# Machine Learning Methods in Weather and Climate Applications: A Survey
###### Abstract
Medium-to-long-term climate prediction.Medium-to-long-term climate forecasting (MLTF) concentrates on projecting climate conditions over periods extending from several months to multiple years, in contrast to short-term weather forecasts, which focus more on immediate atmospheric conditions. The time frame of these climate forecasts can be segmented into medium-term, which generally ranges from a single season up to a year, and long-term, which could span years to decades or even beyond [19]. Unlike weather forecasts, which may provide information on imminent rainfall or snowfall, MLTF centers \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Time Scale** & **Domains** & **Applications** \\ \hline \multirow{8}{*}{Short Term} & Agriculture & The timing for sowing and harvesting; \\  & Agriculture & Irrigation and fertilization plans [5]. \\ \cline{2-3}  & Energy & Predicts output for wind and solar energy [6]. \\ \cline{2-3}  & Transportation & Road traffic safety; Rail transport; \\  & Aviation and maritime industries [7]. \\ \cline{2-3}  & Construction & Project plans and timelines; Safe operations [8]. \\ \cline{2-3}  & Retail and Sales & Adjusts inventory based on weather forecasts [9]. \\ \cline{2-3}  & Tourism and & Operations of outdoor activities \\ \cline{2-3}  & Entertainment & and tourist attractions [10] \\ \cline{2-3}  & Environment and & Early warnings for floods, fires, and other natural disasters [11]. \\ \hline \multirow{8}{*}{Medium—Long Term} & Agriculture & Long-term land management and planning [12]. \\ \cline{2-3}  & Insurance & Preparations for future increases in types of disasters, such as floods and droughts [13]. \\ \cline{2-3}  & Real Estate & Assessment of future sea-level rise or other climate-related factors [14]. \\ \cline{2-3}  & Urban Planning & Water resource management [15]. \\ \cline{2-3}  & Tourism & Long-term investments and planning, such as deciding which regions may become popular tourist destinations in the future [16]. \\ \cline{2-3}  & Public Health & Long-term climate changes may impact the spread of diseases [17]. \\ \hline \end{tabular}
\end{table} 
Table 1: Applications of Short term and medium-long term weather/climate forecasting in daily life. on the average states or trends of climate variables, such as average temperature and precipitation, ocean-atmosphere interactions like El Nino or La Nina conditions, and the likelihood of extreme weather events like droughs or floods, as well as anticipated hurricane activities [20]. The projection also encompasses broader climate trends, such as global warming or localized climatic shifts. These forecasts employ a variety of methods, including statistical models based on historical data and seasonal patterns, dynamical models that operate on complex mathematical equations rooted in physics, and integrated models that amalgamate multiple data sources and methodologies. However, the accuracy of medium- to long-term climate forecasting often falls short when compared with short-term weather predictions due to the intricate, multi-scale, and multi-process interactions that constitute the climate system, not to mention the lack of exhaustive long-term data. The forecasts' reliability can also be influenced by socio-economic variables, human activities, and shifts in policy. Despite these complexities, medium- to-long-term climate projections serve pivotal roles in areas such as resource management, agricultural planning, disaster mitigation, and energy policy formulation, making them not only a multi-faceted, multi-disciplinary challenge but also a crucial frontier in both climate science and applied research. **Survey Scope. ** In recent years, machine learning has emerged as a potent tool in meteorology, displaying strong capabilities in feature abstraction and trend prediction. Numerous studies have employed machine learning as the principal methodology for weather forecasting [21; 22].