Abstract

Climate models struggle to realistically represent the West African monsoon (WAM), which hinders reliable future projections and the development of adequate adaption measures. Low-level clouds over southern West Africa (5°–10°N, 8°W–8°E) during July–September are an integral part of the WAM through their effect on the surface energy balance and precipitation, but their representation in climate models has received little attention. Here 30 (20) years of output from 18 (8) models participating in phase 5 of the Coupled Model Intercomparison Project (Year of Tropical Convection) are used to identify cloud biases and their causes. Compared to ERA-Interim reanalyses, many models show large biases in low-level cloudiness of both signs and a tendency to too high elevation and too weak diurnal cycles. At the same time, these models tend to have too strong low-level jets, the impact of which is unclear because of concomitant effects on temperature and moisture advection as well as turbulent mixing. Part of the differences between the models and ERA-Interim appear to be related to the different subgrid cloud schemes used. While nighttime tendencies in temperature and humidity are broadly realistic in most models, daytime tendencies show large problems with the vertical transport of heat and moisture. Many models simulate too low near-surface relative humidities, leading to insufficient low cloud cover and abundant solar radiation, and thus a too large diurnal cycle in temperature and relative humidity. In the future, targeted model sensitivity experiments will be needed to test possible feedback mechanisms between low clouds, radiation, boundary layer dynamics, precipitation, and the WAM circulation.

Abstract

This study provides an improved understanding of the diurnal cycle of warm season (June–September) rainfall over West Africa, including its underlying physical processes. Rainfall from the Tropical Rainfall Measuring Mission and atmospheric dynamics fields from reanalyses are used to evaluate the 1998–2013 climatology and a case study for 2006.

In both the climatology and the 2006 case study, most regions of West Africa are shown to have a single diurnal peak of rainfall either in the afternoon or at night. Averaging over West Africa produces a diurnal cycle with two peaks, but this type of diurnal cycle is quite atypical on smaller space scales. Rainfall systems are usually generated in the afternoon and propagate westward, lasting into the night. Afternoon rainfall peaks are associated with an unstable lower troposphere. They occur either over topography or in regions undisturbed by nocturnal systems, allowing locally generated instability to dominate. Nocturnal rainfall peaks are associated with the westward propagation of rainfall systems and not generally with local instability. Nocturnal rainfall peaks occur most frequently about 3°–10° of longitude downstream of regions with afternoon rainfall peaks. The diurnal cycle of rainfall is closely associated with the timing of extreme rainfall events.

Abstract

Convection-permitting simulations at 3-km resolution using a regional climate model are analyzed to improve the understanding of the diurnal cycle of rainfall over West Africa and its underlying physical processes. The warm season of 2006 is used for the model simulations. The model produces an accurate representation of the observed seasonal mean rainfall and lower-troposphere circulation and captures the observed westward propagation of rainfall systems. Most of West Africa has a single diurnal peak of rainfall in the simulations, either in the afternoon or at night, in agreement with observations. However, the number of simulated rainfall systems is greater than observed in association with an overestimation of the initiation of afternoon rainfall over topography. The longevity of the simulated propagating systems is about 30% shorter than is observed, and their propagation speed is nearly 20% faster. The model captures the observed afternoon rainfall peaks associated with elevated topography (e.g., the Jos Plateau). Nocturnal rainfall peaks downstream of the topographic afternoon rainfall are also well simulated. However, these nocturnal rainfall peaks are too widespread, and the model fails to reproduce the observed afternoon rainfall peaks over regions removed from topographic influence. This deficiency is related to a planetary boundary layer that is deeper than observed, elevating unstable profiles and inhibiting afternoon convection. This study concludes that increasing model resolution to convection-permitting space scales significantly improves the diurnal cycle of rainfall compared with the models that parameterize convection, but this is not sufficient to fully resolve the issue, perhaps because other parameterizations remain.

Abstract

This study investigates the El Niño–Southern Oscillation (ENSO) contribution to Philippine tropical cyclone (TC) variability, for a range of quarterly TC metrics. Philippine TC activity is found to depend on both ENSO quarter and phase. TC counts during El Niño phases differ significantly from neutral phases in all quarters, whereas neutral and La Niña phases differ only in January–March and July–September. Differences in landfalls between neutral and El Niño phases are significant in January–March and October–December and in January–March for neutral and La Niña phases. El Niño and La Niña landfalls are significantly different in April–June and October–December. Philippine neutral and El Niño TC genesis cover broader longitude–latitude ranges with similar long tracks, originating farther east in the western North Pacific. In El Niño phases, the mean eastward displacement of genesis locations and more recurving TCs reduce Philippine TC frequencies. Proximity of La Niña TC genesis to the Philippines and straight-moving tracks in April–June and October–December increase TC frequencies and landfalls. Neutral and El Niño accumulated cyclone energy (ACE) values are above average, except in April–June of El Niño phases. Above-average quarterly ACE in neutral years is due to increased TC frequencies, days, and intensities, whereas above-average El Niño ACE in July–September is due to increased TC days and intensities. Below-average La Niña ACE results from fewer TCs and shorter life cycles. Longer TC durations produce slightly above-average TC days in July–September El Niño phases. Fewer TCs than neutral years, as well as shorter TC durations, imply less TC days in La Niña phases. However, above-average TC days occur in October–December as a result of higher TC frequencies.

Abstract

African easterly waves (AEWs) can act as seed disturbances for tropical cyclones (TCs) in the Atlantic, and changes in future AEW activity may have important consequences for development of TCs. The simulation of AEWs was investigated using output from phase 5 of the Coupled Model Intercomparison Project (CMIP5) suite of experiments, including coupled historical and future simulations and atmosphere only (AMIP) simulations. Large biases exist in the simulation of low- (850 hPa) and midlevel (700 hPa) eddy kinetic energy (EKE, a proxy for AEW activity) in AMIP and historical simulations. CMIP5 models simulate excessive EKE and deficient rainfall south of 17°N. The same biases exist in historical and AMIP models and are not a consequence of errors in sea surface temperatures. The models also struggle to accurately couple AEWs and rainfall, with little improvement from CMIP3 models. CMIP5 models are unable to propagate AEWs across the coast and into the Atlantic, which is shown to be related to the resolution of the Guinea Highlands. Future projections of the annual cycle of AEW activity show a reduction in late spring and early summer and a large increase between July and October that is consistent with rainfall projections in the Sahel, but large differences exists in future projections between high- and low-resolution models. The simulation of AEWs is challenging for CMIP5 models and must be further diagnosed in order to accurately predict future TC activity and rainfall in the Sahel.

Abstract

The major objective of this study is to re-evaluate the ocean–land transport of moisture for rainfall in West Africa using 1979–2008 NCEP–NCAR reanalysis data. The vertically integrated atmospheric water vapor flux for the surface–850 hPa is calculated to account for total low-level moisture flux contribution to rainfall over West Africa. Analysis of mean monthly total vapor fluxes shows a progressive penetration of the flux into West Africa from the south and west. During spring (April–June), the northward flux forms a “moisture river” transporting moisture current into the Gulf of Guinea coast. In the peak monsoon season (July–September), the southerly transport weakens, but westerly transport is enhanced and extends to 20°N owing to the strengthening West African jet off the west coast. Mean seasonal values of total water vapor flux components across boundaries indicate that the zonal component is the largest contributor to mean moisture transport into the Sahel, while the meridional transport contributes the most over the Guinea coast. For the wet years of the Sahel rainy season (July–September), active anomalies are displaced farther north compared to the long-term average. This includes the latitude of the intertropical front (ITF), the extent of moisture flux, and the zone of strong moisture flux convergence, with an enhanced westerly flow. For the dry Sahel years, the opposite patterns are observed. Statistically significant positive correlations between the zonal moisture fluxes and Sudan–Sahel rainfall totals are most pronounced when the zonal fluxes lead by 1–4 pentads. However, although weak, they still are statistically significant at lags 3 and 4 for meridional moisture fluxes.

Abstract

An ensemble-based multiple linear regression technique is developed to assess the predictability of regional and national June–September (JJAS) anomalies and local monthly rainfall totals for Ethiopia. The ensemble prediction approach captures potential predictive signals in regional circulations and global sea surface temperatures (SSTs) two to three months in advance of the monsoon season. Sets of 20 potential predictors are selected from visual assessments of correlation maps that relate rainfall with regional and global predictors. Individual predictors in each set are utilized to initialize specific forward stepwise regression models to develop ensembles of equal number of statistical model estimates, which allow quantifying prediction uncertainties related to individual predictors and models. Prediction skill improvement is achieved through error minimization afforded by the ensemble.

For retroactive validation (RV), the ensemble predictions reproduce well the observed all-Ethiopian JJAS rainfall variability two months in advance. The ensemble mean prediction outperforms climatology, with mean square error reduction (SS_Clim) of 62%. The skill of the prediction remains high for leave-one-out cross validation (LOOCV), with the observed–predicted correlation r (SS_Clim) being +0.81 (65%) for 1970–2002. For tercile predictions (below, near, and above normal), the ranked probability skill score is 0.45, indicating improvement compared to climatological forecasts. Similarly high prediction skill is found for local prediction of monthly rainfall total at Addis Ababa (r = +0.72) and Combolcha (r = +0.68), and for regional prediction of JJAS standardized rainfall anomalies for northeastern Ethiopia (r = +0.80). Compared to the previous generation of rainfall forecasts, the ensemble predictions developed in this paper show substantial value to benefit society.

Abstract

Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) project changes to the seasonality of both tropical sea surface temperature (SST) and precipitation when forced by an increase in greenhouse gases. Nearly all models project an amplification and a phase delay of the annual cycle for both quantities, indicating a greater annual range and extrema reached later in the year. The authors investigate the nature of the seasonal precipitation changes in AGCM experiments forced by SST perturbations, which represent idealizations of the changes in annual mean, amplitude, and phase as simulated by CMIP5 models. A uniform SST warming is sufficient to force both amplification and a delay of the annual cycle of precipitation. The amplification is due to an increase in the annual mean vertical water vapor gradient, while the delay is affected by changes in the seasonality of the circulation. A budget analysis of this simulation reveals a large degree of similarity with the CMIP5 results. In the second experiment, only the seasonal characteristics of SST are changed. In response to an amplified annual cycle of SST, the annual cycle of precipitation is amplified, while for a delayed SST, the annual cycle of precipitation is delayed. Assuming that SST changes can entirely explain the seasonal precipitation changes, the AGCM simulations herein suggest that the annual mean warming explains most of the amplitude increase and much of the phase delay in the CMIP5 models. However, imperfect agreement between the changes in the SST-forced AGCM simulations and the CMIP5 coupled simulations suggests that coupled effects may play a significant role.

Abstract

A regional climate model with 90-km horizontal resolution on a large domain is used to predict and analyze precipitation changes over East Africa caused by greenhouse gas increases. A pair of six-member ensembles is used: one representing the late twentieth century and another the mid-twenty-first century under a midline emissions scenario. The twentieth-century simulation uses boundary conditions from reanalysis climatology, and these are modified for the mid-twenty-first-century simulation using output from coupled GCMs. The twentieth-century simulation reproduces the observed climate well. In eastern Ethiopia and Somalia, the boreal spring rains that begin in May are cut short in the mid-twenty-first-century simulation. The cause is an anomalous dry, anticyclonic flow that develops over the Arabian Peninsula and the northern Arabian Sea as mass shifts eastward near 20°N in response to strong warming over the Sahara. In Tanzania and southern Kenya, the boreal spring's long rains are reduced throughout the season in the future simulation. This is a secondary response to precipitation enhancement in the Congo basin. The boreal fall “short rains” season is lengthened in the twenty-first-century simulation in the southern Kenya and Tanzania region in association with a northeastward shift of the South Indian convergence zone.