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A preliminary assessment on environmental vulnerability in Southern Africa
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3. PART I—SOME OF THE BIOPHYSCIAL CHANGES THAT MAY ENHANCE OR DEGRADE THE ENVIRONMENT
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- Changes in rainfall and other climate parameters will impact the region
Global environmental change is a topic that has recently been under considerable review (e.g. IGBP, 2001; IPCC, 2001). Cumulative evidence gleaned over the past few decades indicates that planetary changes are occurring rapidly (IGBP, 2001). These changes in turn are acting as feedbacks that all combine to drive the Earth System. Mean annual temperatures have, for example, shown a marked and rapid increase particularly over the past century. Nine of the ten warmest years (1860-present record of data maintained by member of the World Meteorological Organization, WMO) have occurred since 1990 with one of the warmest years being 1998 and 2001 the second warmest (Climate Research Unit and Met Office, UEA). These conditions have been identified as being part of a trend to warmer global temperatures that have resulted in a rise of more than 0.6є C during the past 100 years. The rise in temperature, however, has not been continuous. Since 1976 the global average has nonetheless risen at a rate approximately three times faster than the century-scale trend
(WM0, www.wmo.ch/web). A number of impacts may result from these changes in atmospheric conditions including possible changes in vegetation, surface water availability, rangeland condition etc. Some of these impacts are discussed below.
- Climate variability in the region, including droughts and floods may be more important in the near-term in the region than longer-term climate change
At present no single method exists for producing confident predictions of future climate and therefore climate scenarios are usually used (Perks et al., 2000). Cane (a leading modeller of climate systems) suggests that “The forecasts are far from perfect, especially so for the connections to local conditions with the greatest human consequences” (Cane, 2000). Using Global Circulation Models (GCMs) and other indicators (e.g. development of ENSO, El Niсo/La Niсa) scientists are, however, able to offer probabilistic forecasts of what may be expected for the next season and possible scenarios from which impacts associated with climate change can be gauged.
GCMs, or Global Circulation Models, are types of models that are used to drive various outlooks or scenarios of possible future environmental changes that may be associated with warming. Establishing detailed climate and other environmental changes at a regional scale and for specific areas and places is, however, difficult to obtain from current GCMs. This is because of the uncertainties of the climate system when trying to reduce or ‘downscale’ the scenarios generated from the models to the regional and local scale as well as trying to include all the dynamics of the system. Different GCMs, for example, focus on different aspects (for example one may allow feedbacks from the earth-atmosphere system via sulphates in the model run, others may couple oceans and the atmosphere while others may include the feedbacks and inter-actions of ecology etc.) (Rozensweig and Hillel, 1998).
At present a number of models are used. Those used for the southern African region include GENESIS (Global Environment and Ecology Simulation of Interactive Systems); Hadley Model; and CSM (Climate Systems Model). Using a variety of such GCMS and other techniques (e.g. statistical techniques etc) the following scenarios have been provided for the region.
- Some climate change scenarios for the region
Using some of these models, and mindful of the constraints and limitations of using these outputs, various assessments (e.g. Joubert and Tyson, 1996; Joubert and Hewitson, 1997; Mason and Joubert, 1997) have been made for the region. One indication from the models that may impact on SCF and its work in the region is that variability and the frequency of extreme events are likely to be extremely important in the region. Using the CSIRO9 model Mason and Joubert (1997), for example, found that changes in the number and frequency of extreme rainfall events may be more important than the mean changes in rainfall. Although there are a variety of possible outcomes suggested from these models (Table 1) there still remain uncertainties about obtaining rainfall estimates from GCMs (Hewitson, pers. Com, 2002). These assessments and scenarios can also vary, however, depending on the type of GCM model used. Despite these shortcomings models give some indication of possible environmental changes.
Assessments (e.g. US Country Studies Reports, essentially country studies for most countries in the
region were undertaken see www.gcrio.org/CSP/africa.html for reports relating to Malawi, Botswana, Zimbabwe and other areas) show that for South Africa, Lesotho and Swaziland, and depending on the model used e.g. either GENESIS or Hadley, variations of outcomes can be described. The Hadley model, for example, describes general decreases in rainfall in the study area whereas the GENESIS model describes increases in rainfall relative to the present (see Perks et al., 2000 for more details). Other indications from models used (e.g. UKTR95 GCM) show an expected annual rainfall increase of 30-35% over all of Kenya, with smaller increases (up to 30%) over most of Tanzania, Uganda and north eastern Zambia and very slight increases over smaller areas of western Zimbabwe, Botswana and Namibia (Schulze, Meigh and Horan, 2001). This is in contrast to decreases in annual rainfall south of Tanzania, (between 10% an up to 30% in places).
Table 1: Examples of possible indications of climate change derived from various models and sources (including Shackelton, Lennon and Tosen, 1996; Joubert et al., 1996; Bridgman, 1998) for the region and particularly for South Africa.
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- The increase in temperature will be dependent on latitude.
- The increase in temperature will be greater in the winter rainfall area than in the summer rainfall area.
- The role of the escarpment is important in shaping expected rainfall and other dynamics of the climate system
- Rainfall ( uncertainty surrounds estimates of future rainfall under a doubled carbon dioxide scenario than temperature).
- Overall fewer rain-days are expected, rainfall intensity will increase (implying greater runoff).
- Increases in rainfall likely in summer rainfall, with more intense events
- More convective activity in winter rainfall areas.
- The seasonality of rainfall is unlikely to change and mean annual totals should only vary slightly.
- Rainfall is likely to increase slightly in the tropics (by <10%) and decrease somewhat in the east-central interior by about (10-20%) (Joubert and Tyson, 1996).
- For drought periods the model indicates increasing probabilities of dry spells or dry years in the tropics, to the south-west of the subcontinent and especially over western South Africa and over eastern southern Africa including Mozambique (Joubert et al., 1996; Bridgman, 1998).
- Finally, Hulme analyzing three regions of Africa suggests a wetting in East Africa, drying in southeast Africa and a poorly specified outcome for the Sahel (IPCC, 2001, 494).
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Examples of possible changes in agriculture that may be associated with changes in temperature and rainfall as linked to greenhouse warming
Impacts on food production in a changing and more variable climate have been shown to be linked to changes in temperature, moisture levels, ultra violet radiation, changes in CO2 levels, pests and diseases both in the past and in model simulations. The droughts of the early 1980s and 1990s, for example, seriously impacted the southern African region reducing cereal production and water supplies with resultant impacts on GDP (e.g. largely as a result of drought, manufacturing output in Zimbabwe, for example, declined by 9.5% in 1992 and in South Africa the drought necessitated maize imports totalling US$604 million). The knock-on impacts e.g. loss of farm workers jobs and the reduction of overall livelihoods for many have also been noted (for a detailed assessment of the economic impacts of drought of the mid-1990s see Benson and Clay (1998)). With these realities and a growing food emergency currently evolving in the region, it is useful and essential to explore what the environmental scenarios, using the current science, may be in the near- and long-term future.
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Shorter-term possible impacts on agriculture.
The development of an El Niсo, may mean that rainfall may vary in the forthcoming season
with possible impacts on agricultural production in the region. This condition cannot be reliably determined at present (for reasons outlined below) and readers are advised to monitor this situation more closely.
At a regional level, indications for seasonal rainfall and temperature (possible rainfall and temperatures) that may be expected over the coming season are given, based on various techniques, including GCMs and statistical forecasting methods. Various Seasonal Climate Outlook Forums convene several times before and during the rainy seasons to offer a consolidated ‘outlook’ for regions. Two of these are pertinent here, viz. the Climate Outlook Forum for the Greater Horn of Africa and the Climate Outlook Forum for Southern Africa (the next SARCOF Forum is to be held in Harare in September, 2002).
Some of the key factors that are considered by these Forums are the SSTs (sea-surface temperatures) in the tropical Pacific and how those over the tropical Atlantic and Indian Oceans may influence regional seasonal rainfall. Monitoring SSTs in these regions and associations with the build up of El Niсos and La Niсas have been shown, at times, to influence climate and particularly seasonal climate in certain areas of southern and eastern Africa (see e.g. Glantz, 2001).
While it has been shown that such techniques and methods show some good predicative skill the point, however, must be made that such ‘outlooks’
may not fully account for all the physical and dynamical factors that influence regional, national and local climate variability (see for example, Landsea and Knaff, 2000 and Barnston, Glantz and He, 1999). The biophysical responses to El Niсo and La Niсa (e.g. rainfall and temperature) vary spatially and with time (Mason and Landman, 1999) for South Africa. Despite this variability in cause and effect, El Niсo events are usually associated with below-normal rainfall over land, whereas La Niсa events may result in a wider extent of above-normal rainfall (see Mason and Goddard, 2001).
Warming of the Pacific Ocean and associated teleconnections to rainfall in southern Africa is not the only aspect that is considered when examining ENSO impacts for the region. Sea-surface temperature anomalies of the Indian Ocean are also related to southern African seasonal rainfall (e.g. Landman and Mason, 1999). Warmer (cooler) than average sea-surface temperatures in the Agulhas system, for example, are usually associated with wetter (drier) than average rainfall over the summer rainfall region of
South Africa.2 Over the most recent decades, however, sea-surface temperature variability in the tropical western Indian Ocean has become significantly less dependent on ENSO” (Landman and Mason, 1999, 1490).
“The recent changes in the association between tropical western Indian Ocean sea-surface temperature and rainfall over parts of southern Africa, the apparent ability of sea temperatures in the region to modulate the influence of ENSO events on rainfall over the country, and the ability of sea-surface temperature variability to occur independently of El Niсa and La Niсa events, all emphasize the importance of including the area in both statistically- and dynamically-based seasonal forecasting models” (Landman and Mason, 1999, 1490, emphasis added).
The outcome of the ENSO event for southern Africa, of 1997/98 was, for example, partly influenced by the developments in the Indian Ocean. Before sudden and drastic decisions regarding food relief and other emergency measures are therefore taken, it is essential that the developments of ENSO are closely monitored as well as those developments in the Indian Ocean that may influence the magnitude of such an event.
Some of the more recent indications for current climate outlooks (e.g. NOAA, National Oceanic and Atmospheric Administration, USA and IRI, International Research Institute for Climate Prediction, Columbia, USA) include an examination of the SSTs in the tropical Pacific and potential development of an El Niсo or La Niсa situation. These are usually issued monthly and are based on a consensus of models that forecast ENSO (El Niсo Southern Oscillation) developments for the coming 6 or more months. From recent assessments, there would appear to be indications that warming of the central equatorial Pacific is occurring:
“This behaviour has been observed prior to the onset of many past El Niсo events. However, based on historical observations and the performance of computer models at this time of the year, it is not certain if the expected warming in the eastern pacific will lead to a Pacific basin-wide El Niсo. Thus, while the current ocean conditions exhibit the necessary early conditions for El Niсo, there continues to be substantial uncertainty over whether El Niсo will develop in the next few months. The evolution of the system in the next few months or two will likely make possible forecasts having more certainty”
(IRI, http://iri.columbia.edu/climate/ENSO/).
Recent indications (see http://iri.columbia.edu/, El Niсo Alert issued July 17th 2002) are that ocean conditions in the tropical Pacific have currently reached the minimum level required to represent the onset phase of El Niсo. There is a 90% probability that these conditions will persist for the next 6-9 months, indicating a high likelihood for a fully developed El Niсo for the remainder of 2002 and continuing into early 2003. The forecast SSTs in the tropical Pacific are, however, significantly less than those associated with 1997-98 El Nino. Climate impacts are “anticipated to be weaker than those associated with the 1997-98 but may be substantial in some regions”
(http://iri.columbia.edu/, El Niсo Alert, July 17, 2002).
The timing of El Niсo and rainfall seasonality for the region is also important aspects to consider. Over South Africa, for example, the influence of ENSO events on rainfall is strongest during the summer peak rainfall months (i.e. December to March) when ENSO events have typically reached maturity and when the tropical atmospheric circulation is usually dominant over this area. Further north, e.g. over Zimbabwe, the early- and late-seasonal rains (e.g. October and March) are more severely affected than the mid-season (Mason, 2001). Early indications of El Niсo therefore need to be updated with reference to the rainfall patterns in the region i.e. closer to the rainfall season. The development of El Niсo therefore needs to be tracked
(see http://iri.columbia.edu/).
Using these scenario outputs various seasonal outlooks for Southern Africa are given. For countries in the Greater Horn of Africa consult
(www.cpc.ncep.noaa.gov)
for those in southern consult Drought Monitoring Center
(www.dmc.co.zw) and/or the South African Weather Services
(www.weathersa.co.za). The seasonal forecast is given as a probability for categories (above, near, below-normal) for both temperature and rainfall (see Appendix for an example of such a forecast). The category with the highest probability is the most likely to occur. A forecast for above-normal rainfall, however, does not necessarily mean a good season. Rainfall timing, when and how much can also make a difference, particularly for agriculture (LOGIC, 24-01-2002).
Several problems still frustrate forecast efforts including suitability for users, ‘down scaling’ of the forecast for area-specific usage, reliability of the forecasts etc. (Goddard et al., 2001). Mid-season droughts or dry periods, for example, can heighten and aggravate below-normal conditions particularly for farmers. Usually a mid-season ‘correction’ or update is given for the forecast but these may come too late for users. Unusually dry conditions, for example, have prevailed across portions of south-eastern Africa since Jan 2002 despite the indications of an essentially ‘normal’ season (see Appendix). Above- normal temperatures have also prevailed in several parts of the region. Together these conditions are stressing crops:
“….no relief is expected across the region throughout the period. The dryness is expected to increase moisture deficits during the period, therefore worsening the drought conditions” (Chester V Schmitt, Climate Prediction Centre,
www.cpc.ncep.noaa.gov).
While droughts are a key hazard to monitor in the region, for some areas, including the eastern coastal areas and Mauritius, cyclones are another important atmospheric feature to track. The southwest Indian Ocean cyclone season runs from September to May, with the most active months being January and February. This year is expected to be a normal cyclone season (on average of 12 cyclones per year) (Regional Flood Watch, 25 Jan 2002). Having said this, the role of the Indian Ocean in modulating Southern African rainfall, however, remains a critical component in explaining climate and weather in the SADC region and therefore merits further monitoring and assessment.
Having provided a discussion of some of the current concerns of climate variability in the region, attention now shifts to some of the potential impacts including agricultural, vegetation and hydrological impacts that may constrain livelihoods in the region.
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Longer-term possible impacts on agriculture in parts of the region using a variety of models
In South Africa, several attempts have been made, using various models, to generate scenarios of possible future impacts associated with global warming. The ACRU/CERES (e.g. Schulze et al., 1996) models and the Hadley, Genesis and Climate System Models (e.g. Du Toit et al., 2000) have been used, for example, to assess the potential impacts of changes climate on crop growth (in this case maize production). For these models and scenarios, a range of outcomes is generated depending on the models and data used. Of interest to this report, however, is that most of these models indicate some decreases in yield towards the west of South Africa (with severe reductions indicated in the use of the Hadley scenarios (e.g. Du Toit et al., 2000), but for most of the country potential yield could increase, in some cases, by as much as 5 t/ha (e.g. Hulme, 1996; Schulze, et al., 1996).
Generating scenarios of cereal production, using models, is difficult and variable results can be obtained depending on the model and data used. In Zimbabwe, for example, impacts on maize production have been examined using scenarios generated by GCMs and crop simulations (Muchena and Iglesias, 1995; Matarira et al., 1996). Reduced yields are noted for several areas in Zimbabwe. Some suggest (e.g. Matarira et al., 1996) that under a double CO2 scenario, a 15 to 19% decrease in rainfall is noted and with an increase in evaporation, a 50% decrease in runoff is estimated. One of the key vulnerabilities will then be the decrease in the yield from dams with impacts on agriculture. Decreased maize yields of about 30-40% (in areas of Zimbabwe) have also been noted with some scenarios (Matarira, 1996). Climate variability may, for example, turn low-lying areas into non-maize areas with changes to growing season, planting times and yield (e.g. Muchena, 1994; Matarira et al., 1996; Makhado, 1996).
Livestock is also closely linked to rainfall and changes in annual precipitation. Changes in rain-fed livestock numbers in Africa are and will be closely coupled to changes in annual precipitation. Given that several GCMs predict a decrease in rainfall (10-20%) in the main semi-arid zones of Africa, there is a real possibility that climate may have a negative impact on pastoral livelihoods (IPPC, 2001). Diminished grassland area by encroaching trees (with enrichment of CO2) may also place additional stress on livelihoods derived from rangelands.
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Rangeland and other vegetation changes associated with warming in the region
Rangelands
Several models have been used to indicate possible changes in rangeland condition and production, with suggested gains and losses in yield in some areas. While some indicate negative changes e.g. possible enhanced degradation others indicate possible positive changes. In terms of vegetation and land use, the SADC region is very heterogeneous. Commercial and communal rangelands and irrigated and rain-fed agricultural predominate in the region. Generally the rangelands dominate in the drier more western areas of the region while arable farming flourishes under moist conditions and under irrigation (Hulme, 1996). The rangelands, moreover, are an important livelihood source for several rural communities and commercial farmers. Changes in the rangelands are therefore important to consider.
Table 2: Summary of possible human impacts of climate change in Botswana (after Hulme, 1996, 69).
(Core scenario sees modest drying over large parts of the region;
dry scenario region experiences a decline of up to 20% and a wet scenario in which most of the regions
get wetter Hulme, 1996, ix).
| Impact type |
‘Core’ scenario |
‘Wet’ scenario |
‘Dry’ scenario |
| Sectoral Shifts |
Desert expansion reduces livestock potential in favour of small stock and some wildlife species. |
Little change, possibly better cultivation opportunities. |
Desert expansion reduces livestock potential in favour of small stock and some wildlife species. |
| Productivity and income by sector |
Increase in marginal conditions adversely affects land productivity in large areas. |
Little change; small increase in cultivation. |
Increase in marginal conditions adversely affects land productivity in large areas. |
| Livelihood security/income distribution |
Widespread reduction (extreme events; poorer physical conditions). |
Reduced severity (extreme events). |
Widespread reduction (extreme events; poorer physical conditions). |
| Development potential/carrying capacity |
Decrease, with some differences between regions. |
Same or slight decrease. |
Decrease, with some differences between regions. |
Using a ‘mental model’3, such as that outlined above (Table 2), Hulme (1996) suggests three scenarios that may occur in the region under climate change. For all of the cases the ‘wet scenario’ is associated with increased temperature and increased rainfall and the ‘dry and core scenario’ is associated with increased temperatures and decreased rainfall. As is evident, the impacts flowing from these changes may impact on household livelihoods and may reduce the quality of life of children in the region.
Scholes, Midgely and Wand (2000), in their more recent study on vulnerability and adaptation of rangelands in southern Africa, show that general aridification of rangelands may occur over much of southern Africa, particularly in marginal environments subject to drought. They conclude that climate change impacts may, however, be complicated by rising CO2. The grassland biome may become more favourable to tree growth due to elevated CO2.
Other assessments of possible vegetation changes and impacts on plant diversity have also been done for South Africa, in particular Succulent Karoo Bioclimate Modeling
(see www.nbi.ac.za./climrep/index). Here again various models were used (e.g. HadCM2, CSM and GadCM2 (i.e. essentially models that either includes the influence of sulphates or not in their computations). Essentially, bio climate modelling determines the environmental limits of an entity with a given spatial distribution by matching its known distribution to climatic surfaces
(www.nbi.ac.za). Indications from this bioclimatic modelling show virtual complete loss and disappearance of the Succulent Karoo Biome and expansion of the Savannah Biome into the Grassland Biome areas. Tree encroachment in the grasslands may in turn mean that grass production is suppressed placing a stress on those depending on the grasslands for livelihoods. An increase in diversification of livelihoods for such groups including activities such as ecotourism, to offset these potential negative impacts, is suggested.
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Implications for water supplies and availability in the region in a changing environment
Coupled to vegetation and biome changes is available water. As is clear from some of the model assessments presented above, the indication is that rainfall may increase in some areas and decrease in others depending on the model used. While this may not be very useful to SCF practitioners currently, at least an indication of possible changes in the environmental system can be suggested that may shape future management decisions. As previously indicated, rainfall and run-off assessments have been derived for a 2050 climate scenario using the UKTR95 GCM with marked increases (30-50%) in expected annual rainfall over virtually all of Kenya, smaller increases (30%) over most of Tanzania, Uganda and north-eastern Zambia and very slight rises over smaller areas of western Zimbabwe, Botswana and central Namibia. This is in contrast to those areas with general declines in annual rainfall south of Tanzania, generally in the order of 10% but up to 30% in places.
Mainly as a consequence of anticipated changes in rainfall, including extreme events, changes in frequency and intensity in rainfall, the UKTR95 scenario for 2050 shows decreases in annual runoff of the order of 0-40% over much of South Africa, and over 30% over eastern Zimbabwe and most of Mozambique. Enhanced runoff may be anticipated over northern Zambia and Mozambique as well as over eastern Tanzania, with the most significant increases predicted for Kenya (Schulze, Meigh and Horan, 2001).
Water stress in the region is, however, not only a function of rainfall and other biophysical variables (e.g. evaporation) but also includes such factors as population growth, expanding urbanization and increased economic development as well as various challenges to international water resources (Sharma et al., 1996). Water demand, for example, is projected to rise by 3% until the year 2020, a rate about equal to the region’s population growth rate (SARDC, IUCN and SADC, 1994). By 2025 it is estimated that a number of countries in Africa, several of them in the region, will experience severe water stress (World Bank, 1995). The implications for changes in water availability for the region are therefore critical considerations particularly when viewed against the backdrop of possibly climate variability in the region that has been described above.
Accurate and precise estimates of water vulnerability in the region, however, cannot be given. By using models that try to best capture as many of the variables that may play a role in determining water availability in the region, some indications of water availability can be suggested. More recent hydrological assessments (e.g. Schulze, Meigh and Horan (2001) include the development of an index that accounts for seasonal and inter-annual variation of supply of water, combines both surface and groundwater availability and adds the human dimensions by including supply and demand of water. Using the index, an assessment of the vulnerability of the eastern and southern Africa’s (ESA) hydrology and water resources was made. Under current demands, much of ESA was shown to have adequate water supply. Many areas have groundwater supplies that are as yet untapped in the region. Water shortfalls, however, were shown to exist mainly in Uganda, south-western Kenya, in Zimbabwe around Harare, and over much of South Africa, Lesotho and Swaziland (largely a consequence of high urban population densities combined with high irrigation demands in these areas) (Meigh et al., 1998).
Expanding on this work, and by including such factors as projected population growth, demand increases in water-use sectors (rural, urban and large urban), as well as changes expected with a model output for future climate (UKTR95), a scenario for 2050 was undertaken. By 2050 water shortages are expected to increase with the biggest shortage projected for Mozambique, Tanzania and South Africa. Increases in areas with severe water shortages, where shortages are projected to increase, include South Africa, Tanzania and Uganda.
The potential increase in extreme events (such as droughts and floods), as indicated above, may place additional strains on already water-stressed areas. The case of the impacts of the 1992 drought, for example, is informative on the impacts that such an extreme climate event may have on a country. Using the early 1990s drought as an analogue, Magadza (1996) illustrates, that under a 2XCO2 scenario, lakes, dams and wetlands would be impacted. Evaporation would increase with many of the small impoundments of water either drying up or holding insufficient water for local needs. Investigations, for example, in Lake Mtirikwe (formerly Kyle) during the 1991/92 period, showed that reductions in rainfall following years of persistent low water levels resulted in reductions of water for irrigation for sugar estates and were too low to maintain water supply to the Masvingo urban area. Additional problems of salutation, among others, for example, could further heighten such periods of environmental stress (Magadza, 1996). For other related or ‘knock-on’ impacts arising due to shortages in water in the region see Benson and Clay (1998).
Table 3: Some factors influencing the vulnerability of ESA water resources, now and in the future (adapted from Schulze, Meigh and Horan, 2001).
| Factor |
Explanation |
| Spatial variation |
Vulnerability of water resources can vary markedly over a short distance |
| Lack of physical infrastructure |
A lack of infrastructure inhibits optimal use of water |
| Settlement location |
Many rural dwellers are not located along perennially flowing river channels |
| High variability of runoff within and between seasons |
High costs of water projects because of high variability in the hydrological system |
| Food security |
Climate and hydrological uncertainty constrains self-sufficiency of food. |
Footnote:
- Anomalously warm-sea surface temperatures in the central and tropical western Indian Ocean have also been associated with drier than average conditions over South Africa. Since the late 1970s, the sea-surface temperature variability has been characterized by increasing temperatures in the equatorial Indian Ocean. Furthermore, the ENSO signal has been shown to have weakened in the Indian Ocean sea-surface temperatures since the late 1970s, and this has resulted in a change in the association between Indian Ocean SSTs and December-February rainfall over much of South Africa and Namibia. Prior to the late 1970s, sea surface temperature variability in equatorial Indian Ocean was closely related to ENSO and equatorial SSTs.
- This is a deliberate choice, using a mental rather than a mathematical model because of limitations of data, large uncertainties in the interactions between physical and social responses to regional climate change over the next 60 years and the complexity of the issues under review (Hulme, 1996, 63).
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