A summary report on the Historical Climate INAM Database Recovery

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A summary report on the Historical Climate INAM Database
Recovery (HCIDR) project.
The problem
Mozambique is extremely vulnerable to the effects of drought, storms and floods. The effects of
these natural disasters are further compounded by global warming. To this effect, there is a need
in the country to improve on its alert systems using climate information and dissemination of
information for better climatic risk management and planning climate change adaptation in
different sectors (agriculture, fisheries, health etc) as well as different geographical areas (arid &
semi-arid, flood and/or cyclone prone areas, urban environments).
The National Institute of Meteorology (INAM) has a stockpile of significant amount of historical
data collected but stored in poorly retrievable archives. This is data that can be used to synthesize
key information including historical sequences that are key to improving the projection of
different climate scenarios as well as assessing the validity of downscaling from the global
climatic models. All this information is key to climate-proofing national development projects in
the country. The problem however was that this data was poorly archived in piles of paper. There
was therefore a need to urgently rescue this data to specifically prevent them from being lost,
putting them in user-friendly format for analysis, and to generally improve on the bottom line
needs to manage climate change risks.
The general objective
The main aim of the HCIDR project was to recover historical data archived in piles of paper and
in a poor condition here before.
The CC-DARE contribution to the solution
The project INAM HCIDR used a recovery process of digitilization of historical INAM climate data that
had been archived in poor condition (in piles of paper), thereby making them accessible online. An
important aspect of the HCIDR project was the analysis of the digitilized data in order to improve the
available of information on climate trends in different regions of the country. Such information is a vital
enabler of climate change adaptation initiatives in key sectors of the Mozambican economy such as
agriculture, fisheries etc. To this effect and in line with its overall mission of improving climate
change adaptation in sub-saharan Africa by providing financial and technical assistance to
selected projects, INAM received a total of $ 44,104.84 (forty-four thousand one hundred and four U.S.
dollars and eighty-four U.S. cents) from the CCDARE Programme to impement this project as pilot.
The Big picture
The CC-DARE intervention in Mozambique was successful in providing more climate data and
information in understanding historical climate trends. The availability of this data will ensure
that scientists and other users have access to climate information necessary for their studies and
projects. Further, the rescued data combined with already available data will ensure relevant
authorities in key sectors like agriculture, fisheries etc access better climatic projection data
hence better equiped to mitigate climate change risks and losses caused by the now prevalent
natural disasters, hence bolster economic development. In achieving the aforementioned, CCDARE contributed to the realization of the following direct outcomes of the project;

6 computers were purchased and are now available to continue with digitilization
of data at INAM;

8 staff who were trained in the use of CLICOM are ready and will continue with
the data digitilization under the African Adaptation Program funding;

More data is now available to scientists and other users for their studies and projects.
This rescued data combined with already available data will enable authorities to have
access to better projections that can be used to mitigate against loss caused by natural
disasters and will provide increased information for economic development.

10 INAM Meteorologist and 1 staff member from the Institute of Disaster
Management were trained in the use of RClimedex and are now analysing the
trends of climate extremes using the data made available by the project.
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