Weather forecasts on timescales of days to season can be used to reduce vulnerability to weather variability as well as capitalize on opportunities. Substantial progress has been made in recent years on the development and applications of medium-range weather forecasts and seasonal climate predictions (CFSv2). From the perspective of business, weather forecasts on the sub-seasonal time scale provides an opportunity because it lies between the well-established application of daily weather forecasts and the increasing use of seasonal forecasts. Many decisions fall into the intervening two-weekly to two-monthly time scale, so the application of sub-seasonal forecasts provides the potential to augment actionable forecast information.
There is now a significant opportunity to develop methods that use sub-seasonal forecasts to provide actionable information. Probabilistic forecasts can be used to develop decision rules and hedging strategies, identify risk of exceeding critical thresholds, and support cost/loss scenarios and analysis.
When you look at your business as a whole, the weather only repeats itself year-to-year about 15-20% of the time. If the market-by-market, week-by-week weather volatility is left untouched when building demand forecasts, you are essentially expecting last year to happen again. It rarely does.
ExtendWeather is here to enable you to access this new and exciting data for decision making in your area of sectoral interest. The following brief descriptions review how seasonal and sub-seasonal forecasts may be applied across various sectors. Ultimately the decision making process is left with you as either the investor or planner or policy maker - i.e. the decision maker or team member in a decision support group.
The nation’s energy companies comprise the primary sector engaging the private sector meteorology industry. Weather is a primary driver for commodity prices in energy, having an impact on both energy production and consumption. Improved forecasts on sub-seasonal timescales would support hedging for anticipated energy demand, managing and protecting distribution and transmission infrastructure, and weather related energy trading opportunities and risks. The growth of renewable energy is providing new challenges and opportunities for applications of weather and climate forecasts. On sub-seasonal timescales, probabilistic predictions of wind, solar and hydropower generation can help stabilize energy costs and supply by improving scheduling and trading, maintenance scheduling, reducing curtailments and imbalance penalties, improving decisions about reserve energy sources, maximizing grid integration, and planning capacity commitments. Specific groups from the commercial sector that would benefit from sub-seasonal forecasts include energy trading firms, regional power generators/suppliers, and investors.
Weather forecasts support operational decision making on the timing of cultivating, irrigating, spraying, harvesting. Seasonal forecasts support strategic decisions regarding crop cultivar selection and intended acreage for planting. Sub-seasonal weather forecasts present a specific opportunity to bridge the gap in these two time frames. Viable forecast information beyond the traditional 10 day window can extend the time horizon for agricultural commodity price analysis and forecasting, and so support farmers’ decisions about production, storage and marketing, as well as logistical decisions in dealing with regional shortfalls and excess product availability. For commodities with futures markets, sub-seasonal weather forecasts can support hedging strategies. Futures, forward contracts and hedging are a prevalent practice with agricultural commodities. A sub-seasonal decision support system has the potential to help users better navigate what is often a volatile agricultural commodity marketplace and reign in risk exposure faced by agricultural producers and suppliers. It also has the potential to help various participants in the agriculture cycle more intelligently join in the appropriate risk management markets via the extension of reliable outlooks beyond the current limited time scales.
Application of seasonal and subseasonal foreacst data can provide the ‘look over the horizon’ increasingly required by water resource managers. Flash droughts when temperatures rise quickly and rainfall drops away can be ‘discovered’ weeks in advance and the knowledge can be factored into decision making earlier. Similarly the return of wetter weather can be signaled weeks and months in advance which can an invaluable piece of knowledge when planning for the phasing in of water restrictions or the planning of social media campaigns to change consumer behaviour.
Seasonal and sub-seasonal information on rainfall and cold spells can help forestry people to plan their work particularly during the planting period. Drought, floods and strong winds also have negative effects in the forest. Moreover, summer temperatures and rainfall affect nursery (clonal propagation) yields. Freezing and thawing conditions not only to help forestry workers to understand the growing seasons but also the conditions for driving through the forests and potential harvest conditions. With invasive plants and allergic plants, seasonal forecasts can help predict the change in the pollen production of these plants. To predict disease rates by using spring temperatures for example to predict the risk of a disease in the fall, or seasonal data that will help us come up with an overall risk for the coming season. Use seasonal and sub-seasonal forecast to manage warning systems.