Atlantic climate variability and predictability: A CLIVAR perspective

Three interrelated climate phenomena are at the center of the Climate Variability and Predictability (CLIVAR) Atlantic research: tropical Atlantic variability (TAV), the North Atlantic Oscillation (NAO), and the Atlantic meridional overturning circulation (MOC). These phenomena produce a myriad of impacts on society and the environment on seasonal, interannual, and longer time scales through variability manifest as coherent fluctuations in ocean and land temperature, rainfall, and extreme events. Improved understanding of this variability is essential for assessing the likely range of future climate fluctuations and the extent to which they may be predictable, as well as understanding the potential impact of human-induced climate change. CLIVAR is addressing these issues through prioritized and integrated plans for short-term and sustained observations, basin-scale reanalysis, and modeling and theoretical investigations of the coupled Atlantic climate system and its links to remote regions. In this paper, a brief review of the state of understanding of Atlantic climate variability and achievements to date is provided. Considerable discussion is given to future challenges related to building and sustaining observing systems, developing synthesis strategies to support understanding and attribution of observed change, understanding sources of predictability, and developing prediction systems in order to meet the scientific objectives of the CLIVAR Atlantic program.

The climate sensitivity and its components diagnosed from Earth Radiation Budget data

One of the major uncertainties in the ability to predict future climate change, and hence its impacts, is the lack of knowledge of the earth's climate sensitivity. Here, data are combined from the 1985-96 Earth Radiation Budget Experiment (ERBE) with surface temperature change information and estimates of radiative forcing to diagnose the climate sensitivity. Importantly, the estimate is completely independent of climate model results. A climate feedback parameter of 2.3 +/- 1.4 W m(-2) K-1 is found. This corresponds to a 1.0-4.1-K range for the equilibrium warming due to a doubling of carbon dioxide (assuming Gaussian errors in observable parameters, which is approximately equivalent to a uniform "prior" in feedback parameter). The uncertainty range is due to a combination of the short time period for the analysis as well as uncertainties in the surface temperature time series and radiative forcing time series, mostly the former. Radiative forcings may not all be fully accounted for; however, all argument is presented that the estimate of climate sensitivity is still likely to be representative of longer-term climate change. The methodology can be used to 1) retrieve shortwave and longwave components of climate feedback and 2) suggest clear-sky and cloud feedback terms. There is preliminary evidence of a neutral or even negative longwave feedback in the observations, suggesting that current climate models may not be representing some processes correctly if they give a net positive longwave feedback.

Mechanisms of ocean heat uptake in a coupled climate model and the implications for tracer based predictions of ocean heat uptake

The distribution of tracers in the ocean is often taken as an indication of the ventilation pathways for oceanic water masses. It has been suggested that under anthropogenic forcing heat will be taken up into the interior of the ocean along isopycnal ventilation pathways. This notion is investigated by examining distributions of potential temperature and a passive anomaly temperature tracer in a coupled climate experiment where CO2 is increased at a rate of 2% per year. We show that interior temperature changes cannot be explained solely by passive tracer transport along isopycnals. Heat uptake is strongly affected by changes in circulation and has a substantial diapycnal component.

Climate change and heat-related mortality in six cities Part 1: model construction and validation

Heat waves are expected to increase in frequency and magnitude with climate change. The first part of a study to produce projections of the effect of future climate change on heat-related mortality is presented. Separate city-specific empirical statistical models that quantify significant relationships between summer daily maximum temperature (T max) and daily heat-related deaths are constructed from historical data for six cities: Boston, Budapest, Dallas, Lisbon, London, and Sydney. ‘Threshold temperatures’ above which heat-related deaths begin to occur are identified. The results demonstrate significantly lower thresholds in ‘cooler’ cities exhibiting lower mean summer temperatures than in ‘warmer’ cities exhibiting higher mean summer temperatures. Analysis of individual ‘heat waves’ illustrates that a greater proportion of mortality is due to mortality displacement in cities with less sensitive temperature–mortality relationships than in those with more sensitive relationships, and that mortality displacement is no longer a feature more than 12 days after the end of the heat wave. Validation techniques through residual and correlation analyses of modelled and observed values and comparisons with other studies indicate that the observed temperature–mortality relationships are represented well by each of the models. The models can therefore be used with confidence to examine future heat-related deaths under various climate change scenarios for the respective cities (presented in Part 2).

Data assimilation for marine monitoring and prediction: The MERCATOR operational assimilation systems and the MERSEA developments

During the past 15 years, a number of initiatives have been undertaken at national level to develop ocean forecasting systems operating at regional and/or global scales. The co-ordination between these efforts has been organized internationally through the Global Ocean Data Assimilation Experiment (GODAE). The French MERCATOR project is one of the leading participants in GODAE. The MERCATOR systems routinely assimilate a variety of observations such as multi-satellite altimeter data, sea-surface temperature and in situ temperature and salinity profiles, focusing on high-resolution scales of the ocean dynamics. The assimilation strategy in MERCATOR is based on a hierarchy of methods of increasing sophistication including optimal interpolation, Kalman filtering and variational methods, which are progressively deployed through the Syst`eme d’Assimilation MERCATOR (SAM) series. SAM-1 is based on a reduced-order optimal interpolation which can be operated using ‘altimetry-only’ or ‘multi-data’ set-ups; it relies on the concept of separability, assuming that the correlations can be separated into a product of horizontal and vertical contributions. The second release, SAM-2, is being developed to include new features from the singular evolutive extended Kalman (SEEK) filter, such as three-dimensional, multivariate error modes and adaptivity schemes. The third one, SAM-3, considers variational methods such as the incremental four-dimensional variational algorithm. Most operational forecasting systems evaluated during GODAE are based on least-squares statistical estimation assuming Gaussian errors. In the framework of the EU MERSEA (Marine EnviRonment and Security for the European Area) project, research is being conducted to prepare the next-generation operational ocean monitoring and forecasting systems. The research effort will explore nonlinear assimilation formulations to overcome limitations of the current systems. This paper provides an overview of the developments conducted in MERSEA with the SEEK filter, the Ensemble Kalman filter and the sequential importance re-sampling filter.

Recent oppositely directed trends in solar climate forcings and the global mean surface air temperature. II. Different reconstructions of the total solar irradiance variation and dependence on response time scale

We have previously placed the solar contribution to recent global warming in context using observations and without recourse to climate models. It was shown that all solar forcings of climate have declined since 1987. The present paper extends that analysis to include the effects of the various time constants with which the Earth’s climate system might react to solar forcing. The solar input waveform over the past 100 years is defined using observed and inferred galactic cosmic ray fluxes, valid for either a direct effect of cosmic rays on climate or an effect via their known correlation with total solar irradiance (TSI), or for a combination of the two. The implications, and the relative merits, of the various TSI composite data series are discussed and independent tests reveal that the PMOD composite used in our previous paper is the most realistic. Use of the ACRIM composite, which shows a rise in TSI over recent decades, is shown to be inconsistent with most published evidence for solar influences on pre-industrial climate. The conclusions of our previous paper, that solar forcing has declined over the past 20 years while surface air temperatures have continued to rise, are shown to apply for the full range of potential time constants for the climate response to the variations in the solar forcings.

Climate change and the flowering time of annual crops

Crop production is inherently sensitive to variability in climate. Temperature is a major determinant of the rate of plant development and, under climate change, warmer temperatures that shorten development stages of determinate crops will most probably reduce the yield of a given variety. Earlier crop flowering and maturity have been observed and documented in recent decades, and these are often associated with warmer (spring) temperatures. However, farm management practices have also changed and the attribution of observed changes in phenology to climate change per se is difficult. Increases in atmospheric [CO2] often advance the time of flowering by a few days, but measurements in FACE (free air CO2 enrichment) field-based experiments suggest that elevated [CO2] has little or no effect on the rate of development other than small advances in development associated with a warmer canopy temperature. The rate of development (inverse of the duration from sowing to flowering) is largely determined by responses to temperature and photoperiod, and the effects of temperature and of photoperiod at optimum and suboptimum temperatures can be quantified and predicted. However, responses to temperature, and more particularly photoperiod, at supraoptimal temperature are not well understood. Analysis of a comprehensive data set of time to tassel initiation in maize (Zea mays) with a wide range of photoperiods above and below the optimum suggests that photoperiod modulates the negative effects of temperature above the optimum. A simulation analysis of the effects of prescribed increases in temperature (0-6 degrees C in + 1 degrees C steps) and temperature variability (0% and + 50%) on days to tassel initiation showed that tassel initiation occurs later, and variability was increased, as the temperature exceeds the optimum in models both with and without photoperiod sensitivity. However, the inclusion of photoperiod sensitivity above the optimum temperature resulted in a higher apparent optimum temperature and less variability in the time of tassel initiation. Given the importance of changes in plant development for crop yield under climate change, the effects of photoperiod and temperature on development rates above the optimum temperature clearly merit further research, and some of the knowledge gaps are identified herein.

Climate change and coastal waterbird populations – past declines and future impacts

Considerable attention has been given to the impact of climate change on avian populations over the last decade. In this paper we examine two issues with respect to coastal bird populations in the UK: (1) is there any evidence that current populations are declining due to climate change, and (2) how might we predict the response of populations in the future? We review the cause of population decline in two species associated with saltmarsh habitats. The abundance of Common Redshank Tringa totanus breeding on saltmarsh declined by about 23% between the mid-1980s and mid-1990s, but the decline appears to have been caused by an increase in grazing pressure. The number of Twite Carduelis flavirostris wintering on the coast of East Anglia has declined dramatically over recent decades; there is evidence linking this decline with habitat loss but a causal role for climate change is unclear. These examples illustrate that climate change could be having population-level impacts now, but also show that it is dangerous to become too narrowly focused on single issues affecting coastal birds. Making predictions about how populations might respond to future climate change depends on an adequate understanding of important ecological processes at an appropriate spatial scale. We illustrate this with recent work conducted on the Icelandic population of Black-tailed Godwits Limosa limosa islandica that shows large-scale regulatory processes. Most predictive models to date have focused on local populations (single estuary or a group of neighbouring estuaries). We discuss the role such models might play in risk assessment, and the need for them to be linked to larger-scale ecological processes. We argue that future work needs to focus on spatial scale issues and on linking physical models of coastal environments with important ecological processes.

Adaptation to climate change and variability: farmer responses to intra-seasonal precipitation trends in South Africa

We describe the nature of recent (50 year) rainfall variability in the summer rainfall zone, South Africa, and how variability is recognised and responded to on the ground by farmers. Using daily rainfall data and self-organising mapping (SOM) we identify 12 internally homogeneous rainfall regions displaying differing parameters of precipitation change. Three regions, characterised by changing onset and timing of rains, rainfall frequencies and intensities, in Limpopo, North West and KwaZulu Natal provinces, were selected to investigate farmer perceptions of, and responses to, rainfall parameter changes. Village and household level analyses demonstrate that the trends and variabilities in precipitation parameters differentiated by the SOM analysis were clearly recognised by people living in the areas in which they occurred. A range of specific coping and adaptation strategies are employed by farmers to respond to climate shifts, some generic across regions and some facilitated by specific local factors. The study has begun to understand the complexity of coping and adaptation, and the factors that influence the decisions that are taken.

Uptake pathways: the potential of Bayesian belief networks to assist the management, monitoring and evaluation of development-orientated research

The effectiveness of development assistance has come under renewed scrutiny in recent years. In an era of growing economic liberalisation, research organisations are increasingly being asked to account for the use of public funds by demonstrating achievements. However, in the natural resources (NR) research field, conventional economic assessment techniques have focused on quantifying the impact achieved rather understanding the process that delivered it. As a result, they provide limited guidance for planners and researchers charged with selecting and implementing future research. In response, “pathways” or logic models have attracted increased interest in recent years as a remedy to this shortcoming. However, as commonly applied these suffer from two key limitations in their ability to incorporate risk and assess variance from plan. The paper reports the results of a case study that used a Bayesian belief network approach to address these limitations and outlines its potential value as a tool to assist the planning, monitoring and evaluation of development-orientated research.

Monitoring and evaluation in Malawi

When Ian Wilson and Carlos Barahona of the Statistical Services Centre at the University of Reading were asked to review an evaluation of the effectiveness of an aid package in Malawi, they expected a simple enough task. But few things in the developing world are simple. Where aid for the poorest is concerned, is evidence collected and analysed with enough rigour to enable well-informed decisions to be made?

Climate change and coastal waterbird populations - past declines and future impacts

Considerable attention has been given to the impact of climate change on avian populations over the last decade. In this paper we examine two issues with respect to coastal bird populations in the UK: (1) is there any evidence that current populations are declining due to climate change, and (2) how might we predict the response of populations in the future? We review the cause of population decline in two species associated with saltmarsh habitats. The abundance of Common Redshank Tringa totanus breeding on saltmarsh declined by about 23% between the mid-1980s and mid-1990s, but the decline appears to have been caused by an increase in grazing pressure. The number of Twite Carduelis flavirostris wintering on the coast of East Anglia has declined dramatically over recent decades; there is evidence linking this decline with habitat loss but a causal role for climate change is unclear. These examples illustrate that climate change could be having population-level impacts now, but also show that it is dangerous to become too narrowly focused on single issues affecting coastal birds. Making predictions about how populations might respond to future climate change depends on an adequate understanding of important ecological processes at an appropriate spatial scale. We illustrate this with recent work conducted on the Icelandic population of Black-tailed Godwits Limosa limosa islandica that shows large-scale regulatory processes. Most predictive models to date have focused on local populations (single estuary or a group of neighbouring estuaries). We discuss the role such models might play in risk assessment, and the need for them to be linked to larger-scale ecological processes. We argue that future work needs to focus on spatial scale issues and on linking physical models of coastal environments with important ecological processes.