Extreme daily precipitation in southern South America: statistical characterization and circulation types using observational datasets and regional climate models

Olmo, M. E.; Bettolli, María Laura

doi:10.1007/s00382-021-05748-2

Cited by 31 publications

(31 citation statements)

References 65 publications

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“…3). ESD model performance was better in mean than in extreme precipitation (de ned by the 95th percentile, P95), especially during the warm season, when extreme events highly contribute to the total precipitation amounts (Olmo and Bettolli, 2021a). When studying the intra-annual variability of extreme rainfall -in terms of the annual cycle of P95 in Fig.…”

Section: Discussionmentioning

confidence: 98%

Multi-model ensemble of statistically downscaled GCMs over southeastern South America: historical evaluation and future projections of daily precipitation with focus on extremes

Olmo

Balmaceda-Huarte

Bettolli

2021

Preprint

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High-resolution climate information is required over southeastern South America (SESA) for a better understanding of the observed and projected climate changes due to their strong socio-economic and hydrological impacts. Thereby, this work focuses on the construction of an unprecedented multi-model ensemble of statistically downscaled global climate models (GCMs) for daily precipitation, considering different statistical techniques - including analogs, generalized linear models and neural networks - and a variety of CMIP5 and CMIP6 models. The skills and shortcomings of the different downscaled models were identified. Most of the methods added value in the representation of the main features of daily precipitation, especially in the spatial and intra-annual variability of extremes. The statistical methods showed to be sensitive to the driver GCMs, although the ESD family choice also introduced differences in the simulations. The statistically downscaled projections depicted increases in mean precipitation associated with a rising frequency of extreme events - mostly during the warm season - following the registered trends over SESA. Change rates were consistent among downscaled models up to the middle 21st century when model spread started to emerge. Furthermore, these projections were compared to the available CORDEX-CORE RCM simulations, evidencing a consistent agreement between statistical and dynamical downscaling procedures in terms of the sign of the changes, presenting some differences in their intensity. Overall, this study evidences the potential of statistical downscaling in a changing climate and contributes to its undergoing development over SESA.

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Section: Discussionmentioning

confidence: 98%

Multi-model ensemble of statistically downscaled GCMs over southeastern South America: historical evaluation and future projections of daily precipitation with focus on extremes

Olmo

Balmaceda-Huarte

Bettolli

2021

Preprint

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“…Figure 4 displays the seasonal average values of P95 over SESA during both seasons of the year, separately. During the warm season (October-March), maximum values were found in the centre of the domain with large amounts of precipitation, which makes SESA a distinctive region of South America for precipitation extremes occurrence (Re and Barros, 2009;Solman and Bl azquez, 2019;Olmo and Bettolli, 2021). The observational datasets exhibited some discrepancies in P95 intensities, which were typically underestimated (mainly during the warm season) but the spatial distribution was relatively well captured.…”

Section: Extreme Eventsmentioning

confidence: 99%

“…• Air temperature at 700 and 850 hPa (T700 and T850, respectively). These variables were chosen based on a sensitivity analysis of different predictors, a predictor screening performed in La Plata basin by Bettolli and Penalba (2018) and the evaluation of the synoptic environment associated with extreme rainfall events over SESA (Lavín-Gull on et al, 2021;Olmo and Bettolli, 2021) and mesoscale convection systems by Rasmussen and Houze Jr. (2016). These studies found a baroclinic configuration leaded by a dipolar structure of Z500 anomalies with an anticyclonic (cyclonic) centre over the Atlantic (Pacific) Ocean and an intensification and southern penetration of the SALLJ, strengthening the meridional advections of humid and warm air from the Amazonia to SESA, which significantly enhances the occurrence of extreme rainfall events over the region.…”

Section: Datamentioning

confidence: 99%

“…In particular, we used the 16 weather types (WT) found by a Self-Organizing Maps (SOM) clustering of Z500 anomalies over an extended domain over southern South America by Olmo and Bettolli (2021). This classification spans the variety of synoptic states during the 1979-2017 period of study, and it was found to successfully represent the atmospheric configurations associated with extreme precipitation events over SESA.…”

Section: Generalized Linear Modelsmentioning

confidence: 99%

“…Thereby, an extreme precipitation event was defined using a minimum threshold of 5% of station points exceeding their P95, detecting 577 (460) events during the warm (cold) season in the meteorological stations. This percentage allows the analysis of more structured heavy precipitation systems and also events with a greater spatial extension, in the same way as in Olmo and Bettolli (2021) when analysing these events as simulated by a set of RCMs. In addition, the intra-annual variability of these spatially extended extreme events showed good correspondence with the models' performance as depicted by the P95 annual cycle displayed in Figure 5 (not shown).…”

Section: Extreme Eventsmentioning

confidence: 99%

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Statistical downscaling of daily precipitation over southeastern South America: Assessing the performance in extreme events

Olmo

Bettolli

2021

Intl Journal of Climatology

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The performance of multiple empirical statistical downscaling (ESD) methods was assessed for simulating daily precipitation during 1979-2017 over southeastern South America (SESA), a region where extremes are remarkable. Meteorological stations were used as reference and three gridded precipitation products were included to account for observational uncertainty. The set of ESD models involved different configurations of the analogue method (ANs), deterministic and stochastic versions of neural networks (NNs) and generalized linear models (GLMs) and circulation-conditioned GLMs (GLM_WTs). The years with the largest number of extreme events (wet years) were calibrated separately. The spatio-temporal variability of extremes was assessed by analysing their intensity, spatial extent, frequency and interannual variability. An overall good performance of the ESD models was found for several aspects of daily precipitation. ESD performance dispersion was usually contained in the observational spread. No particular model configuration was found to perform best in all aspects, indicating the advantage of considering a multi-model ensemble. The ANs tended to follow the stations, satisfactorily simulating daily precipitation and its extremes. The deterministic GLMs strongly underestimated precipitation estimates and were not able to represent extreme frequencies and intensities, but this was alleviated by employing a stochastic version of the method. Furthermore, the use of weather types to condition the GLMs (GLM_WTs) considerably improved model performance, particularly for the annual cycle and the spatial structure of extreme precipitation. The NNs adequately reproduced the spatial behaviour and intra-annual variability of extreme precipitation, although they underestimated its intensity in their deterministic version. An analysis of the regional time series of extremes showed consistency among datasets and evidenced the influence of the ENSO teleconnection on the wet years, which were commonly well-simulated by the statistical models. ESD models presented good skills in simulating a wetter climate over SESA, which is of particular importance in a climate change scenario.

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Changes in extreme precipitation events in the Zambezi River basins based on CORDEX‐CORE models, Part II: Future projections under 1.5, 2.0, and 3.0°C global warming levels

Samuel

Wiston

Mphale

et al. 2022

Intl Journal of Climatology

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This study examines the potential implications of 1.5, 2.0, and 3.0°C global warming levels (GWLs) on the austral summer (November–March) extreme precipitation indices over the Zambezi River basin (ZRB) relative to the control period (1971–2000). We computed extreme precipitation based on daily data from observations and the Coordinated Regional Downscaling Experiment (CORDEX)‐Coordinated Output for Regional Evaluations (CORE) multi‐model ensemble mean (ENSMean). First, we evaluated the performance of the CORDEX‐CORE ENSMean in simulating extreme precipitation based on six indices; the number of rainy days (RR1), simple daily intensity index (SDII), maximum consecutive wet days (CWD), maximum consecutive dry days (CDD), heavy precipitation days (R10), and very heavy precipitation days (R20). The results indicate that the CORDEX‐CORE ENSMean can simulate the spatial distributions of extreme precipitation over the ZRB. However, CORDEX‐CORE largely overestimates the magnitudes of RR1 and CWD. The projected changes show a decrease in RR1, CWD, and R10 under all GWLs, with a robust and pronounced decrease under 3.0°C GWL. In contrast, CDD and SDII are projected to increase under all GWLs, with a robust and pronounced increase in CDD under 3.0°C GWL. The regionally averaged changes show that the median values of CWD, RR1, and R10 (SDII and CDD) are projected to decrease (increase) under all GWLs over the ZRB and sub‐basins. The probability density function (PDF) shows negative (positive) shifts in the mean of CWD, RR1, and R10 (SDII and CDD) over the ZRB and sub‐basins under all GWLs. In contrast, R20 is projected to increase (decrease) over most of the western (eastern) ZRB under all GWLs. Assessing the implications of an additional 0.5 and 1.5°C (1.0°C) warming to 1.5°C (2.0°C) GWL shows that limiting GWL to 1.5°C would restrict the future exposure of the ZRB to extreme precipitation.

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Extreme daily precipitation in southern South America: statistical characterization and circulation types using observational datasets and regional climate models

Cited by 31 publications

References 65 publications

Multi-model ensemble of statistically downscaled GCMs over southeastern South America: historical evaluation and future projections of daily precipitation with focus on extremes

Multi-model ensemble of statistically downscaled GCMs over southeastern South America: historical evaluation and future projections of daily precipitation with focus on extremes

Statistical downscaling of daily precipitation over southeastern South America: Assessing the performance in extreme events

Changes in extreme precipitation events in the Zambezi River basins based on CORDEX‐CORE models, Part II: Future projections under 1.5, 2.0, and 3.0°C global warming levels

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