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The quiet revolution of numerical weather prediction

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Cited by:

  1. Linsenmeier, Manuel & Shrader, Jeffrey G., 2023. "Global inequalities in weather forecasts," SocArXiv 7e2jf, Center for Open Science.
  2. Erick C. Jones & Benjamin D. Leibowicz, 2022. "Climate risk management in agriculture using alternative electricity and water resources: a stochastic programming framework," Environment Systems and Decisions, Springer, vol. 42(1), pages 117-135, March.
  3. Nissan, Hannah & Simmons, Will & Downs, Shauna M., 2022. "Building climate-sensitive nutrition programmes," LSE Research Online Documents on Economics 113561, London School of Economics and Political Science, LSE Library.
  4. Mayer, Martin János, 2022. "Benefits of physical and machine learning hybridization for photovoltaic power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  5. Steven M. Ramsey & Jason S. Bergtold & Jessica L. Heier Stamm, 2021. "Field‐Level Land‐Use Adaptation to Local Weather Trends," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(4), pages 1314-1341, August.
  6. Liu, Jiarui & Fu, Yuchen, 2023. "Renewable energy forecasting: A self-supervised learning-based transformer variant," Energy, Elsevier, vol. 284(C).
  7. Soukayna Mouatadid & Paulo Orenstein & Genevieve Flaspohler & Judah Cohen & Miruna Oprescu & Ernest Fraenkel & Lester Mackey, 2023. "Adaptive bias correction for improved subseasonal forecasting," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
  8. Brester, Christina & Kallio-Myers, Viivi & Lindfors, Anders V. & Kolehmainen, Mikko & Niska, Harri, 2023. "Evaluating neural network models in site-specific solar PV forecasting using numerical weather prediction data and weather observations," Renewable Energy, Elsevier, vol. 207(C), pages 266-274.
  9. Husain Najafi & Pallav Kumar Shrestha & Oldrich Rakovec & Heiko Apel & Sergiy Vorogushyn & Rohini Kumar & Stephan Thober & Bruno Merz & Luis Samaniego, 2024. "High-resolution impact-based early warning system for riverine flooding," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  10. Zhang, Gang & Yang, Dazhi & Galanis, George & Androulakis, Emmanouil, 2022. "Solar forecasting with hourly updated numerical weather prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
  11. Jinhua Wen & Yian Hua & Chenkai Cai & Shiwu Wang & Helong Wang & Xinyan Zhou & Jian Huang & Jianqun Wang, 2023. "Probabilistic Forecast and Risk Assessment of Flash Droughts Based on Numeric Weather Forecast: A Case Study in Zhejiang, China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
  12. Lisa Schlosser & Torsten Hothorn & Reto Stauffer & Achim Zeileis, 2018. "Distributional regression forests for probabilistic precipitation forecasting in complex terrain," Working Papers 2018-08, Faculty of Economics and Statistics, Universität Innsbruck, revised Nov 2018.
  13. Meng, Xiaochun & Taylor, James W., 2022. "Comparing probabilistic forecasts of the daily minimum and maximum temperature," International Journal of Forecasting, Elsevier, vol. 38(1), pages 267-281.
  14. Xueliang Zhao & Qilong Sun & Xiaoguang Lin, 2023. "Physical Attention-Gated Spatial-Temporal Predictive Network for Weather Forecasting," Mathematics, MDPI, vol. 11(6), pages 1-10, March.
  15. Sonia Quiroga & Emilio Cerdá, 2017. "Exploring farmers? selection of crop protection levels as an adaptation strategy to climate risks," Proceedings of Economics and Finance Conferences 4507414, International Institute of Social and Economic Sciences.
  16. Yufen Ma & Wei Han & Zhenglong Li & E. Eva Borbas & Ali Mamtimin & Yongqiang Liu, 2023. "Evaluation of CAMEL over the Taklimakan Desert Using Field Observations," Land, MDPI, vol. 12(6), pages 1-21, June.
  17. Robert Basmadjian & Amirhossein Shaafieyoun & Sahib Julka, 2021. "Day-Ahead Forecasting of the Percentage of Renewables Based on Time-Series Statistical Methods," Energies, MDPI, vol. 14(21), pages 1-23, November.
  18. Tang, Wenliang & Yang, Mian & Duan, Hongbo, 2023. "Temperature and corporate tax avoidance: Evidence from Chinese manufacturing firms," Energy Economics, Elsevier, vol. 117(C).
  19. Zack Guido & Sara Lopus & Kurt Waldman & Corrie Hannah & Andrew Zimmer & Natasha Krell & Chris Knudson & Lyndon Estes & Kelly Caylor & Tom Evans, 2021. "Perceived links between climate change and weather forecast accuracy: new barriers to tools for agricultural decision-making," Climatic Change, Springer, vol. 168(1), pages 1-20, September.
  20. Alexander Henzi & Johanna F. Ziegel & Tilmann Gneiting, 2021. "Isotonic distributional regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(5), pages 963-993, November.
  21. Paolo Figini & Simona Cicognani & Lorenzo Zirulia, 2023. "Booking in the Rain. Testing the Impact of Public Information on Prices," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(3), pages 1329-1364, November.
  22. Ying Li & Samuel N. Stechmann, 2022. "Systematic Assessment of the Effects of Space Averaging and Time Averaging on Weather Forecast Skill," Forecasting, MDPI, vol. 4(4), pages 1-20, November.
  23. Patrick Schmidt & Matthias Katzfuss & Tilmann Gneiting, 2021. "Interpretation of point forecasts with unknown directive," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 728-743, September.
  24. Boris V. Malozyomov & Nikita V. Martyushev & Svetlana N. Sorokova & Egor A. Efremenkov & Denis V. Valuev & Mengxu Qi, 2024. "Analysis of a Predictive Mathematical Model of Weather Changes Based on Neural Networks," Mathematics, MDPI, vol. 12(3), pages 1-17, February.
  25. Long Wang & Cheng Chen & Tongguang Wang & Weibin Wang, 2019. "Numerical Simulation of the Aeroelastic Response of Wind Turbines in Typhoons Based on the Mesoscale WRF Model," Sustainability, MDPI, vol. 12(1), pages 1-16, December.
  26. Liu, Chenyu & Zhang, Xuemin & Mei, Shengwei & Zhen, Zhao & Jia, Mengshuo & Li, Zheng & Tang, Haiyan, 2022. "Numerical weather prediction enhanced wind power forecasting: Rank ensemble and probabilistic fluctuation awareness," Applied Energy, Elsevier, vol. 313(C).
  27. Pelosi, A. & Chirico, G.B., 2021. "Regional assessment of daily reference evapotranspiration: Can ground observations be replaced by blending ERA5-Land meteorological reanalysis and CM-SAF satellite-based radiation data?," Agricultural Water Management, Elsevier, vol. 258(C).
  28. Magdalena Cornejo & Nicolás Merener & Ezequiel Merovich, 2024. "Extreme Dry Spells and Larger Storms in the U.S. Midwest Raise Crop Prices," Working Papers 303, Red Nacional de Investigadores en Economía (RedNIE).
  29. Karma Tsering & Manish Shrestha & Kiran Shakya & Birendra Bajracharya & Mir Matin & Jorge Luis Sanchez Lozano & Jim Nelson & Tandin Wangchuk & Binod Parajuli & Md Arifuzzaman Bhuyan, 2022. "Verification of two hydrological models for real-time flood forecasting in the Hindu Kush Himalaya (HKH) region," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(3), pages 1821-1845, February.
  30. Anand, Vaibhav, 2022. "The Value of Forecast Improvements: Evidence from Advisory Lead Times and Vehicle Crashes," MPRA Paper 114491, University Library of Munich, Germany.
  31. Schlenker, Wolfram & Taylor, Charles A., 2021. "Market expectations of a warming climate," Journal of Financial Economics, Elsevier, vol. 142(2), pages 627-640.
  32. Chuyuan Lin & Ying Yu & Lucas Y. Wu & Jiguo Cao, 2023. "Unsupervised learning on U.S. weather forecast performance," Computational Statistics, Springer, vol. 38(3), pages 1193-1213, September.
  33. Tom Brown & Fabian Neumann & Iegor Riepin, 2024. "Price formation without fuel costs: the interaction of elastic demand with storage bidding," Papers 2407.21409, arXiv.org.
  34. Yang, Dazhi & Kleissl, Jan, 2023. "Summarizing ensemble NWP forecasts for grid operators: Consistency, elicitability, and economic value," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1640-1654.
  35. Yang, Dazhi & Wang, Wenting & Gueymard, Christian A. & Hong, Tao & Kleissl, Jan & Huang, Jing & Perez, Marc J. & Perez, Richard & Bright, Jamie M. & Xia, Xiang’ao & van der Meer, Dennis & Peters, Ian , 2022. "A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  36. Jinliang Yao & Junwei Ji & Rongbo Wang & Xiaoxi Huang & Zhiming Kang & Xiaoran Zhuang, 2024. "DSADNet: A Dual-Source Attention Dynamic Neural Network for Precipitation Nowcasting," Sustainability, MDPI, vol. 16(9), pages 1-16, April.
  37. Žiga Zaplotnik & Aleksandar Gavrić & Luka Medic, 2020. "Simulation of the COVID-19 epidemic on the social network of Slovenia: Estimating the intrinsic forecast uncertainty," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-22, August.
  38. Mayer, Martin János & Yang, Dazhi, 2022. "Probabilistic photovoltaic power forecasting using a calibrated ensemble of model chains," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  39. Forbes, Kevin F. & Zampelli, Ernest M., 2020. "Accuracy of wind energy forecasts in Great Britain and prospects for improvement," Utilities Policy, Elsevier, vol. 67(C).
  40. Lin Zhu & Zhihua Zhang & M. James C. Crabbe & Lipon Chandra Das, 2023. "Optimization Hybrid of Multiple-Lag LSTM Networks for Meteorological Prediction," Mathematics, MDPI, vol. 11(22), pages 1-18, November.
  41. M. K. Islam & N. M. S. Hassan & M. G. Rasul & Kianoush Emami & Ashfaque Ahmed Chowdhury, 2023. "Forecasting of Solar and Wind Resources for Power Generation," Energies, MDPI, vol. 16(17), pages 1-23, August.
  42. Cailin Li & Na Sun & Yihui Lu & Baoyun Guo & Yue Wang & Xiaokai Sun & Yukai Yao, 2022. "Review on Urban Flood Risk Assessment," Sustainability, MDPI, vol. 15(1), pages 1-24, December.
  43. Liu, Jiarui & Fu, Yuchen, 2023. "Decomposition spectral graph convolutional network based on multi-channel adaptive adjacency matrix for renewable energy prediction," Energy, Elsevier, vol. 284(C).
  44. Tamás Hajdu & Gábor Hajdu, 2021. "Post-conception heat exposure increases clinically unobserved pregnancy losses," CERS-IE WORKING PAPERS 2104, Institute of Economics, Centre for Economic and Regional Studies.
  45. Alonzo, Bastien & Tankov, Peter & Drobinski, Philippe & Plougonven, Riwal, 2020. "Probabilistic wind forecasting up to three months ahead using ensemble predictions for geopotential height," International Journal of Forecasting, Elsevier, vol. 36(2), pages 515-530.
  46. Mayer, Martin János & Yang, Dazhi, 2023. "Calibration of deterministic NWP forecasts and its impact on verification," International Journal of Forecasting, Elsevier, vol. 39(2), pages 981-991.
  47. Heaney, Claire E. & Tang, Jieyi & Yan, Jintao & Guo, Donghu & Ipock, Jamesson & Kaluvakollu, Sanjana & Lin, Yushen & Shao, Danhui & Chen, Boyang & Mottet, Laetitia & Kumar, Prashant & Pain, Christophe, 2024. "Data assimilation with machine learning for dynamical systems: Modelling indoor ventilation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
  48. Lasse Espeholt & Shreya Agrawal & Casper Sønderby & Manoj Kumar & Jonathan Heek & Carla Bromberg & Cenk Gazen & Rob Carver & Marcin Andrychowicz & Jason Hickey & Aaron Bell & Nal Kalchbrenner, 2022. "Deep learning for twelve hour precipitation forecasts," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
  49. Huang Xiaoyan & He Li & Zhao Huasheng & Huang Ying & Wu Yushuang, 2020. "Objective approach for rainstorm based on dual-factor feature extraction and generalized regression neural network," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(3), pages 1987-2002, December.
  50. Bouche, Dimitri & Flamary, Rémi & d’Alché-Buc, Florence & Plougonven, Riwal & Clausel, Marianne & Badosa, Jordi & Drobinski, Philippe, 2023. "Wind power predictions from nowcasts to 4-hour forecasts: A learning approach with variable selection," Renewable Energy, Elsevier, vol. 211(C), pages 938-947.
  51. Huang, Xiubing & Wang, Naiyu, 2024. "An adaptive nested dynamic downscaling strategy of wind-field for real-time risk forecast of power transmission systems during tropical cyclones," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
  52. Sergei Soldatenko & Rafael Yusupov, 2021. "An Optimal Control Perspective on Weather and Climate Modification," Mathematics, MDPI, vol. 9(4), pages 1-15, February.
  53. Eva D. Regnier & Joel W. Feldmeier, 2022. "D Minus Months: Strategic Planning for Weather-Sensitive Decisions," Decision Analysis, INFORMS, vol. 19(1), pages 1-20, March.
  54. Yang, Dazhi & Yang, Guoming & Liu, Bai, 2023. "Combining quantiles of calibrated solar forecasts from ensemble numerical weather prediction," Renewable Energy, Elsevier, vol. 215(C).
  55. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
  56. Muschinski, Thomas & Mayr, Georg J. & Simon, Thorsten & Umlauf, Nikolaus & Zeileis, Achim, 2024. "Cholesky-based multivariate Gaussian regression," Econometrics and Statistics, Elsevier, vol. 29(C), pages 261-281.
  57. Liu, Bai & Yang, Dazhi & Mayer, Martin János & Coimbra, Carlos F.M. & Kleissl, Jan & Kay, Merlinde & Wang, Wenting & Bright, Jamie M. & Xia, Xiang’ao & Lv, Xin & Srinivasan, Dipti & Wu, Yan & Beyer, H, 2023. "Predictability and forecast skill of solar irradiance over the contiguous United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
  58. Yakoub, Ghali & Mathew, Sathyajith & Leal, Joao, 2023. "Intelligent estimation of wind farm performance with direct and indirect ‘point’ forecasting approaches integrating several NWP models," Energy, Elsevier, vol. 263(PD).
  59. Bashiri Behmiri, Niaz & Fezzi, Carlo & Ravazzolo, Francesco, 2023. "Incorporating air temperature into mid-term electricity load forecasting models using time-series regressions and neural networks," Energy, Elsevier, vol. 278(C).
  60. Ayyoob Sharifi & Zaheer Allam & Bakhtiar Feizizadeh & Hessam Ghamari, 2021. "Three Decades of Research on Smart Cities: Mapping Knowledge Structure and Trends," Sustainability, MDPI, vol. 13(13), pages 1-23, June.
  61. Minjia Chen & Yizhi Wang & Chunhui Yao & Adrian Wonfor & Shuai Yang & Richard Penty & Qixiang Cheng, 2024. "I/O-efficient iterative matrix inversion with photonic integrated circuits," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  62. Franko Pandžić & Tomislav Capuder, 2023. "Advances in Short-Term Solar Forecasting: A Review and Benchmark of Machine Learning Methods and Relevant Data Sources," Energies, MDPI, vol. 17(1), pages 1-19, December.
  63. Conor Sweeney & Ricardo J. Bessa & Jethro Browell & Pierre Pinson, 2020. "The future of forecasting for renewable energy," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 9(2), March.
  64. Baïle, Rachel & Muzy, Jean-François, 2023. "Leveraging data from nearby stations to improve short-term wind speed forecasts," Energy, Elsevier, vol. 263(PA).
  65. Pelosi, A., 2023. "Performance of the Copernicus European Regional Reanalysis (CERRA) dataset as proxy of ground-based agrometeorological data," Agricultural Water Management, Elsevier, vol. 289(C).
  66. Rachel Cassidy & Phil Jordan & Marianne Bechmann & Brian Kronvang & Katarina Kyllmar & Mairead Shore, 2018. "Assessments of Composite and Discrete Sampling Approaches for Water Quality Monitoring," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(9), pages 3103-3118, July.
  67. Andrew J Reagan & Yves Dubief & Peter Sheridan Dodds & Christopher M Danforth, 2016. "Predicting Flow Reversals in a Computational Fluid Dynamics Simulated Thermosyphon Using Data Assimilation," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-19, February.
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