Search Results - "meteorology"

Estimating and understanding crop yields with explainable deep learning in the Indian wheat belt by Wolanin, Aleksandra, Mateo-Garciá, Gonzalo, Camps-Valls, Gustau, Gómez-Chova, Luis, Meroni, Michele, Duveiller, Gregory, You, Liangzhi, Guanter, Luis

“…To do so, we applied a deep neural network to multivariate time series of vegetation and meteorological data to estimate the wheat yield in the Indian Wheat Belt. …”
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The impact of climate change on African economies and opportunities for agrifood system transformation by Tankari, Mahamadou, Fofana, Ismael

“…With respect to extreme weather events including droughts, floods, extreme heat, and cyclones, data from the Emergency Event Database in Africa showed that 80 meteorological, hydrological, and climate-related hazards were reported in 2022 (WMO 2023).…”
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Spatio-temporal variability of climatic variables and its impacts on rice yield in Bangladesh by Al Mamun, Md. Abdullah, Nihad, Sheikh Arafat Islam, Sarkar, Md. Abdur Rouf, Sarker, Mou Rani, Skalicka, Jitka, Skalicky, Milan

“…This research examined monthly, seasonal, and yearly temperature, rainfall, and relative humidity in Bangladesh using data from 35 meteorological stations from 1970–2020. The study utilized the Mann–Kendall method to evaluate trends and employed Sen’s slope to quantify their magnitude. …”
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National Mainstreaming Workshop on Climate Risk Management in Agricultural Extension (CRMAE) for Ethiopia by Belay, Berhanu, Bulo, Million, Ambaw, Gebermedihin, Amha, Yosef, Demissie, Teferi, Solomon, Dawit

“…In response, the Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA), the Ethiopian Meteorological Institute (EMI), the Ministry of Agriculture (MoA), and the Ministry of Labor and Skills (MoLS) collaborated to pilot the integration of CKPs into the crop production course of the ATVET curriculum. …”
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Crop evapotranspiration dynamics in the Ganges and Mekong deltas by Matheswaran, Karthikeyan, Puvanenthirarajah, Suvasthigha, Jampani, Mahesh, Sena, Dipaka Ranjan

“…We used the Google Earth Engine (GEE) version of the Surface Energy Balance Algorithm for Land (SEBAL) model with inputs from ERA5 Land meteorological data and LANDSAT 8 and 9 satellite images covering the period from 2014 to 2024. …”
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Assessing climate risks in rainfed farming using farmer experience, crop calendars and climate analysis by Nidumolu, U. B., Hayman, P. T., Hochman, Z., Horan, H., Reddy, D. R., Sreenivas, G., Kadiyala, D.M.

“…The methods developed in the present study provide a model for end-user engagement by meteorological agencies that strive to better target their climate information delivery.…”
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Empowering farmers with digital El Niño advisories: Insights from Malawi and Zambia by Chiduwa, Mazvita Sheila, Omondi, John O., Masikati, Patricia, Ngoma, Hambulo, Nyagumbo, Isaiah

“…Moreover, results also confirmed that meteorological forecasts played a critical role in influencing farmers’ choices of crop and planting dates. …”
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Empowering farmers with digital El Niño advisories: Insights from Malawi and Zambia by Chiduwa, Mazvita S., Omondi, John Okoth, Masikati, Patricia, Ngoma, Hambulo, Nyagumbo, Isaiah

“…Moreover, results also confirmed that meteorological forecasts played a critical role in influencing farmers’ choices of crop and planting dates. …”
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Incorporating dynamic crop area in hydrological model to address interannual variability in water withdrawal and implication of sustainable water management by Umer, M., Hanasaki, N., Gopalan, S. P., Ali, Zeshan, Oki, T.

“…This study investigates the impact of interannual variations in crop areas on agricultural water withdrawals within the Indus River Basin in Pakistan, by incorporating dynamic crop area based on hydro-meteorological factors in the H08 hydrological model. …”
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Remote sensing and machine learning integration to detect and forecast floods in Lodwar Town, Turkwel Basin, Kenya by Lakew, Haileyesus Belay, Taye, Meron Teferi, Lino, O., Dyer, E.

“…A python-based Decision Tree Regressor (DTR) model was trained using the daily CHIRPS rainfall data with various lag times, along with auxiliary meteorological variables including relative humidity, wind speed, and mean temperature for the period from 2002 to 2024 to predict NDWI of Lodwar Town. …”
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Impact of rainfall variability and extremes on crop intensification and diversification in the coastal region of Bangladesh by Islam, H. M. Touhidul, Ahmed, Sharif, Kamruzzaman, Mohammad, Kumar, Virender, Bhandari, Humnath

“…The average ON and WD of monsoon precipitation were found at the 21st-22nd and 43rd-44th standard meteorological weeks (SMWs), respectively, for all the stations. …”
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Water Impact Calculator: A decision support tool for irrigation scheduling by Garg, Kaushal K.

“…The tool then incorporates rainfall and meteorological data to estimate potential evapotranspiration and crop water demand accurately. …”
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Hydrological modelling of a catchment using the SWAT model in the upper Blue Nile basin of Ethiopia by Taffese, T., Zemadim, Birhanu

“…Data needed for modelling work was collected from available nearby stations and from the recently installed hydrological-meteorological stations. Model performances were compared prior to parameter optimization . …”
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Spatially explicit regionalization of airborne flux measurements using environmental response functions by Metzger, S., Junkermann, W., Mauder, M., Butterbach-Bahl, Klaus, Trancon y Widemann, B., Neidl, F., Schafer, K., Wieneke, S., Zheng, X.H., Schmid, H.P., Foken, T.

“…Boosted regression trees are then used to infer an environmental response function (ERF) between all flux observations (H, LE) and biophysical (LST, EVI) and meteorological drivers. Numerical tests show that ERF predictions covering the entire Xilin River catchment (≈3670 km2) are accurate to ≤18% (1σ). …”
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Flood pulsing in the Sudd Wetland: analysis of seasonal variations in inundation and evaporation in South Sudan by Rebelo, Lisa-Maria, Senay, Gabriel B., McCartney, Matthew P.

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Precipitation characteristics of the South American monsoon system derived from multiple datasets by Carvalho, Leila M. V., Jones, C., Posadas, A., Quiróz, R., Bookhagen, B., Liebmann, B.

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Regional priorities for strengthening climate services for farmers in Africa and South Asia by Sivakumar, Mannava V.K., Collins, C, Jay, A., Hansen, James

“…Expert working groups from all regions prioritized improving the scientific capacity of National Meteorological and Hydrological Services (NMHSs) to develop location specific seasonal climate forecasts at the subnational scale, and enhancing institutional frameworks for collaboration between the different agencies involved in the production and communication of climate services. …”
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CMIP5 Simulations of low-level tropospheric temperature and moisture over the tropical Americas by Carvalho, Leila M. V., Jones, C., Posadas, A., Quiróz, R., Bookhagen, B., Liebmann, B.

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Integrating Indigenous Knowledge with Scientific Seasonal Forecasts for Climate Risk Management in Lushoto District in Tanzania by Mahoo, H.F., Mbungu W, Yonah I, Radeny, Maren A.O., Kimeli, Philip, Kinyangi, James

“…Comparison was made of the seasonal March-April-May (MAM) forecasts in 2012 from IK and Tanzania Meteorological Agency (TMA), with both approaches predicting a normal rainy season. …”
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Potential of MODFLOW to model hydrological interactions in a Semikarst floodplain of the Ozark Border Forest in the Central United States by Chinnasamy, Pennan, Hubbart, J.A.

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