Abstract
AbstractThe interannual variability, trends, and the mean climatology of East African long rains are difficult for models to simulate. This is in part because long rains do not respond in a simple way to large-scale modes of variability such as ENSO and because of interactions with complex topography. Here we focus on the Kenyan regional climate in the ERA-Interim dataset during the long rains to create a set of atmospheric diagnostics that can be applied to the evaluation of climate models. Subseasonal observed rainfall and reanalysis reveal that very wet seasons and very dry seasons develop differently at the beginning of the season. Subseasonal aggregation periods (days 60–80, 80–100, 90–120, 120–150) highlight local (e.g., midtropospheric ascent, moisture flux convergence in the lower to midtroposphere, and midtropospheric moisture) and large-scale (e.g., midtropospheric zonal winds over central Africa, upper-tropospheric velocity potential) diagnostics that are useful to evaluate model atmospheric circulation affecting Kenyan rainfall in mean and wet or dry extremes.
Highlights
The ensemble of models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that forms the modeling basis for the IPCC Fifth Assessment Report (AR5) struggles to simulate projections of future rainfall in East Africa without significant uncertainty (Niang et al 2014; Tierney et al 2015)
As we have shown that changes in seasonal rainfall are influenced by local SSTs and their impact on moisture and divergence, and cross-continental flows, the information gained by examining the long-rains season at the subseasonal level can contribute to a better set of atmospheric diagnostics and understanding of seasonal variability
The relationship between the diagnostics and Kenyan rainfall has been studied for our subseasonal aggregation periods and for the seasonal average to see how these diagnostics perform against the full baseline of long-rains seasons
Summary
The ensemble of models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that forms the modeling basis for the IPCC Fifth Assessment Report (AR5) struggles to simulate projections of future rainfall in East Africa without significant uncertainty (Niang et al 2014; Tierney et al 2015). We demonstrate the value in examining East African long rains at a subregional scale and at a subseasonal scale Taking this approach, we will create new subseasonal aggregation periods based on how the season evolves, in the mean and extreme composites, and create a set of atmospheric diagnostics that can be used to guide future model evaluations. By examining the historical daily mean climatology and perturbations in extreme season rainfall, we will create new subseasonal aggregation periods, and use the associated changes in atmospheric fields to suggest a set of diagnostics with which to understand Kenyan long-rains rainfall. Correlations are calculated using Spearman’s rank correlation (r) with a twosided p value throughout the study
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
