Extreme indices of temperature and precipitation in South America: trends and intercomparison of regional climate models

Abstract

Regional Climate Models (RCMs) provide climate information required for the evaluation of vulnerability, impacts, and adaptation at ner scales than their global driving models. As they explicitly resolve the basic conservation and state equations, they solve physics with more detail, conserving teleconnection of larger scales provided by GCMs. In South America (SA), the regional simulations have been historically evaluated principally on climatological aspects, but the representativeness of extremes still needs a deeper assessment. This study aims to analyze three RCMs driven by different GCMs: RegCM4-7, REMO2015, and Eta in the CORDEX SA region with focus on their capacity to reproduce extreme ETCCDI historical indices of daily precipitation and extreme temperature. Rx5day, CDD, TXx, and TNn were evaluated regarding the historical spatio-temporal variability and trends and climate change projections for the 2071-2099 period in the RCP8.5 were provided.The historical behavior of RCMs (1981RCMs ( -2005 was compared with two gridded products: CPC and Agrometeorological indicators derived from ERA5 reanalysis, previously compared with records from meteorological stations to assess potential observational biases. The results show that the highest observational uncertainty is observed in the regions with more scarce surface stations (North and West of SA) and with complex topography, being more pronounced in the precipitation-based indices. We found that RCMs generally show more agreement in the spatial variability than in the inter-annual variability for all the indices and SA regions. When analyzing the observed trends, all models better reproduce the long term variability of extreme temperature indices. More disagreement is present for Rx5day and CDD indices trends, including substantial spatial heterogeneities in both magnitude and sign of tendency. Climate change projections exhibited signi cant agreement to warmer conditions in TXx and TNn, but precipitation signals differed between RCMs and the driving GCM within each regional model. Maximum dry spells are expected to increase in almost all SA regions whereas the climate change signals in extreme precipitation events are more consistent over southeastern SA (northern and southwestern SA) with positive (negative) changes by the end of the century.

Regional climate projections of daily extreme temperatures in Argentina applying statistical downscaling to CMIP5 and CMIP6 models

“…The regions considered were the Pampas region (R1), northeast Argentina (R2), central Argentina (R3), northwest Argentina (R4) and Argentinian Patagonia (R5) (Fig. 1) following Balmaceda-Huarte and Bettolli (2022).…”

“…Whereas statistical downscaling of daily maximum and minimum temperatures (Tx and Tn, respectively) has been evaluated in a previous work by Balmaceda-Huarte and Bettolli (2022), where a set of analogs, generalised linear models and arti cial neural networks were employed. The authors found, during an observed period using a cross-validation approach, a good performance of the models, being successful to reproduce the mean values, extreme percentiles and temporal variability from seasonal to interannual.…”

Assessment of Precipitation and Hydrological Droughts in South America through Statistically Downscaled CMIP6 Projections

“…The rectangles illustrated in Figure 1 indicate the subdomains selected (Table 1) to analyze hydrological drought events on the continent. We considered subdomain 8 (Patagonia) because, in this region, the Andes have a lower height, while we did not perform analysis for the other parts of the Cordillera due to uncertainties in the reference data [97]. The rectangles illustrated in Figure 1 indicate the subdomains selected (Table 1) to analyze hydrological drought events on the continent.…”

“…For this, daily data from 1995 to 2014 were used, with 0.5 • horizontal resolution-available online: https://ftp.cpc.ncep.noaa.gov/precip/CPC_UNI_PRCP/ GAUGE_GLB/RT/ (accessed on 25 January 2022). CPC data proved adept at representing average and seasonal precipitation patterns over most of SA [93] but presented uncertainties in regions of complex topography, such as the Andes Mountains [97].…”

Future projection of climate extremes across contiguous northeast India and Bangladesh

“…These indices provide a framework for defining and assessing changes in the Earth's climate system (URL: http://etccdi.pacificclimate.org/list_27_indices.shtml ). These statistically reliable indices are designed to capture crucial characteristics such as the frequency, intensity, and duration of daily temperature and precipitation extremes 26 , 40 – 44 . However, research focusing on daily precipitation and temperature in the NEI region has been limited, with only a few studies conducted in the past decade.…”