36

3.2.2. Precipitation

Figure 3.6, Figure 3.7, and Figure 3.8 compare the precipitation between the

baseline and future periods for Q0, Q2, and Q6 respectively. As can be seen,

there is a consensus among the three scenarios on rainfall reduction over the

Mediterranean shores during winter. The differences between the three

scenarios are generally small.

37

Baseline Future

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Figure 3.6 Simulated Baseline and Future Mean Monthly Precipitation for (mm/month) Q0 White areas are off-scale (> 300 mm/month)

39

Baseline Future

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Figure 3.7 Simulated Baseline and Future Mean Monthly Precipitation (mm/month) for Q2 White areas are off-scale (> 300 mm/month)

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Baseline Future

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Figure 3.8 Simulated Baseline and Future Mean Monthly Precipitation (mm/month) for Q6 White areas are off-scale (> 300 mm/month)

43

3.2.3. Potential Evapotranspiration

Figure 3.9, Figure 3.10, and Figure 3.11 compare PET between the baseline and

future periods for Q0, Q2, and Q6 respectively. There is a consensus among the

three scenarios on PET over the Arab region especially during summer. The

differences between the three scenarios are generally small.

44

Baseline Future

Jan

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F

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Figure 3.9 Simulated Baseline and Future Mean Monthly PET (mm/month) for Q0

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Baseline Future

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Figure 3.10 Simulated Baseline and Future Mean Monthly PET (mm/month) for Q2

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Baseline Future

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Figure 3.11 Simulated Baseline and Future Mean Monthly PET (mm/month) for Q6

50

3.2.4. Actual Evaporation

3.2.5. Runoff

51

4. Conclusions and Recommendations

This report presented an approach to develop detailed climate change scenarios

for the Arab region. The report documented the process of developing the

scenarios and presented a preliminary analysis of the changes over the Arab

region. This study represents the first application and analysis of a novel

perturbed physics ensemble approach using regional models for the Arab region.

While the development of this regional climate model represents a major step

forward, further work is required to understand the behaviour of the climate

system as represented by the regional climate ensembles. This may also provide

a deeper physical understanding of the differences between the UK Met Office

and IPCC ensembles.

The current scientific recommendation is not to rely on a single “best” model but

to ensure that a number of models are used to encompass the full range of

possible future climates and base decisions on being able to robustly

accommodate this variation. To ensure a better characterisation of the

uncertainty, it is recommended that the current work is extended to a larger

ensemble that is comparable to the IPCC ensemble (approx. 13-20 members).

This would also strengthen the validity of the results obtained to date. While

future work should definitely include the extension of this work to include

additional ensemble members, additional GCM-RCM combinations, additional

SRES emission scenarios and RCP scenarios and extension of the projections to

2100 should also be considered.

This ensemble-based probabilistic approach to regional climate modelling paves

the way for a probabilistic or risk-based approach to water resources

management. The uncertainty in climate projections should be accepted as part

of integrated water resources planning process based on a range of projections

and scenarios. Current practice is to assume these are equally likely to derive a

statistical interpretation. The advantage of this risk-based approach is that

52

climate change risks can be treated alongside other risks. This approach is

recommended, for example, by the EU for including climate change in context of

the Water Framework Directive.

Integration of these results with results from other regional climate models based

on the same or other GCMs and emission scenario combinations will allow better

characterization of uncertainty cascade. Thus, this study would complement

rather than replicate other studies using other downscaling methods including

other RCMs.

The provided scenarios also pave the way for hydrological impact analysis for the

region. Rainfall and PET data can be inputs for hydrological models either at the

basin-scale (for some of the region main basins such as the Nile, Euphrates,

etc.) or at the region scale if a distributed model of the region (such as VIC) is to

be constructed for the region. The variables presented can help also in assessing

impacts on agriculture, on water demands, and on several other sectors,

especially those related to water resources. Some of the variables (e.g. runoff

and evaporation) can be compared to hydrological model outputs and can be

used to validate and improve the RCM itself.

53

References

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Buontempo, C. et al., 2010. The impact of uncertainties in climate impacts assessments: the case of the Nile basin. In: H.G. Brauch et al. (Editors), Coping with Global Environmental Change, Disasters and Security – Threats, Challenges, Vulnerabilities and Risks. Hexagon Series on Human, Environmental Security and Peace (HESP). Springer-Verlag (in press), Berlin – Heidelberg – New York.

Elshamy, M.E., Sayed, M.A.-A. and Badwy, B., 2009. Impacts of climate change on Nile flows at Dongola using statistically downscaled GCM scenarios. Nile Water Science & Engineering Magazine, 2(Special issue on Water & Climate): 1-14.

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