Publications Using POWER Data¶

Ganesh, K. E., 2023: Studies on the influence of particulate load in the atmosphere in attenuating the incoming solar radiation for two Indian mega cities. Arab J Geosci, 16, 45, https://doi.org/10.1007/s12517-022-11134-x.

Gaso, D. V., A. de Wit, S. de Bruin, L. A. Puntel, A. G. Berger, and L. Kooistra, 2023: Efficiency of assimilating leaf area index into a soybean model to assess within-field yield variability. European Journal of Agronomy, 143, 126718, https://doi.org/10.1016/j.eja.2022.126718.

Gupta, A., M. Gupta, P. K. Srivastava, G. P. Petropoulos, and R. K. Singh, 2023: Potassium Simulation Using HYDRUS-1D with Satellite-Derived Meteorological Data under Boro Rice Cultivation. Sustainability, 15, 2147, https://doi.org/10.3390/su15032147.

Kheyruri, Y., E. Nikaein, and A. Sharafati, 2023: Spatial monitoring of meteorological drought characteristics based on the NASA POWER precipitation product over various regions of Iran. Environ Sci Pollut Res, https://doi.org/10.1007/s11356-023-25283-3.

Oloyede, A., S. Ozuomba, P. Asuquo, L. Olatomiwa, and O. M. Longe, 2023: Data-driven techniques for temperature data prediction: big data analytics approach. Environ Monit Assess, 195, 343, https://doi.org/10.1007/s10661-023-10961-z.

Oloyede, O. A., N. Lopez, S. Ozuomba, P. Asuquo, E. Essien, and A. Agbu, 2023b: Upper-air meteorological dataset for Uyo, using radiosonde. Data in Brief, 46, 108904, https://doi.org/10.1016/j.dib.2023.10890.

Rockett, P. L., I. L. Campos, C. F. Baes, D. Tulpan, F. Miglior, and F. S. Schenkel, 2023: Phenotypic analysis of heat stress in Holsteins using test-day production records and NASA POWER meteorological data. Journal of Dairy Science, 106, 1142–1158, https://doi.org/10.3168/jds.2022-22370.

Torsoni, G. B., L. E. de Oliveira Aparecido, G. M. dos Santos, A. G. Chiquitto, J. R. da Silva Cabral Moraes, and G. de Souza Rolim, 2023: Soybean yield prediction by machine learning and climate. Theor Appl Climatol, https://doi.org/10.1007/s00704-022-04341-9.

Vais, A. A., V. V. Popova, A. A. Andronova, V. N. Nemich, A. G. Nepovinnykh, and P. V. Mikhaylov, 2023: Assessment of Carbon Productivity Dynamics in Aspen Stands under Climate Change Based on Forest Inventories in Central Siberia. Forests, 14, 109, https://doi.org/10.3390/f14010109.

Ahmed, M., A. Hoque, and M. K. Islam, 2022: A Trend Analysis of Climatic Variables in the Karimganj District of Assam, India. IJST, 15, 442–450, https://doi.org/10.17485/IJST/v15i10.109.

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.

Awan, M. M. A., M. Y. Javed, A. B. Asghar, K. Ejsmont, and Zia-ur-Rehman, 2022: Economic Integration of Renewable and Conventional Power Sources—A Case Study. Energies, 15, 2141, https://doi.org/10.3390/en15062141.

Bebeley, J. F., A. Y. Kamara, J. M. Jibrin, F. M. Akinseye, A. I. Tofa, A. M. Adam, N. Kamai, and R. Solomon, 2022: Evaluation and application of the CROPGRO-soybean model for determining optimum sowing windows of soybean in the Nigeria savannas. Sci Rep, 12, 6747, https://doi.org/s41598-022-10505-4.

Bista, D., D. Sapkota, H. Paudel, and G. Adhikari, 2022: Effect of Foliar Application of Growth Regulators on Growth and Yield of Onion (Allium cepa). Int J Hortic Sci Technol, 9, https://doi.org/10.22059/ijhst.2021.321019.451.

Chaichan, W., J. Waewsak, R. Nikhom, C. Kongruang, S. Chiwamongkhonkarn, and Y. Gagnon, 2022: Optimization of stand-alone and grid-connected hybrid solar/wind/fuel cell power generation for green islands: Application to Koh Samui, southern Thailand. Energy Reports, 8, 480–493, https://doi.org/10.1016/j.egyr.2022.07.024.

Chaudhary, S., and A. C. Pandey, 2022: PCA driven watershed prioritization based on runoff modeling and drought severity assessment in parts of Koel river basin, Jharkhand (India). Water Supply, 22, 2034–2054, https://doi.org/10.2166/ws.2021.297.

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, 2022: Spatiotemporal variability of atmospheric CO2 concentration and controlling factors over sugarcane cultivation areas in southern Brazil. Environ Dev Sustain, 24, 5694–5717, https://doi.org/10.1007/s10668-021-01677-6.

Hali̇mi̇, A. H., C. Karaca, and D. Büyüktaş, 2022: Evaluation of NASA POWER Climatic Data against Ground-Based Observations in The Mediterranean and Continental Regions of Turkey. JOTAF,https://doi.org/10.33462/jotaf.1073903.

Hamilton, J., M. Negnevitsky, and X. Wang, 2022: The role of modified diesel generation within isolated power systems. Energy, 240, 122829, https://doi.org/10.1016/j.energy.2021.122829.

Ibrahim, N. A., S. R. Wan Alwi, Z. A. Manan, A. A. Mustaffa, and K. Kidam, 2022: Risk matrix approach of extreme temperature and precipitation for renewable energy systems in Malaysia. Energy, 254, 124471, https://doi.org/10.1016/j.energy.2022.124471.

Jed, M., N. Ihaddadene, M. El Hacen Jed, R. Ihaddadene, and M. El Bah, 2022: Validation of the Accuracy of NASA Solar Irradiation Data for Four African Regions. IJSDP, 17, 29–39, https://doi.org/10.18280/ijsdp.170103.

Kassem, Y., and M. H. A. Abdalla, 2022: Modeling predictive suitability to identify the potential of wind and solar energy as a driver of sustainable development in the Red Sea state, Sudan. Environ Sci Pollut Res, 29, 44233–44254, https://doi.org/s11356-022-19062-9.

Khabibullaev, B. S., K. F. Shomurodov, and B. A. Adilov, 2022: Impact of long-term climate change on Moluccella bucharica (B. Fedtsch.) Ryding population decline in Uzbekistan. Plant Sci. Today,https://doi.org/10.14719/pst.1464.

Khalifa, A., B. Bashir, A. Alsalman, and H. Bachir, 2022: Morphometric-hydro Characterization of the Coastal Line between El-Qussier and Marsa-Alam, Egypt: Preliminary Flood Risk Signatures. Applied Sciences, 12, 6264, https://doi.org/10.3390/app12126264.

Kheyruri, Y., and A. Sharafati, 2022: Spatiotemporal Assessment of the NASA POWER Satellite Precipitation Product over Different Regions of Iran. Pure Appl. Geophys., 179, 3427–3439, https://doi.org/10.1007/s00024-022-03133-6.

Kumar, P., N. Pal, and H. Sharma, 2022: Optimization and techno-economic analysis of a solar photo-voltaic/biomass/diesel/battery hybrid off-grid power generation system for rural remote electrification in eastern India. Energy, 247, 123560, https://doi.org/10.1016/j.energy.2022.123560.

Kwawuvi, D., and Coauthors, 2022: An investigation into the future changes in rainfall onset, cessation and length of rainy season in the Oti River Basin, West Africa. Model. Earth Syst. Environ., 8, 5077–5095, https://doi.org/10.1007/s40808-022-01410-w.

Nawab, F., A. S. Abd Hamid, A. Alwaeli, M. Arif, M. F. Fauzan, and A. Ibrahim, 2022: Evaluation of Artificial Neural Networks with Satellite Data Inputs for Daily, Monthly, and Yearly Solar Irradiation Prediction for Pakistan. Sustainability, 14, 7945, https://doi.org/10.3390/su14137945.

Obiwulu, A. U., N. Erusiafe, M. A. Olopade, and S. C. Nwokolo, 2022: Modeling and estimation of the optimal tilt angle, maximum incident solar radiation, and global radiation index of the photovoltaic system. Heliyon, 8, e09598, https://doi.org/10.1016/j.heliyon.2022.e09598.

Oliveira Aparecido, L. E., J. A. Lorençone, P. A. Lorençone, G. Souza Rolim, K. C. Meneses, J. R. Silva Cabral de Moraes, and G. B. Torsoni, 2022: Can nonlinear agrometeorological models estimate coffee foliation? J Sci Food Agric, 102, 584–596, https://doi.org/10.1002/jsfa.11387.

Perondi, D., K. Boote, R. Souza Nóia Júnior, M. Mulvaney, J. Iboyi, and C. Fraisse, 2022: Assessment of soybean yield variability in the southeastern U.S. with the calibration of genetic coefficients from variety trials using CROPGRO‐Soybean. Agronomy Journal, 114, 1100–1114, https://doi.org/10.1002/agj2.20995.

Quansah, A. D., F. Dogbey, P. J. Asilevi, P. Boakye, L. Darkwah, S. Oduro-Kwarteng, Y. A. Sokama-Neuyam, and P. Mensah, 2022: Assessment of solar radiation resource from the NASA-POWER reanalysis products for tropical climates in Ghana towards clean energy application. Sci Rep, 12, 10684, https://doi.org/10.1038/s41598-022-14126-9.

Rana, M. M. S. P., M. A. Hossain, and N. M. R. Nasher, 2022: Identification of groundwater potential zone using geospatial techniques of agriculture dominated area in Dinajpur district, Bangladesh. Environmental Challenges, 7, 100475, https://doi.org/10.1016/j.envc.2022.100475.

Rizzo, G., S. R. Mazzilli, O. Ernst, W. E. Baethgen, and A. G. Berger, 2022: Season-specific management strategies for rainfed soybean in the South American Pampas based on a seasonal precipitation forecast. Agricultural Systems, 196, 103331, https://doi.org/10.1016/j.agsy.2021.103331.

Smith, K. E., P. J. Moore, N. G. King, and D. A. Smale, 2022: Examining the influence of regional‐scale variability in temperature and light availability on the depth distribution of subtidal kelp forests. Limnology & Oceanography, 67, 314–328, https://doi.org/10.1002/lno.11994.

Tejada, A. T., V. B. Ella, R. M. Lampayan, and C. E. Reaño, 2022: Modeling Reference Crop Evapotranspiration Using Support Vector Machine (SVM) and Extreme Learning Machine (ELM) in Region IV-A, Philippines. Water, 14, 754, https://doi.org/10.3390/w14050754.

Verma, S., A. Sharma, P. K. Yadava, P. Gupta, J. Singh, and S. Payra, 2022: Rapid flash flood calamity in Chamoli, Uttarakhand region during Feb 2021: an analysis based on satellite data. Nat Hazards, 112, 1379–1393, https://doi.org/10.1007/s11069-022-05232-y.

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-.

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/jfr3.1269.

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.2021.11469.

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.2021.10022.

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/w1202033.

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.

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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.2019.03.03.

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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.

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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.

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Schils, R., and Coauthors, 2018: Cereal yield gaps across Europe. European Journal of Agronomy, 101, 109–120, https://doi.org/10.1016/j.eja.2018.09.003.

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Bote, A. D., and J. Vos, 2017: Tree management and environmental conditions affect coffee (Coffea arabica L.) bean quality. NJAS - Wageningen Journal of Life Sciences, 83, 39–46, https://doi.org/10.1016/j.njas.2017.09.00.

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Lopez, J. R., J. M. Winter, J. Elliott, A. C. Ruane, C. Porter, and G. Hoogenboom, 2017: Integrating growth stage deficit irrigation into a process based crop model. Agricultural and Forest Meteorology, 243, 84–92, https://doi.org/10.1016/j.agrformet.2017.05.001.

Mourtzinis, S., J. I. Rattalino Edreira, S. P. Conley, and P. Grassini, 2017: From grid to field: Assessing quality of gridded weather data for agricultural applications. European Journal of Agronomy, 82, 163–172, https://doi.org/10.1016/j.eja.2016.10.013.

Negm, A., J. Jabro, and G. Provenzano, 2017: Assessing the suitability of American National Aeronautics and Space Administration (NASA) agro-climatology archive to predict daily meteorological variables and reference evapotranspiration in Sicily, Italy. Agricultural and Forest Meteorology, 244–245, 111–121, https://doi.org/10.1016/j.agrformet.2017.05.02.

Saha, D., A. R. Kemanian, B. M. Rau, P. R. Adler, and F. Montes, 2017: Designing efficient nitrous oxide sampling strategies in agroecosystems using simulation models. Atmospheric Environment, 155, 189–198, https://doi.org/10.1016/j.atmosenv.2017.01.05.

Seyoum, S., Y. Chauhan, R. Rachaputi, S. Fekybelu, and B. Prasanna, 2017: Characterising production environments for maize in eastern and southern Africa using the APSIM Model. Agricultural and Forest Meteorology, 247, 445–453, https://doi.org/10.1016/j.agrformet.2017.08.023.

Steward, P. R., A. J. Dougill, C. Thierfelder, C. M. Pittelkow, L. C. Stringer, M. Kudzala, and G. E. Shackelford, 2018: The adaptive capacity of maize-based conservation agriculture systems to climate stress in tropical and subtropical environments: A meta-regression of yields. Agriculture, Ecosystems & Environment, 251, 194–202, https://doi.org/10.1016/j.agee.2017.09.019.

Tollenaar, M., J. Fridgen, P. Tyagi, P. W. Stackhouse Jr, and S. Kumudini, 2017: The contribution of solar brightening to the US maize yield trend. Nature Clim Change, 7, 275–278, https://doi.org/10.1038/nclimate3234.

Basir Khan, M. R., R. Jidin, and J. Pasupuleti, 2016: Data from renewable energy assessments for resort islands in the South China Sea. Data in Brief, 6, 117–120, https://doi.org/10.1016/j.dib.2015.11.043.

El-Bendary, N., E. Elhariri, M. Hazman, S. M. Saleh, and A. E. Hassanien, 2016: Cultivation-time Recommender System Based on Climatic Conditions for Newly Reclaimed Lands in Egypt. Procedia Computer Science, 96, 110–119, https://doi.org/10.1016/j.procs.2016.08.109.

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Jain, M., A. Srivastava, Balwinder-Singh, R. Joon, A. McDonald, K. Royal, M. Lisaius, and D. Lobell, 2016: Mapping Smallholder Wheat Yields and Sowing Dates Using Micro-Satellite Data. Remote Sensing, 8, 860, https://doi.org/10.3390/rs8100860.

Mondal, S., R. P. Singh, E. R. Mason, J. Huerta-Espino, E. Autrique, and A. K. Joshi, 2016: Grain yield, adaptation and progress in breeding for early-maturing and heat-tolerant wheat lines in South Asia. Field Crops Research, 192, 78–85, https://doi.org/10.1016/j.fcr.2016.04.017.

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