Escenarios futuros de eventos extremos de precipitación y temperatura en México

Future changes of precipitation and temperature extremes in Mexico

Ernesto Ramos Esteban (2024, [Tesis de maestría])

Diferentes estudios a escala mundial indican un incremento en frecuencia de eventos climáticos extremos debido al calentamiento global y sugieren que podrían intensificarse en el futuro. El objetivo de este trabajo es analizar los posibles cambios de 12 índices climáticos extremos (ICE) de precipitación y temperatura en 15 regiones de México, el sur de los Estados Unidos y Centroamérica para un período histórico (1981-2010), un futuro cercano (2021-2040), un futuro intermedio (2041-2060) y un futuro lejano (2080-2099). Se utilizó el reanálisis ERA5 como referencia en la evaluación histórica de los modelos climáticos globales (MCG) y para las proyecciones se analizaron los ICE de diez MCG del Proyecto de Intercomparación de Modelos Climáticos, fase 6 (CMIP6), de acuerdo con dos escenarios de Vías Socioeconómicas Compartidas (SSPs), uno de bajas emisiones (SSP2-4.5) y otro de altas emisiones (SSP3-7.0). Los MCG reproducen muy bien los índices extremos de temperatura histórica y los días consecutivos secos, pero subestiman la lluvia promedio y la lluvia extrema en las zonas más lluviosas desde el centro de México hasta Centroamérica. Históricamente, se observaron tendencias positivas de las temperaturas extremas (TXx y TNn) en todas las regiones, pero sólo en algunas regiones fueron significativas, mientras que los índices de lluvia extrema (R95p, R10mm y R20mm) presentaron tendencias negativas, pero pequeñas. Las proyecciones indican que las temperaturas extremas podrían seguir incrementándose en el futuro, desde 2° C hasta 5° C a mitad y final de siglo, respectivamente. La contribución de la precipitación extrema arriba del percentil 95 (R95p) se podría incrementar entre un 10 % y 30 %, especialmente en la región subtropical, mientras que la precipitación podría disminuir en las regiones tropicales. Este estudio es el primero que analiza los cambios futuros de índices extremos del CMIP6 a escala regional (en 15 regiones) de México, el sur de Estados Unidos y Centroamérica.

Global-scale studies indicate an increase in the frequency of extreme weather events due to global warming and suggest that they could further intensify in the future. This study aims to assess potential changes in 12 extreme climate indices (ECI) related to precipitation and temperature in 15 regions in Mexico, the southern United States, and Central America for different periods: a historical period (1981-2010), a near future (2021-2040), an intermediate future (2041-2060), and a far future (2080-2099). The ERA5 reanalysis was used as a reference for the historical evaluation of global climate models (GCMs), and ECI from ten GCMs of phase 6 (CMIP6) from the Coupled Model Intercomparison Project were employed for the projections and examined under two Shared Socioeconomic Pathways (SSPs) scenarios, one characterized by low emissions (SSP2-4.5) and another representing high greenhouse gas emissions (SSP3-7.0). The GCMs reproduce historical extreme temperature indices and consecutive dry days very well. However, they underestimate average and extreme rainfall from central Mexico to Central America in the wetter areas. Historically, positive trends in extreme temperatures (TXx and TNn) were observed across all regions. However, statistical significance was only present in certain regions, while extreme rainfall indices (R95p, R10mm, and R20mm) exhibited small negative trends. The projections suggest that extreme temperatures could continue to increase in the future, from 2°C to 5°C by the mid and late century, respectively. The contribution of extreme precipitation above the 95th percentile (R95p) could increase by 10% to 30%, particularly in the subtropical regions, while precipitation might decrease in tropical regions. This study is the first to analyze future changes in extreme indices from CMIP6 at a regional scale (across 15 regions) in Mexico, the southern United States, and Central America.

Centroamérica, CMIP6, escenarios SSP, extremos climáticos, intercomparación de modelos climáticos, México Central America, climate extremes, CMIP6, intercomparison of climate models, Mexico, SSP scenarios CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS DE LA TIERRA Y DEL ESPACIO OCEANOGRAFÍA OCEANOGRAFÍA FÍSICA (VE R 5603 .04) OCEANOGRAFÍA FÍSICA (VE R 5603 .04)

Offshore wind energy climate projection using UPSCALE climate data under the RCP8.5 emission scenario

MARKUS SEBASTIAN GROSS (2016, [Artículo])

In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe)-weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science)- Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP) 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in turn, will provide some guidance for wind power developers and policy makers to prepare and adapt for climate change impacts on wind energy production. Although offshore locations around Mexico were used as a case study, the dataset is global and hence the methodology presented can be readily applied at any desired location. © Copyright 2016 Gross, Magar. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reprod

atmosphere, climate change, Europe, Mexico, sampling, time series analysis, university, weather, wind power, climate, risk, theoretical model, wind, Climate, Models, Theoretical, Risk, Wind CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS DE LA TIERRA Y DEL ESPACIO OCEANOGRAFÍA OCEANOGRAFÍA

Towards gender-inclusive innovation: Assessing local conditions for agricultural targeting

Diana E. Lopez Romain Frelat Lone Badstue (2022, [Artículo])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE CLIMATE FEMALES GENDER HUMANS GENDER EQUALITY

Emmer wheat eco-geographic and genomic congruence shapes phenotypic performance under mediterranean climate

Dana Fuerst SHAILESH YADAV Rajib Roychowdhury Carolina Sansaloni Sariel Hübner (2022, [Artículo])

Emmer Wheat CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT GENETIC VARIATION CLIMATE PHENOLOGY YIELDS MEDITERRANEAN CLIMATE

Esquema de objetivos de inflación, compromiso, comunicación y credibilidad: ¿por qué el Banco de México muestra dificultad para cumplir con su objetivo puntual de inflación del 3%?

César Geovanny Ángeles Sánchez (2021, [Tesis de maestría])

El presente documento realiza tres ejercicios empíricos para los temas de compromiso, comunicación y credibilidad del Banco de México. En última instancia, se busca responder al porqué, durante la implementación del esquema de objetivos de inflación (2003-2020), el Banco de México ha mostrado dificultad para cumplir con su objetivo puntual de inflación del 3%. Ya que, como lo indican los promedios de las series de tiempo, durante este periodo los niveles de la inflación y de las distintas expectativas de inflación se han ubicado por encima de la meta. Si bien los resultados confirman la credibilidad que tiene el Banco de México con el mantener una inflación baja y estable; siguiendo una regla de Taylor, se encuentra evidencia que, durante el periodo 2003-2020, el Banco de México ha sido tolerante con brechas positivas en el nivel de inflación (acentuándose, de manera significativa, durante el 2015-2020). En otras palabras, los resultados del documento sugieren que, durante la implementación del esquema de objetivos de inflación, el Banco de México ha ajustado su tasa de interés en busca de un nivel de inflación que se ubique en el intervalo que va del 3% + 1 punto porcentual pero no en la meta del 3%. Asimismo, resulta interesante que, del 2007 al 2020, cambios en la tasa de interés hayan sido motivados por brechas en el nivel de producción (tal como si el banco central mantuviese un mandato dual). Finalmente, a través de la construcción de un índice de comunicación que emplea los anuncios de política monetaria, se encuentra evidencia que la comunicación del Banco de México influye en las expectativas de inflación implicitas en instrumentos financieros y permite anticipar futuros movimientos en la tasa de interés (“forward guidance”).

Banco de México (1925- ) -- Effect of inflation (Finance) on -- Econometric models. Banks and banking, Central -- Mexico -- Econometric models. CIENCIAS SOCIALES CIENCIAS SOCIALES

GWAS identifies genetic loci underlying nitrogen responsiveness in the climate resilient C4 model Setaria italica (L.)

Tirthankar Bandyopadhyay Stéphanie M. Swarbreck Vandana Jaiswal Rajeev Gupta Alison Bentley Manoj Prasad (2022, [Artículo])

C4 Model Crop Climate Resilience CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE RESILIENCE FOOD SECURITY GENE EXPRESSION NITROGEN

Production vulnerability to wheat blast disease under climate change

Diego Pequeno Jose Mauricio Fernandes Pawan Singh Willingthon Pavan Kai Sonder Richard Robertson Timothy Joseph Krupnik Olaf Erenstein Senthold Asseng (2024, [Artículo])

Wheat Blast Tropical Regions CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT PLANT DISEASES CLIMATE CHANGE PRODUCTION

Hub meeting Honduras: Gestión de la red de innovación en el occidente y oriente de Honduras. ¿Porque genero e inclusion social en Agrilac?

Angela Meentzen (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENDER EQUALITY FOOD SYSTEMS CLIMATE CHANGE WOMEN'S PARTICIPATION

Impacts of climate change on agriculture and household welfare in Zambia: an economy-wide analysis

Hambulo Ngoma (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE SMALLHOLDERS ECONOMIC ANALYSIS

Spatiotemporal analysis of rainfall and temperature variability and trends for climate resilient maize farming system in major agroecology zones of northwest Ethiopia

Kindie Tesfaye Dereje Ademe Enyew Adgo (2023, [Artículo])

Spatiotemporal studies of the annual and seasonal climate variability and trend on an agroecological spatial scale for establishing a climate-resilient maize farming system have not yet been conducted in Ethiopia. The study was carried out in three major agroecological zones in northwest Ethiopia using climate data from 1987 to 2018. The coefficient of variation (CV), precipitation concertation index (PCI), and rainfall anomaly index (RAI) were used to analyze the variability of rainfall. The Mann-Kendall test and Sen’s slope estimator were also applied to estimate trends and slopes of changes in rainfall and temperature. High-significance warming trends in the maximum and minimum temperatures were shown in the highland and lowland agroecology zones, respectively. Rainfall has also demonstrated a maximum declining trend throughout the keremt season in the highland agroecology zone. However, rainfall distribution has become more unpredictable in the Bega and Belg seasons. Climate-resilient maize agronomic activities have been determined by analyzing the onset and cessation dates and the length of the growth period (LGP). The rainy season begins between May 8 and June 3 and finishes between October 26 and November 16. The length of the growth period (LGP) during the rainy season ranges from 94 to 229 days.

Climate Trends Spatiotemporal Analysis Agroecology Zone CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGROECOLOGY CLIMATE CLIMATE VARIABILITY MAIZE