Resultados de búsqueda - "meteorology"

Weather dataset choice introduces uncertainty to estimates of crop yield responses to climate variability and change por Parkes, Ben, Higginbottom, Thomas P., Hufkens, Koen, Ceballos, Francisco, Kramer, Berber, Foster, Timothy

“…In this context, a major challenge in many developing countries is the lack of accessible and reliable meteorological datasets. Gridded weather datasets, derived from combinations of in-situ gauges, remote sensing, and climate models, provide a solution to fill this gap, and have been widely used to evaluate climate impacts on agriculture in data-scarce regions worldwide. …”
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Weather dataset choice introduces uncertainty to estimates of crop yield responses to climate variability and change por Parkes, Ben, Higginbottom, Thomas P., Hufkens, Koen, Ceballos, Francisco, Kramer, Berber, Foster, Timothy

“…In this context, a major challenge in many developing countries is the lack of accessible and reliable meteorological datasets. Gridded weather datasets, derived from combinations of in situ gauges, remote sensing, and climate models, provide a solution to fill this gap, and have been widely used to evaluate climate impacts on agriculture in data-scarce regions worldwide. …”
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Interpretation of climate change and agricultural adaptations by local household farmers: A case study at Bin County, Northeast China por Yu, Qiang-Yi, Wu, Wen-Bin, Liu, Zhen-Huan, Verburg, Peter H., Xia, Tian, Yang, Peng, Lu, Zhong-Jun, You, Liangzhi, Tang, Hua-Jun

“…A case study at Bin County (1980s–2010s), Northeast China, suggested that increased annual average temperature (0.6°C per decade) and decreased annual precipitation (46 mm per decade, both from meteorological datasets) were correctly perceived by 76 and 66.9%, respectively, of farmers from the survey, and that a longer growing season was confirmed by 70% of them. …”
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Training Agricultural Research & Extension Staff to Produce and Communicate Agro-Climatic Information, to Enhance the Resilience and Food Security of Farmers and Pastoralists in Ki... por Dorward, P., Tall, Arame, Kaur, Harneet, Hansen, James

“…Preparation for the course included analysis of historical climate information, as well as training of staff from the Tanzania Meteorological Agency in downscaling using the Climate Prediction Tool (CPT). …”
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Improving Resilience to Climate Impacts in Mali through Improved Availability, Access and Use of Climate Information: Dialogue with Users por Nenkam, Andree M., Sibiry Traoré, Pierre C.

“…Despite a noteworthy legacy in the provision of agro-meteorological extension to farmers (Mason, 2015; Dinku, 2016) , the large landlocked country of Mali is no exception: there, a security crisis in the northern half of the country since 2012 has further aggravated the provision of data from an already sparse weather station network. …”
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Modelling of the effects of environmental factors on rice grain discoloration incidence in Corrientes province, Argentina por Dirchwolf, Pamela M., Moschini, Ricardo Carlos, Gutierrez, Susana A., Carmona, Marcelo Anibal

“…Due to the need to better define the environmental conditions that favour the disease, the aims of this work were to (i) identify the predominant fungi associated, (ii) determine the meteorological variables most closely related, and (iii) develop preliminary weather-based models to predict binary levels of RGD incidence. …”
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Regional isoprenoid emission from Eucalyptus grandis forests in northeastern Argentina por Richter, Klaus, Centritto, Mauro, Di Bella, Carlos Marcelo, Posse Beaulieu, Gabriela

“…A forest inventory, data from a meteorological station and leaf area indices derived from satellite data served as inputs for the model. …”
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Cotton lint yield and quality variability in Georgia, USA: Understanding genotypic and environmental interactions por Scarpin, Gonzalo Joel, Bhattarai, Anish, Hand, Lavesta C., Snider, John L., Roberts, Phillip M., Bastos, Leonardo M.

“…Genotype x environment analysis have been previously performed, although there still exists a gap in knowledge related to i) newer varieties and ii) characterization of environmental potential in relation to meteorological patterns during the growing season. Objectives: i) to quantify the effects of environment, genotype, and management on yield and quality; ii) to evaluate the performance and responsiveness of different genotypes to different environments, and iii) to identify environmental conditions with increased cotton lint yield or quality parameters. …”
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Fusarium species and mycotoxin contamination in maize in Buenos Aires province, Argentina por Castañares, Eliana, Martínez, Mauro, Cristos, Diego Sebastian, Rojas, Dante Emanuel, Lara, Bruno, Stenglein, Sebastian Alberto, Dinolfo, María Inés

“…Due to worldwide concern about food security and the potential risk the global climate change could impart, it will be necessary to develop predictive models based on meteorological conditions to determine the risk of Fusarium presence and mycotoxin production in maize similar to those developed in other crops.…”
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Daily, seasonal, and interannual variability of airborne pollen of Araucaria angustifolia growing in the subtropical area of Argentina por Latorre, Fabiana, Rotundo, Cristian Andres, Abud Sierra, María Laura, Fassola, Hugo Enrique

“…To better understand the reproductive dynamics, the aerobiological curves obtained with Hirst methodology were analyzed during 7 years in San Antonio (Misiones, Argentina), including productivity, seasonality, start, end, duration, and peak, along with the role of meteorological/seasonal climate factors. An alternation between 1 year of high pollen values (1685 pollen grains day m-3, on average), followed by 2 years of a progressive reduction (456 pollen grains day m-3, on average) in productivity, was observed. …”
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Tools to modify cherries harvest time in Alto Valle de Río Negro and Neuquén, Argentina por Raffo Benegas, Maria Dolores, Curetti, Mariela

“…The use of regulators in cherries allows to extend the harvest window in nearly 10 days, depending on each cultivar and the meteorological conditions of the season.…”
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Predicting the fundamental fluxes of an eddy-covariance station using machine learning methods por García-Rodríguez, David, Catret, Pablo, Iglesias, Domingo J., Martínez, Juan J., López, Ernesto, García, Antonio

“…In this study, Linear Regression (LR), Elastic Net (EN) regression, K-Nearest Neighbours (KNN), Gaussian-Process (GP), Decision Tree (TREE) Regression, Random Forest (RF) Regression, XGBoost (XGB) Regression, Support Vector Regression (SVR) and Multi-layer Perceptron (MLP) models have been applied to predict fundamental fluxes of an eddy-covariance station from conventional meteorological parameters. These models reproduced well the estimations of three output parameters from the eddy-covariance station. …”
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Scaling up climate information services through public-private partnership business models por Partey, Samuel T., Nikoi, Gordon K., Ouédraogo, Mathieu, Zougmoré, Robert B.

“…The pilot was executed with 1000 profiled and geo-referenced farmers (33% women) through a collaboration with a private information and communication technology (ICT) company, Esoko in Ghana and the Ghana Meteorological Agency (GMet). During the pilot, Esoko delivered processed weather information received from GMet and other sources to farmers using mobile phone platforms. …”
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Do satellite surface soil moisture observations better retain information about crop-yield variability in drought conditions? por Modanesi, S., Massari, C., Camici, S., Brocca, L., Amarnath, Giriraj

“…The analysis involved generating a Standardized Soil Moisture Index using (1) satellite soil moisture observations from the European Space Agency Climate Change Initiative and (2) the Modern-Era Retrospective Analysis for Research and Applications, version 2 soil moisture data set as well as producing a Standardized Precipitation Index using ground-based rainfall observations from the Indian Meteorological Department. Spanning the period from 1998 to 2015, the study covers Maharashtra and Karnataka states. …”
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User Needs Assessment for Climate Services in Zambia por Clarkson, Graham, Dorward, Peter, Poskitt, Samuel, Mambwe, Dina, Mtonga, Radhia K., Below, Till

“… • There is a gap between the climate and weather information and services that are produced (by Zambia Meteorological Department) and those that farmers are accessing…”
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Impact of Climate Change on the Hydrology of the Upper Awash River Basin, Ethiopia por Emiru, Nega C., Recha, John W.M., Thompson, Julian R., Belay, Abrham, Aynekulu, Ermias, Manyevere, Alen, Demissie, Teferi Dejene, Osano, Philip M., Hussein, Jabir, Molla, Mikias B., Mengistu, Girma M., Solomon, Dawit

“…The Mann–Kendall trend test (MK) was used to assess climate trends. Meteorological drought (SPEI) and hydrological drought (SDI) were also investigated. …”
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Accelerating Impact of CGIAR Climate Research for Africa por International Institute of Tropical Agriculture

“…The project is anchored to CGIAR’s multi-stakeholder platform of the Biorisk Management Facility (BIMAF) hosted by IITA’s station in Benin, West Africa, and includes the following partners: CGIAR Climate Agriculture & Food Security (CCAFS) Research Program, International Water Management Institute (IWMI), Alliance Bioversity-CIAT, World Agroforestry (CIFOR-ICRAF), ICRISAT, Center for Agriculture Biosciences International (CABI), Norwegian Institute of Bioeconomy Research (NIBIO), Crop Research Institute (CSIR/CRI), Ministry of Food and Agriculture (MoFA/PPRSD), Ghana Meteorological Agency, Climate Change & Agriculture Department of the University of Development Studies (CCAD/UDS). …”
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Climate change effects on Chickpea yield and its variability in Andhra Pradesh, India por Kumar, K. Nirmal Ravi, Reddy, M. Jagan Mohan, Babu, Suresh Chandra

“…In view of these findings, it is imperative to advocate the farmers about the importance of cultivating drought-tolerant chickpea varieties, drought-proofing and mitigation strategies, micro-irrigation practices and improving their access to agro-meteorological information towards sustainable chickpea cultivation in Andhra Pradesh.…”
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Data utilized in African Green Climate Fund Agricultural Adaptation Projects and its availability in selected Decision Support Tools (DSTs) por Rosenstock, Todd S., Joshi, Namita, Steward, Peter Richard, Kristal, Jones

“…Consequently, the compiled dataset comprised diverse data, ranging from meteorological and climatological factors influencing climate variability and extremes to socio-economic, environmental, and demographic variables affecting climate risk sensitivity. …”
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Flood risk assessment and adaptation under changing climate for the agricultural system in the Ghanaian White Volta Basin por Smits, W. K., Attoh, Emmanuel M. N. A. N., Ludwig, F.

“…Multi-model climate change data (RCP 8.5) from CORDEX and observation data from the Ghana Meteorological Agency were used for hazard analysis. Data on exposure, vulnerability, and adaptation were collected through structured interviews. …”
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