Forage yield and composition of Avena strigosa Schreb at different harvesting frecuencies and intensities

Edmundo García-Moya Juan Burgueño Rodolfo Ramírez-Valverde Luis Alberto Miranda-Romero (2022, [Artículo])

Saia Oats Sward Height Residual Foliage CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA HARVESTING FREQUENCY FOLIAGE AVENA NUDA YIELDS

Hot Extremes and Climatological Drought Indicators in the Transitional Semiarid-Subtropical Region of Sinaloa, Northwest Mexico

OMAR LLANES CARDENAS OSCAR GERARDO GUTIERREZ RUACHO Iván Hernández Romano ENRIQUE TROYO DIEGUEZ (2022, [Artículo])

"The main goal of this study was to explore the historical and recent spatial concurrence between the frequency (F), duration (D) and intensity (I) of hot extremes (HEs) and the frequency and evolution of meteorological drought in the region of Sinaloa. Based on the values of daily maximum temperatura (Tmax) and precipitation obtained from CLImate COMputing for the interval April–October of a historical period (1963–2000) and a recent period (1982–2014), the HE and the standardized precipitation index (SPI) were calculated on one-month (SPI-1) and four-month (SPI-4) timescales. Spearman rank correlation coefficients (Sr) were used to obtain the significant concurrences (SCs) between HEs and SPI-1, and HEs and SPI-4. El Quelite weather station showed the highest historical SCs between HEs and SPI-1 (−0.66≤Sr≤−0.57). Jaina is the only station that showed SCs with all four indicators of HEs and SPI-4 (−0.47≤Sr≤−0.34). In this study, the concurrence between HEs and SPI-1, and HEs and SPI-4 was determined for the first time. These are phenomena that can decrease the crop yield, particularly for rainfed crops such as maize, sesame and sorghum in the region commonly known as “the breadbasket of Mexico."

frequency and evolution of meteorological droughts, the breadbasket of Mexico, Sinaloa CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS DE LA TIERRA Y DEL ESPACIO CLIMATOLOGÍA CLIMATOLOGÍA REGIONAL CLIMATOLOGÍA REGIONAL

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