Use Of Seasonal Forecasts Research Articles

Exploring the use of seasonal forecasts to adapt flood insurance premiums

Exploring the use of seasonal forecasts to adapt flood insurance premiums

Persistence versus dynamical seasonal forecasts of cereal crop yields.

Climate change is expected to have impacts on the balance of global food trade networks and food security. Thus, seasonal forecasts of precipitation and temperature are an essential tool for stakeholders to make timely choices regarding the strategies required to maximize their expected cereal yield outcomes. The availability of state-of-the-art seasonal forecasts such as the European Centre for Medium-Range Weather Forecasts (ECMWF) system 5 (SEAS5) may be an asset to help decision making. However, uncertainties and reduced skill may hamper the use of seasonal forecasts in several applications. Hence, in this work, we aim to understand the added value of such dynamical forecasts when compared to persistent anomalies of climate conditions used to predict the production of wheat and barley yields. With that in mind, empirical models relating annual wheat and barley yields in Spain to monthly values of precipitation and temperature are developed by taking advantage of ECMWF ERA5 reanalysis. Then, dynamical and persistence forecasts are issued at different lead times, and the skill of the subsequent forecasted yield is verified through probabilistic metrics. The results presented in this study demonstrate two different outcomes: (1) wheat and barley yield anomaly forecasts (dynamical and persistent) start to gain skill later in the season (typically from April onwards); and (2) the added value of using the SEAS5 forecast as an alternative to persistence ranges from 6 to 16%, with better results in the southern Spanish regions.

Exploring the landscape of seasonal forecast provision by Global Producing Centres

Despite the growing demand for seasonal climate forecasts, there is limited understanding of the landscape of organisations providing this critically important climate information. This study attempts to fill this gap by presenting results from an in-depth dialogue with the organisations entrusted with the provision of seasonal forecasts by the World Meteorological Organisation, known as the Global Producing Centres for Long-Range Forecasts (GPCs-LRF). The results provide an overview and detailed description of the organisational setup, mandate, target audience of GPCs-LRF and their interactions with other centres. Looking beyond the GPCs-LRF to other centres providing seasonal forecasts, some of which have been rapidly taking prominent places in this landscape, revealed a heterogeneous and still maturing community of practice, with an increasing number of players and emerging efforts to produce multi-model ensemble forecasts. The dialogues pointed at the need to not only improve climate models and produce more skilful climate forecasts, but also to improve the transformation of the forecasts into useful and usable products. Finally, using the lenses of credibility, salience and legitimacy, we explore ways to bridge the fragmentation of the information offered across the organisations considered and the people involved in the delivery and use of seasonal forecasts. The paper concludes by suggesting ways to address the boundary crossing between science, policy and society in the context of seasonal climate prediction.

The potential benefit of the use of seasonal forecast during the agricultural economic year 2019-2020 in Bulgaria

Seasonal forecasting gained ground in the last decades by building up knowledge on the processes staying behind the climate variability at the seasonal time scale, constructing ever more sophisticated general circulation models and ensemble prediction systems and thus enhancing forecast skill. The seasonal forecast is a climate forecast and is therefore probabilistic in nature. The predictability of the atmospheric circulation at the seasonal scale is limited in the middle latitudes, where Europe and Bulgaria are situated, by its chaotic nature. The current standard is to give forecast of the potential anomalies of the mean seasonal temperature and the seasonal amount of precipitation. The National Institute of Meteorology and Hydrology of Bulgaria has been issuing operationally seasonal forecast for the country since 2005. The goal of this work is to discuss the seasonal forecast for the last agricultural year 2019-2020. The year was characterized by its drought conditions especially in Eastern Bulgaria. This work would show the extent to which it was successfully predicted and how the seasonal forecast could have been used for decision making. The use of agrometeorological indices for the analysis of the skill of the seasonal forecast has been shown.

Understanding the Role of User Needs and Perceptions Related to Sub-Seasonal and Seasonal Forecasts on Farmers' Decisions in Kenya: A Systematic Review

One major challenge facing farmers and other end users of weather and climate information (WCI) in Kenya is the linkage between their perceptions, needs, and engagements with producers of the information. This is highlighted by increased interest in understanding the constraints on appropriate use of weather information by farmers in decision-making. The choice between sub-seasonal and seasonal forecasts can enable better decisions by farmers if the forecast information is reliable and integrated through a coproduction process. This study analyzes user needs and perceptions of crop farmers, pastoralists, and agro-pastoralists in relation to sub-seasonal and seasonal forecasts for five counties in Kenya. A total of 258 peer-reviewed articles and gray literature were systematically analyzed using Search, Appraisal, Synthesis and Analysis (SALSA) to understand how the needs and perceptions of users of WCI shaped access and use in decision-making. The study also evaluated factors influencing use and uptake of sub-seasonal and seasonal forecasts as well as the barriers to use. Results show that farmers' perceptions shaped the choice of WCI that is used and also highlight how sub-seasonal and seasonal forecasts were used for diverse applications. Gender, availability of resources, access, and mode of communication were key factors influencing the use of seasonal forecasts. For example, access to seasonal forecasts of farmers in drier counties enabled them to manage floods and reduce risk. One lesson learned was that farmers combined WCI with other coping practices such as agronomic practices and water efficiency management. Despite a number of challenges by forecast users such as insufficient resources and lack of access to information, there is potential to improve forecasts according to user needs through a coproduction process. This study recommends stakeholder engagements with producers in the development and evaluation of forecast products and communication pathways to improve uptake and use of forecasts in decision-making.

Transforming climate science into usable services: The effectiveness of co-production in promoting uptake of climate information by smallholder farmers in Senegal

Does the provision of weather and climate information services (WCIS) enhance farmer’s use of forecasts in informing farm decisions? This paper assesses the effectiveness of the Multi-disciplinary Working Group (MWG) – a WCIS co-production initiative in Senegal in influencing farmers uptake of weather and climate information (WCI). WCIS are increasingly gaining importance and widely touted as critical in helping farmers adapt to climate variability. While there have been various WCIS initiatives producing and translating climate data into tailored information and knowledge in different parts of the world, there is hardly any rigorous evidence assessing their effectiveness in improving uptake. In this assessment, we use innovative survey methods and apply rigorous analytical approaches that control for self-selection bias to establish causal linkages between the MWG and use of WCIS. Our findings indicate that MWGs are positively associated with farmers’ awareness, access and uptake of WCI resulting in farm management responses depending on the type of information used. The presence of MWGs generally increases farmer’s awareness of WCI by 18%, access by 12% and uptake by 10%. Furthermore, use of seasonal forecasts is generally associated with a higher proportion of farmers using improved seed, fertilizers and manure, but negatively with crop diversification within MWG locations. This suggests that participatory approaches in the provision of tailored climate information and advisory services can lead to higher uptake and use among farmers in informing farm management responses for better adaptation to climate change. We highlight lessons for improved evaluations of WCIS in future.

Using Seasonal Forecast as an Adaptation Strategy: Gender Differential Impact on Yield and Income in Senegal

The use of seasonal forecast has been demonstrated as a good option to reduce the effects of climate variability in sub-Saharan African countries. However, its use, benefits and interests may be different depending on gender. This paper aims at analyzing the gender differential impact of the use of seasonal forecast on the main crop yields (rice, maize, sorghum, millet and groundnut) and farm income in Senegal. We collected data from 1481 farmers (44% women) in four regions of Senegal. We applied the counterfactual outcomes framework of modern evaluation theory to estimate the local average treatment effect (LATE) of the use of the seasonal forecast on crop yield and farm income. The results showed a significant impact of the use of the seasonal forecast (SF) in the main crop yields and the agricultural income for farmers in Senegal. This impact varies according to the sex and the type of the crops. The users (men and women) of the seasonal forecast gained on average 158 kg/ha and 140 kg/ha more yield than the non-users, respectively, for millet and rice crops. The impact of the use of SF is greater for men on millet (202.7 kg/ha vs. 16.7 kg/ha) and rice (321.33 kg/ha vs. −25.3 kg/ha). However, it is greater for women on maize (210 kg/ha vs. −105 kg/ha). Potential users of seasonal forecast had also a positive and significant impact of 41$ per ha on the income. The additional income is more important for men (56$) than women (11$). These findings suggest that the use of seasonal forecast increases the productivity of rural communities and affects men and women differently. The access to and use of SF should therefore be widely promoted among farmers’ organizations; women’s associations should be particularly targeted.

Seasonal Forecasts of the Summer 2016 Yangtze River Basin Rainfall

The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-impact events at long lead times therefore has enormous potential benefit. Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services. The teleconnection from El Ni\~no to Yangtze River basin rainfall meant that the strong El Ni\~no in winter 2015/2016 provided a valuable opportunity to test the application of a dynamical forecast system. This paper therefore presents a case study of a real time seasonal forecast for the Yangtze River basin, building on previous work demonstrating the retrospective skill of such a forecast. A simple forecasting methodology is presented, in which the forecast probabilities are derived from the historical relationship between hindcast and observations. Its performance for 2016 is discussed. The heavy rainfall in the May-June-July period was correctly forecast well in advance. August saw anomalously low rainfall, and the forecasts for the June-July-August period correctly showed closer to average levels. The forecasts contributed to the confidence of decision-makers across the Yangtze River basin. Trials of climate services such as this help to promote appropriate use of seasonal forecasts, and highlight areas for future improvements.

A Framework for Combining Seasonal Forecasts and Climate Projections to Aid Risk Management for Fisheries and Aquaculture

A changing climate, in particular a warming ocean, is likely to impact marine industries in a variety of ways. For example, aquaculture businesses may not be able to maintain production in their current location into the future, or area-restricted fisheries may need to follow the fish as they change distribution. Preparation for these potential climate impacts can be improved with information about the future. Such information can support a risk-based management strategy for industries exposed to both short-term environmental variability and long-term change. In southern Australia, adverse climate impacts on valuable seafood industries have occurred, and they are now seeking advice about future environmental conditions. We introduce a decision tree to explain the potential use of long-term climate projections and seasonal forecasts by these industries. Climate projections provide insight into the likely time in the future when current locations will no longer be suitable for growing or catching particular species. Until this time, seasonal forecasting is beneficial in helping industries plan ahead to reduce impacts in poor years and maximise opportunities in good years. Use of seasonal forecasting can extend the period of time in which industries can cope in a location as environmental suitability declines due to climate change. While a range of short-term forecasting approaches exist, including persistence and climatological forecasts, only dynamic model forecasts provide a viable option for managing environmental risk for marine industries in regions where climate change is reducing environmental suitability and creating novel conditions.

Potential use of seasonal forecasts for operational planning of north European forest management

Weather and climate conditions can have large impacts on the outcome of forest management operations: Suboptimal conditions can increase the amount of driving damage to forest ground caused by the heavy machines used for harvesting, forwarding and soil scarification. Planting of tree seedlings is commonly practised after clear cutting, and drought in summer or soil frost uplifting in autumn reduces the likelihood of successful plant establishment. Weather and climate also influence the risk of forest fires and the occurrence and development of pest and pathogens, and thereby the timing suitable for surveillance and countermeasures.In this study, the potential use of seasonal forecasts to support the operational planning of forest management in northern Europe was assessed. The analysis was based on temperature and precipitation data from WFDEI System 4 with 15 ensemble members representing seasonal hindcasts (retrospective predictions) for the period of 1981–2010. The data was used directly and as input to a soil model from which monthly indices of frozen soil and plant water stress were calculated. Relatively low skills were found for most months, and in particular for longer lead times. Highest skill was found for bias corrected temperature of January to March, with one month lead time. The skill was higher for the soil model indices, in particular those related to soil frost, as they are influenced by cumulative processes and the initial model conditions contribute to the skill. Probabilistic forecasts on frozen soil can thus be valuable for planning of which areas to harvest, taking the risk of driving damage to forest soils and forest roads into account.

Using Climate Forecasts across a State’s Emergency Management Network

AbstractThis paper examines the application by emergency managers in rural areas of forecasts of El Nino and other seasonal climate events to (1) improve the understanding of how diffuse networks can help overcome the obstacles to the use of complex scientific information and (2) to widen the use of seasonal forecasts to improve flood management. The investigation draws on ethnographic techniques of observation and conversation with emergency management networks in the state of Oregon, interviews of nearly 50 emergency managers in the state, and two detailed case studies of Oregon counties that have used seasonal climate forecasts to improve flood management. Emergency managers are more likely to use climate information tied to a time-specific and place-specific forecast and to feasible actions, and when the emergency managers are part of robust professional networks that include scientific professionals as well as end-users of forecast information.

Seasonal forecasting for decision support in marine fisheries and aquaculture

AbstractThe production of marine protein from fishing and aquaculture is influenced by environmental conditions. Ocean temperature, for example, can change the growth rate of cultured animals, or the distribution of wild stocks. In turn these impacts may require changes in fishing or farming practices. In addition to short‐term environmental fluctuations, long‐term climate‐related trends are also resulting in new conditions, necessitating adjustment in fishing, farming and management approaches. Longer‐term climate forecasts, however, are seen as less relevant by many in the seafood sector owing to more immediate concerns. Seasonal forecasts provide insight into upcoming environmental conditions, and thus allow improved decision making. Forecasts based on dynamic ocean models are now possible and offer improved performance relative to statistical forecasts, particularly given baseline shifts in the environment as a result of climate change. Seasonal forecasting is being used in marine farming and fishing operations in Australia, including wild tuna and farmed salmon and prawns, to reduce uncertainty and manage business risks. Forecast variables include water temperature, rainfall and air temperature, and are considered useful up to approximately 4 months into the future, depending on the region and season of interest. Species‐specific habitat forecasts can also be made by combining these environment forecasts with biological habitat preference data. Seasonal forecasts are useful when a range of options are available for implementation in response to the forecasts. The use of seasonal forecasts in supporting effective marine management may also represent a useful stepping stone to improved decision making and industry resilience at longer timescales.

The variability of winter temperature, its impacts on society, and the potential use of seasonal forecasts in Finland

The variability of winter temperature, its impacts on society, and the potential use of seasonal forecasts in Finland

Adapting climate research for development in Africa

AbstractThis paper reviews research on African climate from the major Sahel droughts in the early 1970s to current interest in improving the use of climate science within societal decision‐making processes. During the last decade, and particularly since the mid‐2000s, the development community has begun to engage seriously with the issue of climate change and its implications for the world's poor. This has led to a growing interaction with the climate research community.Recent climate literature is used to explore four research themes and identify knowledge gaps and areas with potential to adapt climate research for development needs. The first theme considers the development and use of seasonal forecasts and their portrayal by some as a relative success story, but with important skill limitations and need for much greater interaction with users. Forecast use is set within a wider context of generally low scientific understanding of the drivers of Africa's high climate variability and low research capacity. The second theme addresses the main influences on African climate variability and their response to climate change; high levels of uncertainty for future rainfall in some regions where remote influences are poorly resolved in global climate models. The third theme summarizes key elements of climate impacts research and shows a situation of rather ad hoc case studies and little engagement with decision‐makers. Recent studies reveal an important move to couple more effectively impacts research with adaptation by focusing on the near future and drawing on current climate–society relationships. The fourth theme looks at the emerging evidence of anthropogenic climate change and secondary effects on African environments and, apart from widespread warming, shows an equivocal situation with evidence for anthropogenic ocean warming affecting regional rainfall. Detection is hampered by data availability and high levels of background variability.Finally, three emergent issues are discussed: (1) reflection on African climate research capacity and international collaboration suggests it is timely to review experiences from recent climate programs in Africa; (2) attempts to untangle climate signals from within complex livelihood systems face significant methodological challenges. These include the need to reconcile scientific observations and local perceptions and to clarify views that may over‐simplify climate–society interactions, to avoid construction of a crisis narrative on Africa and climate change; (3) the challenge of linking climate science with decision‐making to inform adaptation. Demand for information and confidence often exceeds what climate science can realistically achieve in many parts of Africa. WIREs Clim Change 2011 2 428–450 DOI: 10.1002/wcc.115This article is categorized under: Climate and Development > Knowledge and Action in Development Trans‐Disciplinary Perspectives > Regional Reviews

Warm season streamflow variability in the Korean Han River Basin: Links with atmospheric teleconnections

AbstractWarm season (June–September) hydroclimatology is a key determinant of freshwater supplies in the Korean Peninsula. In the Han River Basin, nearly three‐fourths of annual discharge occurs during the warm season. Given the increased reliance on water supplies for numerous human and ecosystem functions, an integrated view of water supplies within the context of the regional hydroclimate will aid efforts to achieve water resources sustainability. To that end, this diagnostic study investigates several key aspects of the Han River hydrologic regime: (i) the warm season hydroclimatology; (ii) understanding the relative contribution of typhoon and non‐typhoon precipitation events to warm season streamflow; and (iii) relationships with large‐scale atmospheric teleconnections patterns and the implied seasonal predictability. Statistical analysis of modelled unimpaired streamflow indicates that the East Atlantic‐Western Russia (EA–WR) teleconnection pattern modulates the Han River streamflow during the warm season. Furthermore, a linear modelling approach using the EA–WR and East Atlantic (EA) teleconnection indices offers a useful empirical framework for understanding the systematic shifts in streamflow probability distributions. Based on these results, potential use of this information for multi‐objective water resources management, environmental flow prescriptions, proactive use of seasonal forecasts, and some open questions are briefly discussed. Copyright © 2010 Royal Meteorological Society

A multiple model assessment of seasonal climate forecast skill for applications

Skilful seasonal climate forecasts have potential to affect decision making in agriculture, health and water management. Organizations such as the National Oceanic and Atmospheric Administration (NOAA) are currently planning to move towards a climate services paradigm, which will rest heavily on skilful forecasts at seasonal (1 to 9 months) timescales from coupled atmosphere‐land‐ocean models. We present a careful analysis of the predictive skill of temperature and precipitation from eight seasonal climate forecast models with the joint distribution of observations and forecasts. Using the correlation coefficient, a shift in the conditional distribution of the observations given a forecast can be detected, which determines the usefulness of the forecast for applications. Results suggest there is a deficiency of skill in the forecasts beyond month‐1, with precipitation having a more pronounced drop in skill than temperature. At long lead times only the equatorial Pacific Ocean exhibits significant skill. This could have an influence on the planned use of seasonal forecasts in climate services and these results may also be seen as a benchmark of current climate prediction capability using (dynamic) couple models.

Use of climate information in soybean farming on the Argentinean pampas

The availability of enhanced climate forecasts offers the potential for farmers to improve responses to climate variability. However, few studies have demonstrated actual effective uses of cli- mate forecasts. Through interaction with regional agricultural experts, we evaluated the opportuni- ties and constraints involved in the use of climate information in decision making regarding soybean farming in the Argentinean pampas. Our results showed that opportunities exist for the successful application of climate information, but consistent with previous research, there is a need to consider the broad and complex context influencing decisions, since climate is just one of the many factors affecting farmers' decisions. More importantly, we showed that adaptive management strategies pro- posed by experts in response to hypothetical climate scenarios produced diverging economic out- comes (both positive and negative). We hypothesized that inconsistency of the observed results could be due to a poor understanding by the agricultural experts of the impacts on regional climate of global climate signals (e.g. a given ENSO phase). An alternative hypothesis was that crop consultants had difficulties in anticipating the agronomic outcomes of management decisions made in response to a given climate forecast. Further research is needed to elucidate to what extent these hypotheses are valid. However, our results suggest that the mere availability of climate forecasts will not neces- sarily benefit growers. In order for there to be an improvement in the use of seasonal forecasts, appro- priate interventions are necessary to enhance decision makers' understanding of the sources and impacts of climate variability, and of the consequences of different responses to a range of climate scenarios.

Weather Derivative Pricing and the Impact of El Nino on US Temperature: Empirical Tests of an Optimal Categorical Forecasting Scheme

Weather derivative pricing for US locations can potentially be improved through the judicious use of seasonal forecasts. However, the number of El Nino and La Nina events that appear in the historical record is small and for many locations the signals are weak. We run some simulation-based tests of an optimal categorical forecasting scheme that takes the small sample size and weak signal into account and tries to produce RMSE-optimal seasonal forecasts.

Implications of Seasonal Climate Forecasts on World Wheat Trade: A Stochastic, Dynamic Analysis

Improvements in seasonal climate forecasts have potential economic implications for international agriculture. A stochastic, dynamic simulation model of the international wheat economy is developed to estimate the potential effects of seasonal climate forecasts for various countries' wheat production, exports and world trade. Previous studies have generally ignored the stochastic and dynamic aspects of the effects associated with the use of climate forecasts. This study shows the importance of these aspects. In particular with free trade, the use of seasonal forecasts results in increased producer surplus across all exporting countries. In fact, producers appear to capture a large share of the economic surplus created by using the forecasts. Further, the stochastic dimensions suggest that while the expected long‐run benefits of seasonal forecasts are positive, considerable year‐to‐year variation in the distribution of benefits between producers and consumers should be expected. The possibility exists for an economic measure to increase or decrease over a 20‐year horizon, depending on the particular sequence of years.Le progrès des prévisions saisonnières du climat a une portée économique pour l'agriculture internationale. Un modèle stochastique et dynamique de l'économie internationale du blé est développé afin d'estimer les effets potentiels des prévisions saisonnières du climat sur la production de blé de divers pays, leurs exportations et le commerce mondial. Les études précédentes ont généralement ignoré les aspects stochastiques et dynamiques des effets liés à l'utilisation des prévisions climatiques. Cette étude montre l'importance de ces aspects. En particulier avec le libre échange l'utilisation de ces prévisions aboutit à l'augmentation des excédents dans tous les pays exportateurs. En fait, il apparaît que les producteurs accaparent une grande part de l'excédent économique créé par l'utilisation de ces prévisions. De plus, les dimensions stochastiques suggèrent que bien que les bénéfices à long terme des prévisions climatiques puissent être substantiels, on s'attend à des variations considérables d'une année à l'autre dans la distribution des bénéfices entre les producteurs et les consommateurs. Il est possible qu'un indicateur économique varie à la baisse sur 20 ans eus fonction de la séquence de variation climatique.

Use of seasonal forecasts of sea surface temperature anomalies for potato fertilization management. Theoretical study considering EPIC model results at Valdivia, Chile

The use of perfect and imperfect forecasts of sea surface temperature anomalies (SSTA) in the Equatorial Pacific for potato fertilization strategies is presented in this study. The applications of SSTA forecasts and the derivation of probabilities of future events are illustrated considering yield outcomes obtained from the EPIC simulation model at Valdivia, Chile (39.4 S). The economic value of both perfect and imperfect forecasts of SSTA is assessed. The study framework incorporates weather modeling, soil-crop modeling and an intertemporal (i.e. time-dependent) economic decision model. The value of perfect SSTA information is found to be positive for cases where the initial fertilization dose (nitrogen and phosphorous) does not preclude expression of the full yield potential for a different type of growing season. In those situations it would be hypothetically possible to use perfect seasonal forecasts of the SSTA to perform further nitrogen adjustments, which would result in additional net economic returns. In the example shown the values ranged from 5 to 22 $/ha depending on the initial fertilization strategy. Imperfect forecasts also produce interesting results when they are used in an intertemporal decision framework. Use of simple forecasts derived from the stochastic properties of SSTA allows the decision maker to capture part of the value of perfect SSTA information. For the case considered here this value was up to 40%. If selected initial fertilization levels are not optimal, nitrogen adjustments based on a simple Markov Chain forecast increase net economic benefits. These additional economic benefits vary between 3 and 10 $/ha in the example, being approximately 60% of the value of perfect SSTA information.