Noel Banda(1, 4), Treaser Thomas(2), Gba-gombo Jovial(3, 4), Zhang Lena(4)
(1)Department of Climate Change and Meteorological Services, P.O. Box 1808, Blantyre, Malawi
(2)University of Malawi, Chancellor College, P.O.Box 280, Zomba, Malawi
(3)Direction de la Meteorologie et de l'Hydrologie, P.0.Box 941, Bangui, Republique Centrafricaine
(4)China Meteorological Administration Training Center
Abstract
Regression and composite analysis were
deployed in this study to investigate rainfall trend and variability
over Malawi from 1951 to 2013. Further analysis was made to understand
relation between moisture transport and variability rainfall during
January to March (JFM) rainfall season. Rainfall data was obtained from
Global Precipitation Climatology Center (GPCC) while Wind, Relative
Humidity and Vertical integral of eastward and northward water vapor
flux were ERA-Interim reanalysis dataset. Results revealed an overall of
negative trend for annual long term rainfall. Spatial trend analysis
also revealed negative trend over large part of Malawi with positive
trend only over part of central and southern region of the country.
Results of composite analysis showed that there was 40% of rainfall
deviation above mean over Central and southern Malawi and were
corresponding to anomalous cyclonic circulation in the Indian Ocean and
low level westerly transfer of moisture from South Atlantic Ocean. The
system tend to reverse during dry years where rainfall deviated 50%
below mean were found corresponding to anomalous low level anticyclonic
circulation and easterly transfer of moisture at low level. Relative
humidity was observed below average during dry years and above average
during wet years. Analysis of rainfall variability and moisture
transport is vital for improvement and provision of more accurate
prediction of seasonal weather forecast which will greatly help to
minimize the socio-economic losses associated with extreme weather
events in the region.
Key words: Rainfall variability, Moisture transport, Regression Analysis, Malawi, JFM
Climatology of annual rainfall over Malawi (32 - 36 degree East, 17 - 9 degree South) based on 1951–2013
The regression analysis of JFM precipitation positive trend (red) and negative trend (blue) in millimeters per year
(a) Mean JFM rainfall, (b) Composite Mean rainfall anomaly
during wet years and (c) Composite Mean rainfall anomaly during dry year
averaged over Malawi based on 1981–2013
Anomaly
of moisture transport at surface in g kg-1ms-1 for (a) wet years (b)
dry years, shaded is the eastward water vapour flux anomaly.
Conclusion
The primary objective of this study was
to investigate the temporal-spatial rainfall distribution and
variability and its relationship to low level moisture transfer over
Malawi by considering wet and dry years during JFM season. Negative
trend of annual rainfall was observed during the study period. Spatial
trend analysis also revealed negative trend over large part of Malawi
with positive trend over part of central and southern region of the
country. Results of composite analysis showed that 40% of rainfall
deviation above mean over Central and southern Malawi was associated to
anomalous low level cyclonic circulation in the Indian Ocean and low
level westerly transfer of moisture from South Atlantic Ocean which were
converging over Malawi and were accompanied by strong rising motion
over the county. While during dry years the region experience reverse of
this system, where negative deviations of rainfall up to 50% below mean
were corresponding to anomalous low level anticyclonic circulation and
easterly transfer of moisture at low level which was accompanied by
sinking motion and low level divergence over Malawi. The analysis of
relative humidity 825hPa exhibit positive anomaly in the central and
southern region of the study region during wet years which corresponded
with positive rainfall anomaly while negative anomaly during dry years
which resulted in negative rainfall anomaly.
This study suggested that conclusions
made in this study are relevant and can be considered in preparation of
seasonal forecast to improve accuracy and reliability and this in return
will help minimize impacts of such extreme events like floods and
drought in future.
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