scholarly journals Opportunities for seasonal forecasting to support water management outside the tropics

2021 ◽  
Author(s):  
Leah Amber Jackson-Blake ◽  
François Clayer ◽  
Elvira de Eyto ◽  
Andrew French ◽  
María Dolores Frías ◽  
...  
Keyword(s):  
Water Management ◽  
Decision Making ◽  
Climate Model ◽  
Added Value ◽  
Seasonal Forecasting ◽  
Qualitative Assessment ◽  
Seasonal Climate ◽  
Climate Forecasts ◽  
Study Sites ◽  
Seasonal Climate Forecasts

Abstract. Advance warning of seasonal conditions has potential to assist water management in planning and risk mitigation, with large potential social, economic and ecological benefits. In this study, we explore the value of seasonal forecasting for decision making at five case study sites located in extratropical regions. The forecasting tools used integrate seasonal climate model forecasts with freshwater impact models of catchment hydrology, lake conditions (temperature, level, chemistry and ecology) and fish migration timing, and were co-developed together with stakeholders. To explore the decision making value of forecasts, we carried out a qualitative assessment of: (1) how useful forecasts would have been for a problematic past season, and (2) the relevance of any “windows of opportunity” (seasons and variables where forecasts are thought to perform well) for management. Overall, stakeholders were optimistic about the potential for improved decision making and identified actions that could be taken based on forecasts. However, there was often a mismatch between those variables that could best be predicted and those which would be most useful for management. Reductions in forecast uncertainty and a need to develop practical hands-on experience were identified as key requirements before forecasts would be used in operational decision making. Seasonal climate forecasts provided little added value to freshwater forecasts in the study sites, and we discuss the conditions under which seasonal climate forecasts with only limited skill are most likely to be worth incorporating into freshwater forecasting workflows.

scholarly journals Could Farmers have Dodged the 2012 Great Plains Drought?

Eos ◽  
2015 ◽  
Vol 96 ◽  
Author(s):  
Colin Schultz
Keyword(s):  
Decision Making ◽  
Great Plains ◽  
Seasonal Climate ◽  
Climate Forecasts ◽  
Decision Making Model ◽  
Seasonal Climate Forecasts

A decision-making model to turn seasonal climate forecasts into information farmers actually need.

Proactive Drought and Extreme Event Preparedness: Seasonal Climate Forecasts offer Benefit for Decision Making in Water Management in Semi-arid Regions

2020 ◽  
Author(s):  
Tanja Portele ◽  
Christof Lorenz ◽  
Patrick Laux ◽  
Harald Kunstmann
Keyword(s):  
Water Management ◽  
Arid Regions ◽  
Extreme Event ◽  
Seasonal Forecast ◽  
Seasonal Forecasts ◽  
Seasonal Climate ◽  
Early Action ◽  
Climate Forecasts ◽  
Semi Arid ◽  
Seasonal Climate Forecasts

<p>Semi-arid regions are the regions mostly affected by drought. In these climatically sensitive regions, the frequency and intensity of drought and hot extremes is projected to increase. With increasing precipitation variability in semi-arid regions, sustainable water management is required. Proactive drought and extreme event preparedness, as well as damage mitigation could be provided by the use of seasonal climate forecasts. However, their probabilistic nature, the lack of clear action derivations and institutional conservatism impedes their application in decision making of the water management sector. Using the latest global seasonal climate forecast product (SEAS5) at 35 km resolution and 7 months forecast horizon of the European Centre for Medium-Range Weather Forecasts, we show that seasonal-forecast-based actions offer potential economic benefit and allow for climate proofing in semi-arid regions in the case of drought and extreme events. Our analysis includes 7 semi-arid, in parts highly managed river basins with extents from tens of thousands to millions of square kilometers in Africa, Asia and South America. The value of the forecast-based action is derived from the skill measures of hit (worthy action) and false alarm (action in vain) rate and is related to economic expenses through ratios of associated costs and losses of an early action. For water management policies, forecast probability triggers for early action plans can be offered based on expense minimization and event maximization criteria. Our results show that even high lead times and long accumulation periods attain value for a range of users and cost-loss situations. For example, in the case of extreme wet conditions (monthly precipitation above 90<sup>th</sup> percentile), seasonal-forecast-based action in 5 out of 7 regions can still achieve more than 50 % of saved expenses of a perfect forecast at 6 months in advance. The utility of seasonal forecasts strongly depends on the user, the cost-loss situation, the region and the concrete application. In general, seasonal forecasts allow decision makers to save expenses, and to adapt to and mitigate damages of extreme events related to climate change.</p>

scholarly journals Assessing Decision Timing and Seasonal Climate Forecast Needs of Winter Wheat Producers in the South-Central United States

2018 ◽  
Vol 57 (9) ◽  
pp. 2129-2140 ◽  
Author(s):  
Toni Klemm ◽  
Renee A. McPherson
Keyword(s):  
United States ◽  
Decision Making ◽  
Winter Wheat ◽  
Lead Time ◽  
The United States ◽  
Seasonal Climate ◽  
Decision Tools ◽  
South Central ◽  
Climate Forecasts ◽  
Seasonal Climate Forecasts

AbstractAgricultural decision-making that adapts to climate variability is essential to global food security. Crop production can be severely impacted by drought, flood, and heat, as seen in recent years in parts of the United States. Seasonal climate forecasts can help producers reduce crop losses, but many nationwide, publicly available seasonal forecasts currently lack relevance for agricultural producers, in part because they do not reflect their decision needs. This study examines the seasonal forecast needs of winter wheat producers in the southern Great Plains to understand what climate information is most useful and what lead times are most relevant for decision-making. An online survey of 119 agricultural advisers, cooperative extension agents in Oklahoma, Kansas, Texas, and Colorado, was conducted and gave insights into producers’ preferences for forecast elements, what weather and climate extremes have the most impact on decision-making, and the decision timing of major farm practices. The survey participants indicated that winter wheat growers were interested not only in directly modeled variables, such as total monthly rainfall, but also in derived elements, such as consecutive number of dry days. Moreover, these agricultural advisers perceived that winter wheat producers needed seasonal climate forecasts to have a lead time of 0–2.5 months—the planning lead time for major farm practices, like planting or harvesting. A forecast calendar and monthly rankings for forecast elements were created that can guide forecasters and advisers as they develop decision tools for winter wheat producers and that can serve as a template for other time-sensitive decision tools developed for stakeholder communities.

Value of seasonal climate forecasts in reducing economic losses for grazing enterprises: Charters Towers case study

2019 ◽  
Vol 41 (3) ◽  
pp. 165
Author(s):  
Duc-Anh An-Vo ◽  
Kate Reardon-Smith ◽  
Shahbaz Mushtaq ◽  
David Cobon ◽  
Shreevatsa Kodur ◽  
...  
Keyword(s):  
Decision Making ◽  
Economic Value ◽  
Simulation Software ◽  
Economic Losses ◽  
Economic Modelling ◽  
Seasonal Climate ◽  
Climate Forecasts ◽  
Net Profit ◽  
Seasonal Climate Forecasts

Seasonal climate forecasts (SCFs) have the potential to improve productivity and profitability in agricultural industries, but are often underutilised due to insufficient evidence of the economic value of forecasts and uncertainty about their reliability. In this study we developed a bio-economic model of forecast use, explicitly incorporating forecast uncertainty. Using agricultural systems (ag-systems) production simulation software calibrated with case study information, we simulated pasture growth, herd dynamics and annual economic returns under different climatic conditions. We then employed a regret and value function approach to quantify the potential economic value of using SCFs (at both current and improved accuracy levels) in decision making for a grazing enterprise in north-eastern Queensland, Australia – a region subject to significant seasonal and intra-decadal climate variability. Applying an expected utility economic modelling approach, we show that skilled SCF systems can contribute considerable value to farm level decision making. At the current SCF skill of 62% (derived by correlating the El Niño Southern Oscillation (ENSO) signal and historical climate data) at Charters Towers, an average annual forecast value of AU$4420 (4.25%) was realised for the case study average annual net profit of AU$104000, while a perfect (no regret) forecast system could result in an increased return of AU$13475 per annum (13% of the case study average annual net profit). Continued improvements in the skill and reliability of SCFs is likely to both increase the value of SCFs to agriculture and drive wider uptake of climate forecasts in on-farm decision making. We also anticipate that an integrated framework, such as that developed in this study, may provide a pathway for better communication with end users to support improved understanding and use of forecasts in agricultural decision making and enhanced sustainability of agricultural enterprises.

scholarly journals Assessing the usability and potential value of seasonal climate forecasts in land management decisions in the southwest UK: challenges and reflections

2017 ◽  
Vol 14 ◽  
pp. 175-180 ◽  
Author(s):  
Marta Bruno Soares
Keyword(s):  
Decision Making ◽  
Land Management ◽  
Current Knowledge ◽  
Management Tool ◽  
Seasonal Climate ◽  
Potential Value ◽  
Climate Forecasts ◽  
Decision Making Processes ◽  
The Uk ◽  
Seasonal Climate Forecasts

Abstract. The potential usability and benefits of seasonal climate forecasts (SCF) to help inform decision-making processes is widely accepted. However, the practical use of SCF in Europe is still fairly recent and, as such, current knowledge of the added benefits of SCF in supporting and improving decision-making is limited. This study is based on research conducted to co-develop a semi-operational climate service prototype – the Land Management Tool (LMTool) – with farmers in South West regions of the UK. The value of the SCF provided to the farmers was examined to help us understand the usability and (potential) value of these forecasts in farmers' decisions during the winter months of 2015/2016. The findings from the study point to the need to explore and develop (new) research methods capable of addressing the complexity of the decision-making processes, such as those in the farming sector. The farmers who used the SCF perceived it as useful and usable as it helped them change and adapt their decision-making and thus, avoid unnecessary costs. However, to fully grasp the potential value of using SCF, farmers emphasised the need for the provision of SCF for longer periods of time to allow them to build trust and confidence in the information provided. This paper contributes to ongoing discussions about how to assess the use and value of SCF in decision-making processes in a meaningful and effective way.

Grand Multi-Model Seasonal Forecasts in the SECLI-FIRM project

2020 ◽  
Author(s):  
Andrea Alessandri ◽  
Franco Catalano ◽  
Matteo De Felice ◽  
Kristian Nielsen ◽  
Alberto Troccoli ◽  
...  
Keyword(s):  
Seasonal Prediction ◽  
Added Value ◽  
Japan Meteorological Agency ◽  
Brier Score ◽  
Seasonal Forecasts ◽  
Seasonal Climate ◽  
Climate Forecasts ◽  
Prediction Systems ◽  
Seasonal Climate Forecasts ◽  
Selection Of

<p>A key objective of the Added Value of Seasonal Climate Forecasts for Integrated Risk Management Decisions (SECLI-FIRM, www.secli-firm.eu) project is the optimisation of the performance of seasonal climate forecasts provided by many producing centers, in a Grand Multi-Model approach, for predictands relevant for the specific case studies considered in SECLI-FIRM.</p><p>The Grand Multi-Model Ensemble (MME) consists of the five Seasonal Prediction Systems (SPSs) provided by the European Copernicus C3S and a selection of other five SPSs independently developed by centres outside Europe, four by the North American (NMME) plus the SPS by the Japan Meteorological Agency (JMA).</p><p>All the possible multi-model combinations have been evaluated showing that, in general, only a limited number of SPSs is required to obtain the maximum attainable performance. Although the selection of models that perform better is usually different depending on the region/phenomenon under consideration, it is shown that the performance of the Grand-MME seasonal predictions is enhanced with the increase of the independence of the contributing SPSs, i.e. by mixing European SPSs with those from NMME-JMA.</p><p>Starting from the definition of the Brier score a novel metric has been developed, named the Brier score covariance (BScov), which estimates the relative independence of the prediction systems. BScov is used to quantify independence among the SPSs and, together with probabilistic skill metrics, used to develop a strategy for the identification of the combinations that optimize the probabilistic performance of seasonal predictions for the study cases.</p>

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