Southern Oscillation Index Phases Research Articles

Plastic Behaviour Buffers Climate Variability in the Wandering Albatross.

Climate change has marked effects on global weather patterns and oceanic systems, impacting animal behaviour and fitness in potentially profound ways. Despite this, we lack detailed information about species' responses to climatic variation. Using an 11-year tracking dataset of over 300 individual birds, we explore the consequences of variation in the southern annular mode (SAM) and southern oscillation index (SOI) for individual behaviour and fitness in wandering albatrosses Diomedea exulans breeding in the Southern Indian Ocean. Our results reveal distinct responses between males and females to climatic variation that align with the impacts of each climatic index on the distinct foraging ranges of each sex. In positive SAM phases, linked to poorer foraging conditions in female ranges and better conditions in male ranges, females exhibited behaviour consistent with reduced foraging success: that is, fewer prey capture attempts and more movement between feeding patches. Males, on the other hand, showed no behavioural change. During positive SOI phases, associated with good foraging conditions in both male and female foraging ranges, both sexes showed evidence of more successful foraging, with birds engaging in more search behaviour, and taking shorter trips with fewer prey capture attempts, together indicating increased food intake per unit time. We found limited evidence for a role of individual variation, as measured through differences in personality, suggesting that plastic responses to climate are sufficiently important so as to obscure inter-individual variation. Supporting this was the finding that individual breeding success was unaffected by climatic variation, suggesting that plastic foraging behaviour allows albatrosses to mitigate climate impacts and maintain reproductive output.

Machine learning-based integration of large-scale climate drivers can improve the forecast of seasonal rainfall probability in Australia

Probabilistic seasonal rainfall forecasting is of great importance for stakeholders such as farmers and policymakers to assist in developing risk management strategies and to inform decisions. In practice, there are two kinds of commonly used tools, dynamical models and statistical models, to provide probabilistic seasonal rainfall forecasts. Dynamical models are based on physical processes but are usually expensive to operate and implement, and rely overly on initial conditions. Statistical models are easy to implement but are usually based on simple or linear relationships between observed variables. Recently, machine learning techniques have been widely used in climate projection and perform well in reproducing historical climate. For these reasons, we conducted a case study in Australia by developing a machine learning-based probabilistic seasonal rainfall forecasting model using multiple large-scale climate indices from the Pacific, Indian and Southern Oceans. Rainfall probabilities of exceeding the climatological median for upcoming seasons from 2011 to 2018 were successively forecasted using multiple climate indices of precedent six months. The performance of the model was evaluated by comparing it with an officially used forecasting model, the SOI (Southern Oscillation Index) phase model (SP) operated by Queensland government in Australia. Results indicated that the random forest (RF) model outperformed the SP model in terms of both distinct forecasts and forecasting accuracy. The RF model increased the percentages of distinct forecasts to 64.9% for spring, to 71.5% for summer, to 65.8% for autumn, and to 63.9% for winter, 1.4 ∼ 3.2 times of the values from the SP model. Forecasting accuracy was also greatly increased by 28%, 167%, 219%, and 76% for four seasons respectively, compared to the SP model. The proposed rainfall forecasting model is based on readily available data, and we believe it can be easily extended to other regions to provide seasonal rainfall outlooks.

Economic benefits of ENSO information in crop management decisions: case study of rice farming in West Java, Indonesia

The El Nino Southern Oscillation (ENSO) strongly influences rainfall extremes in Indonesia with major impacts on droughts and floods and potential consequences for rice production. The Southern Oscillation Index (SOI) is an indicator used to detect the occurrence of ENSO events. A consistently negative (phase 1) and a rapidly falling SOI (phase 3) (indicating an El Nino cycle) were related to high probability of below-average rainfalls in the Ciparay and Bojongsoang areas of Bandung District. Therefore, the use of SOI phase information prior to the planting season would assist farmers in making optimum planting decisions. This study attempted to evaluate the economic benefits of using SOI phase information in March/April to make informed agricultural decisions for the second crop planting (April/May). The use of the SOI phases in conjunction with a crop simulation model would facilitate an objective evaluation of other cropping options. The results indicated that farmers who switched from rice to soybean or maize for the May planting season, following the March/April SOI phase I and III, earned higher incomes. The cumulative net income differences over the 63 years for soybean was about USD 1700 (27% higher at Ciparay) and USD 2350 (45% higher at Bojongsoang) and for maize was about USD 1524 (19% higher at Ciparay) and USD 1970 (35% higher at Bojongsoang).

Integrated large‐scale circulation impact on rainy season precipitation in the source region of the Yangtze River

AbstractMonthly precipitation data at regular grids of 0.5° × 0.5° derived from observations during June–August 1961–2016 were used to reveal characteristics of large‐scale circulations associated with rainy season precipitation over the source region of the Yangtze River (SRYR). The integrated impact of major influencing circulation patterns was examined by principal component analysis and composites. Results showed that the first rainy season precipitation mode associates with the Southern Oscillation Index (SOI) and the Pacific Decadal Oscillation (PDO), explaining 64% of spatial and temporal rainy season precipitation variance in the region. Composites of precipitation pattern under different phases of SOI and PDO revealed that the effect of PDO on precipitation varies with the SOI phase. When in phase with the SOI, PDO‐induced precipitation anomalies are magnified. When out‐of‐phase, anomalies weaken or even disappear. Composites of moisture flux patterns show that large‐scale atmospheric circulation affects the strength of westerlies that transport moisture to the study area and formation of convergence. In coming decades, the PDO is likely to continue in a negative phase with La Niña (positive SOI) events, implying more precipitation during the rainy season. Consequently, this knowledge can be used to improve decision making regarding water supply and flood risk management in the SRYR.

Bimodal climate control of shoreline change influenced by Interdecadal Pacific Oscillation variability along the Cooloola Sand Mass, Queensland, Australia

Wave climate in southeast Queensland, Australia has been correlated to changes in the Southern Oscillation Index (SOI), but observations of shoreline change associated with the variable wave climate have been limited due to a paucity of aerial photography, LiDAR, and other beach profiling datasets in this region. A multi-decadal, sub-annual temporal resolution shoreline dataset spanning 1996 to 2017 was produced using satellite imagery collected by Landsat 5, 7, and 8. A total of 147 shoreline positions were delineated using the Modified Normalized Difference Water Index on cloud-free imagery and corrected for horizontal offsets forced by variable tide stages at the satellite flyover time. The relative influence of SOI, the Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO), and Subtropical Ridge Latitude (STR-L) and Pressure (STR-P) on shoreline dynamics along the Cooloola Sand Mass in Queensland are assessed by performing cross correlations between their respective index values and shoreline change distances calculated by the Digital Shoreline Analysis System. A bimodal climate control of shoreline change is observed dependent upon the phase of the Interdecadal Pacific Oscillation (IPO). IPO modulates the impacts of ENSO on eastern Australia through its control over the position of the South Pacific Convergence Zone and elevating/lowering of tropical Pacific sea surface temperatures. During negative IPO, SOI is negatively correlated to the Cooloola Sand Mass shoreline indicating that the shoreline retreats during negative SOI phases. During positive IPO, the impacts of SOI are weakened and the STR becomes the primary driver of shoreline change with shoreline response being contingent upon its orientation. The SW-NE aligned Noosa North shoreline erodes in response to poleward movement of the STR, likely due to the enhanced cross-shore wave attack as a result of anti-clockwise wave rotation. The opposite response is shown at the SE-NW aligned Rainbow Beach shoreline, which is oriented almost parallel to the incident wave direction and is sheltered by the Double Island Point headland. These results suggest that climate control on shoreline change at Cooloola Sand Mass, and likely other sand islands in the region, is two-tiered, whereby interdecadal variability of the IPO governs the relative influence of SOI and STR under the different IPO phases. The linked climate and shoreline variability correlation shown in this study provides significant insight into how the Cooloola Sand Mass shoreline will respond to future climate changes under a global warming scenario.

The Value of Tactical Adaptation to El Niño–Southern Oscillation for East Australian Wheat

El Niño–Southern Oscillation strongly influences rainfall and temperature patterns in Eastern Australia, with major impacts on frost, heat, and drought stresses, and potential consequences for wheat production. Wheat phenology is a key factor to adapt to the risk of frost, heat, and drought stresses in the Australian wheatbelt. This study explores broad and specific options to adapt wheat cropping systems to El Niño–Southern Oscillation, and more specifically, to the Southern Oscillation Index (SOI) phases ahead of the season (i.e., April forecast) in Eastern Australia, when wheat producers make their most crucial management decisions. Crop model simulations were performed for commercially-grown wheat varieties, as well as for virtual genotypes representing possible combinations of phenology alleles that are currently present in the Australian wheat germplasm pool. Different adaptation strategies were tested at the site level, across Eastern Australia, for a wide range of sowing dates and nitrogen applications over long-term historical weather records (1900–2016). The results highlight that a fixed adaptation system, with genotype maturities, sowing time, and nitrogen application adapted to each location would greatly increase wheat productivity compared to sowing a mid-maturity genotype, mid-season, using current practices for nitrogen applications. Tactical adaptation of both genotype and management to the different SOI phases and to different levels of initial Plant Available Water (‘PAW & SOI adaptation’) resulted in further yield improvement. Site long-term increases in yield and gross margin were up to 1.15 t·ha−1 and AU$ 223.0 ha−1 for fixed adaptation (0.78 t·ha−1 and AU$ 153 ha−1 on average across the whole region), and up to an extra 0.26 t·ha−1 and AU$ 63.9 ha−1 for tactical adaptation. For the whole eastern region, these results correspond to an annual AU$ 440 M increase for the fixed adaptation, and an extra AU$ 188 M for the PAW & SOI tactical adaptation. The benefits of PAW & SOI tactical adaptation could be useful for growers to adjust farm management practices according to pre-sowing seasonal conditions and the seasonal climate forecast.

Influence of climate oscillations on temperature and precipitation over the United Arab Emirates

In this study, we investigate the influence of global climate oscillations on the local temperature and precipitation over the United Arab Emirates (UAE), which is one of the driest regions in the world with very high temperatures and low precipitation. The identification and assessment of remote interactions (teleconnections) are carried out by using ground station and gridded data sets. Monthly rainfall data from six ground stations over the UAE for the period of 1982–2010 is used in this study along with the long-term gridded precipitation and temperature data from the Global Precipitation Climatology Center and Global Historic Climatic Network. Linear correlations, wavelet analysis, and cross-wavelet analysis have been applied to identify the relation between climate indices and precipitation (temperature). The analysis reveals that the strong variability in precipitation is closely associated with the Southern Oscillation Index (SOI) and the Indian Ocean Dipole Index (IOD) during the months of August–March, September–January, respectively. In case of temperature, the strong variability is associated with the North Atlantic Oscillation Index (NAO) and the East Atlantic Oscillation Index (EAO) during the months of April–October, July–December. Spatial analysis of cross-wavelet reveals that the winter precipitation is significantly influenced by SOI and temperature during summer by the NAO. This research concludes that the negative phases of SOI (NAO) play a significant role in the increase of precipitation (decrease in summer temperatures) over the UAE region.

Influence of southern oscillation on autumn rainfall in Iran (1951–2011)

This study aimed to investigate the relationships between southern oscillation and autumn (October–December) rainfall in Iran. It also sought to identify the possible physical mechanisms involved in the mentioned relationships by analyzing observational atmospheric data. Analyses were based on monthly rainfall data from 50 synoptic stations with at least 35 years of records up to the end of 2011. Autumn rainfall time series were grouped by the average Southern Oscillation Index (SOI) and SOI phase methods. Significant differences between rainfall groups in each method were assessed by Kruskal-Wallis and Kolmogorov-Smirnov non-parametric tests. Their relationships were also validated using the linear error in probability space (LEPS) test. The results showed that average SOI and SOI phases during July–September were related with autumn rainfall in some regions located in the west and northwest of Iran, west coasts of the Caspian Sea and southern Alborz Mountains. The El Nino (negative) and La Nina (positive) phases were associated with increased and decreased autumn rainfall, respectively. Our findings also demonstrated the persistence of Southern Pacific Ocean’s pressure signals on autumn rainfall in Iran. Geopotential height patterns were totally different in the selected El Nino and La Nina years over Iran. During the El Nino years, a cyclone was formed over the north of Iran and an anticyclone existed over the Mediterranean Sea. During La Nina years, the cyclone shifted towards the Mediterranean Sea and an anticyclone developed over Iran. While these El Nino conditions increased autumn rainfall in Iran, the opposite conditions during the La Nina phase decreased rainfall in the country. In conclusion, development of rainfall prediction models based on the SOI can facilitate agricultural and water resources management in Iran.

Evaluating the distribution of water resources in western Canada using synoptic climatology and selected teleconnections. Part 1: winter season

AbstractThe Climatic Redistribution of western Canadian Water Resources project was designed to identify regions of increased/decreased water availability by evaluating a suite of atmospheric, hydroclimatic and streamflow variables. This research component focuses on the atmospheric drivers of air temperature and precipitation in the watersheds originating on the leeward slopes of the Rocky Mountains. Dominant winter (November–April) synoptic‐scale mid‐tropospheric circulation patterns from 1950 to 2011 are classified using self‐organizing maps, and frequency distributions for positive/negative phases of the Southern Oscillation Index (SOI), Pacific Decadal Oscillation (PDO) and Arctic Oscillation are statistically compared. Corresponding high‐resolution gridded temperature and precipitation anomalies are calculated for each synoptic type, and spatial patterns of above/below‐average temperature and precipitation and north/south gradients are identified. Gridded 6‐month values of the Standardized Precipitation–Evapotranspiration Index are also used to categorize winters into regions of high/low snowpack. Results indicate high‐pressure ridges over the Pacific Ocean (western North America), and low‐pressure troughs over western North America (Pacific Ocean) are associated with anomalously cool (warm) and wet (dry) conditions in the study region. Several statistically different synoptic type frequencies were found for positive/negative phases of the SOI, PDO and Arctic Oscillation. Most notably, positive (negative) phases of the SOI and negative (positive) phases of the PDO are associated with a higher (lower) frequency of ridging over the Pacific Ocean (western North America). Through improved knowledge of the relationships between teleconnections, mid‐tropospheric circulation and surface climate, the spatial and temporal distribution of water resources in western Canada is better understood. Copyright © 2014 John Wiley & Sons, Ltd.

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

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.

Modelled yield and water use efficiency of maize in response to crop management and Southern Oscillation Index in a soil-climate transect in Argentina

Maize responses to individual management factors have been widely investigated but studies of higher-order interactions involving multiple factors are rare. This paper investigates the responses of grain yield and water use efficiency of rainfed maize to sowing date, stubble condition, hybrids of contrasting cycle length, soil depth and their interactions, and how these responses are affected by El Niño – Southern Oscillation (ENSO) phenomenon. Grain yield and water balance were modelled with CropSyst using 33 years of weather data for eight locations in an east–west transect in the Southern Pampas of Argentina. Modelled grain yield decreased westward, in parallel with decreasing rainfall. Southern Oscillation Index (SOI) discriminated crop season rainfall and grain yield, with lower rainfall and grain yield for SOI phase Consistently Positive (CP) and higher rainfall and grain yield for SOI phase Consistently Negative (CN). Differences in grain yield between stubble and bare soil were constant across location. High available water, as related to soil depth, increased grain yield across the transect. The effect of sowing date and stubble varied with SOI phase; for CN, highest grain yields were obtained with early sowing whereas for CP grain yield showed no correlation with sowing date. Yield differences between bare soil and stubble conditions were higher under CP than under CN, reflecting the positive effect of stubble in years with rainfall below average. Water use efficiency (WUE=yield per unit evapotranspiration) averaged 19.0kgha−1mm−1 for soils with stubble and 16.5kgha−1mm−1 for bare soil. We conclude that SOI provides an agronomically meaningful predictor of seasonal conditions that can be used to estimate crop production and manage risk by adjusting key management practices.

Non-stationary influence of El Niño-Southern Oscillation and winter temperature on oak latewood growth in NW Iberian Peninsula

The properties of El Niño-Southern Oscillation (ENSO), such as period, amplitude, and teleconnection strength to extratropical regions, have changed since the mid-1970s. ENSO affects the regional climatic regime in SW Europe, thus tree performance in the Iberian Peninsula could be affected by recent ENSO dynamics. We established four Quercus robur chronologies of earlywood and latewood widths in the NW Iberian Peninsula. The relationship between tree growth and the Southern Oscillation Index (SOI), the atmospheric expression of ENSO, showed that only latewood growth was correlated negatively with the SOI of the previous summer-autumn-winter. This relationship was non-stationary, with significant correlations only during the period 1952-1980; and also non-linear, with enhanced latewood growth only in La Niña years, i.e. years with a negative SOI index for the previous autumn. Non-linear relationship between latewood and SOI indicates an asymmetric influence of ENSO on tree performance, biassed towards negative SOI phases. During La Niña years, climate in the study area was warmer and wetter than during positive years, but only for 1952-1980. Winter temperatures became the most limiting factor for latewood growth since 1980, when mean regional temperatures increased by 1°C in comparison to previous periods. As a result, higher winter respiration rates, and the extension of the growing season, would probably cause an additional consumption of stored carbohydrates. The influence of ENSO and winter temperatures proved to be of great importance for tree growth, even at lower altitudes and under mild Atlantic climate in the NW Iberian Peninsula.

A new objective procedure for classifying New Zealand synoptic weather types during 1958–2008

AbstractA set of 12 daily weather types has been obtained for the New Zealand region from the 51‐year NCAR/NCEP dataset by using a two‐stage classification procedure (rotated T‐mode principal component analysis followed by convergent K‐means clustering). Analysis of this classification confirms previous studies and provides further insight into the variation features of the regional synoptic weather on the seasonal, interannual and longer‐time scales.There are seasonal variations in both intensity and frequency of synoptic weather types. For example, southern highs are more frequent in summer and autumn, while troughs and lows occur more often in winter and secondarily spring. The high and low centres of weather types tend to be more intense in winter than summer.The frequency and lifetime of synoptic weather types fluctuate on the interannual and decadal scales; there exist significant correlations between frequencies of individual weather types and Southern Oscillation Index (SOI). In all seasons, the frequencies of weather types can change with phases of SOI. The most significant changes in weather type frequencies during the negative SOI phase occur in spring, and characterized by more frequent occurrence of weather types which provide prevailing southwesterly to westerly winds and reduced prominence of anticyclonic situations. The most significant changes in type frequencies during the positive SOI phase occur in summer, with more frequent anticyclonic types but less frequent cyclonic types. The frequency change in winter seems different from other seasons, although consistent with previous studies. In addition, the probability of extremely frequent occurrence or lack of occurrence of certain weather types during a month also varies significantly with SOI phases and with seasons, indicating that the chance for extreme weather conditions to occur is conditional on SOI.The results can be useful for climate forecasts, studies of climate extremes, air pollution, climatic impacts on human health and other environmental problems. Copyright © 2010 Royal Meteorological Society

Interannual variability of SST, SLA and wind waves in the Hawaii area and their responses to ENSO

Time series of sea surface temperature (SST), wind speed and significant wave height (SWH) from meteorological buoys of the National Data Buoy Center (NDBC) are useful for studying the interannual variability and trend of these quantities at the buoy areas. The measurements from 4 buoys (B51001, B51002, B51003 and B51004) in the Hawaii area are used to study the responses of the quantities to EI Nino and Southern Oscillation (ENSO). Long-term averages of these data reflect precise seasonal and climatological characteristics of SST, wind speed and SWH around the Hawaii area. Buoy observations from B51001 suggest a significant warming trend which is, however, not very clear from the other three buoys. Compared with the variability of SST and SWH, the wind speeds from the buoy observations show an increasing trend. The impacts of EI Nino on SST and wind waves are also shown. Sea level data observed by altimeter during October 1992 to September 2006 are analyzed to investigate the variability of sea level in the Hawaii area. The results also show an increasing trend in sea level anomaly (SLA). The low-passed SLA in the Hawaii area is consistent with the inverse phase of the low-passed SOI (Southern Oscillation Index). Compared with the low-passed SOI and PDO (Pacific Decadal Oscillation), the low-passed PNA (Pacific-North America Index) has a better correlation with the low-passed SLA in the Hawaii area.

Value of historical climate knowledge, SOI-based seasonal climate forecasting and stored soil moisture at sowing in crop nitrogen management in south eastern Australia

Abstract This paper explores the value of using historical climate knowledge, Southern Oscillation Index (SOI) and stored soil moisture at sowing time of wheat and canola crops to manage nitrogen application for increasing economic benefits from crop production and reducing drainage of farming systems at Walbundrie in Southeast Australia. The Agricultural Production System Simulator (APSIM) was used to simulate crop production and drainage passing the crop root zone in response to nitrogen application rates from 0 to 300 kgN ha−1 year−1 using historical climate records from 1889 to 2002. The skills of SOI phases to forecast growing season rainfall and crop yield were analysed. The impact of nitrogen management based on historical climate knowledge, SOI phases and stored soil moisture was assessed. The results showed that while the optimal N rate for maximum economic return was around 150 kgN ha−1 year−1 based on long-term average climatic conditions, it varied significantly from year to year depending on rainfall. Compared with current N application rate of 100 kgN ha−1 year−1 in the study region, the optimal N rate of 150 kgN ha−1 year−1 derived from historical climate knowledge could lead to an increase of wheat gross margin by AU$74 ha−1 year−1. The April to May SOI phases were useful predictors of growing season rainfall and grain yield of wheat and canola crops. The optimal N rates were 100, 150, 200 kgN ha−1 year−1 in the years when April/May SOI phases were falling/negative, near zero, and rising/positive, respectively. Based on such management, wheat gross margin was only increased by 2%, 0%, and 1%, respectively, corresponding to a mean increase in gross margin of AU$6 ha−1, compared with N management at the optimal fixed N rate of 150 kgN ha−1 year−1. Stored soil water at sowing time (SSMS) showed positive correlation with crop yield. However, combining April/May SOI phases and SSMS to manage N application only increased wheat gross margin by AU$8.8 ha−1, and reduced deep drainage by 1.7 mm year−1 for wheat, compared with N management based historical climate knowledge. Similar results were obtained for a continuous canola cropping system.

Quality and potential utility of ENSO-based forecasts of spring rainfall and wheat yield in south-eastern Australia

Reliable seasonal climate forecasts are needed to aid tactical crop management decisions in south-eastern Australia (SEA). In this study we assessed the quality of two existing forecasting systems, i.e. the five phases of the Southern Oscillation Index (SOI) and a three phase Pacific Ocean sea-surface temperatures (SSTs), to predict spring rainfall (i.e. rainfall from 1 September to 31 November), and simulated wheat yield. The quality of the forecasts was evaluated by analysing four attributes of their performance: their reliability, the relative degree of shift and dispersion of the distributions, and measure of forecast consistency or skill. Available data included 117 years of spring rainfall and 104 years of grain yield simulated using the Agricultural Production Systems Simulator (APSIM) model, from four locations in SEA. Average values of spring rainfall were 102–174 mm with a coefficient of variation (CV) of 47%. Average simulated wheat yields were highest (5609 kg/ha) in Albury (New South Wales) and lowest (1668 kg/ha) in Birchip (Victoria). The average CV for simulated grain yields was 36%. Griffith (NSW) had the highest yield variability (CV = 50%). Some of this year-to-year variation was related to the El Niño Southern Oscillation (ENSO). Spring rainfall and simulated wheat yields showed a clear association with the SOI and SST phases at the end of July. Important variations in shift and dispersion in spring rainfall and simulated wheat yields were observed across the studied locations. The forecasts showed good reliability, indicating that both forecasting systems could be used with confidence to forecast spring rainfall or wheat yield as early as the end of July. The consistency of the forecast of spring rainfall and simulated wheat yield was 60–83%. We concluded that adequate forecasts of spring rainfall and grain yield could be produced at the end of July, using both the SOI and SST phase systems. These results are discussed in relation to the potential benefit of making tactical top-dress applications of nitrogen fertilisers during early August.

Precipitation in Nepal between 1987 and 1996

AbstractRain gauge station data from 1987 to 1996 were used to investigate spatial and temporal variability in monthly precipitation and annual and seasonal precipitation patterns over Nepal. Maximum annual precipitation increased with altitude for elevations below 2000 m but decreased for elevations of 2000–3500 m. The data revealed a negative relationship between annual precipitation and elevation only in western Nepal. Annual precipitation averaged on a 0.25° grid exceeded 3000 mm/yr in central Nepal but was less than 1000 mm/yr over Nepal's northwestern mountains. Only winter precipitation over western Nepal was heavier than precipitation over central and eastern Nepal. A time series of standardized precipitation anomalies averaged over Nepal revealed no significant long‐term trends. Further, almost no stations exhibited significant long‐term trends by Kendall's rank correlation analysis. A correlation analysis between summer monsoon precipitation and the All Indian Rainfall (AIR) index revealed positive and negative correlations in western and eastern Nepal, respectively. This analysis also revealed a positive correlation, but no negative correlation, between summer monsoon precipitation and the Southern Oscillation Index (SOI) in western and eastern Nepal. Composite differences in temperature, 850‐hPa winds, outgoing longwave radiation (OLR), and precipitation rates between low and high AIR phases revealed that moist air from the Arabian Sea supported precipitation over western Nepal, whereas cold dry air from the Tibetan Plateau suppressed precipitation over eastern Nepal. However, composite differences in precipitation between low and high SOI phases revealed no anomalies for Nepal. Copyright © 2007 Royal Meteorological Society

Modelling management strategies for wheat–soybean double crops in the south-eastern Pampas

Favourable prices and new technologies have recently stimulated the adoption of wheat–soybean double crops in the south-eastern Pampas. To assess the largely unknown long-term performance of this strategy, we used CERES-Wheat and CROPGRO-Soybean with slight adaptations to account for double cropping. Models and climate records were combined to analyse management practices allowing for earlier soybean sowing, which was assumed to be the key for high soybean yield and whole-system performance. Practices investigated were: (i) short-season wheat cultivars; (ii) non-selective herbicides for faster drying of wheat before harvest; (iii) relay double cropping, where soybean is sown on standing wheat before crop maturity in contrast to sequential cropping where soybean is sown after wheat harvest. Models reproduced phenology and yield of crops in double cropping systems to the level required for our investigation. Advancing wheat harvest with herbicides and using current early wheat varieties had little impact on soybean yield. A hypothetical frost-resistant wheat allowing for earlier wheat sowing and harvest highlighted the potential to increase the yield of sequential soybean by 23%. Average soybean yield increased from 1738 kg ha −1 in sequential to 2099 kg ha −1 in relay cropping, whereas wheat yield was similar in both cropping variants. Seasonal variability in rainfall and simulated yield was partially accounted by the Southern Oscillation Index (SOI), indicating the potential for this signal to be used in risk management. The amount of rainfall during the period of yield generation in wheat and the remaining soil water at the end of the wheat growing season were higher during consistently negative SOI phase, and lower during consistently positive phase in September. In the period between 1971 and 2003 average October–December temperature increased at 0.038 °C year −1. Higher temperature accelerated simulated wheat development and advanced harvest (0.15 day year −1) with no impact on yield; this allowed for earlier sowing of double cropped soybean, which together with more favourable temperature increased simulated soybean yield at a rate of 26.2 kg ha −1 year −1. Hence, our modelling study indicated that: (i) wheat–soybean relay double cropping outperformed its sequential counterpart, (ii) seasonal variability in rainfall and yield could be partially accounted by Southern Oscillation Index (SOI) and (iii) long-term trends in crop phenology and yield could be associated with increased mean temperature.

Quantification of linkages between large-scale climatic patterns and precipitation in the Colorado River Basin

This study analyzed the linkages between large-scale climate patterns and regional precipitation variability, in particular the interannual variation of seasonal precipitation in the Colorado River Basin. Two climate indices, the Southern Oscillation Index (SOI) and the Pacific Decadal Oscillation (PDO), were selected to represent climate patterns. Conceptual influence indices, which quantify the strength of linkages between climate patterns and precipitation variability, were developed based on the Standardized Precipitation Index (SPI). In turn, the spatial variability of the influence indices within the Colorado River Basin was examined for different combinations of SOI and PDO phases and lead times from zero to three seasons. Precipitation in two seasons (winter and summer) significantly responded to the El Niño-Southern Oscillation (ENSO) phases by decreasing winter precipitation in the lower basin (to high ENSO phase) and by increasing summer precipitation in the upper basin (to low ENSO phase). The PDO phase enhanced those relationships both in intensity and frequency. The overall results of this study revealed that the precipitation of the Colorado River Basin was significantly influenced by climate fluctuation phases.

Effects of El Niño Southern Oscillation and Pacific Interdecadal Oscillation on Water Supply in the Columbia River Basin

Decadal climate variability in the form of the Pacific Interdecadal Oscillation (PDO) is analyzed with the El Niño Southern Oscillation (ENSO) to assess impacts on seasonal water supply in the Columbia River Basin and to test for statistical significance. The cross-correlation functions indicate a significant correlation between seasonal runoff and both the Southern Oscillation Index (SOI) and PDO, suggesting a time period where ENSO events have the most significant impact on the January through July volume runoff at The Dalles Dam. Correlation functions indicate volume runoff is directly related to SOI phase and inversely related to PDO phase. Results show there is a statistically significant change in the mean January through July volume runoff only when El Niño events occur during the positive phase of the PDO and when La Niña events occur during the negative phase of the PDO. Precipitation and temperature patterns are illustrated to explain this shift in the mean runoff. While slight shifts in variability are evident for the various climate conditions, significance tests show that the changes in variability do not differ significantly from the neutral condition.