Potential of Equatorial Atlantic Variability to Enhance El Nino Prediction

Extraordinarily strong El Niño events, such as those of 1982/83 and 1997/98, have been poorly predicted by operational seasonal forecasts made before boreal spring, despite significant advances in understanding, improved models, and enhanced observational networks. The Equatorial Atlantic Zonal Mode – a phenomenon similar to El Niño but much weaker and peaking in boreal summer – impacts winds over the Pacific, and hence affects El Niño, and also potentially its predictability. Here we use a climate model to perform a suite of seasonal predictions with and without SST in the Atlantic restored to observations. We show for the first time that knowledge of Equatorial Atlantic sea surface temperature (SST) significantly improves the prediction across boreal spring of major El Niño events and also weaker variability. This is because Atlantic SST acts to modulate El Niño variability, rather than triggering events. Our results suggest that better prediction of major El Niño events might be achieved through model improvement in the Equatorial Atlantic

Controlling Spatiotemporal Chaos in a Realistic El Niño Prediction Model

A method for controlling low-order chaotic behavior of continuous spatiotemporal systems is developed and demonstrated in a complex, realistic 3D partial differential equation model that is used successfully for predicting El Niño events in the equatorial Pacific. An unstable periodic orbit that involves a full-domain oscillation is stabilized using a feedback control applied to a single degree of freedom at a carefully chosen single “choke point” in space. A general criterion is presented for determining the optimal points in reconstructed delay-coordinate phase space at which to apply the feedback control.Earth and Planetary Science

Properties of Tropical Cyclones in Atmospheric General Circulation Models

The properties of tropical cyclones in three atmospheric general circulation models (AGCMs) with low-resolution are discussed. The models are analysed for a period of 40 years. Characteristics of the tropical cyclones in the models are analysed and compared with those of observations, such as genesis position, number of cyclones, accumulated cyclone activity, number of storm days, tracks, and others. The three AGCMs have different levels of skill in simulating the different aspects of tropical cyclone activity in different regions. Some of the weak and strong features in simulating tropical cyclone activity variables are common for the three models, others are unique for each model and basin. The relation between model tropical cyclones and ENSO is analyzed in a paper currently in preparation

Toward an ethical framework for climate services: A White Paper of the Climate Services Partnership Working Group on Climate Services Ethics

This paper is intended to spur thinking and dialogue among the wide and relatively diverse community of actors engaged in practical activities surrounding the production, translation, transfer and use of climate information for societal decision making. This white paper is intended to start a conversation on ethics in the climate services community. To that end, the CSP Working Group on Climate Services Ethics is accepting comments on this white paper online at www.climate-services.org/ethics

Climate Services for Resilient Development (CSRD) Technical Exchange in Eastern Africa Workshop Report

In 2005, the International Research Institute for Climate and Society published its assessment of key gaps in the use of climate information for health, agriculture, water and other sectors in countries across Africa. The results from the report were less than stellar. After an extensive review of use of climate information in the development sectors of Africa, the authors concluded that the continent suffered from “market atrophy” – the reinforcing effect of zero effective supply of climate information and zero effective demand. Twelve years later, organizations such as the IRI, CSRD, CCAFS, ICPAC, and UKMO have made enormous strides at increasing both climate information supply and demand through the implementation of climate data platforms and the organizing of capacity-building seminars. In order to capitalize on the presence of the many climate and sector experts from across the IGAD region, the organizations above held a joint event, the Climate Services for Resilient Development (CSRD) Technical Exchange workshop, in Zanzibar on August 23-25, 2017, immediately after the 47th Greater Horn of Africa Climate Outlook Forum (GHACOF47). The workshop was designed to offer potential and existing users a platform to voice their needs for the development and better use of historical, monitored and forecast information for the management of drought across climate-sensitive sectors

An empirical parameterization of subsurface entrainment temperature for improved SST anomaly simulations in an intermediate ocean model

An empirical model for the temperature of subsurface water entrained into the ocean mixed layer (Te) is presented and evaluated to improve sea surface temperature anomaly (SSTA) simulations in an intermediate ocean model (IOM) of the tropical Pacific. An inverse modeling approach is adopted to estimate Te from an SSTA equation using observed SST and simulated upper-ocean currents. A relationship between Te and sea surface height (SSH) anomalies is then obtained by utilizing a singular value decomposition (SVD) of their covariance. This empirical scheme is able to better parameterize Te anomalies than other local schemes and quite realistically depicts interannual variability of Te, including a nonlocal phase lag relation of Te variations relative to SSH anomalies over the central equatorial Pacific. An improved Te parameterization naturally leads to better depiction of the subsurface effect on SST variability by the mean upwelling of subsurface temperature anomalies. As a result, SSTA simulations are significantly improved in the equatorial Pacific; a comparison with other schemes indicates that systematic errors of the simulated SSTAs are significantly small—apparently due to the optimized empirical Teparameterization. Cross validation and comparisons with other model simulations are made to illustrate the robustness and effectiveness of the scheme. In particular it is demonstrated that the empirical Te model constructed from one historical period can be successfully used to improve SSTA simulations in another

On Sub-ENSO Variability

Multichannel singular spectrum analysis (MSSA) of surface zonal wind, sea surface temperature (SST), 20° isotherm depth, and surface zonal current observations (between 1990 and 2004) identifies three coupled ocean–atmosphere modes of variability in the tropical Pacific: the El Niño–Southern Oscillation (ENSO), the annual cycle, and a mode with a 14–18-month period, which is referred to as sub-ENSO in this study. The sub-ENSO mode accounts for the near 18-month (near annual) variability prior to (following) the 1997/98 El Niño event. It was strongest during this El Niño event, with SST anomalies exceeding 1°C. Sub-ENSO peak SST anomalies are ENSO-like in structure and are associated with eastward propagating heat content variations. However, the SST anomalies are preceded by and in near quadrature with relatively strong remotely forced westward propagating zonal current variations, suggesting the sub-ENSO mode arises from the zonal-advective feedback. The sub-ENSO mode is found to exist also in an intermediate complexity model (ICM) of the tropical Pacific. A heat budget analysis of the model’s sub-ENSO mode shows it indeed arises from the zonal-advective feedback. In the model, both ENSO and sub-ENSO modes coexist, but there is a weak nonlinear interaction between them. Experiments also show that the observed changes in sub-ENSO’s characteristics may be explained by changes in the relative importance of zonal and vertical advection SST tendencies

Current Approaches to Seasonal to Interannual Climate Predictions

This review paper presents an assessment of the current state of knowledge and capability in seasonal climate prediction at the end of the 20th century. The discussion covers the full range of issues involved in climate forecasting, including (1) the theory and empirical evidence for predictability; (2) predictions of surface boundary conditions, such as sea surface temperatures (SSTs) that drive the predictable part of the climate; (3) predictions of the climate; and (4) a brief consideration of the application of climate forecasts. Within this context, the research of the coming decades that seeks to address shortcomings in each area is described

Retrospective El Niño hindcasts/forecasts using an improved intermediate coupled model

A new intermediate coupled model (ICM) is presented and employed to make retrospective predictions of tropical Pacific sea surface temperature (SST) anomalies. The ocean dynamics is an extension of the McCreary baroclinic modal model to include varying stratification and certain nonlinear effects. A standard configuration is chosen with 10 baroclinic modes plus two surface layers, which are governed by Ekman dynamics and simulate the combined effects of the higher baroclinic modes from 11 to 30. A nonlinear correction associated with vertical advection of zonal momentum is incorporated and applied (diagnostically) only within the two surface layers, forced by the linear part through nonlinear advection terms. As a result of these improvements, the model realistically simulates the mean equatorial circulation and its variability. The ocean thermodynamics include an SST anomaly model with an empirical parameterization for the temperature of subsurface water entrained into the mixed layer (Te), which is optimally calculated in terms of sea surface height (SSH) anomalies using an empirical orthogonal function (EOF) analysis technique from historical data. The ocean model is then coupled to a statistical atmospheric model that estimates wind stress (τ) anomalies based on a singular value decomposition (SVD) analysis between SST anomalies observed and τ anomalies simulated from ECHAM4.5 (24-member ensemble mean). The coupled system exhibits realistic interannual variability associated with El Niño, including a predominant standing pattern of SST anomalies along the equator and coherent phase relationships among different atmosphere–ocean anomaly fields with a dominant 3-yr oscillation period. Twelve-month hindcasts/forecasts are made during the period 1963–2002, starting each month. Only observed SST anomalies are used to initialize the coupled predictions. As compared to other prediction systems, this coupled model has relatively small systematic errors in the predicted SST anomalies, and its SST prediction skill is apparently competitive with that of most advanced coupled systems incorporating sophisticated ocean data assimilation. One striking feature is that the model skill surpasses that of persistence at all lead times over the central equatorial Pacific. Prediction skill is strongly dependent on the season, with the correlations attaining a minimum in spring and a maximum in fall. Cross-validation experiments are performed to examine the sensitivity of the prediction skill to the data periods selected for training the empirical Te model. It is demonstrated that the artificial skill introduced by using a dependently constructed Te model is not significant. Independent forecasts are made for the period 1997–2002 when no dependent data are included in constructing the two empirical models (Te and τ). The coupled model has reasonable success in predicting transition to warm phase and to cold phase in the spring of 1997 and 1998, respectively. Potential problems and further improvements are discussed with the new intermediate prediction system