Implementing Weather Generators for Prediction of Future Climate Changes: A Review Paper
Article Sidebar
Main Article Content
Abstract
The changes in weather and climate patterns have prompted the world to conduct comprehensive and in-depth studies and research due to their direct impact on all aspects of life. Therefore, predicting climate using historical data for a specific area is vital to studying and knowing the level of impact of the resulting change in terms of hydrological, meteorological, and agricultural aspects. In this study, a comprehensive review of the latest and most popular weather generators used in the world was surveyed. A thorough evaluation of 92 papers published between 2000 and 2023 was analyzed and discussed in terms of the geographical locations and climatological conditions, time scale, predictors, and capabilities of weather generators models. Starting in early September 2023, the study made use of the search boxes on Scopus, IEEE Xplore, ScienceDirect, Web of Science, Semantic Scholar, PubMed, and Connected Papers databases. The terms "Weather Generators", "Climate Changes", and “Meteorological Parameters" were mixed with auxiliary words like "Applications", "Program," "Code", and "Software", as well as different variations of the terms "forecasting", "projection", and "prediction", in addition to the main terms. Hence, the reviewed papers provide an insightful tool for researchers to use the weather generator models in similar studies. Ultimately, the study presents a comprehensive and cutting-edge overview of weather generator applications, highlighting the most promising approach for future studies, which helps researchers and those interested in understanding the causes of climate change.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
THIS IS AN OPEN ACCESS ARTICLE UNDER THE CC BY LICENSE http://creativecommons.org/licenses/by/4.0/
Plaudit
References
Core Writing Team, Pachauri RK, Meyer LA. Climate Change 2014: Synthesis Report. IPCC, Geneva, Switzerland; 2014.
Diffenbaugh NS, Field CB. Changes in Ecologically Critical Terrestrial Climate Conditions. Science 2013; 341(6145): 486–492.
Hsiang SM, Burke M, Miguel E. Quantifying the Influence of Climate on Human Conflict. Science 2013; 341(6151): 1235367.
Ansari A, Pranesti A, Telaumbanua M, Alam T, Taryono, Wulandari RA, et al. Evaluating the Effect of Climate Change on Rice Production in Indonesia Using Multimodelling Approach. Heliyon 2023; 9(9): e19539.
Diffenbaugh NS, Swain DL, Touma D, Lubchenco J. Anthropogenic Warming Has Increased Drought Risk in California. Proceedings of the National Academy of Sciences of the United States of America 2015; 112(13): 3931–3936.
Easterling DR, Meehl GA, Parmesan C, Changnon SA, Karl TR, Mearns LO. Climate Extremes: Observations, Modeling, and Impacts. Science 2000; 289(5487): 2068–2074.
Duan Z, Song X. Mapping Cover and Management Factor Based on Weather Generator and Remote Sensing. International Workshop on Education Technology and Training & International Workshop on Geoscience and Remote Sensing; 2008; Shanghai, China; pp. 464–467.
Hong NM, Lee TY, Chen YJ. Daily Weather Generator with Drought Properties by Copulas and Standardized Precipitation Indices. Environmental Monitoring and Assessment 2016; 188(6): 335.
Ullrich SL, Hegnauer M, Nguyen DV, Merz B, Kwadijk J, Vorogushyn S. Comparative Evaluation of Two Types of Stochastic Weather Generators for Synthetic Precipitation in the Rhine Basin. Journal of Hydrology 2021; 601: 126588.
Collados-Lara AJ, Pardo-Igúzquiza E, Pulido-Velazquez D. Assessing the Impact of Climate Change – and Its Uncertainty – on Snow Cover Areas by Using Cellular Automata Models and Stochastic Weather Generators. Science of the Total Environment 2021; 788: 147693.
Li Y, Sun Y. A Multi-Site Stochastic Weather Generator for High-Frequency Precipitation Using Censored Skew-Symmetric Distribution. Spatial Statistics 2021; 41: 100484.
Farhani N, Carreau J, Kassouk Z, Mougenot B, Le Page M, Lili-Chabaane Z, et al. Sub-Daily Stochastic Weather Generator Based on Reanalyses for Water Stress Retrieval in Central Tunisia. HAL 2020; hal-02902163.
Ahn KH. Coupled Annual and Daily Multivariate and Multisite Stochastic Weather Generator to Preserve Low- and High-Frequency Variability to Assess Climate Vulnerability. Journal of Hydrology 2020; 581: 124396.
Verdin A, Rajagopalan B, Kleiber W, Podestá G, Bert F. A Conditional Stochastic Weather Generator for Seasonal to Multi-Decadal Simulations. Journal of Hydrology 2018; 556: 835–846.
Hashmi MZ, Shamseldin AY, Melville BW. Downscaling of Future Rainfall Extreme Events: A Weather Generator Based Approach. *18th World IMACS Congress and MODSIM 2009 - International Congress on Modelling and Simulation: Interfacing Modelling and Simulation with Mathematical and Computational Sciences, Proceedings*; 2009; pp. 3928–3934.
Al-Mukhtar M, Dunger V, Merkel B. Evaluation of the Climate Generator Model CLIGEN for Rainfall Data Simulation in Bautzen Catchment Area, Germany. Hydrology Research 2014; 45(4–5): 615–630.
Ibeje AO, Osuagwu JC, Onosakponome OR. A Markov Model for Prediction of Annual Rainfall. International Journal of Scientific Engineering and Applied Science (IJSEAS) 2018; 4(3): 1–7.
Ng JL, Abd Aziz S, Huang YF, Wayayok A, Rowshon M. Generation of a Stochastic Precipitation Model for the Tropical Climate. Theoretical and Applied Climatology 2018; 133(1–2): 489–509.
Dastidar AG, Ghosh D, Dasgupta S, De UK. Higher Order Markov Chain Models for Monsoon Rainfall over West Bengal, India. Indian Journal of Radio and Space Physics 2010; 39(1): 39–44.
Abreu MC, de Souza A, Lyra GB, de Oliveira-Júnior JF, Pobocikova I, de Almeida LT, et al. Assessment and Characterization of the Monthly Probabilities of Rainfall in Midwest Brazil Using Different Goodness-of-Fit Tests as Probability Density Functions Selection Criteria. Theoretical and Applied Climatology 2023; 151(1–2): 491–513.
Mahgoub Mohamed T, Abd Allah Ibrahim A. Fitting Probability Distributions of Annual Rainfall in Sudan. SUST Journal of Engineering and Computer Sciences (JECS) 2016; 17(2): 21–30.
Ye L, Hanson LS, Ding P, Wang D, Vogel RM. The Probability Distribution of Daily Precipitation at the Point and Catchment Scales in the United States. Hydrology and Earth System Sciences 2018; 22(12): 6519–6531.
Richardson CW. Stochastic Simulation of Daily Precipitation, Temperature, and Solar Radiation. Water Resources Research 1981; 17(1): 182–190.
Racsko P, Szeidl L, Semenov M. A Serial Approach to Local Stochastic Weather Models. Ecological Modelling 1991; 57(1–2): 27–41.
Yiou P. AnaWEGE: A Weather Generator Based on Analogues of Atmospheric Circulation. Geoscientific Model Development 2014; 7(2): 531–543.
Mairech H, López-Bernal Á, Testi L, Villalobos FJ. ClimaSG: A Weather Generator for Crop Modelling and Water Requirements Studies. Agricultural Water Management 2022; 271: 107789.
Saha A, Ravela S. Downscaling Extreme Rainfall Using Physical-Statistical Generative Adversarial Learning. Journal of Advances in Modeling Earth Systems 2022; 14(9): e2022MS003120.
Gilewski P. Application of Global Environmental Multiscale (GEM) Numerical Weather Prediction (NWP) Model for Hydrological Modeling in Mountainous Environment. Atmosphere 2022; 13(9): 1367.
Sommer PS, Kaplan JO. A Globally Calibrated Scheme for Generating Daily Meteorology from Monthly Statistics: Global-WGEN (GWGEN) v1.0. Geoscientific Model Development 2017; 10(10): 3771–3791.
Vallam P, Qin XS. Multi-Site Rainfall Simulation at Tropical Regions: A Comparison of Three Types of Generators. Meteorological Applications 2016; 23(3): 425–437.
Hartkamp AD, White JW, Hoogenboom G. Comparison of Three Weather Generators for Crop Modeling: A Case Study for Subtropical Environments. Agricultural Systems 2003; 76(2): 539–560.
Hernández-Bedolla J, Solera A, Paredes-Arquiola J, Sanchez-Quispe ST, Domínguez-Sánchez C. A Continuous Multisite Multivariate Generator for Daily Temperature Conditioned by Precipitation Occurrence. Water 2022; 14(21): 3525.
Nesrine Farhani, Julie Carreau, Zeineb Kassouk, Bernard Mougenot, Michel Le Page, Zohra Lili-Chabaane, Rim Zitouna-Chebbi GB. Regional Sub-Daily Stochastic Weather Generator Based on Reanalyses for Surface Water Stress Estimation in Central Tunisia. Environmental Modelling & Software 2022; 155: 105446.
Mehrotra R, Li J, Westra S, Sharma A. A Programming Tool to Generate Multi-Site Daily Rainfall Using a Two-Stage Semi Parametric Model. Environmental Modelling and Software 2015; 63: 230–239.
Hermann N’ V, Bi G, Adjakpa TT, Allechy FB, Youan Ta M, Yapi AF, et al. Performance of Multi-Site Stochastic Weather Generator MulGETS: Application to the Lobo Watershed (Western Center of Côte d’Ivoire). International Journal of Innovative Science and Research Technology 2020; 5(12): 1274–1279.
Fodor N, Dobi I, Mika J, Szeidl L. Applications of the MVWG Multivariable Stochastic Weather Generator. The Scientific World Journal 2013; 2013: 348547.
Vu TM, Mishra AK, Konapala G, Liu D. Evaluation of Multiple Stochastic Rainfall Generators in Diverse Climatic Regions. Stochastic Environmental Research and Risk Assessment 2018; 32(5): 1337–1353.
Vu TM, Mishra AK, Konapala G, Liu D. Generation of Multi-Site Stochastic Daily Rainfall with Four Weather Generators a Case Study of Gloucester Catchment in Australia. Stochastic Environmental Research and Risk Assessment 2018; 32(5): 1337–1353.
Emanuele Cordano EE. The Stationarity of Two Statistical Downscaling Methods for Precipitation Under Different Choices of Cross-Validation Periods. Italian Journal of Agrometeorology 2016; 21(3): 17–30.
Cordano E, Eccel E. Tools for Stochastic Weather Series Generation in R Environment. Italian Journal of Agrometeorology 2016; 21(3): 31–42.
Soltani A, Hoogenboom G. Minimum Data Requirements for Parameter Estimation of Stochastic Weather Generators. Climate Research 2003; 25: 109–119.
Ng JL, Abd Aziz S, Huang YF, Wayayok A, Rowshon MK. Stochastic Modelling of Seasonal and Yearly Rainfalls with Low-Frequency Variability. Stochastic Environmental Research and Risk Assessment 2017; 31(9): 2215–2233.
Flecher C, Naveau P, Allard D, Brisson N. A Stochastic Daily Weather Generator for Skewed Data. Water Resources Research 2010; 46(7): W07519.
Chen J, Brissette FP, Leconte R. WeaGETS – A Matlab-Based Daily Scale Weather Generator for Generating Precipitation and Temperature. Procedia Environmental Sciences 2012; 13: 2222–2235.
Muza MN. Application of Weather Generation to High Frequency and High Resolution Gridded Datasets in Sao Paulo. Advances in Plants & Agriculture Research 2014; 1(2): 00009.
Qian B, Gameda S, De Jong R, Falloon P, Gornall J. Comparing Scenarios of Canadian Daily Climate Extremes Derived Using a Weather Generator. Climate Research 2010; 41(2): 131–149.
Xiaoying Yang, Ruimin He, Jinyin Ye, Mou Leong Tan, Xiyan Ji, Lit Tan GW. Integrating an Hourly Weather Generator with an Hourly Rainfall SWAT Model for Climate Change Impact Assessment in the Ru River Basin, China. Atmospheric Research 2020; 244: 105059.
Vesely FM, Paleari L, Movedi E, Bellocchi G, Confalonieri R. Quantifying Uncertainty Due to Stochastic Weather Generators in Climate Change Impact Studies. Scientific Reports 2019; 9(1): 11011.
Timothy J. Osborn, Craig J. Wallace ICH& TMM. Pattern Scaling Using ClimGen Monthly-Resolution Future Climate Scenarios Including Changes in the Variability of Precipitation. Climatic Change 2016; 134(3): 353–369.
Forsythe N, Fowler HJ, Blenkinsop S, Burton A, Kilsby CG, Archer DR, Harpham MZH. Application of a Stochastic Weather Generator to Assess Climate Change Impacts in a Semi-Arid Climate: The Upper Indus Basin. Journal of Hydrology 2014; 517: 1019–1034.
Xu YP, Ma C, Pan SL, Zhu Q, Ran QH. Evaluation of a Multi-Site Weather Generator in Simulating Precipitation in the Qiantang River Basin, East China. Journal of Zhejiang University: Science A (Applied Physics & Engineering) 2014; 15(3): 219–230.
Doaa R. Mohammed RKM. Climate Change’s Impacts on Drought in Upper Zab Basin, Iraq: A Case Study. Tikrit Journal of Engineering Science 2024; 31(1): 161–171.
Ahmadi M, Etedali HR, Elbeltagi A. Evaluation of the Effect of Climate Change on Maize Water Footprint under RCPs Scenarios in Qazvin Plain, Iran. Agricultural Water Management 2021; 254: 106963.
Shagega FP, Munishi SE, Kongo VM. Prediction of Future Climate in Ngerengere River Catchment, Tanzania. Physics and Chemistry of the Earth 2019; 112: 200–209.
Chisanga CB, Phiri E, Chinene VRN. Statistical Downscaling of Precipitation and Temperature Using Long Ashton Research Station Weather Generator in Zambia: A Case of Mount Makulu Agriculture Research Station. American Journal of Climate Change 2017; 06(03): 487–512.
Osman Y, Al-Ansari N, Abdellatif M, Aljawad SB, Knutsson S. Expected Future Precipitation in Central Iraq Using LARS-WG Stochastic Weather Generator. Engineering 2014; 06(13): 948–959.
Liu J, Williams JR, Wang X, Yang H. Using MODAWEC to Generate Daily Weather Data for the EPIC Model. Environmental Modelling and Software 2009; 24(5): 655–664.
Al-Mukhtar M, Qasim M. Future Predictions of Precipitation and Temperature in Iraq Using the Statistical Downscaling Model. Arabian Journal of Geosciences 2019; 12(2): 1–15.
Smith K, Strong C, Rassoul-Agha F. Multisite Generalization of the SHArP Weather Generator. Journal of Applied Meteorology and Climatology 2018; 57(9): 2113–2127.
Martin Dubrovsky, Radan Huth HD& MWR. Parametric Gridded Weather Generator for Use in Present and Future Climates - Focus on Spatial Temperature Characteristics. Theoretical and Applied Climatology 2020; 139(3–4): 1031–1044.
Glenis V, Pinamonti V, Hall JW, Kilsby CG. A Transient Stochastic Weather Generator Incorporating Climate Model Uncertainty. Advances in Water Resources 2015; 85: 14–26.
Obaidullah Yaqubi, Auline Rodler, Sihem Guernouti MM. Creation and Application of Future Typical Weather Files in the Evaluation of Indoor Overheating in Free-Floating Buildings. Building and Environment 2022; 216: 109008.
Aliabadi AA, Chen X, Yang J, Madadizadeh A, Siddiqui K. Retrofit Optimization of Building Systems for Future Climates Using an Urban Physics Model. Building and Environment 2023; 243: 110654.
Li Z, Brissette F, Chen J. Assessing the Applicability of Six Precipitation Probability Distribution Models on the Loess Plateau of China. International Journal of Climatology 2014; 34(2): 462–471.
Ng JL, Abd Aziz S, Huang YF, Wayayok A, Rowshon M. Generation of a Stochastic Precipitation Model for the Tropical Climate. Theoretical and Applied Climatology 2018; 133(1–2): 489–509.
Wei W, Yan Z, Jones PD. Potential Predictability of Seasonal Extreme Precipitation Accumulation in China. Journal of Hydrometeorology 2017; 18(4): 1071–1080.
Chowdhury AK, Kar KK, Shahid S, Chowdhury R, Rashid MM. Evaluation of Spatio-Temporal Rainfall Variability and Performance of a Stochastic Rainfall Model in Bangladesh. International Journal of Climatology 2019; 39(11): 4256–4273.
Gao C, Booij MJ, Xu YP. Development and Hydrometeorological Evaluation of a New Stochastic Daily Rainfall Model: Coupling Markov Chain with Rainfall Event Model. Journal of Hydrology 2020; 589: 125118.
Mehrotra R, Sharma A, Kumar DN, Reshmidevi TV. Assessing Future Rainfall Projections Using Multiple GCMS and a Multi-Site Stochastic Downscaling Model. Journal of Hydrology 2013; 488: 84–100.
Abas N, Daud ZM, Yusof F. A Comparative Study of Mixed Exponential and Weibull Distributions in a Stochastic Model Replicating a Tropical Rainfall Process. Theoretical and Applied Climatology 2014; 118(3): 597–607.
Long Y, Tang R, Wang H, Jiang C. Monthly Precipitation Modeling Using Bayesian Non-Homogeneous Hidden Markov Chain. Hydrology Research 2019; 50(2): 562–576.
Patidar S, Tanner E, Soundharajan BS, Sengupta B. Associating Climatic Trends with Stochastic Modelling of Flow Sequences. Geosciences 2021; 11(6): 263.
Lee T, Singh VP. Discrete k-Nearest Neighbor Resampling for Simulating Multisite Precipitation Occurrence and Model Adaption to Climate Change. Geoscientific Model Development 2019; 12(3): 1189–1207.
Chen J, Brissette FP. Comparison of Five Stochastic Weather Generators in Simulating Daily Precipitation and Temperature for the Loess Plateau of China. International Journal of Climatology 2014; 34(10): 3089–3105.