期刊
INTERNATIONAL JOURNAL OF CLIMATOLOGY
卷 41, 期 1, 页码 469-482出版社
WILEY
DOI: 10.1002/joc.6632
关键词
Congo; mesoscale; convection; Africa; climatology; MCS; rainfall; variability; propagation
资金
- Division of Atmospheric and Geospace Sciences [NSF AGS 1535439]
The Congo basin in central Africa experiences intense convection through mesoscale convective systems (MCSs) during the rainy seasons. This study tracks MCSs over a 33-year period and identifies seasonal differences using satellite and reanalysis data. Results show significant variability and differences between seasons, with potential localized terrain effects near the Great Rift Valley.
The Congo basin in central equatorial Africa is home to some of the most intense convection in the global tropics. Mesoscale convective systems (MCSs) provide much of the annual rainfall over this region during the March-April-May (MAM) and September-October-November (SON) rainy seasons. Features of these systems are essential to rainfall variability in this region and greatly impact human health, agriculture, livestock, and drought monitoring. Knowledge of variability is hindered by the lack of in-situ observations and meteorological stations. The present study identifies and tracks MCSs for the 33-year period 1983-2015 for MAM and SON. MCS and environmental parameters are calculated for the rainy seasons using satellite and reanalysis data. Spatial distributions of MCS parameters and diurnal cycles for select MCS parameters are compared to prior research. Statistical significance testing is performed to determine if there are meaningful differences between the seasons. Seasonal differences are briefly discussed. 650 hPa relative vorticity patterns suggest localized terrain effects may play a role near a local maximum in MCS initiation frequency in the lee of the Great Rift Valley. Spatial distributions of 33-year MCS counts, trajectories, speeds, sizes, maximum intensities, and durations, based on initiation locations, agree well with prior research. Differences between seasons are statistically significant and variable and latitude dependent. There is high interannual variability among all MCS and environmental parameters.
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