scholarly journals Forecasting rainfall based on the Southern Oscillation Index phases at longer lead-times in Australia

2013 ◽  
Vol 35 (4) ◽  
pp. 373 ◽  
Author(s):  
David H. Cobon ◽  
Nathan R. Toombs
Keyword(s):  
Key Management ◽  
Southern Oscillation Index ◽  
Southern Oscillation ◽  
Warm Season ◽  
Lead Times ◽  
Phase System ◽  
Management Decisions ◽  
Operational Forecasts ◽  
Eastern Australia ◽  
Forecast Quality

Under the extensive grazing conditions experienced in Australia, pastoralists would benefit from a long lead-time seasonal forecast issued for the austral warm season (November–March). Currently operational forecasts are issued publicly for rolling 3-month periods at lead-times of 0 or 1 month, usually without an indication of forecast quality. The short lag between the predictor and predictand limits use of forecasts because pastoralists operating large properties have insufficient time to implement key management decisions. The ability to forecast rainfall based on the Southern Oscillation Index (SOI) phase system was examined at 0–5-month lead-times for Australian rainfall. The SOI phase system provided a shift of adequate magnitude in the rainfall probabilities (–40 to +30%) and forecast quality for the 5-month austral warm season at lead-times >0 months. When data used to build the forecast system were used in verification, >20% of locations had a significant linear error in probability space (LEPS) and Kruskal–Wallis (KW) test for lead-times of 0–2 months. The majority of locations showing forecast quality were in northern Australia (north of 25°S), predominately in north-eastern Australia (north of 25°S, east of 140°E). Pastoralists in these areas can now apply key management decisions with more confidence up to 2 months before the November–March period. Useful lead-times of ≥3 months were not found.

The Southern Oscillation Index as a predictor of seasonal rainfall in the arable areas of the inland Australian subtropics

1993 ◽  
Vol 44 (6) ◽  
pp. 1337 ◽  
Author(s):  
JS Russell ◽  
IM McLeod ◽  
MB Dale ◽  
TR Valentine
Keyword(s):  
Southern Oscillation Index ◽  
Southern Oscillation ◽  
Linear Trend ◽  
Summer Rainfall ◽  
Seasonal Rainfall ◽  
Four Seasons ◽  
Eastern Australia ◽  
Australian Continent ◽  
Ace Algorithm ◽  
Linear Trends

A detailed study has been carried out in four regions in the subtropics of Eastern Australia to determine the relationship between the Southern Oscillation Index (SOI) and subsequent seasonal rainfall. The period studied was from 1915 to 1991 for 3-monthly periods of spring (SON), summer (DJF), autumn (MAM) and winter (JJA). The 3-monthly prior SOI values were plotted against seasonal rainfall of the four regions and four seasons. These data were widely scattered but with a linear trend showing increased seasonal rainfall as the SOI increased. Linear trends were plotted for each season and region. Comparisons were made between the use of the ACE algorithm, which transforms the SOI and rainfall data, and the use of linear trends. Polynomials were used to calculate equations for each region and season, but only spring and summer produced satisfactory ACE functions. Estimates were made of spring and summer rainfall relative to prior SOI values for each region. While the SOI as a predictor of rainfall broadly estimates spring and summer rainfall, this variable has limited usefulness on its own. One of the options available with the ACE program is that additional independent variables can be added as required. Current research suggests that sea surface temperature data from specific ocean areas surrounding the Australian continent is the most useful additional variable at present. However the complexity of such an analysis is greatly increased.

Relationship between the Southern Oscillation Index and Australian sugarcane yields

1994 ◽  
Vol 45 (7) ◽  
pp. 1557 ◽  
Author(s):  
I Kuhnel
Keyword(s):  
Southern Hemisphere ◽  
Southern Oscillation Index ◽  
Southern Oscillation ◽  
Significance Testing ◽  
The Past ◽  
Northern Areas ◽  
Eastern Australia ◽  
North Eastern ◽  
Sugarcane Yield ◽  
The Relationship

This study examines the relationship between the Southern Oscillation Index and the sugarcane yield anomalies at 27 mills in north-eastern Australia (Queensland) for the period 1950-1989. The major results of this work indicate that the SO1 alone seems to have only a limited value as predictor of total sugarcane yields over large areas (i.e. the whole of Queensland). However, on a smaller scale, the SO1 appears to be a useful indicator of yields for the northern sugarcane districts. In these northern areas, the highest correlations with the SO1 are reached during the southern hemisphere spring and summer months 6 to 11 months prior to the harvest. They are negative and explain about 40% of the total variance. They also suggest that a positive SO1 during the spring and summer months tends to be followed by lower-than-normal yields at the following harvest and vice versa. This signal is rather robust and withstands rigorous significance testing. Moreover, it appears that the relationship between the SO1 and the sugarcane yields has been relatively strong and stable for the past 40 years, but weakened substantially during the 1930-1940 period.

The value of skill in seasonal climate forecasting to wheat crop management in a region with high climatic variability

1996 ◽  
Vol 47 (5) ◽  
pp. 717 ◽  
Author(s):  
GL Hammer ◽  
DP Holzworth ◽  
R Stone
Keyword(s):  
Crop Management ◽  
Seasonal Forecast ◽  
Seasonal Forecasting ◽  
Wheat Crop ◽  
Phase System ◽  
Management Decisions ◽  
Seasonal Climate ◽  
Climate Forecasting ◽  
Daily Weather Data ◽  
Forecast Quality

In Australia, and particularly in the northern part of the grain belt, wheat is grown in an extremely variable climate. The wheat crop manager in this region is faced with complex decisions on choice of planting time, varietal development pattern, and fertiliser strategy. A skilful seasonal forecast would provide an opportunity for the manager to tailor crop management decisions more appropriately to the season. Recent developments in climate research have led to the development of a number of seasonal climate forecasting systems. The objectives of this study were to determine the value of the capability in seasonal forecasting to wheat crop management, to compare the value of the existing forecast methodologies, and to consider the potential value of improved forecast quality. We examined decisions on nitrogen (N) fertiliser and cultivar maturity using simulation analyses of specific production scenarios at a representative location (Goondiwindi) using long-term daily weather data (1894-1989). The average profit and risk of making a loss were calculated for the possible range of fixed (i.e. the same every year) and tactical (i.e. varying depending on seasonal forecast) strategies. Significant increase in profit (up to 20%) and/or reduction in risk (up to 35%) were associated with tactical adjustment of crop management of N fertiliser or cultivar maturity. The forecasting system giving greatest value was the Southern Oscillation Index (SOI) phase system of Stone and Auliciems (1992), which classifies seasons into 5 phases depending on the value and rate of change in the SOI. The significant skill in this system for forecasting both seasonal rainfall and frost timing generated the value found in tactical management of N fertiliser and cultivar maturity. Possible impediments to adoption of tactical management, associated with uncertainties in forecasting individual years, are discussed. The scope for improving forecast quality and the means to achieve it are considered by comparing the value of tactical management based on SO1 phases with the outcome given perfect prior knowledge of the season. While the analyses presented considered only one decision at a time, used specific scenarios, and made a number of simplifying assumptions, they have demonstrated that the current skill in seasonal forecasting is sufficient to justify use in tactical management of crops. More comprehensive studies to examine sensitivities to location, antecedent conditions, and price structure, and to assumptions made in this analysis, are now warranted. We have examined decisions related only to management of wheat. It would be appropriate to pursue similar analyses in relation to management decisions for other crops, cropping sequences, and the whole farm enterprise mix.

The resolution and potential value of Australian seasonal rainfall forecasts based on the five phases of the Southern Oscillation Index

2009 ◽  
Vol 60 (3) ◽  
pp. 230 ◽  
Author(s):  
Andrew L. Vizard ◽  
Garry A. Anderson
Keyword(s):  
Southern Oscillation Index ◽  
Southern Oscillation ◽  
Mean Value ◽  
Expected Value ◽  
Variance Ratio ◽  
Large Shift ◽  
Potential Value ◽  
Eastern Australia ◽  
Forecasting System ◽  
Cape York

We assess the resolution of the Southern Oscillation Index (SOI) seasonal rainfall forecasting system and calculate the loss in potential value of the forecasting system using a cost/loss model. Forecasts of the probability of a ‘dry’ autumn, winter, spring, and summer were obtained for 226 towns across Australia, based on the 5 phases of the SOI. For every town the variance ratio, the observed forecast variance as a proportion of the variance of a perfect forecasting system, was calculated for each season. Value score curves, showing the expected value of the forecasts as a proportion of the expected value of perfect information, were calculated for every town for each season. Maps of variance ratio and maps of mean value scores across Australia were produced by ordinary kriging. In all seasons and regions the SOI forecasting system had a variance ratio of less than 0.20, indicating that resolution and skill were never high. Variance ratios greater than 0.10 only occurred in parts of south-eastern Australia and the Cape York region during spring and in the Townsville region during summer. The variance ratio was less than 0.05 for the majority of Australia during autumn, winter, and summer. The mean value scores for actions that are only triggered by a large shift in the forecast from climatology were uniformly close to zero in all seasons and regions, indicating that little or no value can be derived in such cases. Actions triggered by a moderate shift of the forecast were also generally associated with low value scores. Mean value scores above 0.20 were limited to actions with a decision threshold close to climatology and only occurred in parts of south-eastern Australia and the Cape York region during spring and in the Townsville region during summer. We conclude that the imperfect resolution of the SOI forecasting system has a substantial effect on potential value. The forecasting system can potentially deliver value to users with actions that are triggered by a small shift in the forecast from climatology, especially in eastern Australia during spring, but not to users with actions that are only triggered by a large shift of the forecasts from climatology.

scholarly journals Sub-seasonal precipitation prediction for Africa: Forecast evaluation and sources of predictability

2020 ◽  
Author(s):  
Felipe M. de Andrade ◽  
Matthew P. Young ◽  
David MacLeod ◽  
Linda C. Hirons ◽  
Steven J. Woolnough ◽  
...  
Keyword(s):  
Southern Oscillation ◽  
Forecast Evaluation ◽  
Precipitation Forecast ◽  
Lead Times ◽  
Seasonal Precipitation ◽  
Madden Julian Oscillation ◽  
Probabilistic Forecasts ◽  
Different Seasons ◽  
The Impact ◽  
Forecast Quality

AbstractThis paper evaluates sub-seasonal precipitation forecasts for Africa using hindcasts from three models (ECMWF, UKMO, and NCEP) participating in the Subseasonal to Seasonal (S2S) prediction project. A variety of verification metrics are employed to assess weekly precipitation forecast quality at lead times of one to four weeks ahead (Weeks 1-4) during different seasons. Overall, forecast evaluation indicates more skilful predictions for ECMWF over other models and for East Africa over other regions. Deterministic forecasts show substantial skill reduction in Weeks 3-4 linked to lower association and larger underestimation of predicted variance compared to Weeks 1-2. Tercile-based probabilistic forecasts reveal similar characteristics for extreme categories and low quality in the near-normal category. Although discrimination is low in Weeks 3-4, probabilistic forecasts still have reasonable skill, especially in wet regions during particular rainy seasons. Forecasts are found to be over-confident for all weeks, indicating the need to apply calibration for more reliable predictions. Forecast quality within the ECMWF model is also linked to the strength of climate drivers’ teleconnections, namely El Niño-Southern Oscillation, Indian Ocean Dipole, and the Madden-Julian Oscillation. The impact of removing all driver-related precipitation regression patterns from observations and hindcasts shows reduction of forecast quality compared to including all drivers’ signals, with more robust effects in regions where the driver strongly relates to precipitation variability. Calibrating forecasts by adding observed regression patterns to hindcasts provides improved forecast associations particularly linked to the Madden-Julian Oscillation. Results from this study can be used to guide decision-makers and forecasters in disseminating valuable forecasting information for different societal activities in Africa.

Long range forecasts of the numbers of Helicoverpa punctigera and H. armigera (Lepidoptera: Noctuidae) in Australia using the Southern Oscillation Index and the Sea Surface Temperature

2000 ◽  
Vol 90 (2) ◽  
pp. 133-146 ◽  
Author(s):  
D.A. Maelzer ◽  
M.P. Zalucki
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Pest Management ◽  
Southern Oscillation Index ◽  
Southern Oscillation ◽  
Sea Surface ◽  
Multiple Regressions ◽  
Eastern Australia ◽  
Trap Catches

The use of long-term forecasts of pest pressure is central to better pest management. We relate the Southern Oscillation Index (SOI) and the Sea Surface Temperature (SST) to long-term light-trap catches of the two key moth pests of Australian agriculture, Helicoverpa punctigera (Wallengren) and H. armigera (Hübner), at Narrabri, New South Wales over 11 years, and for H. punctigera only at Turretfield, South Australia over 22 years. At Narrabri, the size of the first spring generation of both species was significantly correlated with the SOI in certain months, sometimes up to 15 months before the date of trapping. Differences in the SOI and SST between significant months were used to build composite variables in multiple regressions which gave fitted values of the trap catches to less than 25% of the observed values. The regressions suggested that useful forecasts of both species could be made 6–15 months ahead. The influence of the two weather variables on trap catches of H. punctigera at Turretfield were not as strong as at Narrabri, probably because the SOI was not as strongly related to rainfall in southern Australia as it is in eastern Australia. The best fits were again given by multiple regressions with SOI plus SST variables, to within 40% of the observed values. The reliability of both variables as predictors of moth numbers may be limited by the lack of stability in the SOI-rainfall correlation over the historical record. As no other data set is available to test the regressions, they can only be tested by future use. The use of long-term forecasts in pest management is discussed, and preliminary analyses of other long sets of insect numbers suggest that the Southern Oscillation Index may be a useful predictor of insect numbers in other parts of the world.

scholarly journals Relationships between Southeast Australian Temperature Anomalies and Large-Scale Climate Drivers

2014 ◽  
Vol 27 (4) ◽  
pp. 1395-1412 ◽  
Author(s):  
Alexandre O. Fierro ◽  
Lance M. Leslie
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Power Spectra ◽  
Warm Season ◽  
Principal Component ◽  
Temperature Variability ◽  
Maximum Temperature ◽  
Past Century ◽  
Tasman Sea ◽  
Australian Continent

Abstract Over the past century, particularly after the 1960s, observations of mean maximum temperatures reveal an increasing trend over the southeastern quadrant of the Australian continent. Correlation analysis of seasonally averaged mean maximum temperature anomaly data for the period 1958–2012 is carried out for a representative group of 10 stations in southeast Australia (SEAUS). For the warm season (November–April) there is a positive relationship with the El Niño–Southern Oscillation (ENSO) and the Pacific decadal oscillation (PDO) and an inverse relationship with the Antarctic Oscillation (AAO) for most stations. For the cool season (May–October), most stations exhibit similar relationships with the AAO, positive correlations with the dipole mode index (DMI), and marginal inverse relationships with the Southern Oscillation index (SOI) and the PDO. However, for both seasons, the blocking index (BI, as defined by M. Pook and T. Gibson) in the Tasman Sea (160°E) clearly is the dominant climate mode affecting maximum temperature variability in SEAUS with negative correlations in the range from r = −0.30 to −0.65. These strong negative correlations arise from the usual definition of BI, which is positive when blocking high pressure systems occur over the Tasman Sea (near 45°S, 160°E), favoring the advection of modified cooler, higher-latitude maritime air over SEAUS. A point-by-point correlation with global sea surface temperatures (SSTs), principal component analysis, and wavelet power spectra support the relationships with ENSO and DMI. Notably, the analysis reveals that the maximum temperature variability of one group of stations is explained primarily by local factors (warmer near-coastal SSTs), rather than teleconnections with large-scale drivers.

scholarly journals A first shallow firn-core record from Glaciar La Ollada, Cerro Mercedario, central Argentine Andes

2006 ◽  
Vol 43 ◽  
pp. 14-22 ◽  
Author(s):  
David Bolius ◽  
Margit Schwikowski ◽  
Theo Jenk ◽  
Heinz W. Gäggeler ◽  
Gino Casassa ◽  
...  
Keyword(s):  
El Niño ◽  
Southern Oscillation Index ◽  
El Nino ◽  
Southern Oscillation ◽  
Winter Precipitation ◽  
Time Span ◽  
Paleoclimate Reconstruction ◽  
Central Chile ◽  
Annual Layer ◽  
Firn Core

AbstractIn January 2003, shallow firn cores were recovered from Glaciar Esmeralda on Cerro del Plomo (33°14’S, 70°13’W; 5300 ma.s.l.), central Chile, and from Glaciar La Ollada on Cerro Mercedario (31°58’S, 70°07’W; 6070 ma.s.l.), Argentina, in order to find a suitable archive for paleoclimate reconstruction in a region strongly influenced by the El Nino-Southern Oscillation. In the area between 28°S and 35°S, the amount of winter precipitation is significantly correlated to the Southern Oscillation Index, with higher values during El Nino years. Glaciochemical analysis indicates that the paleo-record at Glaciar La Ollada is well preserved, whereas at Glaciar Esmeralda the record is strongly influenced by meltwater formation and percolation. A preliminary dating of the Mercedario core by annual-layer counting results in a time-span of 17 years (1986-2002), yielding an average annual net accumulation of 0.45 m w.e.

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