The observed climate and future projected climate change for the Lamu Seascape is represented by the weather station at Lamu. This station provides precipitation data for the period 1979 – 2000.
OBSERVED CLIMATE ANA LYSIS
RESULTS – PRECIPITATION
Explanation of observed climate plots – Precipitation.
Wide bars indicate the median monthly rainfall for the climate period. Narrow bars indicate the
10 th and 90 th percentile range of monthly rainfall for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).
Figure A.1: Annual cycle of monthly rainfall (mm) for Lamu station.

Figure A.2: Annual cycle of monthly mean dry spell duration for Lamu station.
Figure A.3: Annual cycle of monthly rain days > 0.5 mm (days) for Lamu station.
Figure A.4: Annual cycle of monthly rain days > 10 mm (days) for Lamu station.
Figure A.5: Annual cycle of monthly rain days > 90th percentile for Lamu (90th percentile = 25.2 mm).
OBSERVED CLIMATE DISCUSSION
The Lamu station has a tropical climate which is modulated by its location on the coast. It experiences bimodal rains with the long rains occurring from April - June and short rains from November to December.
The dry spell duration is short throughout the year with the exception of the main dry season (January –
March) where long durations between rain events are evident during some years, however this interannual variability may be exaggerated due to errors within the data. The long rains experience more

frequent and intense rainfall than the short rains, with heavy (> 10mm) and extreme rainfall (> 90 th percentile) being experienced most often during May.
FUTURE CLIMATE ANALYSIS
CLIMATE PROJECTIONS - PRECIPITATION
Explanation of climate projection plots – Precipitation
Top panel - climatologies: Grey bars indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red bars indicate the same but for the future period multimodel projections (2046-2065).
Bottom panel – anomalies: Wide bars indicate the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a solid black line.
Figure A.6: Change in monthly total rainfall for Lamu station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure A.7: Change in monthly mean dry spell duration for Lamu station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure A.8: Change in monthly rain day frequency > 0.5 mm Lamu station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure A.9: Change in monthly rain day > 10mm frequency for Lamu station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure A.10: Change in monthly rain days above the 90th percentile of observed record for Lamu station (90th percentile = 25.2 mm) under
SRES A2 (left) and SRES B1 (right) emission scenario.
PROJECTED CHANGES DISCUSSION
The most robust projected change in precipitation is found between June and August where monthly total rainfall is projected to decrease. Models generally project an increase in rain day frequency from
November through to April, with most positive change in extreme rainfall occurring in October and
November, with a decrease between June to September for all types of rainfall frequency. A decrease in the dry spell duration during the dry season (January – April) is shown for most models suggesting that the period between rain events may increase into the future.

The observed climate and future projected climate change for the Kwale – East Usambara Landscape are represented by the weather stations at Monbasa and Tanga. The Mombasa station provides daily minimum and maximum temperature and precipitation for the period 1957-2003, while the Tanga station only provides daily precipitation data (1979-2000). Large gaps in the records and the low quality of the records make these records unsuitable for trend analysis to be performed for this region.
OBSERVED CLIMATE ANA LYSIS
RESULTS - PRECIPITATION
Explanation of observed climate plots – Precipitation.
Wide bars indicate the median monthly rainfall for the climate period. Narrow bars indicate the
10 th and 90 th percentile range of monthly rainfall for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).
Figure B.1: Annual cycle of monthly rainfall (mm) for Mombasa (left) and Tanga (right) stations.

Figure B.2: Annual cycle of monthly mean dry spell duration for Mombasa (left) and Tanga (right) stations.
Figure B.3: Annual cycle of monthly rain days > 0.5 mm (days) for Mombasa (left) and Tanga (right) stations.
Figure B.4: Annual cycle of monthly rain days > 10 mm (days) for Mombasa (left) and Tanga (right) stations.
Figure B.5: Annual cycle of monthly rain days > 90th percentile for Mombasa (90th percentile = 25.7 mm) (left) and Tanga (90th percentile =
24.0 mm)(right).

RESULTS – TEMPERATURE
Explanation of observed climate plots – Temperature.
Dashed line indicates the median monthly value for the climate period. The blue envelope indicates the 10 th and 90 th percentile range of the monthly values for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).
Figure B.6: Annual cycle of monthly mean maximum daily temperatures (deg C) for Mombasa (left) and TANGA (right) stations.
Figure B.7: Annual cycle days/month exceeding 32 deg C for Mombasa (left) and TANGA (right) stations.
Figure B.8: Annual cycle of monthly mean minimum daily temperatures (deg C) for Mombasa (left) and TANGA (right) stations.

OBSERVED CLIMATE DISCUSSION
The Mombasa and Tanga stations have a tropical climate which is modulated by their proximity to the coast. They experience bimodal rains centered on April - June (‘long’ rains) and October to December
(‘short’ rains) with a core dry season from January to March. Light rainfall occurs from March –
December, but heavy and extreme rainfall is restricted to the long and short rains. Temperatures are warm with low diurnal and interseasonal variability. The warmest temperatures occur during March where more than half of the days exce ed 32°C and coolest temperatures occur around August.
FUTURE CLIMATE ANALYSIS
CLIMATE PROJECTIONS - PRECIPITATION
Explanation of climate projection plots – Precipitation
Top panel - climatologies: Grey bars indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red bars indicate the same but for the future period multimodel projections (2046-2065).
Bottom panel – anomalies: Wide bars indicate the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a solid black line.

FigureB.9: Change in monthly total rainfall for Mombasa stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure B.10: Change in monthly total rainfall for Tanga stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure B.11: Change in monthly mean dry spell duration for Mombasa stations under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure B.12: Change in monthly mean dry spell duration for Tanga stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure B.13: Change in monthly rain day frequency > 0.5 Mombasa stations under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure B.14: Change in monthly rain day frequency > 0.5 for Tanga stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure B.15: Change in monthly rain day > 10mm frequency for Mombasa stations under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure B.16: Change in monthly rain day > 10mm frequency for Tanga stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure B.17: Change in monthly rain days above the 90th percentile of observed record for Mombasa station (90th percentile = 25.7 mm) under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure B.18: Change in monthly rain days above the 90th percentile of observed record for Tanga station (90th percentile = 24.0 mm) under
SRES A2 (left) and SRES B1 (right) emission scenario.
CLIMATE PROJECTIONS - TEMPERATURE
Explanation of climate projection plots – Temperature
Top panel - climatologies: Grey envelope indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red envelope indicate the same but for the future period multi-model projections (2046-2065).
Bottom panel – anomalies: Blue envelope indicate the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a dashed black curve.

Figure B.19: Change in monthly mean maximum daily temperature (deg C) for Mombasa station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure B.20: Change in monthly mean maximum daily temperature (deg C) for Tanga station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure B.21: Change in monthly days exceeding 32 deg C for Mombasa under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure B.22 Change in monthly days exceeding 32 deg C for Tanga under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure B.23 Change in monthly mean minimum daily temperature (deg C) for Mombasa station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure B.24: Change in monthly mean minimum daily temperature (deg C) for Tanga station under SRES A2 (left) and SRES B1 (right) emission scenario.
PROJECTED CHANGES DISCUSSION
The most robust message is for a decrease in rainfall during the short dry season and for a small but robust increase in rainfall from November – February. Dry spell duration is projected to decrease during main dry season though the confidence is quite low. Rainfall frequency is generally projected to decrease between June – September, with a general increase during the rest of the year. Both minimum and ma ximum temperatures are projected to increase into the future by roughly 2° C under the SRES A2

scenario and by 1.5° C under the SRESB1 scenario. The number of days on which the temperature exceeds 32° C is projected to increase significantly so that most days between December and March exceed this threshold. The largest change is projected to occur during May and November.

The observed climate and future projected climate change for the Udzungwa Landscape is represented by the weather station at Iringa. This station provides precipitation data for the period 1960 – 1990.
OBSERVED CLIMATE ANA LYSIS
RESULTS - PRECIPITATION
Explanation of observed climate plots – Precipitation.
Wide bars indicate the median monthly rainfall for the climate period. Narrow bars indicate the
10 th and 90 th percentile range of monthly rainfall for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).
Figure C.1: Annual cycle of monthly rainfall (mm) for Iringa station.
Figure C.2: Annual cycle of monthly mean dry spell duration for Iringa station.

Figure C.3: Annual cycle of monthly rain days > 0.5 mm (days) for Iringa station.
Figure C.4: Annual cycle of monthly rain days > 10 mm (days) for Iringa station.
Figure C.5: Annual cycle of monthly rain days > 90th percentile for Iringa (90th percentile = 22.5 mm).
OBSERVED CLIMATE DISCUSSION
The Iringa station is found at high elevation in central Tanzania. Even though it is located within the tropics, the rainfall record shows a single rainfall season between December and April instead of the typical bimodal cycle.

FUTURE CLIMATE ANALYSIS
CLIMATE PROJECTIONS - PRECIPITATION
Explanation of climate projection plots – Precipitation
Top panel - climatologies: Grey bars indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red bars indicate the same but for the future period multimodel projections (2046-2065).
Bottom panel – anomalies: Wide bars indicate the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a solid black line.
Figure C.6: Change in monthly total rainfall for Iringa station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure C.7: Change in monthly mean dry spell duration for Iringa station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure C.8: Change in monthly rain day frequency > 0.5 mm Iringa station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure C.9: Change in monthly rain day > 10mm frequency for Iringa station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure C.10: Change in monthly rain days above the 90th percentile of observed record for Iringa station (90th percentile = 22.5 mm) under
SRES A2 (left) and SRES B1 (right) emission scenario.
PROJECTED CHANGES DISCUSSION
The downscaled results suggest a slight increase in frequency and intensity of rainfall during the mid to late rainy season (January – March) and a clear increase in the average number of days between rain events during the dry season (May – October).

The observed climate and future projected climate change for the Rumaki and Matumbi Hill Sea and
Landscape is represented by the weather station at Dar es Salaam, since it is the closest station to the study area. This station provides daily minimum and maximum temperature and precipitation data for the period 1958 – 2000. The quality of the record deteriates after 1990 and therefore trends were only undertaken for the period 1958-1990.
OBSERVED CLIMATE ANA LYSIS
RESULTS – PRECIPITATION
Explanation of observed climate plots – Precipitation.
Wide bars indicate the median monthly rainfall for the climate period. Narrow bars indicate the
10 th and 90 th percentile range of monthly rainfall for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).
Figure D.1: Annual cycle of monthly rainfall (mm) for Dar Es Salaam station.

Figure D.2: Decadal trend of monthly rainfall (mm/decade) for Dar Es Salaam station.
Figure D.3: Annual cycle of monthly mean dry spell duration for Dar Es Salaam station.
Figure D.4: Decadal trend of monthly mean dry spell duration (days/decade) for Dar Es Salaam and Beira (right) stations.
Figure D.5: Annual cycle of monthly rain days > 0.5 mm (days) for Dar Es Salaam station.

Figure D.6: Decadal trend of monthly rain days > 0.5 mm (days/decade) for Dar Es Salaam station.
Figure D.7: Annual cycle of monthly rain days > 10 mm (days) for Dar Es Salaam station.
Figure D.8: Decadal trend of monthly rain days > 10 mm (days/decade) for Dar Es Salaam station.
Figure D.9: Annual cycle of monthly rain days > 90th percentile for Dar Es Salaam (90th percentile = 29.0 mm) (left) and Beira (90th percentile = 38.0 mm)(right).

Figure D.10: Decadal trend of monthly rain days > 90th percentile for (days/decade) Dar Es Salaam (90th percentile = 29.0 mm) (left) and
Beira (90th percentile = 38.0 mm)(right).
RESULTS - TEMPERATURE
Explanation of observed climate plots – Temperature.
Dashed line indicates the median monthly value for the climate period. The blue envelope indicates the 10 th and 90 th percentile range of the monthly values for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).
Figure D.11: Annual cycle of monthly mean maximum daily temperatures (degC) for Dar Es Salaam station.
Figure D.12: Decadal trend of monthly mean maximum daily temperatures (degC/decade) for Dar Es Salaam station.

Figure D.13: Annual cycle days/month exceeding 32 deg C for Dar Es Salaam station.
Figure D.14: Decadal trend in days/month exceeding 32 deg C for Dar Es Salaam station.
Figure D.15: Annual cycle of monthly mean minimum daily temperatures (degC/decade) for Dar Es Salaam station.
Figure D.16: Annual cycle of monthly mean minimum daily temperatures (degC) for Dar Es Salaam station.

OBSERVED CLIMATE DISCUSSION
Dar es Salaam features a tropical climate which is modulated by its location on the coast. It experiences bimodal rains with the long rains occurring from March – May and the short rains from November –
December. Dry spells between rain events is generally short since light rain occurs throughout the year, but heavy and extreme rainfall are restricted to the two peak rain seasons. The rainfall trends are complex, but do suggestion that the frequency and intensity of rainfall is generally decreasing, while the tails of the rainy seasons are getting wetter.
Temperatures are warm with low diurnal and interseasonal variability. The warmest temperatures occur during February – March, where on average half the days exceed 32°C, while the coolest temperatures occur in July and August. Generally negative trends are found in the maximum temperature and the number of days exceeding 32°C with the largest trends occurring during the peak of the two rain seasons.
A positive trend is found in minimum temperature throughout the year but is strongest during the first half when minimum temperatures are higher.
CLIMATE CHANGE ANALYSIS
CLIMATE PROJECTIONS - PRECIPITATION
Explanation of climate projection plots – Precipitation
Top panel - climatologies: Grey bars indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red bars indicate the same but for the future period multimodel projections (2046-2065).
Bottom panel – anomalies: Wide bars indicate the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a solid black line.

Figure D.17: Change in monthly total rainfall for Dar Es Salaam station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure D.18: Change in monthly mean dry spell duration for Dar Es Salaam station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure D.19: Change in monthly rain day frequency > 0.5 mm Dar Es Salaam station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure D.20: Change in monthly rain day > 10mm frequency for Dar Es Salaam station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure D.21: Change in monthly rain days above the 90th percentile of observed record for Dar Es Salaam station (90th percentile = 29.0 mm) under SRES A2 (left) and SRES B1 (right) emission scenario.
CLIMATE PROJECTIONS - TEMPERATURE
Explanation of climate projection plots – Temperature
Top panel - climatologies: Grey envelope indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red envelope indicates the same but for the future period multi-model projections (2046-2065).
Bottom panel – anomalies: Blue envelope indicates the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a dashed black curve.

Figure D.22: Change in monthly mean maximum daily temperature (deg C) for Dar Es Salaam station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure D.23: Change in monthly days exceeding 32 deg C (days) for Dar Es Salaam

Figure D.24: Change in monthly mean minimum daily temperature (deg C) for Dar Es Salaam station under SRES A2 (left) and SRES B1 (right) emission scenario.
PROJECTED CHANGES DISCUSSION
The downscaled results suggest a decrease in rainfall during the main dry season (June – October) and an increase during the rest of the year. Rain day frequency shows the same general tendency and is associated with an increase in dry spell duration during the dry season. Both minimum and maximum temperatures are projected to increase into the future by roughly 2° C under the SRES A2 scenario and by 1.5° C under the SRESB1 scenario. The number of days on which the temperature exceeds 32° C is projected to increase significantly with the largest change projected to occur during October which might be linked to the delay in the onset of the short rains.

The Greater Ruvuma Landscape covers a large geographic and does not represent a unified climatic zone. The observed climate and future projected climate change for this region is represented by the weather stations at Lichinga and Songea, since these are the only two stations which met the data quality standards. These stations are located in the more mountainous terrain in the far west of the study area and therefore do not provide the most representative climate for the whole landscape. The Songea station provides daily data for the period 1979-2000, while the Lichinga station record extends from 1951-
1990 and meets the data quality requirement for trend analysis to be performed.
OBSERVED CLIMATE ANALYSIS
RESULTS - PRECIPITATION
Explanation of observed climate plots – Precipitation.
Wide bars indicate the median monthly rainfall for the climate period. Narrow bars indicate the
10 th and 90 th percentile range of monthly rainfall for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).

Figure E.1: Annual cycle of monthly rainfall (mm) for Lichinga (left) and Songea (right) stations.
Figure E.2: Decadal trend of monthly rainfall (mm/decade) for Lichinga station.
Figure E.3: Annual cycle of monthly mean dry spell duration for Lichinga (left) and Songea (right) stations.
Figure E.4: Decadal trend of monthly mean dry spell duration (days/decade) for Lichinga station.

Figure E.5: Annual cycle of monthly rain days > 0.5 mm (days) for Lichinga (left) and Songea (right) stations.
Figure E.6: Decadal trend of monthly rain days > 0.5 mm (days/decade) for Lichinga station.
Figure E.7: Annual cycle of monthly rain days > 10 mm (days) for Lichinga (left) and Songea (right) stations.
Figure E.8: Decadal trend of monthly rain days > 10 mm (days/decade) for Lichinga station.

Figure E.9: Annual cycle of monthly rain days > 90th percentile for Lichinga (90th percentile = 25.1 mm) (left) and Songea (90th percentile =
28.5 mm) (right).
Figure E.10: Decadal trend of monthly rain days > 90th percentile (days/decade) for Lichinga (90th percentile = 25.1 mm).
RESULTS - TEMPERATURE
Explanation of observed climate plots – Temperature.
Dashed line indicates the median monthly value for the climate period. The blue envelope indicates the 10 th and 90 th percentile range of the monthly values for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).

Figure E.11: Annual cycle of monthly mean maximum daily temperatures (degC) for Lichinga (left) and Songea (right) stations.
Figure E.12: Decadal trend of monthly mean maximum daily temperatures (degC/decade) for Lichinga station.
Figure E.13: Annual cycle days/month exceeding 32 deg C for Lichinga (left) and Songea (right) stations.
Figure E.14: Decadal trend in days/month exceeding 32 deg C for Lichinga station.

Figure E.15: Annual cycle of monthly mean minimum daily temperatures (degC/decade) for Lichinga (left) and Songea (right) stations.
Figure E.16: Annual cycle of monthly mean minimum daily temperatures (degC) for Lichinga station.
OBSERVED CLIMATE DISCUSSION
The two stations within the Greater Ruvuma Landscape are found within the tropics however their climates are modulated by their location far inland and at higher attitude than the rest of the study area.
The stations experience a single rainy season during summer from November to April and a clear dry season during the winter months. Rainfall is higher and more frequent in the Lichinga station than the
Songea. Rainfall trends are presented for Lichinga and suggest an expansion of the rainy season with positive trends in March, October and November for both frequency and intensity of rainfall. There is also a positive trend in the dry spell duration from June to September.
The temperatures of these stations are lower than the other stations and probably the rest of the Greater
Ruvuma Landscape, with very few days exceeding the 32° C threshold.. Maximum daytime temperatures are found at the beginning of summer (October –November) before they peak of the rainy season, while the lowest maximum temperatures are found in July. Highest minimum temperatures are found throughtout summer (November – April, but decrease during the core of the winter. Trend analysis of the
Lichinga station record shows a negative trend in maximum and minimum temperatures during October and November which may be associated with the increase trend in rainfall a during this time.

FUTURE CLIMATE ANALYSIS
CLIMATE PROJECTIONS - PRECIPITATION
Explanation of climate projection plots – Precipitation
Top panel - climatologies: Grey bars indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red bars indicate the same but for the future period multimodel projections (2046-2065).
Bottom panel – anomalies: Wide bars indicate the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a solid black line.
Figure E.17: Change in monthly total rainfall for Lichinga stations under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure E.18: Change in monthly total rainfall for Songea stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure E.19: Change in monthly mean dry spell duration for Lichinga stations under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure E.20: Change in monthly mean dry spell duration for Songea stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure E.21: Change in monthly rain day frequency > 0.5 mm Lichinga stations under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure E.22: Change in monthly rain day frequency > 0.5 mm for Songea stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure E.23: Change in monthly rain day > 10mm frequency for Lichinga stations under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure E.24: Change in monthly rain day > 10mm frequency for Songea stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure E.25: Change in monthly rain days above the 90th percentile of observed record for Lichinga station (90th percentile = 25.1 mm) under
SRES A2 (left) and SRES B1 (right) emission scenario.

Figure E.26: Change in monthly rain days above the 90th percentile of observed record for Songea station (90th percentile = 28.5 mm) under
SRES A2 (left) and SRES B1 (right) emission scenario.
CLIMATE PROJECTIONS - TEMPERATURE
Explanation of climate projection plots – Temperature
Top panel - climatologies: Grey envelope indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red envelope indicate the same but for the future period multi-model projections (2046-2065).
Bottom panel – anomalies: Blue envelope indicate the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a dashed black curve.

Figure E.27: Change in monthly mean maximum daily temperature (deg C) for Lichinga station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure E.28: Change in monthly mean maximum daily temperature (deg C) for Songea station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure E.29: Change in monthly days exceeding 32 deg C for Lichinga station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure E.30: Change in monthly days exceeding 32 deg C for Songea station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure E.31: Change in monthly mean minimum daily temperature (deg C) for Lichinga station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure E.32: Change in monthly mean minimum daily temperature (deg C) for Songea station under SRES A2 (left) and SRES B1 (right) emission scenario.
PROJECTED CHANGES DISCUSSION
The downscaling results suggest a decrease in the start of the rainy season (October – December). A decrease in the frequency of rain days is projected during the shoulder seasons which is supported by the projected lengthening of the number of days between rain events during winter and spring (especially for the Songea station under the SRESA2 scenario). Maximum daily temperatures are projected to increase by b etween 2 and 2.5°C with the largest warming occurring during the warmest months (October and

November). Days where the maximum temperature exceeds 32° C are rare in the current climate but are projected to increase by up to 8 days / month in Songea under the SRESA2 scenario.
The observed climate and future projected climate change for the Mtwara – Quirimbus Complex is represented by the weather station at Mtwara. This station provides precipitation data for the period 1957
– 2000, however the quality of the record deteriorates after 1990 and therefore trends were only undertaken for the period 1957-1990.
OBSERVED CLIMATE ANA LYSIS
RESULTS - PRECIPITATION
Explanation of observed climate plots – Precipitation.
Wide bars indicate the median monthly rainfall for the climate period. Narrow bars indicate the
10 th and 90 th percentile range of monthly rainfall for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).
Figure F.1: Annual cycle of monthly rainfall (mm) for Mtwara station.

Figure F.2: Decadal trend of monthly rainfall (mm/decade) for Mtwara station.
Figure F.3: Annual cycle of monthly mean dry spell duration for Mtwara station.
Figure F.4: Decadal trend of monthly mean dry spell duration (days/decade) for Mtwara and Beira (right) stations.
Figure F.5: Annual cycle of monthly rain days > 0.5 mm (days) for Mtwara station.

Figure F.6: Decadal trend of monthly rain days > 0.5 mm (days/decade) for Mtwara station.
Figure F.7: Annual cycle of monthly rain days > 10 mm (days) for Mtwara station.
Figure F.8: Decadal trend of monthly rain days > 10 mm (days/decade) for Mtwara station.
Figure F.9: Annual cycle of monthly rain days > 90th percentile for Mtwara (90th percentile = 29.2 mm) (left) and Beira (90th percentile =
38.0 mm)(right).

Figure F.10: Decadal trend of monthly rain days > 90th percentile for (days/decade) Mtwara (90th percentile = 29.2 mm) (left) and Beira
(90th percentile = 38.0 mm)(right).
OBSERVED CLIMATE DISCUSSION
The Mtwara station is located on the coast and experiences a tropical climate with summer rainfall occurring between December – April. Rainfall frequency and intensity is high throughout the summer, with extreme rainfall being most common during January. The rainfall trends are quite complex with months within the peak rainy season showing trends of alternating sign. The trend in dry spell duration shows a positive trend during winter associated with the decrease in the frequency of rain events during this time.
Of all months, February shows the strongest trend (negative) in both the frequency and intensity of rainfall.
FUTURE CLIMATE ANALYSIS
CLIMATE PROJECTIONS - PRECIPITATION
Explanation of climate projection plots – Precipitation
Top panel - climatologies: Grey bars indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red bars indicate the same but for the future period multimodel projections (2046-2065).
Bottom panel – anomalies: Wide bars indicate the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a solid black line.

Figure F.11: Change in monthly total rainfall for Mtwara station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure F.12: Change in monthly mean dry spell duration for Mtwara station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure F.13: Change in monthly rain day frequency > 0.5 mm Mtwara station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure F.14: Change in monthly rain day > 10mm frequency for Mtwara station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure F.15: Change in monthly rain days above the 90th percentile of observed record for Mtwara station (90th percentile = 29.2 mm) under
SRES A2 (left) and SRES B1 (right) emission scenario.
PROJECTED CHANGES DISCUSSION
The downscaling results suggest a decrease in the rainfall frequency and intensity during the start and end of the rainy season, and an increase in the core of the season (January – February). This is associated with an increase in the dry spell length during the dry season (May – October).

The observed climate and future projected climate change for the Primireas e Segundas Seascape is represented by the weather station at Lumbo. This station provides precipitation data for the period 1979-
2000.
HISTORICAL CLIMATE ANALYSIS
RESULTS - PRECIPITATION
Explanation of observed climate plots – Precipitation.
Wide bars indicate the median monthly rainfall for the climate period. Narrow bars indicate the
10 th and 90 th percentile range of monthly rainfall for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).
Figure G.1: Annual cycle of monthly rainfall (mm) for Lumbo station.

Figure G.2: Annual cycle of monthly mean dry spell duration for Lumbo station.
Figure G.3: Annual cycle of monthly rain days > 0.5 mm (days) for Lumbo station.
Figure G.4: Annual cycle of monthly rain days > 10 mm (days) for Lumbo station.
Figure G.5: Annual cycle of monthly rain days > 90th percentile for Lumbo (90th percentile = 28.0 mm).
OBSERVED CLIMATE DISCUSSION
The Lumbo station is located on the coast just to the north of the study area. The site experiences predominantly summer rainfall from November to April with maximum monthly rainfall averaging around
120 mm/month. Heavy and extreme rainfall is restricted to the summer months and dry spell duration is longest between September – November.

FUTURE CLIMATE ANALYSIS
CLIMATE PROJECTIONS - PRECIPITATION
Explanation of climate projection plots – Precipitation
Top panel - climatologies: Grey bars indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red bars indicate the same but for the future period multimodel projections (2046-2065).
Bottom panel – anomalies: Wide bars indicate the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a solid black line.
Figure G.6: Change in monthly total rainfall for Lumbo station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure G.7: Change in monthly mean dry spell duration for Lumbo station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure G.8: Change in monthly rain day frequency > 0.5 mm Lumbo station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure G.9: Change in monthly rain day > 10mm frequency for Lumbo station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure G.10: Change in monthly rain days above the 90th percentile of observed record for Lumbo station (90th percentile = 28.0 mm) under
SRES A2 (left) and SRES B1 (right) emission scenario.
PROJECTED CHANGES DISCUSSION
The downscaling results suggest a decrease in the rainfall frequency and intensity at the start of the rainy season and an increase during the core of the season (January – March). The length of time between rain events is projected to decrease during the first half of the dry season but increase toward the end of the season (October).

The observed climate and future projected climate change for the Delta of the Zambezi River and
Marromeu Complex is represented by the weather stations at Quelimane and Beira. Both station provide all three daily variables for the period 1951-1990 and are of sufficiently high quality that trend analysis was possible.
OBSERVED CLIMATE ANA LYSIS
RESULTS - PRECIPITATION
Explanation of observed climate plots – Precipitation.
Wide bars indicate the median monthly rainfall for the climate period. Narrow bars indicate the
10 th and 90 th percentile range of monthly rainfall for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).
Figure H.1: Annual cycle of monthly rainfall (mm) for Quelimane (left) and Beira (right) stations.

H.2: Decadal trend of monthly rainfall (mm/decade) for Quelimane (left) and Beira (right) stations.
Figure
Figure H.3: Annual cycle of monthly mean dry spell duration for Quelimane (left) and Beira (right) stations.
Figure H.4: Decadal trend of monthly mean dry spell duration (days/decade) for Quelimane and Beira (right) stations.
Figure H.5: Annual cycle of monthly rain days > 0.5 mm (days) for Quelimane (left) and Beira (right) stations.

Figure H.6: Decadal trend of monthly rain days > 0.5 mm (days/decade) for Quelimane (left) and Beira (right) stations.
Figure H.7: Annual cycle of monthly rain days > 10 mm (days) for Quelimane (left) and Beira (right) stations.
Figure H.8: Decadal trend of monthly rain days > 10 mm (days/decade) for Quelimane (left) and Beira (right) stations.

Figure H.9: Annual cycle of monthly rain days > 90th percentile for Quelimane (90th percentile = 32.4 mm) (left) and Beira (90th percentile =
38.0 mm)(right).
Figure H.10: Decadal trend of monthly rain days > 90th percentile (days/decade) for Quelimane (90th percentile = 32.4 mm) (left) and Beira
(90th percentile = 38.0 mm)(right).
RESULTS - TEMPERATURE
Explanation of observed climate plots – Temperature.
Dashed line indicates the median monthly value for the climate period. The blue envelope indicates the 10 th and 90 th percentile range of the monthly values for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).

Figure H.11: Annual cycle of monthly mean maximum daily temperatures (degC) for Quelimane (left) and Beira (right) stations.
Figure H.12: Decadal trend of monthly mean maximum daily temperatures (degC/decade) for Quelimane (left) and Beira (right) stations.
Figure H.13: Annual cycle days/month exceeding 32 deg C for Quelimane (left) and Beira (right) stations.
Figure H.14: Decadal trend in days/month exceeding 32 deg C for Quelimane (left) and Beira (right) stations.

Figure H.15: Annual cycle of monthly mean minimum daily temperatures (degC/decade) for Quelimane (left) and Beira (right) stations.
Figure H.16: Annual cycle of monthly mean minimum daily temperatures (degC) for Quelimane (left) and Beira (right) stations.
OBSERVED CLIMATE DISCUSSION
The Quelimane and Beira stations are located along the Mozambique coast within the summer rainfall region. Total monthly rainfall is high from December to March averaging around 200 mm/month. Rainfall is most frequent during summer, but light rainfall occurs throughout the year with a minimum during spring. Extreme rainfall is restricted to the core summer season. Rainfall trends are complex and differ between the two locations.
Temperatures are warm over these locations, though Beira is slightly cooler than Quelimane. A clear seasonal cycle is evident with warmest daytime temperatures occurring during summer and coolest temperatures in June and July. M aximum temperatures exceeding 32 °C occur more often for Quelimane than Beira with up to half of the days during January and February reaching this threshold. Minimum temperatures are mild with little interannual variability. Temperature trends for these two locations also show significant differences between locations. Quelimane shows negative trends in all months for both maximum and minimum temperature. While Beira shows generally positive trends.

FUTURE CLIMATE ANALYSIS
CLIMATE PROJECTIONS - PRECIPITATION
Explanation of climate projection plots – Precipitation
Top panel - climatologies: Grey bars indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red bars indicate the same but for the future period multimodel projections (2046-2065).
Bottom panel – anomalies: Wide bars indicate the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a solid black line.
Figure H.17: Change in monthly total rainfall for Quelimane stations under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure H.18: Change in monthly total rainfall for Beira stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure H.19: Change in monthly mean dry spell duration for Quelimane stations under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure H.20: Change in monthly mean dry spell duration for Beira stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure H.21: Change in monthly rain day frequency > 0.5 mm Quelimane stations under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure H.22: Change in monthly rain day frequency > 0.5 mm for Beira stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure H.23: Change in monthly rain day > 10mm frequency for Quelimane stations under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure H.24: Change in monthly rain day > 10mm frequency for Beira stations under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure H.25: Change in monthly rain days above the 90th percentile of observed record for Quelimane station (90th percentile = 32.4 mm) under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure H.26: Change in monthly rain days above the 90th percentile of observed record for Beira station (90th percentile = 38.0 mm) under
SRES A2 (left) and SRES B1 (right) emission scenario.
CLIMATE PROJECTIONS - TEMPERATURE
Explanation of climate projection plots – Temperature
Top panel - climatologies: Grey envelope indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red envelope indicates the same but for the future period multi-model projections (2046-2065).
Bottom panel – anomalies: Blue envelope indicates the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a dashed black curve.

Figure H.27: Change in monthly mean maximum daily temperature (deg C) for Quelimane station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure H.28: Change in monthly mean maximum daily temperature (deg C) for Beira station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure H.29: Change in monthly days exceeding 32 deg C for Quelimane station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure H.30: Change in monthly days exceeding 32 deg C for Beira station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure H.31: Change in monthly mean minimum daily temperature (deg C) for Quelimane station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure H.32: Change in monthly mean minimum daily temperature (deg C) for Beira station under SRES A2 (left) and SRES B1 (right) emission scenario.
PROJECTED CHANGES DISCUSSION
The downscaling results for this region are quite messy, with only a suggestion of a decrease in rainfall frequency and intensity during October and November and surprisingly to an increase during July. The frequency of light rain events is projected to increase during May to July. Both minimum and maximum temperatures are projected to increase into the future by roughly 2° C under the SRES A2 scenario and

by 1.5° C under the SRESB1 scenario. The number of days on which the temperature exceeds 32° C is projected to increase significantly especially from January to March.
The observed climate and future projected climate change for the Bazaruto Seascape is reporesented by the weather station record at Vilanculos. This station provides precipitation data for the period 1979 –
2000.
OBSERVED CLIMATE ANA LYSIS
RESULTS - PRECIPITATION
Explanation of observed climate plots – Precipitation.
Wide bars indicate the median monthly rainfall for the climate period. Narrow bars indicate the
10 th and 90 th percentile range of monthly rainfall for each month during the climate period.
Trends – Wide bars indicate the decadal trend for each month during the climate period (change per decade).
Figure I.1: Annual cycle of monthly rainfall (mm) for Vilanculos station.

Figure I.2: Annual cycle of monthly mean dry spell duration for Vilanculos station.
Figure I.3: Annual cycle of monthly rain days > 0.5 mm (days) for Vilanculos station.
Figure I.4: Annual cycle of monthly rain days > 10 mm (days) for Vilanculos station.

Figure I.5: Annual cycle of monthly rain days > 90th percentile for Vilanculos (90th percentile = 31.0 mm).
OBSERVED CLIMATE DISCUSSION
The Vilanculos station is located on the coast of Mozambique in the subtropics. The monthly total rainfall is low in relation to the other regions, however the interannual variability is very high suggesting that there may be errors remaining in the data. The rainy season extends from November to April, with maximum frequency and intensity occurring during February and March.
FUTURE CLIMATE ANALYSIS
CLIMATE PROJECTIONS - PRECIPITATION
Explanation of climate projection plots – Precipitation
Top panel - climatologies: Grey bars indicate the 10 th to 90 th percentile range of the control period multi-model climatologies (1961-2000). Red bars indicate the same but for the future period multimodel projections (2046-2065).
Bottom panel – anomalies: Wide bars indicate the 10 th and 90 th percentile range of the future change (future minus the control) with the median change marked as a solid black line.

Figure I.6: Change in monthly total rainfall for Vilanculos station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure I.7: Change in monthly mean dry spell duration for Vilanculos station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure I.8: Change in monthly rain day frequency > 0.5 mm Vilanculos station under SRES A2 (left) and SRES B1 (right) emission scenario.

Figure I.9: Change in monthly rain day > 10mm frequency for Vilanculos station under SRES A2 (left) and SRES B1 (right) emission scenario.
Figure I.10: Change in monthly rain days above the 90th percentile of observed record for Vilanculos station (90th percentile = 31.0 mm) under SRES A2 (left) and SRES B1 (right) emission scenario.
PROJECTED CHANGES DISCUSSION
The downscaling results for this region are quite messy with models disagreeing on the sign of change for all variables and months of the year. This disagreement prevents any robust climate change messages to be formed.