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The El Nino Southern Oscillation (ENSO) is a major source of interannual climate variability. ENSO life cycles and the associated teleconnections evolve over multiple years at a global scale. This analysis is the first attempt to characterize the structure of the risk posed by trans-Pacific ENSO teleconnections to crop production in the greater Pacific Basin region. In this analysis we identify the large-scale atmospheric dynamics of ENSO teleconnections that affect heat and moisture stress during the growing seasons of maize, wheat and soy. We propose a coherent framework for understanding how trans-Pacific ENSO teleconnections pose a correlated risk to crop yields in major agricultural belts of the Americas, Australia and China over the course of an ENSO life cycle by using observations and a multi-model ensemble of climate anomalies during crop flowering seasons. Trans-Pacific ENSO teleconnections are often (but not always) offsetting between major producing regions in the Americas and those in northern China or Australia. El Ninos tend to create good maize and soybean growing conditions in the US and southeast South America, but poor growing conditions in northern China, southern Mexico and the Cerrado in Brazil. The opposite is true during La Nina. Wheat growing conditions in southeast South America generally have the opposite sign of those in Australia. Furthermore, multi-year La Ninas can force multi-year growing season anomalies in Argentina and Australia. Most ENSO teleconnections relevant for crop flowering seasons are the result of a single trans-Pacific circulation anomaly that develops in boreal summer and persists through the following spring. During the late summer and early fall of a developing ENSO event, the tropical Pacific forces an atmospheric anomaly in the northern midlatitudes that spans the Pacific from northern China to North America and in the southern midlatitudes from Australia to southeast South America. This anomaly directly links the soybean and maize growing seasons of the US, Mexico and China and the wheat growing seasons of Argentina, southern Brazil and Australia. The ENSO event peaks in boreal winter, when the atmospheric circulation anomalies intensify and affect maize and soybeans in southeast South America. As the event decays, the ENSO-induced circulation anomalies persist through the wheat flowering seasons in China and the US.

In this analysis we show how globally coherent teleconnections from life-cycles of the El Nino Southern Oscillation (ENSO) lead to correlated crop production anomalies in North and South America. We estimate the magnitude of ENSO-induced Pan-American production anomalies and discuss how increasing crop harvesting frequency may affect Pan-American production variability. We find that ENSO accounts for ∼72%, 30% and 57% of Pan-American maize, soybean and wheat production variability, respectively. ENSO-induced production anomalies are greatest for maize, with median anomalies of ∼5% of Pan-American production. ENSO-induced yield anomalies for maize and soybeans tend to be of the same sign in North America and southeast South America but of an opposite sign in northeast Brazil. Teleconnections for wheat are more complicated because ENSO affects wheat yields via lagged soil moisture teleconnections in the US and an increased probability of disease in South America, but anomalies tend to be of the same sign in North America and southeast South America. After broadly characterizing ENSO-induced production anomalies, we demonstrate that they are not static in time. Increasing crop harvesting frequency has affected the correlated risks posed by ENSO. We use a soil water balance to show that in Brazil changing to a safrinha cropping cycle increases both the mean water stress and the ENSO-induced soil water content anomalies during flowering in both the maize and soybean seasons, which is a result of increasing evaporative demand during times of lower precipitation and moving the flowering seasons into months with strong ENSO teleconnections. Increasing crop harvesting frequency in Brazil has therefore increased ENSO-induced production variability of soybeans and maize.

Summary Here we analyze the variability of MAM (March–April–May) and JJAS (June–July–August–September) seasonal Satluj River flow into the Bhakra dam in India through Pearson anomaly correlation and composite analyses with antecedent and concurrent seasonal climatic and atmospheric circulation patterns. The MAM seasonal inflow of Bhakra dam is significantly correlated with winter (DJF/FM) precipitation and temperature of the Satluj basin while the correlation with FM was more prominent for precipitation (snow = +0.72, rainfall = +0.60), and temperature (diurnal temperature range (DTR) = −0.76 and maximum temperature ( T max ) = −0.57). The JJAS inflow was also positively correlated with DJF/FM as well as JJAS precipitation of the Satluj basin while the correlation with basin average FM was the largest (+0.54). These suggested that both MAM and JJAS inflow anomalies are linked with DJF/FM climate over the Western Himalayas and adjoining north and central Indian plains, which were also found to be linked with the fluctuation of equatorial concurrent Sea Surface Temperature anomalies over the western Indian Ocean (max anomaly correlation was > +0.70) and mean sea level pressure over western pole of the Southern Oscillation sea-saw region (max Pearson anomaly correlation was ∼ +0.60). Low (high) MAM inflow was found to be associated with negative (positive) precipitation anomalies over the basin and north India in DJF and FM while FM precipitation anomaly is more concentrated over the Western Himalayas. In addition, low (high) JJAS inflow is also associated with negative (positive) precipitation anomalies over the basin and north India in DJF and over the Western Himalaya in FM and JJAS. Negative geopotential height anomaly at 500 h Pa (Z500) over Siberia and northwestern pacific in DJF, and positive Z500 anomaly over the northwest India in FM were noticed in low MAM inflow years. Whereas high inflow in MAM was linked with a negative Z500 anomaly between two positive Z500 anomaly regions – one over eastern Siberia stretched up to northern Pacific and second over the Eastern Europe in DJF, which gets stronger in FM. We also found southwesterly (northeasterly) wind vectors at 850 h Pa pressure level (uv850) bringing more (less) moisture to the Western Himalayas in DJF and FM in high (low) MAM/JJAS flow years.

El Nino-Southern Oscillation (ENSO) is by far the most energetic, and at present also the most predictable, short-term fluctuation in the Earth's climate system, though the limits of its predictability are still a subject of considerable debate. As a result of over two-decades of intensive observational, theoretical and modeling efforts, ENSO's basic dynamics is now well understood and its prediction has become a routine practice at application centers all over the world. The predictability of ENSO largely stems from the ocean-atmosphere interaction in the tropical Pacific and the low-dimensional nature of this coupled system. Present ENSO forecast models, in spite of their vast differences in complexity, exhibit comparable predictive skills, which seem to have hit a plateau at moderate level. However, mounting evidence suggests that there is still room for improvement. In particular, better model initialization and data assimilation, better simulation of surface heat and freshwater fluxes, and better representation of the relevant processes outside of the tropical Pacific, could all lead to improved ENSO forecasts.

Severe drought is the greatest recurring natural disaster to strike North America. A remarkable network of centuries-long annual tree-ring chronologies has now allowed for the reconstruction of past drought over North America covering the past 1000 or more years in most regions. These reconstructions reveal the occurrence of past “megadroughts” of unprecedented severity and duration, ones that have never been experienced by modern societies in North America. There is strong archaeological evidence for the destabilizing influence of these past droughts on advanced agricultural societies, examples that should resonate today given the increasing vulnerability of modern water-based systems to relatively short-term droughts. Understanding how these megadroughts develop and persist is a timely scientific problem. Very recently, climate models have succeeded in simulating all of the major droughts over North America from the Civil War to the severe 1998–2004 drought in the western U.S. These numerical experiments indicate the dominating importance of tropical Pacific Ocean sea surface temperatures (SSTs) in determining how much precipitation falls over large parts of North America. Of central importance to drought formation is the development of cool “La Nina-like” SSTs in the eastern tropical Pacific region. This development appears to be partially linked to changes in radiative forcing over that region, which affects the Bjerknes feedback mechanism of the ENSO cycle there. Paradoxically, warmer conditions over the tropical Pacific region lead to the development of cool La Nina-like SSTs there, which is drought inducing over North America. Whether or not this process will lead to a greater prevalence of drought in the future as the world warms due to accumulating greenhouse gases is unclear at this time.

We develop a swamp water mosquito population model that is forced solely by environmental variability. Measured temperature and land surface wetness conditions are used to simulate Anopheles walkeri population dynamics in a northern New Jersey habitat. Land surface wetness conditions, which represent oviposition habitat availability, are derived from simulations using a dynamic hydrology model. Using only these two density-independent effects, population model simulations of biting Anoph. walkeri correlate significantly with light trap collections. These results suggest that prediction of mosquito populations and the diseases they transmit could be better constrained by inclusion of environmental variability.

We review forecasts of the future of El Nino and the Southern Oscillation (ENSO), a coupled instability of the ocean–atmosphere system in the tropical Pacific with global impacts. ENSO in the modern world is briefly described, and the physics of the ENSO cycle is discussed. Particular attention is given to the Bjerknes feedback, the instability mechanism which figures prominently in ENSO past and future. Our knowledge of ENSO in the paleoclimate record has expanded rapidly within the last 5 yr. The ENSO cycle is present in all relevant records, going back 130 kyr. It was systematically weaker during the early and middle Holocene, and model studies indicate that this results from reduced amplification in the late summer and early fall, a consequence of the altered mean climate in response to boreal summer perihelion. Data from corals shows substantial decadal and longer variations in the strength of the ENSO cycle within the past 1000 yr; it is suggested that this may be due to solar and volcanic variations in solar insolation, amplified by the Bjerknes feedback. There is some evidence that this feedback has operated in the 20th century and some model results indicate that it will hold sway in the greenhouse future, but it is very far from conclusive. The comprehensive general circulation models used for future climate projections leave us with an indeterminate picture of ENSO's future. Some predict more ENSO activity, some less, with the highly uncertain consensus forecast indicating little change.

Caribbean rainfall is affected by climate variability of Pacific and Atlantic origin, e.g. the El Nino-Southern Oscillation (ENSO) phenomenon, and variability in the North Atlantic High sea level pressure (SLP) center, respectively. During the lifetime of an ENSO cycle, the basin experiences dry and wet extremes. In the case of a warm event, the dry extreme precedes the mature ENSO phase, and can be explained in terms of a direct response to the atmospheric anomaly generated by the warm sea surface temperatures (SST) in the eastern equatorial Pacific. The wet extreme follows the mature phase, and is consistent with the lagged warming effect of ENSO on tropical North Atlantic SSTs. The wintertime state of the North Atlantic High is hypothesized to affect Caribbean rainfall through its effect on tropical SST. A strong North Atlantic High SLP center during the early months of the calendar year strengthens the trade winds, hence cooling SSTs in the tropical latitudes of the North Atlantic. The effect lingers on most noticeably until the start of the Caribbean rainy season, in May–June, when cool SSTs are associated with deficient rainfall in the basin.

A correlation between ENSO (El Nino/Southern Oscillation) and rainfall in southern Africa has been recognized for at least a decade. This recognition has led to the expectation that ENSO-based climate predictions will have significant applications in agricultural management. This study is an analysis of the potential for using ENSO predictions to reduce risk in agricultural production associated with rainfall variability at the site level. Records of sea-surface temperatures in the equatorial Pacific during November, December and January were used to define El Nino, La Nina and neutral years. Climate data from four sites in four of the five agroecological zones (AEZ) in Zimbabwe were analyzed with respect to ENSO phases and used to drive a maize growth simulation model parameterized for soil conditions typical of each area, using two nitrogen fertilizer treatments and three planting dates. The four sites (Karoi, AEZ II; Gweru, AEZ III; Masvingo, AEZ IV; and Beitbridge, AEZ V) all showed a decrease in seasonal precipitation associated with the El Nino phase, compared to both neutral and La Nina years. At sites in zones II and III, within-season rainfall variability increased for both El Nino and La Nina years relative to neutral years. While average simulated maize yields were generally lowest in El Nino years, variability in rainfall pattern and standard deviation of yields at the site level was high within each ENSO phase, indicating that more precise seasonal climate predictions would be necessary for forecasts to be valuable in crop management decisions in Zimbabwe. However, simulation results point towards the relative importance of predicting favorable cropping seasons as opposed to poor ones with respect to better nitrogen management and yield improvement for the more marginal sites.

This paper describes a fourth-order finite difference model of the equatorial ocean that is designed to study dynamic and thermodynamic processes on time scales of a decade or less. It is a primitive equation model employing the reduced gravity assumption so that the deep ocean is at rest below the active upper ocean. The model consists of a surface mixed layer and an active layer below, which is divided into an arbitrary number of numerical layers by means of a sigma coordinate. The model can be used in an unstratified version, when temperature acts as a passive tracer, as well as in the full stratified version. The numerical formulation of the model is described in detail. Experiments comparing three different horizontal smoothers: Shapiro filter, Laplacian friction, and biharmonic friction are presented. It is concluded that, at the level needed to maintain computational stability, the Shapiro filter damps the fields least; in addition, it is faster and easier to implement when the horizontal finite difference grid is stretched.