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Convectively coupled equatorial Kelvin waves (CCEKWs) are those types of equatorially trapped disturbances that propagate eastward and are among the most common intra-seasonal oscillations in the tropics. There exists two-way feedback between the inter-tropical convergence zone (ITCZ) and these equatorially trapped disturbances. Outgoing Longwave Radiation (OLR) was utilized as a proxy for deep convection. For CCEKWs, the modes are located over the West Atlantic, equatorial West Africa, and the Indian Ocean. The influence of other circulations and climate dynamics is studied for finding other drivers of climate within East Africa. The results show a positive relationship between Indian and Atlantic Oceans Sea Surface Temperatures and March-May rainfall over equatorial East Africa over the period of 1980 to 2010. This influence is driven by the Walker circulation and anomalous moisture influx enhanced by winds. Composite analysis reveals strong lower-tropospheric westerlies during the active phase of the CCKWs activities over Equatorial East Africa. The winds are in the opposite direction with the upper-tropospheric winds, which are easterlies. Singular Value Decomposition shows a strong coupling interaction between rainfall over equatorial East Africa and CCKWs. This study concludes that Kelvin waves are not the main factors that influence rainfall during the rainy season. Previous studies show that the main influencing factors are ITCZ, El-Nino Southern Oscillation (ENSO), and tropical anticyclones that borders the African continent. However, CCKWs are a significant factor during the dry seasons.

This paper focuses on one of the high resolution models used for weather forecasting at Kenya Meteorological Department (KMD). It reviews the skill and accuracy of the Weather Research and Forecasting (WRF) - Environmental Modeling System (EMS) model, in simulating weather over Kenya. The study period was March to May 2011, during the rainy season over Kenya. The model output was compared with the observed data from 27 synoptic stations spread over the study area, to determine the performance of the model in terms of its skill and accuracy in forecasting. The spatial distribution of rainfall and temperature showed that the WRF model was capable of reproducing the observed general pattern especially for temperature. The model has skill in forecasting both rainfall and temperature over the study area. However, the model may underestimate rainfall of more than 10 mm/day and displace its location and overestimate rainfall of less than 1 mm/day. Therefore, during the period of enhanced rainfall especially in the month of April and part of May the model forecast needs to be complemented by other models or forecasting methods before giving a forecast. There is need to improve its performance over the domain through review of the parameterization of small scale physical processes and more observed data need to be simulated into the model.

This study reviews the effect of urbanization on human thermal comfort over Nairobi city in Kenya. Urbanization alters urban center's land use and land cover, modifying the climate of the urban setting. The modification in climate affects human comfort and the environment at large. This study focuses on the recent studies conducted in Nairobi city and many other cities globally to examine modification of wind, temperature and humidity over Nairobi. There was observed reduction in wind speed and relative humidity over the city, posing threat to human and animal comfort and the environment at large. The city of Nairobi, just like other cities globally is observed to experience urban heat island (UHI). The observed increase in minimum temperature as compared to maximum temperature signifies overall warming. A combination of all these changes reduces human comfort. Borrowing lessons from developed cities, increasing the urban forest cover is thus suggested as one of the practical and effective measures that can help prevent further modification of weather and urban climates. The study recommends further research involving multi-sectoral urban stake holders, on forcing driving urban thermal comfort. In the short term, design and construction of appropriate structures can help minimize energy consumption and emissions, thus enhancing comfort.

Extreme weather and climate events such as floods and droughts are common in East Africa, causing huge socio-economic losses. This study links the east African October-December (OND) rainfall, Indian Ocean Dipole (IOD) and Mascarene High (MH).Correlation analysis is applied to quantify the relationship between the index of IOD (Dipole Mode Index (DMI)) and OND rainfall. Results show that there exists a significant correlation between OND rainfall and DMI, with a correlation coefficient of 0.6. During dry years, MH is observed to intensify and align itself in the southeast-northwest orientation, stretching up to the continent, which in turn inhibits the influx of moisture from Indian Ocean into East Africa. During wet years, MH weakens, shifts to the east and aligns itself in the zonal orientation. Moisture from Indian Ocean is freely transported into east Africa during wet years. Analysis of the drought and flood years with respect to the different variables including wind, velocity potential and divergence/ convergence revealed that the drought (flood) years were characterized by divergence (convergence) in the lower troposphere and convergence (divergence) at the upper level, implying sinking (rising) motion, especially over the western Indian Ocean and the study area. Convergence at low level gives rise to vertical stretching, whereas divergence results in vertical shrinking, which suppresses convection due to subsidence. Positive IOD (Negative IOD) event results into flood (drought) in the region. The evolution of these phenomena can thus be keenly observed for utilization in the update of seasonal forecasts.

Understanding drought occurrence and evolution is important in minimizing the impacts associated with it. This work assesses the performance of 10 commonly used meteorological indices to measure drought in Morocco. The studied indices are Deciles Index (DI), Percent of Normal Index (PNI), Z‐Score Index (ZSI), China‐Z Index (CZI), Rainfall Anomaly Index (RAI), Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI), its self‐calibrated variant (scPDSI) and Palmer Z Index (PZI). Rainfall and temperature gridded data is sourced from PERSIANN‐CDR and ERA5, respectively, for the period 1983–2021. The study area exhibits three main climatic regimes; subhumid, semi‐arid and arid, with a drying and warming climate, as depicted by the rainfall and temperature trends analysis. Results show that most rainfall‐based indices perform relatively poorly in drought monitoring in the study area. DI and PNI appear to be inconsistent and abnormally responsive to rainfall. RAI reports droughts 56.5% more frequently and slightly underestimate drought intensity compared to other indices. Similarly, ZSI and CZI largely underestimate drought intensity. PDSI and scPDSI are computationally demanding, often underestimate drought intensity and overestimate drought duration by at least 115% compared to SPI and SPEI. Conversely, PZI can be used for drought onset detection as it reported droughts early compared to the other indices. SPI and SPEI perform overall better regarding their consistent drought identification and severity assessment. However, SPEI is found to be more suitable than SPI in the arid and semi‐arid regions and performed better considering the warming climate of the country. [ABSTRACT FROM AUTHOR]