Publications Using POWER Data¶
Akram, H., D. F. Levia, J. E. Herrick, H. Lydiasari, and N. Schütze, 2022: Water requirements for oil palm grown on marginal lands: A simulation approach. Agricultural Water Management, 260, 107292, https://doi.org/10.1016/j.agwat.2021.107292.
Araghi, A., C. J. Martinez, and J. E. Olesen, 2022: Evaluation of multiple gridded solar radiation data for crop modeling. European Journal of Agronomy, 133, 126419, https://doi.org/10.1016/j.eja.2021.126419.
Ait M’Barek, S., A. Rochdi, Y. Bouslihim, and A. Miftah, 2021: Multi‐Site Calibration and Validation of SWAT Model for Hydrologic Modeling and Soil Erosion Estimation: A Case Study in El Grou Watershed, Morocco. Ecol. Eng. Environ. Technol., 22, 45–52, https://doi.org/10.12912/27197050/141593.
Al-Kilani, M. R., M. Rahbeh, J. Al-Bakri, T. Tadesse, and C. Knutson, 2021: Evaluation of Remotely Sensed Precipitation Estimates from the NASA POWER Project for Drought Detection Over Jordan. Earth Syst Environ, 5, 561–573, https://doi.org/10.1007/s41748-021-00245-2.
Anas, H., E. Mghouchi Youness, Y. Halima, A. Nawal, and C. Mohamed, 2021: Novel climate classification based on the information of solar radiation intensity: An application to the climatic zoning of Morocco. Energy Conversion and Management, 247, 114770, https://doi.org/10.1016/j.enconman.2021.114770.
Ali-Ou-Salah, Hamza, Benyounes Oukarfi, and Tlemcani Mouhaydine, 2021: Short-Term Solar Radiation Forecasting Using a New Seasonal Clustering Technique and Artificial Neural Network. International Journal of Green Energy, 6, 37, https://doi.org/10.1080/15435075.2021.1946819.
Banik, R., P. Das, S. Ray, and A. Biswas, 2021: An Improved ANN Model for Prediction of Solar Radiation Using Machine Learning Approach. Applications of Internet of Things, J.K. Mandal, S. Mukhopadhyay, and A. Roy, Eds., Vol. 137 of Lecture Notes in Networks and Systems, Springer Singapore, 233–242.
Bansal, N., P. Pany, and G. Singh, 2021: Visual degradation and performance evaluation of utility scale solar photovoltaic power plant in hot and dry climate in western India. Case Studies in Thermal Engineering, 26, 101010, https://doi.org/10.1016/j.csite.2021.101010.
Berghuijs, H. N. C., and Coauthors, 2021: Calibrating and testing APSIM for wheat-faba bean pure cultures and intercrops across Europe. Field Crops Research, 264, 108088, https://doi.org/10.1016/j.fcr.2021.108088.
Bhattacharjee, S., and C. Nandi, 2021: Design of a voting based smart energy management system of the renewable energy based hybrid energy system for a small community. Energy, 214, 118977, https://doi.org/10.1016/j.energy.2020.118977.
Bre, F., R. M. e Silva Machado, L. K. Lawrie, D. B. Crawley, and R. Lamberts, 2021: Assessment of solar radiation data quality in typical meteorological years and its influence on the building performance simulation. Energy and Buildings, 250, 111251, https://doi.org/10.1016/j.enbuild.2021.111251.
Chan, H.-P., K. I. Konstantinou, and M. Blackett, 2021: Spatio-temporal surface temperature variations detected by satellite thermal infrared images at Merapi volcano, Indonesia. Journal of Volcanology and Geothermal Research, 420, 107405, https://doi.org/10.1016/j.jvolgeores.2021.107405.
Costa-Neto, G., G. Galli, H. F. Carvalho, J. Crossa, and R. Fritsche-Neto, 2021: EnvRtype : a software to interplay enviromics and quantitative genomics in agriculture. G3 Genes|Genomes|Genetics, 11, jkab040, https://doi.org/10.1093/g3journal/jkab040.
da Costa, L. M., G. A. de Araújo Santos, G. C. de Mendonça, L. F. F. Morais Filho, K. C. de Meneses, G. de Souza Rolim, and N. La Scala, 2021: Spatiotemporal variability of atmospheric CO2 concentration and controlling factors over sugarcane cultivation areas in southern Brazil. Environ Dev Sustain, https://doi.org/10.1007/s10668-021-01677-6.
Damak, F., M. S. M. Bougi, D. Araoka, K. Baba, M. Furuya, M. Ksibi, and K. Tamura, 2021: Soil geochemistry, edaphic and climatic characteristics as components of Tunisian olive terroirs: Relationship with the multielemental composition of olive oils for their geographical traceability. Euro-Mediterr J Environ Integr, 6, 37, https://doi.org/10.1007/s41207-021-00241-y.
Dias, H. B., and P. C. Sentelhas, 2021: Assessing the performance of two gridded weather data for sugarcane crop simulations with a process-based model in Center-South Brazil. Int J Biometeorol, 65, 1881–1893, https://doi.org/10.1007/s00484-021-02145-6.
Elkhrachy, I., Q. B. Pham, R. Costache, M. Mohajane, K. U. Rahman, H. Shahabi, N. T. T. Linh, and D. T. Anh, 2021: Sentinel‐1 remote sensing data and Hydrologic Engineering Centres River Analysis System two‐dimensional integration for flash flood detection and modelling in New Cairo City, Egypt. J Flood Risk Management, 14, https://doi.org/10.1111/jfr3.12692.
Hajjarpoor, A., and Coauthors, 2021: Environmental characterization and yield gap analysis to tackle genotype-by-environment-by-management interactions and map region-specific agronomic and breeding targets in groundnut. Field Crops Research, 267, 108160, https://doi.org/10.1016/j.fcr.2021.108160.
Gunes, O. E., A.C. Basara, and Y. Sisman, 2021: Determination of Precipitation Trend by Time Series: A case study Erbaa Plain. Advanced GIS,1(1)8-14.
Isaza Cuervo, F., C. A. Arredondo-Orozco, and G. C. Marenco-Maldonado, 2021: Photovoltaic power purchase agreement valuation under real options approach. Renewable Energy Focus, 36, 96–107, https://doi.org/10.1016/j.ref.2020.12.006.
Izar-Tenorio, Jorge, Jaramillo, Paulina, and Williams, Nathan, 2021: Techno-economic feasibility of small-scale pressurized irrigation in Ethiopia, Rwanda, and Uganda through an integrated modeling approach. https://doi.org/10.5281/ZENODO.5082395.
Jarrett, C., L. L. Powell, T. T. R. Claire, M. Tchoumbou, and B. Helm, 2021: Moult of overwintering Wood Warblers Phylloscopus sibilatrix in an annual-cycle perspective. J Ornithol, https://doi.org/10.1007/s10336-021-01859-z.
Jat, R., B. R. Gurjar, and D. Lowe, 2021: Regional pollution loading in winter months over India using high resolution WRF-Chem simulation. Atmospheric Research, 249, 105326, https://doi.org/10.1016/j.atmosres.2020.105326.
Jha, P. K., A. Araya, Z. P. Stewart, A. Faye, H. Traore, B. J. Middendorf, and P. V. V. Prasad, 2021: Projecting potential impact of COVID-19 on major cereal crops in Senegal and Burkina Faso using crop simulation models. Agricultural Systems, 190, 103107, https://doi.org/10.1016/j.agsy.2021.103107.
Kadiri, W. O. J., A. S. Fasina, and T. S. Babalola, 2021: Soil organic carbon concentration and stock of arable land use of two agro-ecological zones of Nigeria. Journal of the Saudi Society of Agricultural Sciences, 20, 180–189, https://doi.org/10.1016/j.jssas.2021.01.004.
Kapica, J., F. A. Canales, and J. Jurasz, 2021: Global atlas of solar and wind resources temporal complementarity. Energy Conversion and Management, 246, 114692, https://doi.org/10.1016/j.enconman.2021.114692.
Komarek, A. M., C. Thierfelder, and P. R. Steward, 2021: Conservation agriculture improves adaptive capacity of cropping systems to climate stress in Malawi. Agricultural Systems, 190, 103117, https://doi.org/10.1016/j.agsy.2021.103117.
Kudria, S., I. Ivanchenko, B. Tuchynskyi, K. Petrenko, O. Karmazin, and O. Riepkin, 2021: Resource potential for wind-hydrogen power in Ukraine. International Journal of Hydrogen Energy, 46, 157–168, https://doi.org/10.1016/j.ijhydene.2020.09.211.
Li, C., Y. Zheng, Z. Li, L. Zhang, L. Zhang, Y. Shan, and Q. Tang, 2021: Techno-economic and environmental evaluation of grid-connected and off-grid hybrid intermittent power generation systems: A case study of a mild humid subtropical climate zone in China. Energy, 230, 120728, https://doi.org/10.1016/j.energy.2021.120728.
Li, Z., and Coauthors, 2021: Integrating an interferometric synthetic aperture radar technique and numerical simulation to investigate the Tongmai old deposit along the Sichuan-Tibet Railway. Geomorphology, 377, 107586, https://doi.org/10.1016/j.geomorph.2020.107586.
Lorençone, J. A., L. E. de O. Aparecido, P. A. Lorençone, and J. R. D. S. C. de Moraes, 2021: Previsão Da Produtividade Do Café Com Base Em Dados Agroclimáticos E Aprendizagem De Máquina / Forecasting Coffee Yield Based On Agroclimatic Data And Machine Learning. Intern. Journ. Env. Res. Res. Sci., 3, https://doi.org/10.48075/ijerrs.v3i1.26255.
Martin, C., Q. Zhang, D. Zhai, X. Zhang, and C. M. Duarte, 2021: Anthropogenic litter density and composition data acquired flying commercial drones on sandy beaches along the Saudi Arabian Red Sea. Data in Brief, 36, 107056, https://doi.org/10.1016/j.dib.2021.107056.
Marzouk, O. A., 2021: Assessment of global warming in Al Buraimi, sultanate of Oman based on statistical analysis of NASA POWER data over 39 years, and testing the reliability of NASA POWER against meteorological measurements. Heliyon, 7, e06625, https://doi.org/10.1016/j.heliyon.2021.e06625.
Mbuthia, J. M., M. Mayer, and N. Reinsch, 2021: Modeling heat stress effects on dairy cattle milk production in a tropical environment using test-day records and random regression models. Animal, 15, 100222, https://doi.org/10.1016/j.animal.2021.100222.
Mompremier, R., Y. Her, G. Hoogenboom, K. Migliaccio, R. Muñoz-Carpena, Z. Brym, R. W. Colbert, and W. Jeune, 2021: Modeling the response of dry bean yield to irrigation water availability controlled by watershed hydrology. Agricultural Water Management, 243, 106429, https://doi.org/10.1016/j.agwat.2020.106429.
Morais Filho, L. F. F., K. C. de Meneses, G. A. de A. Santos, E. da S. Bicalho, G. de S. Rolim, and N. La Scala Jr, 2021: xCO2 temporal variability above Brazilian agroecosystems: A remote sensing approach. Journal of Environmental Management, 288, 112433, https://doi.org/10.1016/j.jenvman.2021.112433.
Moreno-Gamboa, F., and C. Nieto-Londoño, 2021: Hybrid Brayton Multi-Stage Concentrated Solar Power Plant Energy and Exergy Performance Study. Journal of Energy Resources Technology, 143, 062108, https://doi.org/10.1115/1.4050486.
Mugi-Ngenga, E., S. Zingore, L. Bastiaans, N. P. R. Anten, and K. E. Giller, 2021: Farm‐scale assessment of maize–pigeonpea productivity in Northern Tanzania. Nutr Cycl Agroecosyst, https://doi.org/10.1007/s10705-021-10144-7.
Ndiaye, P. M., A. Bodian, L. Diop, A. Dezetter, E. Guilpart, A. Deme, and A. Ogilvie, 2021: Future trend and sensitivity analysis of evapotranspiration in the Senegal River Basin. Journal of Hydrology: Regional Studies, 35, 100820, https://doi.org/10.1016/j.ejrh.2021.100820.
Okafor, G. C., I. Larbi, E. C. Chukwuma, C. Nyamekye, A. M. Limantol, and S.-Q. Dotse, 2021: Local climate change signals and changes in climate extremes in a typical Sahel catchment: The case of Dano catchment, Burkina Faso. Environmental Challenges, 5, 100285, https://doi.org/10.1016/j.envc.2021.100285.
de Oliveira Aparecido, P. A. Lorençone, J. A. Lorençone, K. C. de Meneses, and J. R. da Silva Cabral de Moraes, 2021: Climate changes and their influences in water balance of Pantanal biome. Theor Appl Climatol, 143, 659–674, https://doi.org/10.1007/s00704-020-03445-4.
Pushpalatha, R., and B. Gangadharan, 2021: Assessing the influence of climate model biases in predicting yield and irrigation requirement of cassava. Model. Earth Syst. Environ., 7, 307–315, https://doi.org/10.1007/s40808-020-01038-8.
Parenti, A., G. Cappelli, W. Zegada-Lizarazu, C. Martín Sastre, M. Christou, A. Monti, and F. Ginaldi, 2021: SunnGro: A new crop model for the simulation of sunn hemp (Crotalaria juncea L.) grown under alternative management practices. Biomass and Bioenergy, 146, 105975, https://doi.org/10.1016/j.biombioe.2021.105975.
Rana, N., and Coauthors, 2021: A preliminary assessment of the 7th February 2021 flashflood in lower Dhauli Ganga valley, Central Himalaya, India. J Earth Syst Sci, 130, 78, https://doi.org/10.1007/s12040-021-01608-z.
Rodrigues, G. and R.Braga, 2021: Evaluation of NASA POWER Reanalysis Products to Estimate Daily Weather Variables in a Hot Summer Mediterranean Climate. Agronomy, 11, 6, https://doi.org/10.3390/agronomy11061207.
Rodrigues, G. C., and R. P. Braga, 2021: Estimation of Daily Reference Evapotranspiration from NASA POWER Reanalysis Products in a Hot Summer Mediterranean Climate. Agronomy, 11, 2077, https://doi.org/10.3390/agronomy11102077.
Shahhosseini, M., G. Hu, I. Huber, and S. V. Archontoulis, 2021: Coupling machine learning and crop modeling improves crop yield prediction in the US Corn Belt. Sci Rep, 11, 1606, https://doi.org/10.1038/s41598-020-80820-1.
Shin, J., I. Hwang, D. Kim, T. Moon, J. Kim, W. H. Kang, and J. E. Son, 2021: Evaluation of the light profile and carbon assimilation of tomato plants in greenhouses with respect to film diffuseness and regional solar radiation using ray-tracing simulation. Agricultural and Forest Meteorology, 296, 108219, https://doi.org/10.1016/j.agrformet.2020.108219.
Tambo, J. A., M. Matimelo, M. Ndhlovu, F. Mbugua, and N. Phiri, 2021: Gender-differentiated impacts of plant clinics on maize productivity and food security: Evidence from Zambia. World Development, 145, 105519, https://doi.org/10.1016/j.worlddev.2021.105519.
Zagarese, H. E., and Coauthors, 2021: Patterns of CO2 concentration and inorganic carbon limitation of phytoplankton biomass in agriculturally eutrophic lakes. Water Research, 190, 116715, https://doi.org/10.1016/j.watres.2020.116715.
Almeida Silva, K., G. de Souza Rolim, T. T. Borges Valeriano, and J. R. da Silva Cabral de Moraes, 2020: Influence of El Niño and La Niña on coffee yield in the main coffee-producing regions of Brazil. Theor Appl Climatol, 139, 1019–1029, https://doi.org/10.1007/s00704-019-03039-9.
Amos, C., A. Rahman, J. Gathenya, E. Friedler, F. Karim, and A. Renzaho, 2020: Roof-Harvested Rainwater Use in Household Agriculture: Contributions to the Sustainable Development Goals. Water, 12, 332, https://doi.org/10.3390/w12020332.
Awe, G. O., T. N. Akomolafe, J. Umam, and M. B. Ayuba, 2020: Efficiency of small pan evaporimeter in monitoring evapotranspiration under poly-covered house and open-field conditions in a hot, tropical region of Nigeria. Journal of Hydrology: Regional Studies, 32, 100735, https://doi.org/10.1016/j.ejrh.2020.100735.
Bessah, E., A. O. Raji, O. J. Taiwo, S. K. Agodzo, O. O. Ololade, and A. Strapasson, 2020: Hydrological responses to climate and land use changes: The paradox of regional and local climate effect in the Pra River Basin of Ghana. Journal of Hydrology: Regional Studies, 27, 100654, https://doi.org/10.1016/j.ejrh.2019.100654.
Chan, H.-P., and K. I. Konstantinou, 2020: Multiscale and multitemporal surface temperature monitoring by satellite thermal infrared imagery at Mayon Volcano, Philippines. Journal of Volcanology and Geothermal Research, 401, 106976, https://doi.org/10.1016/j.jvolgeores.2020.106976.
Duarte, Y. C. N., and P. C. Sentelhas, 2020: NASA/POWER and DailyGridded weather datasets—how good they are for estimating maize yields in Brazil? Int J Biometeorol, 64, 319–329, https://doi.org/10.1007/s00484-019-01810-1.
Duarte, Y. C. N., and P. C. Sentelhas, 2020: Correction to: NASA/POWER and DailyGridded weather datasets—how good they are for estimating maize yields in Brazil? Int J Biometeorol, 64, 331–332, https://doi.org/10.1007/s00484-019-01834-7.
Frid, S. E., V. M. Simonov, N. V. Lisitskaya, N. R. Avezova, and A. E. Khaitmukhamedov, 2020: Efficiency of Solar Trackers and Bifacial Photovoltaic Panels for Southern Regions of the Russian Federation and the Republic of Uzbekistan. Appl. Sol. Energy, 56, 425–430, https://doi.org/10.3103/S0003701X20060031.
Gárate-Escamilla, H., C. C. Brelsford, A. Hampe, T. M. Robson, and M. B. Garzón, 2020: Greater capacity to exploit warming temperatures in northern populations of European beech is partly driven by delayed leaf senescence. Agricultural and Forest Meteorology, 284, 107908, https://doi.org/10.1016/j.agrformet.2020.107908.
Hariharan, R., 2020: COVID-19: A Boon for Tropical Solar Parks?: A Time Series Based Analysis and Forecasting of Solar Irradiance. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 1–9, https://doi.org/10.1080/15567036.2020.1839603.
Kyatengerwa, C., D. Kim, and M. Choi, 2020: A national-scale drought assessment in Uganda based on evapotranspiration deficits from the Bouchet hypothesis. Journal of Hydrology, 580, 124348, https://doi.org/10.1016/j.jhydrol.2019.124348.
Laarabi, B., Y. El Baqqal, A. Dahrouch, and A. Barhdadi, 2020: Deep analysis of soiling effect on glass transmittance of PV modules in seven sites in Morocco. Energy, 213, 118811, https://doi.org/10.1016/j.energy.2020.118811.
Jourdier, B., 2020: Evaluation of ERA5, MERRA-2, COSMO-REA6, NEWA and AROME to simulate wind power production over France. Adv. Sci. Res., 17, 63–77, https://doi.org/10.5194/asr-17-63-2020.
Liu, X., M. Charles, and B. R. Bakshi, 2019: Including Ecosystem Services in Life Cycle Assessment: Methodology and Application to Urban Farms. Procedia CIRP, 80, 287–291, https://doi.org/10.1016/j.procir.2018.12.004.
Mao, J., T. Addanki, M. Gebhard, F. Ghio, and H. Li, 2020: Eco-agriculture and Renewable Energy System Concept for a Rural Community in Ghana. IOP Conf. Ser.: Earth Environ. Sci., 568, 012046, https://doi.org/10.1088/1755-1315/568/1/012046.
Meneses, K. C. de, L. E. D. O. Aparecido, K. C. de Meneses, and M. F. de Farias, 2020: Estimating Potential Evapotranspiration in Maranhão State Using Artificial Neural Networks. Rev. bras. meteorol., 35, 675–682, https://doi.org/10.1590/0102-77863540072.
Moreno-Cadena, L. P., and Coauthors, 2020: Importance of genetic parameters and uncertainty of MANIHOT, a new mechanistic cassava simulation model. European Journal of Agronomy, 115, 126031, https://doi.org/10.1016/j.eja.2020.126031.
Nathan, O. O., N. K. Felix, K. N. Milka, M. Anne, A. Noah, and M. N. Daniel, 2020: Suitability of different data sources in rainfall pattern characterization in the tropical central highlands of Kenya. Heliyon, 6, e05375, https://doi.org/10.1016/j.heliyon.2020.e05375.
Nyagumbo, I., W. Mupangwa, L. Chipindu, L. Rusinamhodzi, and P. Craufurd, 2020: A regional synthesis of seven-year maize yield responses to conservation agriculture technologies in Eastern and Southern Africa. Agriculture, Ecosystems & Environment, 295, 106898, https://doi.org/10.1016/j.agee.2020.106898.
Okal, H. A., F. K. Ngetich, and J. M. Okeyo, 2020: Spatio-temporal characterisation of droughts using selected indices in Upper Tana River watershed, Kenya. Scientific African, 7, e00275, https://doi.org/10.1016/j.sciaf.2020.e00275.
de Oliveira Aparecido, L. E., J. R. da Silva Cabral de Moraes, K. C. de Meneses, G. B. Torsoni, R. F. de Lima, and C. T. S. Costa, 2020: Köppen-Geiger and Camargo climate classifications for the Midwest of Brasil. Theor Appl Climatol, 142, 1133–1145, https://doi.org/10.1007/s00704-020-03358-2.
Ozerova, M. G., A. V. Bastron, A. S. Debrin, N. B. Mikheeva, and I. N. Ermakova, 2020: The use of light filters in the photovoltaic solar power station to improve economic efficiency. IOP Conf. Ser.: Earth Environ. Sci., 421, 032016, https://doi.org/10.1088/1755-1315/421/3/032016.
Otter, P., and Coauthors, 2020: Economic evaluation of water supply systems operated with solar-driven electro-chlorination in rural regions in Nepal, Egypt and Tanzania. Water Research, 187, 116384, https://doi.org/10.1016/j.watres.2020.116384.
Perdinan, J. A. Winkler, and J. A. Andresen, 2020: Evaluation of Multiple Approaches to Estimate Daily Solar Radiation for Input to Crop Process Models. Atmosphere, 12, 8, https://doi.org/10.3390/atmos12010008.
Rattalino Edreira, J. I., S. Mourtzinis, G. Azzari, J. F. Andrade, S. P. Conley, D. Lobell, J. E. Specht, and P. Grassini, 2020: From sunlight to seed: Assessing limits to solar radiation capture and conversion in agro-ecosystems. Agricultural and Forest Meteorology, 280, 107775, https://doi.org/10.1016/j.agrformet.2019.107775.
Rodrigo, P. M., 2020: Balancing the shading impact in utility-scale dual-axis tracking concentrator photovoltaic power plants. Energy, 210, 118490, https://doi.org/10.1016/j.energy.2020.118490.
Ramborun, V., S. Facknath, and B. Lalljee, 2020: Moving toward sustainable agriculture through a better understanding of farmer perceptions and attitudes to cope with climate change. The Journal of Agricultural Education and Extension, 26, 37–57, https://doi.org/10.1080/1389224X.2019.1690012.
Rattalino Edreira, J. I., S. Mourtzinis, G. Azzari, J. F. Andrade, S. P. Conley, J. E. Specht, and P. Grassini, 2020: Combining field-level data and remote sensing to understand impact of management practices on producer yields. Field Crops Research, 257, 107932, https://doi.org/10.1016/j.fcr.2020.107932.
Salazar, G., C. Gueymard, J. B. Galdino, O. de Castro Vilela, and N. Fraidenraich, 2020: Solar irradiance time series derived from high-quality measurements, satellite-based models, and reanalyses at a near-equatorial site in Brazil. Renewable and Sustainable Energy Reviews, 117, 109478, https://doi.org/10.1016/j.rser.2019.109478.
Schwalbert, R. A., T. Amado, G. Corassa, L. P. Pott, P. V. V. Prasad, and I. A. Ciampitti, 2020: Satellite-based soybean yield forecast: Integrating machine learning and weather data for improving crop yield prediction in southern Brazil. Agricultural and Forest Meteorology, 284, 107886, https://doi.org/10.1016/j.agrformet.2019.107886.
Shadab, A., S. Ahmad, and S. Said, 2020: Spatial forecasting of solar radiation using ARIMA model. Remote Sensing Applications: Society and Environment, 20, 100427, https://doi.org/10.1016/j.rsase.2020.100427.
Sayago, S., G. Ovando, J. Almorox, and M. Bocco, 2020: Daily solar radiation from NASA-POWER product: assessing its accuracy considering atmospheric transparency. null, 41, 897–910, https://doi.org/10.1080/01431161.2019.1650986.
Fried, S. E., Lisitskaya, N. V., Tarasenko, A. B., Frolov, N. D., and Suleimanov, М. Zh., 2020: Using photovoltaic water heaters in hot climates. https://doi.org/10.5281/ZENODO.4018982.
Teixeira de Aguiar, J., and M. Lobo, 2020: Reliability and discrepancies of rainfall and temperatures from remote sensing and Brazilian ground weather stations. Remote Sensing Applications: Society and Environment, 18, 100301, https://doi.org/10.1016/j.rsase.2020.100301.
Aboelkhair, H., M. Morsy, and G. El Afandi, 2019: Assessment of agroclimatology NASA POWER reanalysis datasets for temperature types and relative humidity at 2 m against ground observations over Egypt. Advances in Space Research, 64, 129–142, https://doi.org/10.1016/j.asr.2019.03.032.
Aristizábal, A. J., J. Herrera, M. Castaneda, S. Zapata, D. Ospina, and E. Banguero, 2019: A new methodology to model and simulate microgrids operating in low latitude countries. Energy Procedia, 157, 825–836, https://doi.org/10.1016/j.egypro.2018.11.248.
Barzegar, R., M. Ghasri, Z. Qi, J. Quilty, and J. Adamowski, 2019: Using bootstrap ELM and LSSVM models to estimate river ice thickness in the Mackenzie River Basin in the Northwest Territories, Canada. Journal of Hydrology, 577, 123903, https://doi.org/10.1016/j.jhydrol.2019.06.075.
Esan, A. B., A. F. Agbetuyi, O. Oghorada, K. Ogbeide, Ayokunle. A. Awelewa, and A. E. Afolabi, 2019: Reliability assessments of an islanded hybrid PV-diesel-battery system for a typical rural community in Nigeria. Heliyon, 5, e01632, https://doi.org/10.1016/j.heliyon.2019.e01632.
Freire, M. M., and Coauthors, 2019: Site analysis in the Argentinean Andean region for the placement of astrophysical observatories and solar photovoltaic power plants. The case of the “Leoncito 2” site. Advances in Space Research, 64, 551–566, https://doi.org/10.1016/j.asr.2019.04.023.
Jha, P. K., P. Athanasiadis, S. Gualdi, A. Trabucco, V. Mereu, V. Shelia, and G. Hoogenboom, 2019: Evaluating the applicability of using daily forecasts from seasonal prediction systems (SPSs) for agriculture: a case study of Nepal’s Terai with the NCEP CFSv2. Theor Appl Climatol, 135, 1143–1156, https://doi.org/10.1007/s00704-018-2433-5.
Kimaru, A. N., J. M. Gathenya, and C. K. Cheruiyot, 2019: The Temporal Variability of Rainfall and Streamflow into Lake Nakuru, Kenya, Assessed Using SWAT and Hydrometeorological Indices. Hydrology, 6, 88, https://doi.org/10.3390/hydrology6040088.
Lollato, R. P., J. T. Edwards, and T. E. Ochsner, 2017: Meteorological limits to winter wheat productivity in the U.S. southern Great Plains. Field Crops Research, 203, 212–226, https://doi.org/10.1016/j.fcr.2016.12.014.
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