Browsing by Author "Montenegro Ambrosi, Martin Patricio"

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Assessment of the Impact of Higher Temperatures Due to Climate Change on the Mortality Risk Indexes in Ecuador Until 2070
(2022) Campozano Parra, Lenin Vladimir
Extreme weather conditions, including intense heat stress due to higher temperatures, could trigger an increase in mortality risk. One way to evaluate the increase in mortality risk due to higher temperatures is the high risk warming (HRW) index, which evaluates the difference between the future and base period of a given percentile of daily maximum temperature (Tmax). Another is to calculate the future increase in the number of days over the temperature of such percentile, named high risk days (HRD) index. Previous studies point to the 84th percentile as the optimum temperature. Thus, this study aims to evaluate HRW and HRD indexes in Ecuador from 2011 to 2070 over the three natural climate zones, e.g., Coast, Andes, and Amazon. This climate analysis is based on historical data from meteorological stations and projections from CSIRO-MK36, GISS-E2, and IPSL-CM5A-MR, CMIP5 global climate models with dynamical scale reduction through weather research forecasting (WRF). The representative concentration pathways (RCPs), 8.5, were considered, which are related to the highest increases in future temperature. The results indicate that HRW and HRD will experience a larger increase in the period 2041–2070 compared with the period 1980–2005; in particular, these two indices will have a progressively increasing trend from 2011 onward. Specifically, the HRW calculated from the CMIP5 models for all stations is expected to grow from 0.6°C to 1.4°C and 1.8°C to 4.6°C for 2010–2040 and 2041–2070, respectively. Also, it is expected that the HRD for all stations will increase from 42 to 74 and 120 to 227 warming days for 2011–2040 and 2041–2070, respectively. The trends derived using Sen’s slope test show an increase in the HRW between 0.5°C and 0.9°C/decade and of the HRD between 2.88 and 4.9 days/decade since 1985. These results imply a high increase in heat-related mortality risks related to climate change in Ecuador. In terms of spatial distribution, three Ecuadorian regions experienced more critical temperature conditions with higher values of HRW and HRD for 2070. As a response to the increased frequency trends of warming periods in tropical areas, urgent measures should be taken to review public policies and legislation to mitigate the impacts of heat as a risk for human health in Ecuador.
Climate change influences of temporal and spatial drought variation in the andean high mountain basin
(2019) Zhiña Villa, Dario Xavier; Montenegro Ambrosi, Martin Patricio; Montalván Pérez, Lisseth Mariela; Mendoza Sigüenza, Daniel Emilio; Contreras Silva, Juan José; Campozano Parra, Lenin Vladimir; Avilés Añazco, Alex Manuel
Climate change threatens the hydrological equilibrium with severe consequences for living beings. In that respect, considerable differences in drought features are expected, especially for mountain-Andean regions, which seem to be prone to climate change. Therefore, an urgent need for evaluation of such climate conditions arises; especially the effects at catchment scales, due to its implications over the hydrological services. However, to study future climate impacts at the catchment scale, the use of dynamically downscaled data in developing countries is a luxury due to the computational constraints. This study performed spatiotemporal future long-term projections of droughts in the upper part of the Paute River basin, located in the southern Andes of Ecuador. Using 10 km dynamically downscaled data from four global climate models, the standardized precipitation and evapotranspiration index (SPEI) index was used for drought characterization in the base period (1981−2005) and future period (2011−2070) for RCP 4.5 and RCP 8.5 of CMIP5 project. Fitting a generalized-extreme-value (GEV) distribution, the change ratio of the magnitude, duration, and severity between the future and present was evaluated for return periods 10, 50, and 100 years. The results show that magnitude and duration dramatically decrease in the near future for the climate scenarios under analysis; these features presented a declining effect from the near to the far future. Additionally, the severity shows a general increment with respect to the base period, which is intensified with longer return periods; however, the severity shows a decrement for specific areas in the far future of RCP 4.5 and near future of RCP 8.5. This research adds knowledge to the evaluation of droughts in complex terrain in tropical regions, where the representation of convection is the main limitation of global climate models (GCMs). The results provide useful information for decision-makers supporting mitigating measures in future decades.
Extreme rainfall variations under climate change scenarios. Case of study in an andean tropical river basin
(2022) Avilés Añazco, Alex Manuel; Montenegro Ambrosi, Martin Patricio; Mendoza Sigüenza, Daniel Emilio; Mora Serrano, Diego Esteban; García Ávila, Fausto Fernando
Maximum rainfall events have triggered hazards that harm ecosystems and populations. Climate change could modify these extreme events, becoming more severe and frequent. Knowing the patterns of Spatio-temporal changes in the distribution of extreme rainfall in Andean regions represents a research challenge due to the complex climate behavior in the tropical mountain basins. The study aimed to analyze future Spatio-temporal changes in maximum daily rainfall patterns. The methods and analysis were performed in the Paute river basin in Ecuador through observed and simulated data from 1985 to 2005. The outputs of an ensemble regional climate model of Ecuador (RCM) based on CMIP5 models were used with two representative concentrations pathways (RCP), scenarios 4.5 and 8.5, in two future periods; future 1 from 2011 to 2040 and future 2 from 2041 to 2070. The General Extreme Value (GEV) distribution was used to fit the maximum annual daily rainfall. The maximum rainfall change factor between historical and future periods was calculated for 5,10,30, 60, and 100 years return periods. The results showed an increment of maximum rainfall spatial average in all return periods for RCP 4.5 and 8.5 in the future 1. Future 2 presented an increment of maximum rainfall spatial average in all return periods for RCP 4.5 and 8.5 scenarios except for the 30,60 and 100 years return periods of the RCP 4.5 scenario, displaying a decrease of maximum rainfall spatial average. Knowing rainfall pattern projections could help formulate actions to diminish the risks of extreme rainfall.
Future meteorological droughts in Ecuador: decreasing trends and associated spatio temporal features derived from CMIP5 models
(2020) Campozano Parra, Lenin Vladimir; Ballari, Daniela Elisabet; Montenegro Ambrosi, Martin Patricio; Avilés Añazco, Alex Manuel
Droughts are one of the most spatially extensive disasters that are faced by societies. Despite the urgency to define mitigation strategies, little research has been done regarding droughts related to climate change. The challenges are due to the complexity of droughts and to future precipitation uncertainty from Global Climate Models (GCMs). It is well-known that climate change will have more impact on developing countries. This is the case for Ecuador, which also has the additional challenges of lacking meteorological drought studies covering its three main regions: Coast, Highlands, and Amazon, and of having an intricate orography. Thus, this study assesses the spatio-temporal characteristics of present and future droughts in Ecuador under Representative Concentrations Pathways (RCP) 4.5 and 8.5. The 10 km dynamically downscaled products (DGCMs) from Coupled Model Intercomparison Project 5 (CMIP5) was used. The Standardized Precipitation Index (SPI) for droughts was calculated pixel-wise for present time 1981–2005 and for future time 2041-2070. The results showed a slightly decreasing trend for future droughts for the whole country, with a larger reduction for moderate droughts, followed by severe and extreme drought events. In the Coast and Highland regions, the intra-annual analysis showed a reduction of moderate and severe future droughts for RCP 4.5 and for RCP 8.5 throughout the year. Extreme droughts showed small and statistically non-significant decreases. In the Amazon region, moderate droughts showed increases from May to October, and decreases for the rest of the year. Additionally, severe drought increases are expected from May to December, and decreases from January to April. Finally, extreme drought increases are expected from January to April, with larger increases in October and November. Thus, in the Amazon, the rainy period showed a decreasing trend of droughts, following the wetter in wet- and drier in dry paradigm. Climate change causes decision-making process and calls for adaptation strategies being more challenging. In this context, our study has contributed to better mapping the space-time evolution of future drought risk in Ecuador, thus providing valuable information for water management and decision making as Ecuador faces climate change. © Copyright © 2020 Campozano, Ballari, Montenegro and Avilés.
Rainfall forecasting using diverse predictors based on random forest over an andena basin
(Universidad de Cuenca, 2024-01-02) Montenegro Ambrosi, Martin Patricio; Córdova Mora, Mario Andrés
The hydrological cycle is primarily driven by rainfall, and accurately forecasting rainfall becomes challenging in regions marked by diverse influencing factors and significant spatial variations, as observed in the tropical Andes. Rainfall in the tropical Andes is associated to various sea surface temperature (SST) indices, such as ONI, NIÑO 1+2, TNI, and atmospheric variables, including temperature, wind, and humidity. The SST indices could better explain seasonal rainfall anomalies and the atmospheric variables could better explain faster changes in atmospheric conditions associated to rainfall. Considering both SST and atmospheric variables provides a comprehensive approach to forecast rainfall in the tropical Andes. This study aims to forecast cumulative 30 days moving average rainfall in the Paute Basin River using the Random Forest technique to forecast 30, 60, and 90 steps ahead, utilizing a variety of predictors. The rainfall precipitation product used was IMERG Late Run. Sea surface indices were sourced from the National Oceanic and Atmospheric Administration (NOAA). Atmospheric variables were obtained from the fifth-generation European Centre for MediumRange Weather Forecasts reanalysis for global climate and weather (ERA5). The ERA5 variables were used to build indices associated with rainfall in the study area through Pearson correlation. Five distinct models were developed, gradually incorporating predictors such as past rainfall (ILP), oceanic climate indices (GCI), regional atmospheric indices (RCD), and combinations of GCI+RCD and GCI+RCD+ILP. The results indicate that the most effective model is GCI+RCD+ILP, achieving R (MAE) values of 0.92 (9.38 mm/cumulative 30 days), 0.93 (9.85 mm/cumulative 30 days), and 0.94 (9.68 mm/cumulative 30 days) for 30, 60, and 90 steps ahead, respectively. The next steps are related to the operative implementation of these models, which will offer valuable information for water management, and the mitigation of impacts associated to droughts and floods.