On measuring quality of a probabilistic commodity forecast for a system that incorporates seasonal climate forecasts

Regional commodity forecasts are being used increasingly in agricultural industries to enhance their risk management and decision-making processes. These commodity forecasts are probabilistic in nature and are often integrated with a seasonal climate forecast system. The climate forecast system is based on a subset of analogue years drawn from the full climatological distribution. In this study we sought to measure forecast quality for such an integrated system. We investigated the quality of a commodity (i.e. wheat and sugar) forecast based on a subset of analogue years in relation to a standard reference forecast based on the full climatological set. We derived three key dimensions of forecast quality for such probabilistic forecasts: reliability, distribution shift, and change in dispersion. A measure of reliability was required to ensure no bias in the forecast distribution. This was assessed via the slope of the reliability plot, which was derived from examination of probability levels of forecasts and associated frequencies of realizations. The other two dimensions related to changes in features of the forecast distribution relative to the reference distribution. The relationship of 13 published accuracy/skill measures to these dimensions of forecast quality was assessed using principal component analysis in case studies of commodity forecasting using seasonal climate forecasting for the wheat and sugar industries in Australia. There were two orthogonal dimensions of forecast quality: one associated with distribution shift relative to the reference distribution and the other associated with relative distribution dispersion. Although the conventional quality measures aligned with these dimensions, none measured both adequately. We conclude that a multi-dimensional approach to assessment of forecast quality is required and that simple measures of reliability, distribution shift, and change in dispersion provide a means for such assessment. The analysis presented was also relevant to measuring quality of probabilistic seasonal climate forecasting systems. The importance of retaining a focus on the probabilistic nature of the forecast and avoiding simplifying, but erroneous, distortions was discussed in relation to applying this new forecast quality assessment paradigm to seasonal climate forecasts. Copyright (K) 2003 Royal Meteorological Society.

Simulation supplements field studies to determine no-till dryland corn population recommendations for semiarid western Nebraska

In a 2-yr multiple-site field study conducted in western Nebraska during 1999 and 2000, optimum dryland corn (Zea mays L.) population varied from less than 1.7 to more than 5.6 plants m(-2), depending largely on available water resources. The objective of this study was to use a modeling approach to investigate corn population recommendations for a wide range of seasonal variation. A corn growth simulation model (APSIM-maize) was coupled to long-term sequences of historical climatic data from western Nebraska to provide probabilistic estimates of dryland yield for a range of corn populations. Simulated populations ranged from 2 to 5 plants m(-2). Simulations began with one of three levels of available soil water at planting, either 80, 160, or 240 mm in the surface 1.5 m of a loam soil. Gross margins were maximized at 3 plants m(-2) when starting available water was 160 or 240 mm, and the expected probability of a financial loss at this population was reduced from about 10% at 160 mm to 0% at 240 mm. When starting available water was 80 mm, average gross margins were less than $15 ha(-1), and risk of financial loss exceeded 40%. Median yields were greatest when starting available soil water was 240 mm. However, perhaps the greater benefit of additional soil water at planting was reduction in the risk of making a financial loss. Dryland corn growers in western Nebraska are advised to use a population of 3 plants m(-2) as a base recommendation.

Genotype and environment effects on dynamics of harvest index during grain filling in sorghum

An approach based on a linear rate of increase in harvest index (141) with time after anthesis has been used as a simple means-to predict grain growth and yield in many crop simulation models. When applied to diverse situations, however, this approach has been found to introduce significant error in grain yield predictions. Accordingly, this study was undertaken to examine the stability of the HI approach for yield prediction in sorghum [Sorghum bicolor (L.) Moench]. Four field experiments were conducted under nonlimiting water. and N conditions. The experiments were sown at times that ensured a broad range in temperature and radiation conditions. Treatments consisted of two population densities and three genotypes varying in maturity. Frequent sequential harvests were used to monitor crop growth, yield, and the dynamics of 111. Experiments varied greatly in yield and final HI. There was also a tendency for lower HI with later maturity. Harvest index dynamics also varied among experiments and, to a lesser extent, among treatments within experiments. The variation was associated mostly with the linear rate of increase in HI and timing of cessation of that increase. The average rate of HI increase was 0.0198 d(-1), but this was reduced considerably (0.0147) in one experiment that matured in cool conditions. The variations found in IN dynamics could be largely explained by differences in assimilation during grain filling and remobilization of preanthesis assimilate. We concluded that this level of variation in HI dynamics limited the general applicability of the HI approach in yield prediction and suggested a potential alternative for testing.

Climate change and biotic invasions: a case history of a tropical woody vine

The impacts of climate change in the potential distribution and relative abundance of a C3 shrubby vine, Cryptostegia grandiflora, were investigated using the CLIMEX modelling package. Based upon its current naturalised distribution, C. grandiflora appears to occupy only a small fraction of its potential distribution in Australia under current climatic conditions; mostly in apparently sub-optimal habitat. The potential distribution of C. grandiflora is sensitive towards changes in climate and atmospheric chemistry in the expected range of this century, particularly those that result in increased temperature and water use efficiency. Climate change is likely to increase the potential distribution and abundance of the plant, further increasing the area at risk of invasion, and threatening the viability of current control strategies markedly. By identifying areas at risk of invasion, and vulnerabilities of control strategies, this analysis demonstrates the utility of climate models for providing information suitable to help formulate large-scale, long-term strategic plans for controlling biotic invasions. The effects of climate change upon the potential distribution of C. grandiflora are sufficiently great that strategic control plans for biotic invasions should routinely include their consideration. Whilst the effect of climate change upon the efficacy of introduced biological control agents remain unknown, their possible effect in the potential distribution of C. grandiflora will likely depend not only upon their effects on the population dynamics of C. grandiflora, but also on the gradient of climatic suitability adjacent to each segment of the range boundary.

Speleothem U-series dating of semi-synchronous climate oscillations during the last deglaciation

Evidence for nearly synchronous climate oscillations during the last deglaciation has been found throughout the Northern Hemisphere but few records are based on independent time scales of calendar years. We present a rare uranium-series dated oxygen-carbon isotope record for a speleothem from Tangshan Cave, China, which demonstrates that abrupt deglacial climatic oscillations from 16 800 to 10 500 yr BP are semi-synchronous with those found in Greenland ice core records. Relatively rapid shifts in speleothem oxygen isotope ratios demonstrate that the intensity of the East Asian monsoon switched in parallel with the abrupt transitions separating the Bolling-Allerod, Younger Dryas, and pre-Boreal climatic reversals. However, the dated isotopic transitions appear to have lasted longer. Our results demonstrate the dominant role of atmospheric teleconnections in the rapid propagation of deglacial climatic signals on a hemispheric scale, and highlight the importance of U-series dated speleothems in the timing and characterization of abrupt climate change. (C) 2003 Elsevier B.V. All rights reserved.