Use of Seasonal Climate Forecasts in Rangeland-Based Livestock Operations in West Texas

Jochec, Kristi G.; Mjelde, James W.; Lee, Andrew C.; Conner, J. Richard

doi:10.1175/1520-0450(2001)040<1629:uoscfi>2.0.co;2

Cited by 34 publications

(24 citation statements)

References 9 publications

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“…Both aspects, the availability of long data sets and the selection of the areas and variables where calibration and/or combination are beneficial, need to be considered in the context of the application to end-user models (e.g. Cantelaube and Terres 2005;Challinor et al, 2005;Marletto et al, 2005;Morse et al, 2005) and of the decision-making process of users (Sarewitz et al, 2000;Jochec et al, 2001;Hartmann et al, 2002;Murnane et al, 2002;Archer, 2003). This is the framework where the actual predictive potential of a multi-model seasonal forecast system can be determined.…”

Section: Discussion and Concluding Remarksmentioning

confidence: 99%

The rationale behind the success of multi-model ensembles in seasonal forecasting – II. Calibration and combination

Doblas‐Reyes

Hagedorn

Palmer

2005

Tellus A: Dynamic Meteorology and Oceanography

113

102

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A B S T R A C TThe DEMETER multi-model ensemble system is used to investigate the enhancement in seasonal predictability that can be achieved by calibrating single-model ensembles and combining them to issue multi-model predictions. The forecast quality of both deterministic and probabilistic predictions is assessed and compared to the skill of a simple multi-model ensemble where all the single models are equally weighted. Both calibration and combination are carried out using crossvalidation. Single-model seasonal ensembles are calibrated using canonical correlation analysis for model adjustment and variance inflation for reliability enhancement. Results indicate that both model adjustment and inflation increase the skill of tropical predictions for single-model ensembles, provided that the training time series are long enough. Some improvements are also found for extratropical areas, although mostly due to an increase of reliability associated with the inflation. The beneficial impact of calibration is smaller for the simple multi-model than for the single-model ensembles due to the relatively high reliability of the former. The raw single-model predictions are also linearly combined using grid-point multiple linear regression to create an optimized multi-model system. Results indicate that the forecast quality of the simple multi-model ensemble is generally difficult to improve using multiple linear regression due to the lack of robustness of the regression coefficients. As in the case of the calibration, longer time series would be preferred to achieve a significant forecast quality improvement. Over the tropics, a multiple linear regression, that uses the principal components of the model anomalies for the target area as predictors indicates a substantial gain in skill even with the available sample size. The implications of these results in an operational context are discussed.

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Section: Discussion and Concluding Remarksmentioning

confidence: 99%

The rationale behind the success of multi-model ensembles in seasonal forecasting – II. Calibration and combination

Doblas‐Reyes

Hagedorn

Palmer

2005

Tellus A: Dynamic Meteorology and Oceanography

113

102

View full text Add to dashboard Cite

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“…Constraints identified from case studies of climate forecast use are increasing in prominence in the literature (e.g., Stern and Easterling 1999;Roncoli and Magistro 2000;Letson et al 2001;Jochec et al 2001;Broad et al 2002;Ziervogel and Downing 2004). This expansion is due in part to the increased production and dissemination of climate forecasts and to the great prominence of the 1997/98 ENSO event.…”

Section: Bai1s-november 2004mentioning

confidence: 99%

Factors that Influence the Use of Climate Forecasts: Evidence from the 1997/98 El Niño Event in Peru

Orlove

Broad²,

Petty

2004

Bull. Amer. Meteor. Soc.

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The use of forecasts in coastal Peru during the 1997/98 El Nino differed from patterns described in the literature, particularly in the influence of user education and the time of hearing the forecasts on levels of forecast use. A PPROACHES TO THE STUDY OF CLIMATE FORECASTS.The promotion of the use of seasonal to interannual climate information by U.S. government and international agencies has increased the number of studies that address the use of forecasts. This work has largely been applications oriented. These studies seek to identify the current and potential patterns of forecast use, the integration of forecasts into decision making, and the most appropriate ways to communicate information to various groups. Much of this work has rested on models that calculate the influence of forecasts on different socioeconomic activities in various societal contexts (Stern and Easterling 1999). In addition, empirical research has complemented these modeling studies by examining concrete patterns of forecast perception and communication and, in some cases, of forecast use as well. Numerous factors have been identified that influence perception, communication, interpretation, and use of forecasts [see Stern and Easterling (1999) for a recent review of climate forecast applications studies]. Our study of the fishery sector in five Peruvian ports during the 1997/98 El Nino concurs with earlier studies that indicate that subpopulations differ significantly in their use of this information; it also supports the long-established claim that perceived accuracy influences forecast use. However, our study suggests that the timing of forecast dissemination, sectoral sensitivity, and socioeconomic variables influence forecast use in ways different from those commonly presented in modeling studies and in

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“…Users may need assistance with interpreting probabilistic forecasts. They may need more information and education about how to use predictions (Jochec et al 2001;Klopper 1999;Sonka et al 1992).…”

Section: Challenges Associated With Climate Forecast Informationmentioning

confidence: 99%

“…In the United States and Australia it has been found that an accuracy of between 70 and 80% is desired for a seasonal forecast (Jochec et al 2001;Pulwarty et al 1997) before decision makers consider changing a stocking rate or crop type decision (Childs et al 1991).…”

Section: Percentage Probability Forecasts Likely To Influence Decisionsmentioning

confidence: 99%

Climate information needs of Gascoyne - Murchison pastoralists: a representative study of the Western Australian grazing industry

Keogh

Watson

Bell³

et al. 2005

Aust. J. Exp. Agric.

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Abstract. The Gascoyne-Murchison region of Western Australia experiences an arid to semi-arid climate with a highly variable temporal and spatial rainfall distribution. The region has around 39.2 million hectares available for pastoral lease and supports predominantly cattle and sheep grazing leases. In recent years a number of climate forecasting systems have been available offering rainfall probabilities with different lead times and forecast periods; however, the extent to which these systems are capable of fulfilling the requirements of the local pastoralists is still ambiguous. Issues can range from ensuring forecasts are issued with sufficient lead time to enable key planning or decisions to be revoked or altered, to ensuring forecast language is simple and clear, to negate possible misunderstandings in interpretation. A climate research project sought to provide an objective method to determine which available forecasting systems had the greatest forecasting skill at times of the year relevant to local property management. To aid this climate research project, the study reported here was undertaken with an overall objective of exploring local pastoralists' climate information needs. We also explored how well they understand common climate forecast terms such as 'mean', 'median' and 'probability', and how they interpret and apply forecast information to decisions. A stratified, proportional random sampling was used for the purpose of deriving the representative sample based on rainfall-enterprise combinations.In order to provide more time for decision-making than existing operational forecasts that are issued with zero lead time, pastoralists requested that forecasts be issued for May-July and January-March with lead times counting down from 4 to 0 months. We found forecasts of between 20 and 50 mm break-of-season or follow-up rainfall were likely to influence decisions. Eighty percent of pastoralists demonstrated in a test question that they had a poor technical understanding of how to interpret the standard wording of a probabilistic median rainfall forecast. This is worthy of further research to investigate whether inappropriate management decisions are being made because the forecasts are being misunderstood.We found more than half the respondents regularly access and use weather and climate forecasts or outlook information from a range of sources and almost three-quarters considered climate information or tools useful, with preferred methods for accessing this information by email, faxback service, internet and the Department of Agriculture Western Australia's Pastoral Memo. Despite differences in enterprise types and rainfall seasonality across the region we found seasonal climate forecasting needs were relatively consistent. It became clear that providing basic training and working with pastoralists to help them understand regional climatic drivers, climate terminology and jargon, and the best ways to apply the forecasts to enhance decision-making are important to improve their use of information. C...

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Use of Seasonal Climate Forecasts in Rangeland-Based Livestock Operations in West Texas

Cited by 34 publications

References 9 publications

The rationale behind the success of multi-model ensembles in seasonal forecasting – II. Calibration and combination

The rationale behind the success of multi-model ensembles in seasonal forecasting – II. Calibration and combination

Factors that Influence the Use of Climate Forecasts: Evidence from the 1997/98 El Niño Event in Peru

Climate information needs of Gascoyne - Murchison pastoralists: a representative study of the Western Australian grazing industry

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