Exploratory Analysis of Similarities in Solar Cycle Magnetic Phases with Southern Oscillation Index Fluctuations in Eastern Australia

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.

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Relationship between the Southern Oscillation Index and Australian sugarcane yields

Australian Journal of Agricultural Research ◽

10.1071/ar9941557 ◽

1994 ◽

Vol 45 (7) ◽

pp. 1557 ◽

Cited By ~ 13

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.

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

The Rangeland Journal ◽

10.1071/rj12105 ◽

2013 ◽

Vol 35 (4) ◽

pp. 373 ◽

Cited By ~ 12

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.

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The influence of the Southern Oscillation Index on the timing of breeding of a forest-bird community in south-eastern Australia

Wildlife Research ◽

10.1071/wr21004 ◽

2021 ◽

Author(s):

R. Marchant ◽

M. Guppy ◽

S. Guppy

Keyword(s):

Southern Oscillation Index ◽

Southern Oscillation ◽

Bird Community ◽

Timing Of Breeding ◽

Forest Bird ◽

South Eastern ◽

Eastern Australia ◽

South Eastern Australia

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Australian rainfall patterns and the southern oscillation. 1. A continental perspective

Pacific Conservation Biology ◽

10.1071/pc040028 ◽

2004 ◽

Vol 10 (1) ◽

pp. 28 ◽

Cited By ~ 7

Author(s):

R. G. Vines ◽

J. C. Noble ◽

S. G. Marsden

Keyword(s):

Solar Cycle ◽

Southern Oscillation ◽

Sunspot Cycle ◽

Annual Rainfall ◽

Climatic Effects ◽

Eastern Australia ◽

Cyclic Variations ◽

Filter Analysis ◽

Australian Rainfall ◽

Yearly Data

Various Australian rainfall records have been subjected to filter-analysis. The results represent an extension of the findings of Currie and Vines (1996) in their analyses of more than 300 annual rainfall-series gathered from weather stations widely spaced across the continent. Further evidence is presented for the existence of "cyclic" variations in precipitation with periods of 16?20 years and 10?11 years. Links are suggested with the luni-solar cycle of 18.6 years and the sunspot cycle of nominal period 10?12 years. A shorter "cycle" of 6?7 years is also postulated. Similar analyses of yearly data for the Southern Oscillation yield further suggestions of "cycles" that correspond closely with those obtained from the rainfall records. Explanations are proposed which appear to account for a substantial proportion of the interannual variability of rainfall, particularly in eastern Australia - with connections being made between EI Ni�o/Southern Oscillation events and the incidence of drought in various parts of the continent. A major implication is that a variety of climatic effects in different parts of the world can be largely ascribed to the influence of the (18.6 year) luni-solar cycle.

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

Crop and Pasture Science ◽

10.1071/cp08277 ◽

2009 ◽

Vol 60 (3) ◽

pp. 230 ◽

Cited By ~ 5

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.

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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

Bulletin of Entomological Research ◽

10.1017/s0007485300000249 ◽

2000 ◽

Vol 90 (2) ◽

pp. 133-146 ◽

Cited By ~ 21

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.

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Middle Atmosphere Temperature Changes Derived from SABER Observations during 2002-2020

Journal of Climate ◽

10.1175/jcli-d-20-1010.1 ◽

2021 ◽

pp. 1

Author(s):

X. R. Zhao ◽

Z. Sheng ◽

H. Q. Shi ◽

L. B. Weng ◽

Y. He

Keyword(s):

Solar Cycle ◽

Middle Atmosphere ◽

Southern Oscillation ◽

Linear Trend ◽

Stratospheric Ozone ◽

Recovery Period ◽

Lower Thermosphere ◽

Quasi Biennial Oscillation ◽

Atmosphere Temperature ◽

Temperature Responses

AbstractUsing temperature data measured by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument from February 2002 to March 2020, the temperature linear trend and temperature responses to the solar cycle (SC), Quasi-Biennial Oscillation (QBO), and El Niño-Southern Oscillation (ENSO) were investigated from 20 km to 110 km for the latitude range of 50°S-50°N. A four-component harmonic fit was used to remove the seasonal variation from the observed monthly temperature series. Multiple linear regression (MLR) was applied to analyze the linear trend, SC, QBO, and ENSO terms. In this study, the near-global mean temperature shows consistent cooling trends throughout the entire middle atmosphere, ranging from -0.28 to -0.97 K/decade. Additionally, it shows positive responses to the solar cycle, varying from -0.05 to 4.53 K/100sfu. A solar temperature response boundary between 50°S and 50°N is given, above which the atmospheric temperature is strongly affected by solar activity. The boundary penetrates deep below the stratopause to ~ 42 km over the tropical region and rises to higher altitudes with latitude. Temperature responses to the QBO and ENSO can be observed up to the upper mesosphere and lower thermosphere. In the equatorial region, 40%-70% of the total variance is explained by QBO signals in the stratosphere and 30%-50% is explained by the solar signal in the upper middle atmosphere. Our results, obtained from 18-year SABER observations, are expected to be an updated reliable estimation of the middle atmosphere temperature variability for the stratospheric ozone recovery period.

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

Annals of Glaciology ◽

10.3189/172756406781812474 ◽

2006 ◽

Vol 43 ◽

pp. 14-22 ◽

Cited By ~ 10

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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Climatology of Heavy Orographic Rainfall Induced by Tropical Cyclones over Madagascar: From Synoptic to Mesoscale Perspectives

Earth Science Research ◽

10.5539/esr.v5n2p132 ◽

2016 ◽

Vol 5 (2) ◽

pp. 132 ◽

Cited By ~ 2

Author(s):

Tatiana A. Arivelo ◽

Yuh-Lang Lin

Keyword(s):

Tropical Cyclones ◽

Southern Oscillation Index ◽

Southern Oscillation ◽

Rainfall Variability ◽

Eastern Coast ◽

Quasi Biennial Oscillation ◽

Trade Winds ◽

Southwest Indian Ocean ◽

The North ◽

Orographic Rainfall

Variability of and generation mechanisms for Madagascar rainfall are studied by conducting climatological, synoptic and mesoscale analyses. It is found the rainfall variability is highly sensitive to seasons with high variability in summer (Nov-Apr). The rainfall in summer is controlled by the Intertropical Convergence Zone (ITCZ) and orographic rainfall associated with tropical cyclones (TCs), while the rainfall in winter (May-Oct) is controlled by trade winds and local orographic rainfall along the eastern coast. Synoptic analysis reveals that major climate variations in summer are associated with ITCZ position, which is closely related to TC genesis locations and quasi-biennial oscillation (QBO). Linkages between El-Niño Southern Oscillation Index (ENSO) and Southern Oscillation Index (SOI) are identified as the cause of inconsistent dry or wet summers. Mesoscale analysis depicts the importance of the orographic effects on prevailing wind, which are controlled by the orography in both seasons. In winter, the prevailing trade winds over the Southwest Indian Ocean are from the east and are split to the north and south when it impinges on Malagasy Mountains. On the other hand, in summer the prevailing easterlies are weaker leading to the production of lee vortices, in addition to the flow splitting upstream of the mountain. Thus, the flow is classified into two regimes: (a) flow-over regime with no lee vortices under high Froude number (Fr=1.2-1.8) flow, and (b) flow-around regime with lee vortices under low Fr (=0.88-1.16) flow. A case study of TC Domoina (1984) indicates that the long-lasting heavy rainfall was induced by the strong orographic blocking of Madagascar. The shorter-term (e.g., 2 days) heavy orographic precipitation is characterized by large VH ∙Ñh which is composed by two common ingredients, namely a strong low-level wind normal to the mountain (VH) and a steep mountain slope (∇h).

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