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Suggestion for citations:
Volume:
Revermann, R., Krewenka, K.M., Schmiedel, U., Olwoch, J.M., Helmschrot, J. & Jürgens, N. (eds.) (2018)
Climate change and adaptive land management in southern Africa – assessments, changes, challenges, and
solutions. Biodiversity & Ecology, 6, Klaus Hess Publishers, Göttingen & Windhoek.
Articles (example):
Archer, E., Engelbrecht, F., Hänsler, A., Landman, W., Tadross, M. & Helmschrot, J. (2018) Seasonal
prediction and regional climate projections for southern Africa. In: Climate change and adaptive land
management in southern Africa – assessments, changes, challenges, and solutions (ed. by Revermann, R.,
Krewenka, K.M., Schmiedel, U., Olwoch, J.M., Helmschrot, J. & Jürgens, N.), pp. 14–21, Biodiversity
& Ecology, 6, Klaus Hess Publishers, Göttingen & Windhoek.
Corrections brought to our attention will be published at the following location:
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Biodiversity & Ecology
Journal of the Division Biodiversity, Evolution and Ecology of Plants,
Institute for Plant Science and Microbiology, University of Hamburg
Volume 6:
Climate change and adaptive land management
in southern Africa
Assessments, changes, challenges, and solutions
Edited by
Rasmus Revermann1, Kristin M. Krewenka1, Ute Schmiedel1,
Jane M. Olwoch2, Jörg Helmschrot2,3, Norbert Jürgens1
1 Institute for Plant Science and Microbiology, University of Hamburg
2 Southern African Science Service Centre for Climate Change and Adaptive Land Management
3 Department of Soil Science, Faculty of AgriSciences, Stellenbosch University
Hamburg 2018
RPlease cite the article as follows:
Archer, E., Engelbrecht, F., Hänsler, A., Landman, W., Tadross, M. & Helmschrot, J. (2018)
Seasonal prediction and regional climate projections for southern Africa. In: Climate change and
adaptive land management in southern Africa assessments, changes, challenges, and solutions
(ed. by Revermann, R., Krewenka, K.M., Schmiedel, U., Olwoch, J.M., Helmschrot, J. & Jürgens,
N.), pp. 14-21, Biodiversity & Ecology, 6, Klaus Hess Publishers, Göttingen & Windhoek.
doi:10.7809/b-e.00296
14 C        A
Climate
Abstract: Temperatures over southern Africa have been increasing rapidly over the last ve decades, at a rate of about twice
the global rate of temperature increase. Further drastic increases, in the order of 6°C by the end of the century relative to the
present-day climate, may occur over the central and western interior regions under low-mitigation futures. Moreover, south-
ern Africa is projected to become generally drier under low-mitigation climate change futures. Such changes will leave little
room for adaptation in a region that is already characterised as dry and hot. Impacts on crop and livestock farming may well
be devastating, and signifi cant changes may occur in terms of vegetation cover in the savannas, particularly in the presence
of human-induced land degradation. Under modest to high mitigation, southern Africa will still experience further climate
change, but amplitudes of change will be reduced, potentially leaving more room for adaptation. Skilful seasonal forecasts
may become an increasingly important adaptation tool in southern Africa, especially when combined with a robust weather
station monitoring network.
Resumo: A temperatura no Sul de África tem vindo a aumentar rapidamente ao longo das últimas cinco décadas, a uma
taxa de cerca do dobro da global. Aumentos adicionais drásticos, na ordem dos 6°C até ao nal do século em relação ao
clima actual, poderão ocorrer nas regiões interiores centrais e ocidentais sob cenários futuros de baixa mitigação. Além dis-
so, prevê-se que o Sul de África irá tornar-se geralmente mais seco sob cenários futuros de baixa mitigação das alterações
climáticas. Tais alterações deixarão pouco espaço para a adaptação numa região que já é caracterizada como seca e quente.
Os impactos na agricultura e na pecuária poderão ser devastadores, e alterações signifi cativas poderão ocorrer em termos
de cobertura vegetativa nas savanas, particularmente na presença de degradação da terra induzida pelo Homem. Com uma
mitigação média-alta, o Sul de África continua infl uenciado pelas alterações climáticas, mas as amplitudes são reduzidas,
deixando potencialmente mais espaço para a adaptação. Previsões sazonais competentes poderão tornar-se numa ferramenta
de adaptação cada vez mais importante no Sul de África, especialmente quando combinadas com redes robustas de moni-
torização por estações meteorológicas.
Seasonal prediction and regional climate
projections for southern Africa
Emma Archer1,5*, Francois Engelbrecht3,7, Andreas Hänsler2, Willem Landman4, Mark Tadross6, Jörg Helmschrot 8,9
1 CSIR Natural Resources and the Environment, Building 1, cnr Carlow and Rustenburg Roads, Emmarentia 2193,
Johannesburg, South Africa
2 Climate Service Center Germany (GERICS), Chilehaus – Eingang B, Fischertwiete 1, 20095 Hamburg, Germany
3 CSIR Natural Resources and the Environment, Building 33, Meiring Naude Road, Pretoria 0001, South Africa
4 Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Private Bag X20,
Hatfi eld 0028, South Africa
5 Global Change Institute, University of the Witwatersrand, 1 Jan Smuts Avenue, Braamfontein 2000, Johannesburg,
South Africa
6 UNDP/Climate Systems Analysis Group, University of Cape Town, Pvt Bag, Rondebosch 7700, South Africa
7 School of Geography, Archaeology and Environmental Sciences, University of the Witwatersrand, Private Bag 2,
WITS 2050, South Africa
8 SASSCAL Regional Secretariat, 28 Robert Mugabe Avenue, Windhoek, Namibia
9 Stellenbosch University, Faculty of AgriSciences, PO Box X1, Stellenbosch 7602, South Africa
* Corresponding author: earcher@csir.co.za
B  E 6 2018 15
Climate
Introduction
The past few years in southern Africa (in
both the summer and winter rainfall re-
gions) have demonstrated yet again the
vulnerability of the subcontinent to cli-
mate variability. Multi-year below-nor-
mal summer rainfall has had a severe im-
pact on key sectors, including agriculture
and water, as have multiple more recent
winters with below-normal rainfall (see,
for example, Archer et al., 2017).
Such conditions have highlighted the
need for climate science in the region
that truly enables us to both predict con-
ditions of climatic risk in the shorter to
the longer term and to use such infor-
mation to improve short- and long-term
readiness (Winsemius et al., 2014). In
this overview article, we describe work
in climate prediction undertaken on both
longer-term climate change projections
and seasonal early warning. We conclude
by a brief discussion of the essentials be-
yond climate science, where we may po-
tentially eff ectively translate information
into real utility.
Projections of future
climate change over
southern Africa
Later in this chapter, we consider climate
observations and data availability; and it
should be noted at the start of discuss-
ing the latest fi ndings in terms of climate
change projections for the continent that
observation and data gaps remain a sig-
nifi cant concern. Observed data also con-
strain our work in the area of seasonal
forecasting and early warning (see sec-
tion to follow). Figure 4, for example,
shows the uneven coverage of observed
climate data for the continent, particu-
larly outside of South Africa. That limi-
tation notwithstanding (and we provide
more detail later in the chapter), substan-
tive work has been undertaken in terms of
climate change projections on the conti-
nent. Climate change is projected to have
widespread impacts in southern African
during the 21st century, particulalrly un-
der low-mitigation futures (Niang et al.,
2014). Temperatures are projected to rise
rapidly, at 1.5 to 2 times the global rate
of temperature increase (James & Wash-
ington, 2013; Engelbrecht et al., 2015).
Indeed, the observed rate of temperature
increase is particularly high over the in-
terior regions of southern Africa. Here
temperature trends as high as a 2 to 3.6°C
increase per century have been recorded
over the period 1961–2010 (Engelbrecht
et al., 2015; Kruger & Sekele, 2013). In
addition to the projected increases in sur-
face temperature, the southern African
region is also projected to become gener-
ally drier under e nhanced anthropogenic
forcing (Christensen et al., 2007; Engel-
brecht et al., 2009; Haensler et al., 2010,
2011; James & Washington, 2013; Niang
et al., 2014). These regional changes
will plausibly have a range of impacts
in southern Africa, including impacts on
energy demand (in terms of achieving hu-
man comfort in buildings and factories),
agriculture (e.g., reductions of yield in
the maize crop under higher tempera-
tures and reduced soil moisture; Land-
man et al., 2017), livestock production
(e.g., higher cattle mortality as a result of
oppressive temperatures), water security
(through reduced rainfall and enhanced
evapotranspiration; Engelbrecht et al.,
2015) and human health (through oppres-
sive temperatures; Garland et al., 2015).
Moreover, climate change is to take
place not only through changes in aver-
age temperature and rainfall patterns, but
also through changes in the attributes of
extreme weather events. For the southern
African region, generally drier condi-
tions and the more frequent occurrence of
dry spells are plausible over most of the
interior (Christensen et al., 2007; Engel-
brecht et al., 2009; Haensler et al., 2011).
Tropical cyclone tracks are projected
to shift northward, bringing more ood
events to northern Mozambique and
fewer to the Limpopo province in South
Africa (Malherbe et al., 2013). Cut-off
low related fl ood events are also pro-
jected to occur less frequently in South
Africa (e.g., Engelbrecht et al., 2013) in
response to a poleward displacement of
the westerly wind regime. Intense thun-
derstorms plausibly may occur more
frequently over South Africa in a gener-
ally warmer climate (e.g., Engelbrecht
et al., 2013). Perhaps most important is
that the regional changes in circulation
that are plausible over southern Africa,
in particular an increase in the frequency
and intensity of mid-level high-pressure
systems, may plausibly induce the more
frequent occurrence of heat-wave events
over the region (e.g., Engelbrecht et al.,
2015; Garland et al., 2015).
It is against this background that a fo-
cused eff ort was made to further explore
the climate change futures of southern
Africa through a coordinated SASSCAL
research programme, in addition to other
research active in the subcontinent and
on the continent more broadly. At the
CSIR in South Africa and at the Cli-
mate Service Center Germany (GER-
ICS), the most recent global circulation
model (GCM) projections of the Coupled
Model Intercomparison Project Phase
Five (CMIP5) and Assessment Report
Five (AR5) of the I ntergovernmental
Panel on Climate Change (IPCC) were
downscaled to 50 km resolution over Af-
rica. These simulations are for the period
1961 to 2100, follow the experimental
design recommended by the Coordinated
Downscaling Experiment (CORDEX),
and have been derived for low- (Rep-
resentative Concentration Pathway 8.5
[RCP8.5]), modest-high- (RCP4.5) and
high-mitigation (RCP2.6) scenarios. The
data of these simulations are also made
available to the international science
community via the CORDEX databases.
The regional climate model used at the
CSIR is the conformal-cubic atmospher-
ic model (CCAM), a variable-resolution
global climate model (GCM) developed
by the Commonwealth Scientifi c and In-
dustrial Research Organisation (CSIRO)
(McGregor, 2005). At GERICS the
simulations have been conducted with
the REMO regional climate model. For
each of the RCPs, six diff erent GCMs
were downscaled, so that the results pre-
sented below are based on an ensemble
of possible future developments. The
CCAM simulations were performed on
supercomputers at the Centre for High-
Performance Computing (CHPC) of the
Meraka Institute of the CSIR in South
Africa; the REMO simulations were con-
ducted at the German Climate Comput-
ing Center in Hamburg, Germany.
The CCAM projected changes in an-
nual rainfall over southern Africa are
16 C        A
Climate
shown in Figure 1 for the far-future
period 2080–2099 compared to the
present-day (1971–2000). A general pat-
tern of rainfall decreases is projected for
subtropical southern Africa. An excep-
tion is Mozambique, where rainfall in-
creases are projected for the central and
northern parts in particular. There is some
uncertainty in the projections over the in-
terior of the central subcontinent, where
a minority of projections indicate rainfall
increases over specifi c regions, or de-
creases that are small in amplitude. The
largest rainfall decreases are projected
for Angola and over the southern parts of
South Africa. The projected decreases in
Angola may be occurring in conjunction
with changes in the Angola low-pressure
system and the general strengthening of
the subtropical high-pressure belt over
southern Africa (e.g., Engelbrecht et al.,
2009). Over South Africa, the rainfall
decreases projected for the southwest-
ern Cape are occurring in association
with a poleward displacement of the
westerlies and frontal systems under low
mitigation (e.g., Christensen et al., 2007;
Engelbrecht et al., 2009).
Drastic temperature increases of 4–7°C
are projected to occur over the western
interior regions of southern Africa under
low mitigation (Fig. 2). Relatively small-
er increases are projected for Mozam-
bique (where general increases in rainfall
and cloud cover are projected) and along
the coastal areas (due to the moderating
eff ects of the ocean).
Incorporating 16 regional climate
change projections conducted by GER-
ICS (using the REMO model) and other
institutions in the frame of the CORDEX
initiative for the southern African region,
analyses of projected changes for a set
of climate indices along various tran-
sects over the SASSCAL region have
been conducted based on larger regional
climate model ensembles for RCP4.5
and RCP8.5. The median projection of
change in annual maximum temperature
is about 3°C (RCP4.5) to 5°C (RCP8.5)
in the interior and about 1.5 to 2°C less
at the coastal areas in the west, east, and
south. The spread between the diff erent
simulations is about 2°C (RCP4.5) to
3°C (RCP8.5), leading to a maximum
projected increase in maximum annual
temperature of about 7°C (RCP8.5) over
the semi-arid to arid western parts of the
SASSCAL region (Fig. 3). The CCAM
projections (Fig. 2) are consistent with
the range of changes projected by the
CORDEX ensemble (Fig. 3).
The SASSCAL projections and analy-
ses convey a clear message that a low-
mitigation climate future may have
devastating impacts on the southern
African region. Drastically rising aver-
age temperatures and related extreme
events (e.g., very hot days, heat-wave
days, and high re danger) are plausi-
ble to have a negative impact on crop
yield, livestock production, and human
health. The general reductions in rain-
fall may induce further stress for rainfed
agriculture in the region. For example,
the Kalahari Desert receives annual pre-
cipitation rates of about 250 mm in the
arid south-western parts and rising to
more than 600 mm towards the centre
and north-east of Botswana. For the end
of the century, not only rising tempera-
tures are projected but also a reduction
in the annual rainfall rate. With a later
onset of the rainy season and an earlier
cessation, the number of dry days out-
side the rainy season increases and the
rainy season itself shortens. As a result,
semi-arid and arid domains are estimated
to expand by 5–8%, infl uencing the eco-
system and its vegetation, hydrology,
Figure 1: CCAM projected change in the annual average rainfall totals (units 10*mm/
day) over southern Africa at 50 km resolution, for the time period 2080–2099 relative to
1971–2000. The downscalings were obtained from six diff erent CMIP5 GCM projections
under low mitigation (RCP8.5).
B  E 6 2018 17
Climate
and human proceedings (Stringer et al.,
2009). Climate change has already been
noticeably present during the past dec-
ades (Kusangaya et al., 2014), and the
associated intensifi cation and expansion
of agriculture and livestock farming has
reinforced land use pressure. Due to the
absence of suffi cient surface water re-
sources, groundwater resources are used
to address the rising demand for water
and, consequently, the number of wells
and boreholes in the Kalahari Desert
has increased remarkably during the
last century (Christelis & Struckmeier,
2011). Projected climate extremes, in
combination with population growth,
may cause an overutilization of limited
Figure 2: CCAM projected change in the annual average temperature (°C) over southern
Africa at 50 km resolution, for the time period 2080–2099 relative to 1971–2000. The
downscalings were obtained from six diff erent CMIP5 GCM projections under low mitigation
(RCP8.5).
resources in central Botswana, which in
turn may cause migration to other areas.
Also, coastlines may be aff ected.
While the west coast of southern Af-
rica is comparably dry (< 500 mm), the
east coast receives more rainfall (700–
1200 mm), with a decreasing trend from
north to south. As shown by Oltmanns
(2015), projections indicate a decline in
precipitation for most coastlines, except
for northern Mozambique, for which an
increase by approximately 10% is pro-
jected. A similar tendency can be seen
for rainfall intensity. The west coast will
barely experience extreme events (more
than 20 mm/day), but an increase in ex-
treme events is projected for the north-
ern Mozambican coastline (declining
slightly towards the south). Although
aspects of agriculture in Mozambique
may benefi t from an increase in rainfall,
the country simultaneously needs to pre-
pare for the likelihood of an increasing
number of ood events associated with
landfalling tropical lows and cyclones
under climate change. The plausibility
of a signifi cant reduction of rainfall over
the mega-dam region of South Africa is
a further cause for concern. Even under
modest-high mitigation, southern Africa
will experience potentially signifi cant
changes in the regional climate. Over the
interior regions, temperature increases
may well still reach values of 3–4°C, and
it remains plausible that the region will
become generally drier. Nevertheless,
temperature increases under modest-high
mitigation, though signifi cant, are on the
order of half the amplitude of changes
under low mitigation. This implies the
availability of more options for adapta-
tion and more time to adapt before criti-
cal temperature thresholds are exceeded
for the fi rst time.
It is important to consider what the
implications of the projected changes in
climate may be for vegetation in south-
ern Africa, particularly in the savannas,
where complex interactions occur be-
tween grasses, trees, fi re, and CO2 (Bond
& Midgley, 2012). In fact, rising levels
of CO2 strongly favour trees over grasses
in the savannas, potentially causing bush
encroachment and spawning the hypoth-
esis of the “forestation of Africa” under
climate change (West et al., 2012). How-
ever, the substantial reductions in rainfall
projected for southern Angola and Zam-
bia in particular, in combination with
more frequent fi res occurring under dras-
tic temperature increases (Engelbrecht et
al., 2015) and human-induced land deg-
radation, may in fact result in decreasing
tree cover in the savannas (Engelbrecht
& Engelbrecht, 2016). Dynamic vegeta-
tion-fi re models that can also incorporate
scenarios of human-induced changes
in land use are required to objectively
project the vegetation future of south-
ern Africa, yet few such models have to
date been developed and applied over the
region.
18 C        A
Climate
Seasonal variability and
early warning
Southern African seasonal climate
anomalies are (generally) predictable
(Barnston et al., 1996), although work
in this area remains challenged by the
lack of observational data in certain ar-
eas (see section to follow). The notion of
a predictable climate, further supported
by the discovery in the 1980s of the El
Niño-Southern Oscillation (ENSO) phe-
nomenon as a primary driver of seasonal-
to-interannual variability over the region
(Ropelewski & Halpert, 1987, 1989),
led to the development of operational
seasonal prediction systems for rainfall
(Mason, 1998; Jury et al., 1999) and for
temperature (Klopper et al., 1998). The
initial modelling in southern Africa was
undertaken mainly from the early 1990s
by a number of institutions that devel-
oped statistical seasonal forecast models
(Mason, 1998; Jury et al., 1999; Land-
man & Mason, 1999). A few years later,
in the early 2000s, atmospheric general
circulation models (AGCMs) for opera-
tional seasonal forecasting and research
began to be used (e.g. Landman et al.,
2001). Major advances in seasonal fore-
cast system and infrastructure develop-
ment have occurred since then, including
the World Meteorological Organisation’s
recognition of the South African Weather
Service (SAWS) as a Global Producing
Centre for Long-Range Forecasting, the
development of objective mult i-model
forecasting systems for southern Africa
(Landman & Beraki, 2012), and, signifi -
cantly, the development of a fully cou-
pled ocean-atmosphere model at SAWS
for operational seasonal forecast produc-
tion (Beraki et al., 2014). Nested regional
climate models as seasonal forecasting
tools were also investigated (Landman et
al., 2005, 2009; Kgatuke et al., 2008; Rat-
nam et al., 2011). A review on aspects of
seasonal forecast development in South
Africa can be found in Landman (2014).
After forecasts were demonstrated to
obtain the highest levels of skill when
statistical methods and global model
forecasts are blended into a multi-tiered
forecast system (Landman et al., 2001), a
move away from compiling operational
forecasts subjectively through consensus
discussions was introduced by making
use of objective multi-model forecast
systems (Landman & Beraki, 2012). Over
the past 10 years or so, modelling advanc-
es obtained locally were largely focused
on the development, testing, and use of
fully coupled ocean-atmosphere models
in seasonal forecast production (Beraki et
al., 2012; Landman et al., 2012), the dem-
onstrated potential of forecasts through
the development of objective applications
models (Malherbe et al., 2014), and the
modelling of intra-seasonal characteris-
tics (Engelbrecht et al., 2017).
Notwithstanding these developments,
a number of caveats regarding season-
al forecasting in South Africa may be
identifi ed that require the attention of
modellers, forecast producers, and us-
ers of forecasts. These include (but are
not limited to) the need to demonstrate
the benefi ts derived from using seasonal
forecasts, including nancial benefi ts;
expanding on the knowledge of current
skill levels and identifying factors limit-
ing forecast skill; the development and
testing of forecast systems for areas of
southern Africa largely neglected up to
now (i.e., the south-western and south-
ern Cape); the development of schemes
40°0'0"E30°0'0"E20°0'0"E10°0'0"E
10°0'0"S20°0'0"S30°0'0"S
Location of the Transects
¯
0 500 1.000
kilometres
Cartography:
V. Oltm anns
2015-06-12
Figure 3: Range of projected changes in annual maximum temperature along an east-west
(25S) and a north-south (20E) transect for the time period 2071–2100 relative to 1971–2000
for the RCP4.5 and RCP8.5 scenarios. For each of the scenarios, the projections are based
on an ensemble of 16 transient regional climate change simulations from the CORDEX Af-
rica database. The black line represents the median change. The dark-grey area refl ects the
range defi ned by the 25th to 75th percentiles of all simulations centred on the median. The
light grey area spans the range between the ensemble minimum and maximum. Figures are
taken from Oltmanns (2015).
B  E 6 2018 19
Climate
for process-based verifi cation; the build-
ing of so-called earth system models for
improved forecasts through, for example,
data assimilation systems and tropical-
extra-tropical ocean-land-atmosphere
coupling; the operational production of
forecasts to address seasonal character-
istics such as onset, cessation, and sub-
seasonal variations; the production and
testing of high spatial and temporal reso-
lution forecasts; operational applications
model development; and, through co-
production, the development of method-
ologies to better communicate seasonal
forecast information to a variety of users
in terms of complexity and application.
Data gaps and needs
Lötter et al. (2018) describe a key chal-
lenge in the SADC region as being the
lack of long-term reliable climate re-
cords, particularly outside of South
Africa. Such records are essential both
for measurement and interpretation of
current trends (e.g., Kruger & Sekele,
2013; Engelbrecht et al., 2015) and for
providing the critical ability to interpret
the occurrence of extreme events against
the historical record. In addition, a robust
observation network supports a range of
tasks from shorter-term forecasting to
seasonal predictions to multi-decadal cli-
mate change projections (Engelbrecht et
al., 2011) through the process of model
evaluation and validation and by provid-
ing options for statistical downscaling
(e.g., Landman et al., 2017). It also sup-
ports adaptation eff orts, such as climate
index–driven insurance schemes (e.g.,
Malherbe et al., 2018).
Figure 4 (from Lötter et al., 2018)
shows the sparseness of climate records,
making it evident that certain areas are
particularly poorly served. It may be
noted that in this regard SASSCAL has
in recent years made a considerable ef-
fort to rescue historic climate data and to
expand the weather station observational
network in Namibia, Botswana, Zambia,
and Angola (Kaspar et al., 2015; Muche
et al., 2018; Posada et al., 2018).
Moving forward
At a time of recent and current drought
in both southern Africa’s summer and
winter rainfall periods, it is an opportune
moment to consider the role of climate
prediction in supporting both shorter-
term coping and longer-term adaptation
to climate variability and change. While
improved prediction can by no means
stand alone in support of improved re-
sponse, improvements are essential at
both a national and regional level. It is
hoped that such improvements in pre-
diction as those detailed here (including
attention to gaps in data and the obser-
vational network) might be matched with
improved support for response and adap-
tation to support the evolution of a more
resilient subcontinent.
a
b
Figure 4: The locations of NOAA’s Global Historical Climate Network (GHCN) weather
stations, as used by CRU, across Africa (a) and the number of weather stations collecting
daily temperature records across southern Africa from 1850 to 2014 used in the gridded
CRUTEM4 product (b). Station density increased consistently from the start of the 20th
century and peaked in the 1970s, after which it began to decline. Source: Davis & Vincent,
2017 (reproduced with the permission of the authors).
20 C        A
Climate
Acknowledgements
The research was carried out in the
framework of SASSCAL and was spon-
sored by the German Federal Ministry of
Education and Research (BMBF) under
promotion number 01LG1201M. The
CCAM simulations contributed by the
CSIR as a contribution to the SASSCAL
climate tasks were performed on the
supercomputers of the Centre for High
Performance Computing (CHPC) of
the Meraka Institute of the CSIR. Co-
funding for this work was provided by a
CSIR Parliamentary Grant project on the
development of the fi rst African-based
Earth System Model. Further co-funding
was provided by the NERC project UM-
FULA, grant number NE/M02007X/1.
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Landman, W.A., DeWitt, D. Lee, D.-E.,
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rainfall prediction skill over South Africa: 1-
vs. 2-tiered forecasting systems. Weather
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Landman, W.A., Engelbrecht, F.A., Hewitson,
B., Malherbe, J., & Van der Merwe, J.
(2017) Towards bridging the gap between
climate change projections and maize
producers in South Africa. Theoretical and
Applied Climatology, 11-17. CrossRef
Landman, W.A., Kgatuke, M.M., Mbedzi, M.,
Beraki, A., Bartman, A. & du Piesanie, A.
(2009) Performance comparison of some
dynamical and empirical downscaling
methods for South Africa from a seasonal
climate modelling perspective. International
Journal of Climatology 29, 1535-1549.
CrossRef
Landman, W.A. & Mason, S.J. (1999)
Operational long-lead prediction of South
African rainfall using canonical correlation
analysis. International Journal of
Climatology, 19, 10731090. CrossRef
Landman, W.A., Mason, S.J., Tyson, P.D. &
Tennant, W.J. (2001) Retro-active skill of
multitiered forecasts of summer rainfall over
southern Africa. International Journal of
Climatology, 21, 119. CrossRef
Landman, W.A., Seth, A., Camargo, S.J.
(2005) The effect of regional climate model
domain choice on the simulation of tropical
cyclone-like vortices in the southwestern
Indian Ocean. Journal of Climate, 18, 1263
1274. CrossRef
Lötter, D., Davis, C., Archer, E., Vincent, L.,
Pardoe, J., Tadross, M., Landman. W.,
Stuart-Hill, S. & Tadross, M. (2018) Climate
information needs in southern Africa.
CCCEP Working Paper (under review).
Malherbe, J., Engelbrecht, F.A. & Landman,
W.A. (2013) Projected changes in tropical
cyclone climatology and landfall in the
Southwest Indian Ocean region under
enhanced anthropogenic forcing. Climate
Dynamics, 40, 28672886. CrossRef
Malherbe, J., Iyahen, E., Engelbrecht, F.,
Chamunorwa, M. & Helmschrot, J. (2018)
The Extreme Climate Index (ECI), a tool for
monitoring regional extreme events. This
volume. CrossRef
Malherbe, J., Landman, W.A., Olivier, C.,
Sakuma, H. & Luo, J.-J. (2014). Seasonal
forecasts of the SINTEX-F coupled model
applied to maize yield and streamflow
estimates over north-eastern South Africa.
Meteorological Applications, 21, 733-742.
CrossRef
Mason, S.J. (1998) Seasonal forecasting of
South African rainfall using a non-linear
discriminant analysis model. International
Journal of Climatology, 18, 147164.
CrossRef
McGregor, J.L. (2005) C-CAM geometric
aspects and dynamical formulation. CSIRO
Atmospheric Research Technical Paper, 70.
Muche, G., Kruger, S., Hillmann, T. et al.
(2018) SASSCAL WeatherNet: present
state, challenges and achievements of the
regional climatic observation network and
database. This volume. CrossRef
Niang, I., Ruppel, O.C., Abdrabo, M.A., Essel,
A., Lennard, C., Padgham, J. & Urquhart, P.
(2014) Africa. Climate change 2014:
impacts, adaptation, and vulnerability. Part
B: regional aspects (ed. by V.R. Barros,
C.B. Field, D.J. Dokken et al.), pp. 1199
1265. Cambridge University Press,
Cambridge, UK.
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Southern Africa using CORDEX climate
projections. MSc thesis, Friedrich Schiller
University Jena (unpublished).
Posada R., Riede, J., Kaspar, F., Mhanda, A.,
Radithupa, M., Stegling, J., Nascimento, D.,
Tima, L., Kanyanga, J., Nkonde, E.,
Swaswa, M. & Waitolo, D. (2018)
Cooperation of meteorological services
within SASSCAL on improving the
management of observed climate data. This
volume. CrossRef
Ratnam, J.V., Behera, S.K., Masumoto, Y.,
Takahashi, K. & Yamagata, T. (2011) A
simple regional coupled model experiment
for summer-time climate simulation over
southern Africa. Climate Dynamics, 39,
22072217. CrossRef
Ropelewski, C.F. & Halpert, M.S. (1987)
Global and regional scale precipitation
patterns associated with the El Niño
Southern Oscillation. Monthly weather
review, 115, 16061626. CrossRef
Ropelewski, C.F. & Halpert, M.S. (1989)
Precipitation patterns associated with the
high index of the Southern Oscillation.
Journal of Climate, 2, 268284. CrossRef
Stringer, L., Dyer, J., Reed, M., Dougill, A.,
Twyman, C. & Mkwambisi, D. (2009)
Adaptations to climate change, drought and
desertification: local insights to enhance
policy in southern Africa. Environmental
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West, A.G., Midgley, G.F. & Bond, W.J.
(2012) The reforestation of Africa? South
African Journal of Science, 108, 24.
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Archer Van Garderen, E., Wetterhall, F.,
Pappenberger, F. & Werner, M.G.F. (2014)
The potential value of seasonal forecasts in a
changing climate in southern Africa.
Hydrology and Earth System Sciences, 18,
15251538. CrossRef
... In the case of freshwater species conservation in the Lesotho Highlands, knowing if there is indeed high relative species richness and cold-evolved species is paramount given growing anthropogenic activity (e.g., waste pollution and agriculture; see Pullanikkatil and Urama, 2011;Chatanga and Seleteng-Kose, 2021;Turpie et al., 2021) and global warming-this is particularly relevant for southern Africa and cold-evolved species, where climatic change is likely to increase substantially over the next century (Dallas and Rivers-Moore, 2014;Serdeczny et al., 2016;Archer et al., 2018;Bentley et al., 2018;Weber et al., 2018). However, conservation relies on accurately being able to quantify relative biodiversity richness in the Highlands as compared with the surroundings and, in this case, decipher cold-evolved species from not (i.e., through determining the evolutionary and spatial origins of species). ...
... Future climatic projections show a decrease in rainfall and an increasing frequency of drought periods (Kundzewicz et al., 2014;Luetkemeier & Liehr, 2015;Masih et al., 2014;Ujeneza & Abiodun, 2015). In combination with an increasing potential evaporation, these conditions likely result in reduced water availability (Angula & Kaundjua, 2016;Archer et al., 2018;Engelbrecht et al., 2009). It is important to find solutions for effective water storage, particularly during the dry seasons (Arendt et al., 2021). ...
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Semiarid regions are often affected by water scarcity and poor water quality. Seasonal changes in precipitation and drought events increase the pressure of use on water bodies and their pollution. In Central Northern Namibia, a high seasonal intra- and inter-annual variability of precipitation caused a 5-year lasting drought period. In the semiarid region, ephemeral channels and water pans represent the main water source, besides the institutionalized water supply. No systematic analysis of its quality has been conducted so far. The states of the surface waters at the end of the dry season in 2017 and the end of the rainy seasons in 2018 and 2019 were characterized by the analysis of physical–chemical parameters, focusing on usability. The first results show coarse contamination of the waters, which results in high turbidity values. Salt concentrations, such as Ca²⁺ and Na⁺, greatly increased due to evaporation. Al is present in high concentrations in solid and liquid phases, which indicates direct anthropogenic pollution. Spatial differences are evident in the study area and based on the precipitation gradient, land use, and population density. The waters cannot be used as drinking water without prior treatment.
... Most of the study region is projected to experience decreases of minimum relative humidity of between 6 and 9% across all three percentiles (Fig. 7d-f). emission scenario (e.g., Engelbrecht et al. 2011;Archer et al. 2018;Engelbrecht and Monteiro 2021). Tropical cyclone tracks are also projected continuously varying northwards to northern Mozambique, hence becoming fewer over North-eastern regions of South Africa, Limpopo province (Malherbe et al. 2013). ...
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Rising surface air temperatures, coupled with delays in the onset of austral summer rains and increased fuel load have amplified forest fire risk over southern Africa. This study investigates interactions between climate change and fire risk in South Africa’s northern savanna biome. We employ the CCAM model to simulate the reference climate and project future forest fire risk on the savanna. An ensemble of six CMIP5 GCMs were downscaled to 8 km to project climate change in the far-future (2080 to 2099) under RCP8.5 emission scenario. The models were validated using ERA5-Land reanalyses whilst future projections focused on the 10th, 50th and 90th percentiles. The frequency of high fire risk days was calculated using a McArthur Forest Fire Danger Index (FFDI) which links meteorological variables to fire danger. The ensemble simulated widespread temperature rises of between 4.5 and 6 °C across the savanna, whilst rainfall is projected to decline by up to 20 mm/month, with corresponding decreases in minimum relative humidity. Heat wave days are projected to increase to above 8 days per annum, whilst soil moisture deficiency increases by above 50 mm on the savanna. Consequently, mean annual high fire danger days are projected to reach a peak frequency of 25 days in October, with an autumnal secondary peak. Spatially, greater increases in high FFDI days were projected over the western savanna extending toward neighbouring Botswana. This study contributes to understanding fire risk under unprecedented temperature rises which appear to be modulating fire intensity in the study region.
... These changes in large-scale circulation patterns in response to climate change have consequences on regional weather conditions and air quality (e.g., Ibebuchi & Paeth 2021). Given the vulnerability of the southern African region to climate change (Archer et al. 2018), such as an increase in drought in the subtropical domains of southern Africa (e.g., Lazenby et al. 2018;Maúre et al. 2018;Sousa et al. 2018;Spinonia et al. 2019) and changes in the track and intensity of tropical cyclones in the southwest Indian Ocean (e.g., Malherbe et al. 2013;Fitchett et al. 2016;Muthige et al. 2018), this study is dedicated to advance the understanding of how future climate change will affect the frequency of occurrence of circulation patterns in Africa south of the equator. ...
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The impact of climate change on the frequency of occurrence of atmospheric circulation patterns can have a wide range of consequences ranging from weather extremes to the modification of pollutant transport. This study uses 11 CMIP6 global climate models (GCMs) to investigate the impact of future climate change on the frequency of occurrence of atmospheric circulation patterns, in Africa south of the equator. Here it is shown from the historical analysis that there are statistically significant trends in the frequency of occurrence of some of the classified circulation types (CTs) in the study region. Further, under the SSP5-8.5 and SSP2-4.5 emission scenarios, the historical CTs were reproduced, suggesting that future climate change will not constrain the existence of the CTs. However, for future emission scenarios, the ensemble of the GCMs projects notable changes in the spatial structure of the CTs and statistically significant trends in the frequency of occurrence of most of the CTs, towards the end of the 21st century. The intensity of the projected changes in the spatial structure and linear trends in the frequency of occurrence of the CTs are relatively stronger under the higher emission scenario. As regards changes in synoptic circulations in the study region, the ensemble of the GCMs project, (i) a positive trend in the frequency of occurrence of austral summer dominant CTs associated with atmospheric blocking of the Southern Hemisphere mid-latitude cyclones, adjacent to South Africa; (ii) alternating frequent periods of enhanced (suppressed) anticyclonic circulation at the western branch of the Mascarene high possibly due to a more positive phase of the Southern Annular Mode (warmer southwest Indian Ocean); (iii) possible weakening of the Angola low. The aforementioned changes can be expected to have direct impacts on the regional climates in the study region.
... Research has mainly focused on the mechanisms affecting local precipitation (Wilks, 2011), characterizing the meteorological (Archer et al., 2019) and agricultural drought (Watson et al., 2022). While recent climate change projections have been developed for Africa (Haensler, 2010;Haensler et al., 2011;Archer et al., 2018;Weber, 2018;Lim Kam Sian et al., 2021;Majdi et al., 2022), their bearing on local hydrological condition and function affect the development of appropriate adaptation strategies and the rate at which Africa acts to reduce the effects of global warming (Kusangaya et al., 2014). Furthermore, uncertainty still remains whether hydrological models can reproduce hydrological flows considering future non-stationary climatic conditions, which has been an issue for rainfall-runoff model applications around the world (Deb and Kiem, 2020;Fowler et al., 2020). ...
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Rainfall-runoff models are frequently used for assessing climate risks by predicting changes in streamflow and other hydrological processes due to anticipated anthropogenic climate change, climate variability, and land management. Historical observations are commonly used to calibrate empirically the performance of conceptual hydrological mechanisms. As a result, calibration procedures are limited when extrapolated to novel climate conditions under future scenarios. In this paper, rainfall-runoff model performance and the simulated catchment hydrological processes were explored using the JAMS/J2000 model for the Berg River catchment in South Africa to evaluate the model in the tails of the current distribution of climatic conditions. An evolutionary multi-objective search algorithm was used to develop sets of parameters which best simulate "wet" and "dry" periods, providing the upper and lower bounds for a temporal uncertainty analysis approach to identify variables which are affected by these climate extremes. Variables most affected included soil-water storage and timing of interflow and groundwater flow, emerging as the overall dampening of the simulated hydrograph. Previous modeling showed that the JAMS/J2000 model provided a "good" simulation for periods where the yearly long-term mean precipitation shortfall was <28%. Above this threshold, and where autumn precipitation was reduced by 50%, this paper shows that the use of a set of "dry" parameters is recommended to improve model performance. These "dry" parameters better account for the change in streamflow timing of concentration and reduced peak flows, which occur in drier winter years, improving the Nash-Sutcliffe Efficiency (NSE) from 0.26 to 0.60 for the validation period 2015-2018, although the availability of climate data was still a potential factor. As the model performance was "good" (NSE > 0.7) during "wet" periods using parameters from a long-term calibration, "wet" parameters were not recommended for the Berg River catchment, but could play a large role in tropical climates. The results of this study are likely transferrable to other conceptual rainfall/runoff models, but may differ for various climates. As greater climate variability drives hydrological changes around the world, future empirically-based hydrological projections need to evaluate assumptions regarding storage and the simulated hydrological processes, to enhanced climate risk management.
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In arid habitats, recent increases in summer temperatures associated with global warming are adversely affecting many animal populations. However, annual rainfall also varies widely in many of these areas, and we do not yet fully understand the relative impact of variation in temperature and rainfall on the demography of arid-zone species. Here, we examine the effects of temperature and rainfall variation on the demography of meerkats Suricata suricatta in the southern Kalahari over the last 25 years. During this period, average maximum monthly air temperatures at our study site increased by around 1.5°C to 3.2°C, while annual rainfall fluctuated without a consistent trend. We show that annual changes in female fecundity and recruitment were more closely correlated with variation in rainfall. Increasing air temperatures were associated with reductions in the recruitment of pups and the survival of some age classes but, in most cases, the demographic consequences of high temperatures were modest compared to the effects of low rainfall, which in some years led to the near cessation of successful reproduction and the extinction of many smaller groups. For instance, exceptionally low rainfall in 2012-2013 was associated with low recruitment and with declines in group size and population density, which fell by over 50%. Unusually hot years did not have similar consequences. Following the 2012-2013 drought, intermittent years of low rainfall and frequent droughts continued to suppress recruitment and slowed the population's recovery. Future changes in temperature may affect the dynamics and size of the meerkat population, but our work suggests that over the last 25 years, annual changes in rainfall have exerted a stronger influence on meerkat demography. Our study demonstrates the importance of long-term, individual-based data for determining how changes in climate affect the dynamics of animal populations, especially in arid environments where bottom-up processes often dominate.
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Productive agricultural supply chains require the support of functional ecosystems, but intense agricultural practices change local hydrological systems (e.g. river diversion). In this study, the impact of farm dams was assessed for the Verlorenvlei catchment, a sensitive ecosystem currently under a state of hydrological change in South Africa. We developed a new module for the Jena Adaptable Modelling System (JAMS)/J2000 rainfall–runoff model to assess the streamflow impact from the points of abstraction, losses during storage and irrigation. The model achieved a satisfactory streamflow calibration with efficiencies Nash Sutcliffe Efficiency (NSE, logNSE) of 0.52 and 0.51. The irrigated area reduced simulated streamflow by 12 to 19%. The results from the study agree with remote sensed evapotranspiration, measured lake surface water levels and streamflow, but uncertainty remains in the total simulated dam evaporation. While many catchments lack the data required for a detailed irrigation impact assessment, this approach considers total water use, dam storage to area relationships and general farming practices.
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Background: The climate of southern Africa is expected to become hotter and drier with more frequent severe droughts and the incidence of diarrhoea to increase. From 2015 to 2018, Cape Town, South Africa, experienced a severe drought which resulted in extreme water conservation efforts. We aimed to gain a more holistic understanding of the relationship between diarrhoea in young children and climate variability in a system stressed by water scarcity. Methods: Using a mixed-methods approach, we explored diarrhoeal disease incidence in children under 5 years between 2010 to 2019 in Cape Town, primarily in the public health system through routinely collected diarrhoeal incidence and weather station data. We developed a negative binomial regression model to understand the relationship between temperature, precipitation, and relative humidity on incidence of diarrhoea with dehydration. We conducted in-depth interviews with stakeholders in the fields of health, environment, and human development on perceptions around diarrhoea and health-related interventions both prior to and over the drought, and analysed them through the framework method. Results: From diarrhoeal incidence data, the diarrhoea with dehydration incidence decreased over the decade studied, e.g. reduction of 64.7% in 2019 [95% confidence interval (CI): 5.5-7.2%] compared to 2010, with no increase during the severe drought period. Over the hot dry diarrhoeal season (November to May), the monthly diarrhoea with dehydration incidence increased by 7.4% (95% CI: 4.5-10.3%) per 1 °C increase in temperature and 2.6% (95% CI: 1.7-3.5%) per 1% increase in relative humidity in the unlagged model. Stakeholder interviews found that extensive and sustained diarrhoeal interventions were perceived to be responsible for the overall reduction in diarrhoeal incidence and mortality over the prior decade. During the drought, as diarrhoeal interventions were maintained, the expected increase in incidence in the public health sector did not occur. Conclusions: We found that that diarrhoeal incidence has decreased over the last decade and that incidence is strongly influenced by local temperature and humidity, particularly over the hot dry season. While climate change and extreme weather events especially stress systems supporting vulnerable populations such as young children, maintaining strong and consistent public health interventions helps to reduce negative health impacts.
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This paper describes the development and testing of a simple local seasonal forecast system of rainfall and hydrological conditions. The primary target group is agricultural extension officers who communicate forecasts to small-scale farmers at local level. Two pilot areas within the Limpopo river basin in South Africa were used, one in the Luvuvhu river basin in Vhembe district and the other in the Letaba river basin in Mopani district. Local rainfall and hydrological forecasts of runoff, soil moisture and evapotranspiration were produced, built on readily available deterministic seasonal meteorological forecasts for large-scale rainfall from CSIR (Council for Scientific and Industrial Research, South Africa), produced from an ensemble of seasonal forecasts using the CCAM (Conformal-Cubic Atmospheric Model) global forecast model. Hydrological forecasts were produced through a “proxy” approach, whereby outputs from the ACRU (Agricultural Catchment Research Unit) agrohydrological model provided expected hydrological responses from observed years that are representative of the rainfall anomalies predicted by the global seasonal forecast. Locally monitored soil moisture augmented the hydrological forecasts. The local seasonal forecast system does not require sophisticated calculations or a complex operational environment and complements coarser scale forecasts disseminated by the provincial departments of agriculture. Results of three rainfall seasons from 2013 to 2016 in the pilot areas showed the proxy approach to have relatively good matches between forecasts and available observations, showing better predictability for below normal rainfall seasons with exception for an extreme monthly rainfall event. The forecasts matched observed conditions best during the strong El Niño phase of ENSO (El Niño Southern Oscillation) for 2015/2016.
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Consistent and reliable climate observations for Southern Africa are an important source of information for climate service-related activities. Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) supported the cooperation among the national meteorological services of Angola, Botswana, Germany, and Zambia to improve the management of observed climate data in the region. This cooperation allowed the stablisation of a climate data management system in which CLIMSOFT, a freely available software suite for storing climate data, is the main component. Additional open-source applications have been developed to provide an easy-to-use interface to visualize, download, digitize, and import climate data from and into CLIMSOFT. Besides that, substantial progress in the storage, quality control, and management of present and historical climate data recorded in paper media has been achieved. The measures taken were accompanied by continuous training and support to ensure the long-term maintenance of the new data management.
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Automatic weather stations (AWSs) serve a number of goals in the SASSCAL context and beyond. A sufficient cover and density in geographical space is needed to record spatial climatic variability and to feed climate models and forecast services. In addition, research projects using an ecosystem approach require robust information on local weather. In response to these goals and under consideration of the low density of climate stations in the SASSCAL region (Angola, Botswana, Namibia, South Africa, and Zambia), the establishment of a network of weather stations was initiated in 2009–2010. The SASSCAL network, meanwhile, includes 154 AWSs and has achieved a reputation for providing unprecedented progress in terms of coverage and access to climatic data for the SASSCAL region. This paper presents the most important strategic and technical steps, from setting up the station network for data transmission and data quality controls to the Internet publication of the SASSCAL WeatherNet climatic data.
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Subsistence farming in southern Africa is vulnerable to extreme weather conditions. The yield of rain-fed agriculture depends largely on rainfall-related factors such as total seasonal rainfall, anomalous onsets and lengths of the rainy season and the frequency of occurrence of dry spells. Livestock, in turn, may be seriously impacted by climatic stress with, for example, exceptionally hot days, affecting condition, reproduction, vulnerability to pests and pathogens and, ultimately, morbidity and mortality. Climate change may affect the frequency and severity of extreme weather conditions, impacting on the success of subsistence farming. A potentially interesting adaptation measure comprises the timely forecasting and warning of such extreme events, combined with mitigation measures that allow farmers to prepare for the event occurring. This paper investigates how the frequency of extreme events may change in the future due to climate change over southern Africa and, in more detail, the Limpopo Basin using a set of climate change projections from several regional climate model downscalings based on an extreme climate scenario. Furthermore, the paper assesses the predictability of these indicators by seasonal meteorological forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system. The focus is on the frequency of dry spells as well as the frequency of heat stress conditions expressed in the temperature heat index. In areas where their frequency of occurrence increases in the future and predictability is found, seasonal forecasts will gain importance in the future, as they can more often lead to informed decision-making to implement mitigation measures. The multi-model climate projections suggest that the frequency of dry spells is not likely to increase substantially, whereas there is a clear and coherent signal among the models of an increase in the frequency of heat stress conditions by the end of the century. The skill analysis of the seasonal forecast system demonstrates that there is a potential to adapt to this change by utilizing the weather forecasts, given that both indicators can be skilfully predicted for the December–February season, at least 2 months ahead of the wet season. This is particularly the case for predicting above-normal and below-normal conditions. The frequency of heat stress conditions shows better predictability than the frequency of dry spells. Although results are promising for end users on the ground, forecasts alone are insufficient to ensure appropriate response. Sufficient support for appropriate measures must be in place, and forecasts must be communicated in a context-specific, accessible and understandable format.
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The skill in predicting intraseasonal characteristics of synoptic type occurrences at the seasonal time scale over the all-year rainfall region of South Africa (35°–33°S and 21°–27°E) is assessed by utilizing an ensemble of simulations performed using the GloSea5 coupled ocean–atmosphere model. Hindcasts of daily sea-level pressure fields of 14 austral spring [September–October–November (SON)] and summer [December–January–February (DJF)] seasons, initialized in August and November, respectively, are analysed. The skill assessment is achieved through the use of self-organizing maps. Deterministic and probabilistic assessment of synoptic type frequency forecasts indicate that intraseasonal circulation variability over the Cape south coast region is marginally predictable at seasonal time scales, more so during SON than DJF. In particular, the results obtained demonstrate that there is potential for the skillful seasonal prediction of the anomalous frequency of occurrence of high-impact rainfall events associated with cut-off lows within SON seasons.
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Regional climate modelling was used to produce high resolution climate projections for Africa, under a "business as usual scenario", that were translated into potential health impacts utilizing a heat index that relates apparent temperature to health impacts. The continent is projected to see increases in the number of days when health may be adversely affected by increasing maximum apparent temperatures (AT) due to climate change. Additionally, climate projections indicate that the increases in AT results in a moving of days from the less severe to the more severe Symptom Bands. The analysis of the rate of increasing temperatures assisted in identifying areas, such as the East African highlands, where health may be at increasing risk due to both large increases in the absolute number of hot days, and due to the high rate of increase. The projections described here can be used by health stakeholders in Africa to assist in the development of appropriate public health interventions to mitigate the potential health impacts from climate change.
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An analysis of observed trends in African annual-average near-surface temperatures over the last five decades reveals drastic increases, particularly over parts of the subtropics and central tropical Africa. Over these regions, temperatures have been rising at more than twice the global rate of temperature increase. An ensemble of high-resolution downscalings, obtained using a single regional climate model forced with the sea-surface temperatures and sea-ice fields of an ensemble of global circulation model (GCM) simulations, is shown to realistically represent the relatively strong temperature increases observed in subtropical southern and northern Africa. The amplitudes of warming are generally underestimated, however. Further warming is projected to occur during the 21st century, with plausible increases of 4–6 °C over the subtropics and 3–5 °C over the tropics by the end of the century relative to present-day climate under the A2 (a low mitigation) scenario of the Special Report on Emission Scenarios. High impact climate events such as heat-wave days and high fire-danger days are consistently projected to increase drastically in their frequency of occurrence. General decreases in soil-moisture availability are projected, even for regions where increases in rainfall are plausible, due to enhanced levels of evaporation. The regional dowscalings presented here, and recent GCM projections obtained for Africa, indicate that African annual-averaged temperatures may plausibly rise at about 1.5 times the global rate of temperature increase in the subtropics, and at a somewhat lower rate in the tropics. These projected increases although drastic, may be conservative given the model underestimations of observed temperature trends. The relatively strong rate of warming over Africa, in combination with the associated increases in extreme temperature events, may be key factors to consider when interpreting the suitability of global mitigation targets in terms of African climate change and climate change adaptation in Africa.
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A major task of the newly established "Southern African Science Service Centre for Climate Change and Adaptive Land Management" (SASSCAL; www.sasscal.org) and its partners is to provide science-based environmental information and knowledge which includes the provision of consistent and reliable climate data for Southern Africa. Hence, SASSCAL, in close cooperation with the national weather authorities of Angola, Botswana, Germany and Zambia as well as partner institutions in Namibia and South Africa, supports the extension of the regional meteorological observation network and the improvement of the climate archives at national level. With the ongoing rehabilitation of existing weather stations and the new installation of fully automated weather stations (AWS), altogether 105 AWS currently provide a set of climate variables at 15, 30 and 60 min intervals respectively. These records are made available through the SASSCAL WeatherNet, an online platform providing near-real time data as well as various statistics and graphics, all in open access. This effort is complemented by the harmonization and improvement of climate data management concepts at the national weather authorities, capacity building activities and an extension of the data bases with historical climate data which are still available from different sources. These activities are performed through cooperation between regional and German institutions and will provide important information for climate service related activities.
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Multi-decadal regional projections of future climate change are introduced into a linear statistical model in order to produce an ensemble of austral mid-summer maximum temperature simulations for southern Africa. The statistical model uses atmospheric thickness fields from a high-resolution (0.5° x 0.5°) reanalysis-forced simulation as predictors in order to develop a linear recalibration model which represent the relationship between atmospheric thickness fields and gridded maximum temperatures across the region. The regional climate model, the conformal-cubic atmospheric model (CCAM), projects maximum temperatures increases over southern Africa to be in the order of 4°C under low mitigation towards the end of the century, or even higher. The statistical recalibration model is able to replicate these increasing temperatures and the atmospheric thickness – maximum temperature relationship is shown to be stable under future climate conditions. Since dry-land crop yields are not explicitly simulated by climate models but are sensitive to maximum temperature extremes, the effect of projected maximum temperature change on dry-land crops of the Witbank maize production district of South Africa, assuming other factors remain unchanged, is then assessed by employing a statistical approach similar to the one used for maximum temperature projections.