Gutierrez R. A., Junquas Clémentine, Armijos E., Sörensson A. A., Espinoza J. C. (2024). Performance of regional climate model precipitation simulations over the terrain-complex Andes-Amazon transition region. Journal of Geophysical Research : Atmospheres, 129 (1), p. e2023JD038618 [23 p.]. ISSN 2169-897X.
Auteurs
Gutierrez R. A., Junquas Clémentine, Armijos E., Sörensson A. A., Espinoza J. C.
Source
Journal of Geophysical Research : Atmospheres, 2024,
129 (1), p. e2023JD038618 [23 p.] ISSN 2169-897X
Regional climate models (RCMs) are widely used to assess future impacts associated with climate change at regional and local scales. RCMs must represent relevant climate variables in the present-day climate to be considered fit-for-purpose for impact assessment. This condition is particularly difficult to meet over complex regions such as the Andes-Amazon transition region, where the Andean topography and abundance of tropical rainfall regimes remain a challenge for numerical climate models. In this study, we evaluate the ability of 30 regional climate simulations (6 RCMs driven by 10 global climate models) to reproduce historical (1981-2005) rainfall climatology and temporal variability over the Andes-Amazon transition region. We assess spatio-temporal features such as spatial distribution of rainfall, focusing on the orographic effects over the Andes-Amazon "rainfall hotspots" region, and seasonal and interannual precipitation variability. The Eta RCM exhibits the highest spatial correlation (up to 0.6) and accurately reproduces mean annual precipitation and orographic precipitation patterns across the region, while some other RCMs have good performances at specific locations. Most RCMs simulate a wet bias over the highlands, particularly at the eastern Andean summits, as evidenced by the 100%-2,500% overestimations of precipitation in these regions. Annual cycles are well represented by most RCMs, but peak seasons are exaggerated, especially at equatorial locations. No RCM is particularly skillful in reproducing the interannual variability patterns. Results highlight skills and weaknesses of the different regional climate simulations, and can assist in the selection of regional climate simulations for impact studies in the Andes-Amazon transition zone. Regional climate models (RCMs) are useful numerical tools to investigate future climate change impacts (e.g., future water availability, frequency of floods and droughts, regional warming). Regarding regional scale, RCMs are expected to perform better than global climate models due to finer spatial resolution. However, in the Andes-Amazon transition region, assessing the performance of RCMs is challenging due to complex terrain and scarcity of observations. This region is of critical importance for the water cycle of local and regional ecological systems, but has been often overlooked in RCM assessments. Here, we evaluate how 30 regional climate simulations perform in representing precipitation regional contrasts, wet-dry seasons, and year-to-year changes over the Andes-Amazon transition region. We find that models perform differently over specific regions, with prominent overestimations at high altitudes by most RCMs. However, Eta RCM has the best performance regarding regional patterns of precipitation and its wet-dry fluctuations. Besides overestimations during austral summer and spring, wet-dry seasonal fluctuations are well simulated by most RCMs, but none excels in representing wet-dry yearly fluctuations. Strengths and weaknesses of different regional climate simulations are shown, and can help choose the most appropriate simulations for distinct impact studies in this region. Precipitation output from 30 regional climate simulations is assessed over the Andes-Amazon in terms of climatology and temporal variabilityThe spatio-temporal behavior of seasonality is well reproduced by most simulations, with overestimations during austral summer and springWhile orographic precipitation is a major challenge for most regional climate models, Eta satisfactorily reproduces climate patterns in the Andes-Amazon region
