Encouraging use of seasonal climate forecasts by farmers

McCrea, Rod; Dalgleish, Len; Coventry, William L.

doi:10.1002/joc.1164

Cited by 35 publications

(31 citation statements)

References 25 publications

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“…probability of exceedance, median rainfall) compared with the non-user respondents. This finding may differ from McCrea et al (2005), who found the level of forecast understanding important in predicting the use of seasonal climate forecasts by grain growers in southern Queensland and northern New South Wales. Our study indicates that some seasonal forecasts maybe misinterpreted by graziers, and management decisions may have been made that were not intended.…”

Section: Use Of Seasonal Forecasts and Understanding The Terminologycontrasting

confidence: 93%

“…Mail-out surveys using non-purposive sampling of farmers returned variable response rates between 6 and 52% [Childs et al 1991 (43%); Bayley et al 1994 (6%); Hayman and Alston 1999 (20%); Austen et al 2002 (52%); Keogh et al 2004aKeogh et al (43%), 2004b; Keogh et al 2005 (47%)]. Purposive sampling of selected Queensland graziers returned a 65% response rate (Paull and Hall 1999) and of selected farmers with previous experience in dryland and opportunity cropping practices in southern Queensland and northern New South Wales returned a 30% response rate (McCrea et al 2005).…”

Section: Response Ratesmentioning

confidence: 99%

“…Desired levels of forecast reliability, forecast presentation style, use of terminology, proof of value, access to expertise and perceptions regarding climate information have previously been identified as factors limiting the uptake and use of climate forecasts (Childs et al 1991;Changnon et al 1995;Nicholls 1999;Hartmann et al 2002;McCrea et al 2005). Despite this awareness there have been only minor adjustments to the SOI phase system (a key statistical operational forecast system in Australia) and its presentation format since 1991, for example some modifications to wording and map definition.…”

Section: Customising Climate Information To Suit User Needsmentioning

confidence: 99%

“…Discussions with users of seasonal forecasts in the United States indicate that even managers with technical backgrounds consistently misinterpret Climate Prediction Centre outlooks (Pagano et al 2001). Alternative ways of describing seasonal forecasts such as using frequencies rather than probabilities (Coventry 2001;McCrea et al 2005) may have merit. The challenge of educating producers exists because these terms and concepts are difficult to understand (and apply) (Tversky and Kahneman 1974) and repeated tuition is often needed.…”

Section: Local Championsmentioning

confidence: 99%

“…Seasonal climate forecasts are now used by 30-40% of agricultural producers in decision making (Australian Government Department of Agriculture Fisheries and Forestry 2004; Keogh et al 2004aKeogh et al , 2005. Desired levels of forecast reliability, forecast presentation style, use of terminology, proof of value, access to expertise and perceptions regarding climate information have previously been identified as factors limiting the uptake and use of climate forecasts (Childs et al 1991;Changnon et al 1995;Nicholls 1999;Hartmann et al 2002;McCrea et al 2005).…”

Section: Introductionmentioning

confidence: 99%

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Summative evaluation of climate application activities with pastoralists in western Queensland

Cobon¹,

Bell²,

Park³

et al. 2008

Rangel. J.

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Abstract. Survey methods were engaged to measure the change in use and knowledge of climate information by pastoralists in western Queensland. The initial mail survey was undertaken in 2000-01 (n = 43) and provided a useful benchmark of pastoralists climate knowledge. Two years of climate applications activities were completed and clients were re-surveyed in 2003 (n = 49) to measure the change in knowledge and assess the effectiveness of the climate applications activities. Two methods were used to assess changes in client knowledge, viz., self-assessment and test questions. We found that the use of seasonal climate forecasts in decision making increased from 36% in 2001 (n = 42) to 51% in 2003 (n = 49) (P = 0.07). The self-assessment technique was unsatisfactory as a measure of changing knowledge over short periods (1-3 years), but the test question technique was successful and indicated an improvement in climate knowledge among respondents. The increased levels of use of seasonal climate forecasts in management and improved knowledge was partly attributed to the climate applications activities of the project.Further, those who used seasonal forecasting (n = 25) didn't understand key components of forecasts (e.g. probability, median) better than those who didn't use seasonal forecasts (n = 24) (P > 0.05). This identifies the potential for misunderstanding and misinterpretation of forecasts among users and highlights the need for providers of forecasts to understand the difficulties and prepare simply written descriptions of forecasts and disseminate these with the maps showing probabilities.The most preferred means of accessing climate information were internet, email, 'The Season Ahead' newsletter and newspaper. The least preferred were direct contact with extension officers and attending field days and group meetings. Eighty-six percent of respondents used the internet and 67% used ADSL broadband internet (April 2003). Despite these findings, extension officers play a key role in preparing and publishing the information on the web, in emails and newsletters. We also believe that direct contact with extension officers trained in climate applications is desirable in workshop-like events to improve knowledge of the difficult concepts underpinning climate forecasts, which may then stimulate further adoption.

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Section: Use Of Seasonal Forecasts and Understanding The Terminologycontrasting

confidence: 93%

Section: Response Ratesmentioning

confidence: 99%

Section: Customising Climate Information To Suit User Needsmentioning

confidence: 99%

Section: Local Championsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Summative evaluation of climate application activities with pastoralists in western Queensland

Cobon¹,

Bell²,

Park³

et al. 2008

Rangel. J.

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Farmers' accuracy interpreting seasonal climate forecast probability

Coventry

Dalgleish

2013

Intl Journal of Climatology

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We explored errors interpreting the seasonal climate forecast (SCF) statement 'In the next 3 months, the probability of exceeding median rainfall is 30 %' used by the Australian media. Study one comprised 73 farmers and 12 climate staff and (1) developed a five-item multiple-choice questionnaire assessing understanding for the SCF, and (2) assessed errors interpreting the statement. The farmers who incorrectly interpreted the statement (29%) as forecasting a wetter season than normal had a lower understanding of the statement, in contrast to farmers making the correct interpretation (56%) and the climate staff. The statement appeared to be misinterpreted as a specific value of rain that was above the median by 30%, because of (1) difficulty conceptualizing above median rainfall and below median rainfall as distinct events, and (2) the percentage being interpreted as a specific value and not as a notion of chance. Study two, with 72 laypersons, showed more errors and slower responses with statements of probabilities less than 50% (i.e. 30 %) than statements of probabilities greater than 50% (i.e. 70 %), explained by the positive connotation biases of the event above median rainfall and/or the use of the term probability.

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An evaluation strategy of skill of high‐resolution rainfall forecast for specific agricultural applications

Rakesh

Goswami

2016

Meteorological Applications

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ABSTRACT:A strategy for validation of rainfall forecasts for specific agricultural applications is presented. The focus is mainly on the design of specific forecast advisories that are risk-free and useful in spite of their inherent errors. The strategy works for these specific applications because the forecast advisories are based on when NOT to irrigate or apply fertilizer/pesticide because rain is predicted (risk-free because wrong forecast only delays irrigation/application of fertilizer/pesticide within tolerance). Thus, unlike in conventional forecast evaluation, a forecast is considered as valid if the forecasted rain (or no rain) is correct for the day of the forecast (D0C) or the next day or the day after (designated D1C and D2C, respectively), as the farmer can afford to postpone the field application for a couple of days beyond the scheduled date. The methodology has been evaluated for rainfall forecasts over Karnataka (a state in southwest India with nearly 56% of the workforce engaged in agriculture). Here, forecast validation against rain gauge observations is presented at comparable resolutions for the southwest (June to September) and the northeast (October to December) monsoon seasons during 2011-2014. Analyses demonstrate that forecasts over several areas which may appear to be less reliable based on conventional evaluation (D0C) are found to have useful skill for the specific agro-applications as evident from evaluation based on D1C and D2C criteria. Our analysis shows that the evaluation strategy presented is effective during the non-rainy (January-May) season also. It is pointed out that such an approach can help to meet the challenges in designing and implementing best practices in agriculture by combining immediate gains for the end users with long-term sustainability.

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Encouraging use of seasonal climate forecasts by farmers

Cited by 35 publications

References 25 publications

Summative evaluation of climate application activities with pastoralists in western Queensland

Summative evaluation of climate application activities with pastoralists in western Queensland

Farmers' accuracy interpreting seasonal climate forecast probability

An evaluation strategy of skill of high‐resolution rainfall forecast for specific agricultural applications

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