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.

scholarly journals Climate Forecasts for Corn Producer Decision Making

2014 ◽  
Vol 18 (5) ◽  
pp. 1-8 ◽  
Author(s):  
Eugene S. Takle ◽  
Christopher J. Anderson ◽  
Jeffrey Andresen ◽  
James Angel ◽  
Roger W. Elmore ◽  
...  
Keyword(s):  
United States ◽  
Decision Making ◽  
Weather Conditions ◽  
The United States ◽  
Climate Forecast ◽  
Climate Information ◽  
Corn Production ◽  
Decision Tools ◽  
Decision Cycle ◽  
Climate Forecasts

Abstract Corn is the most widely grown crop in the Americas, with annual production in the United States of approximately 332 million metric tons. Improved climate forecasts, together with climate-related decision tools for corn producers based on these improved forecasts, could substantially reduce uncertainty and increase profitability for corn producers. The purpose of this paper is to acquaint climate information developers, climate information users, and climate researchers with an overview of weather conditions throughout the year that affect corn production as well as forecast content and timing needed by producers. The authors provide a graphic depicting the climate-informed decision cycle, which they call the climate forecast–decision cycle calendar for corn.

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.

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.

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 Prediction of Rice Production in the Philippines Using Seasonal Climate Forecasts

2013 ◽  
Vol 52 (3) ◽  
pp. 552-569 ◽  
Author(s):  
Naohisa Koide ◽  
Andrew W. Robertson ◽  
Amor V. M. Ines ◽  
Jian-Hua Qian ◽  
David G. DeWitt ◽  
...  
Keyword(s):  
Rainy Season ◽  
Lead Time ◽  
General Circulation ◽  
The Philippines ◽  
Dry Season ◽  
Rice Production ◽  
Production Data ◽  
Seasonal Climate ◽  
Climate Forecasts ◽  
Seasonal Climate Forecasts

AbstractPredictive skills of retrospective seasonal climate forecasts (hindcasts) tailored to Philippine rice production data at national, regional, and provincial levels are investigated using precipitation hindcasts from one uncoupled general circulation model (GCM) and two coupled GCMs, as well as using antecedent observations of tropical Pacific sea surface temperatures, warm water volumes (WWV), and zonal winds (ZW). Contrasting cross-validated predictive skills are found between the “dry” January–June and “rainy” July–December crop-production seasons. For the dry season, both irrigated and rain-fed rice production are shown to depend strongly on rainfall in the previous October–December. Furthermore, rice-crop hindcasts based on the two coupled GCMs, or on the observed WWV and ZW, are each able to account for more than half of the total variance of the dry-season national detrended rice production with about a 6-month lead time prior to the beginning of the harvest season. At regional and provincial levels, predictive skills are generally low. The relationships are found to be more complex for rainy-season rice production. Area harvested correlates positively with rainfall during the preceding dry season, whereas the yield has positive and negative correlations with rainfall in June–September and in October–December of the harvested year, respectively. Tropical cyclone activity is also shown to be a contributing factor in the latter 3-month season. Hindcasts based on the WWV and ZW are able to account for almost half of the variance of the detrended rice production data in Luzon with a few months’ lead time prior to the beginning of the rainy season.

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.

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