamitsu, R. Kistler et al., “The NCEP/NCAR 40-year reanalysis project,” Bulletin of the American Meteorological Society, vol. 77, no. 3, pp. 437–471, 1996.
[16]
M. Kanamitsu, W. Ebisuzaki, J. Woollen et al., “NCEP-DOE AMIP-II reanalysis (R-2),” Bulletin of the American Meteorological Society, vol. 83, no. 11, pp. 1631–1643, 2002.
[17]
S. Saha, S. Moorthi, and H. -L. Pan, “The NCEP climate forecast system reanalysis,” Bulletin of the American Meteorological Society, vol. 91, pp. 1015–1057, 2010.
[18]
D. R. Legates and C. J. Willmott, “Mean seasonal and spatial variability in gauge-corrected, global precipitation,” International Journal of Climatology, vol. 10, no. 2, pp. 111–127, 1990.
[19]
G. J. Huffman, R. F. Adler, P. Arkin et al., “The Global Precipitation Climatology Project (GPCP) combined precipitation dataset,” Bulletin of the American Meteorological Society, vol. 78, no. 1, pp. 5–20, 1997.
[20]
B. Rudolf, H. Hauschild, W. Rueth, and U. Schneider, “Terrestrial precipitation analysis: operational method and required density of point measurements,” in Global Precipitations and Climate Change, M. Desbois and F. Desalmond, Eds., vol. 26 of NATO ASI Series I, pp. 173–186, Springer, 1994.
[21]
G. J. Huffman, “Estimates of root-mean-square random error for finite samples of estimated precipitation,” Journal of Applied Meteorology, vol. 36, no. 9, pp. 1191–1201, 1997.
[22]
G. J. Huffman, R. F. Adler, B. Rudolf, U. Schneider, and P. R. Keehn, “Global precipitation estimates based on a technique for combining satellite-based estimates, rain gauge analysis, and NWP model precipitation information,” Journal of Climate, vol. 8, no. 5, pp. 1284–1295, 1995.
[23]
V. E. Kousky and R. W. Higgins, “An alert classification system for monitoring and assessing the ENSO cycle,” Weather and Forecasting, vol. 22, no. 2, pp. 353–371, 2007.
[24]
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.
[25]
V. B. S. Silva, V. E. Kousky, and R. W. Higgins, “Daily precipitation statistics for South America: an intercomparison between NCEP reanalyses and observations,” Journal of Hydrometeorology, vol. 12, no. 1, pp. 101–117, 2011.
[26]
J. A. Marengo, W. R. Soares, C. Saulo, and M. Nicolini, “Climatology of the low-level jet east of the andes as derived from the NCEP–NCAR reanalyses: characteristics and temporal variability,” Journal of Climate, vol. 17, pp. 2261–2280, 2004.
[27]
C. A. S. Coelho, C. B. Uvo, and T. Ambrizzi, “Exploring the impacts of the tropical Pacific SST on the precipitation patterns over South America during ENSO periods,” Theoretical and Applied Climatology, vol. 71, no. 3-4, pp. 185–197, 2002.
