Accuracy of Giovanni and Marksim software packages for generating daily rainfall data in selected bimodal climatic areas in Tanzania
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Date
2014
Journal Title
Journal ISSN
Volume Title
Publisher
Tanzania Journal of Agricultural Sciences
Abstract
Agricultural adaptation to climate change requires accurate, unbiased, and reliable climate data.
Availability of observed climatic data is limited because of inadequate weather stations. Rainfall
simulation models are important tools for generating rainfall data in areas with limited or no
observed data. Various weather generators have been developed that can produce time series of
climate data. Verification of the applicability of the generated data is essential in order to determine
their accuracy and reliability for use in areas different from those that were used during models
development. Marksim and Giovanni weather generators were compared against 10 years of
observed data (1998-2007) for their performance in simulating rainfall in four stations within
the northern bimodal areas of Tanzania. The observed and generated data were analyzed using
climatic dialog of the INSTAT program. Results indicated that during the long rain season (masika)
Giovanni predicted well the rainfall amounts, rainy days, and maximum dry spells compared to
Marksim model. The Marksim model estimated seasonal lengths much better than the Giovanni
model during masika. During short rain season (vuli), Giovanni was much better than Marksim.
All the two software packages had better predictions during masika compared to vuli. The Giovanni
model estimated probabilities of occurrence of rainfall much better (RMSE = 0.23, MAE = 0.18,
and d =0.75) than Marksim (RMSE = 0.28, MAE = 0.23, and d = 0.63). The Marksim model
over-predicted the probabilities of occurrence of dry spells greater than seven days (MBE = 0.17)
compared to the Giovanni model (MBE = 0.01). In general the Giovanni model was more accurate
than the Marksim model in most of the observed weather variables. The web based Giovanni model
is better suited to the northern bimodal areas of Tanzania. The Marksim model produced more
accurate climatic data when the long-term average climate data are used as input variables. This
study recommends the use of rainfall data generated using Giovanni software over Marksim, for
areas receiving bimodal rainfall regimes similar to the northern bimodal areas of Tanzania.
Description
Tanzania Journal of Agricultural Sciences 2014, Vol13(1): 12-25
Keywords
Bimodal rainfall, Long-term average climate data, Dry spells, Giovanni, INSTAT, Marksim