Search Results

You are looking at 1 - 10 of 21 items for

  • Author or Editor: Richard Washington x
  • All content x
Clear All Modify Search
Martin Todd and Richard Washington

Abstract

Algorithms to estimate rainfall from passive microwave or optical data from polar-orbiting satellites are limited by poor temporal sampling and are best suited to produce estimates integrated over periods of one month or more. There are numerous applications in the atmospheric sciences in which rainfall estimates are required at a much greater frequency. These can be derived from geostationary satellite infrared data, but currently no global archive of such products exists. This paper presents a simple technique to reconstruct Geostationary Operational Environmental Satellite Precipitation Index (GPI) estimates of rainfall over the global Tropics and subtropics at 3-hourly, 2.5° resolution from cloud-top temperature statistics contained in the extensive International Satellite Cloud Climatology Project D1 dataset. It is shown that the Reconstructed GPI (RGPI) estimates correlate very strongly with the GPI and have minimal bias, irrespective of the integration period selected or the underlying surface type. Comparison with the independent NASA WetNet PIP-3 surface rainfall validation data shows that the RGPI estimates of rainfall composited over monthly periods match the validation data with accuracy very similar to that of the GPI and are comparable to many passive microwave algorithms. Both the RGPI and GPI estimates of rainfall match the validation data more closely over the tropical Pacific Ocean than over the tropical and subtropical land masses where a positive bias is apparent. With 3-hourly temporal resolution, the RGPI represents a useful new resource for climate studies.

Full access
Emma Howard and Richard Washington

Abstract

The Angola low is a key feature of the southern Africa wet season atmosphere that influences precipitation across the continent. This paper uses ERA-Interim to show that the synoptic expression of the Angola low is a combination of dry heat lows and moist tropical low pressure systems. The Angola heat low and Angola tropical low composites are contrasted against similar lows observed in other continental tropical regions and found to be broadly comparable. The implications that the distinction between dry and moist events has for the interannual relationship among the Angola low, precipitation, and ENSO are examined. The tropical lows exhibit unusual semistationary behavior by lingering in the Angola region rather than traveling offshore. This behavior is proposed to be caused by an integrated sea breeze–anabatic wind that enhances (inhibits) cyclonic vorticity stretching and convection inland (near the coast). The combined effect of the heat lows and the anchored tropical lows creates the Angola low in the climatological average. By elucidating the mechanisms of the Angola low, this research improves the foundation of process-based evaluation of southern Africa present and future climate in CMIP and AMIP models.

Full access
Emma Howard and Richard Washington

Abstract

Projected rainfall decline in southern Africa is likely to be highly sensitive to subtleties in the local atmospheric circulation. In an effort to understand the regional circulation complexities, a novel algorithm is developed to identify the Congo air boundary (CAB) in ERA-5, a high-resolution reanalysis dataset. The CAB, a forgotten feature of the circulation, is defined in the austral spring and early summer, using surface humidity gradients and near-surface wind convergence lines, and it is found to be an indicator of the location of the southern edge of the African rain belt. A related convergence-line and dryline feature, described in this paper as the Kalahari discontinuity (KD), is also identified. It is established that either a dryline CAB or KD is present in southern Africa for over 95% of days between August and December, with arc lengths typically exceeding 10°. The seasonal and diurnal cycles of the CAB and the KD are presented, and their prevalence in station observational data is confirmed. The interannual variability of the CAB latitude and detection frequency is found to explain at least 55% of interannual spring rainfall variability in southern Africa between 15° to 25°S. Links are established with the Angola and Kalahari heat lows and tropical temperate trough events.

Open access
Emma Howard and Richard Washington

Abstract

In southern Africa, models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) predict robust future drying associated with a delayed rainy-season onset in the austral spring and a range of wetting and drying patterns in the austral summer. This paper relates these rainfall changes to dynamical shifts in two classes of weather systems: the Congo Air Boundary (CAB) and tropical lows. Objective algorithms are used to track these features in CMIP5 model output. It is then established that the climatological locations and frequencies of these systems are reasonably well represented in the CMIP5 models. RCP8.5 end-of-twenty-first-century projections are compared with historical end-of-twentieth-century simulations. Future projections in tropical-low locations and frequencies diverge, but indicate an overall average decrease of 15% and in some cases a northward shift. The projected spatial change in the tropical-low frequency distribution is weakly positively correlated to the projected spatial change in the austral summer rainfall distribution. Meanwhile, future projections indicate a 13% increase in CAB frequency from October to December. This is associated with the gradual climatological CAB breakdown occurring half a month later on average in end-of-twenty-first-century RCP8.5 projections. A delay in the gradual seasonal decline of the CAB prevents rainfall to the south of the CAB’s mean position, most of which is shown to occur on CAB breakdown days, hence creating the austral spring drying signal and delayed wet-season onset. Intermodel variability in the magnitude of CAB frequency increase is able to explain intermodel variability in the projected drying.

Restricted access
Ellen Dyer and Richard Washington

Abstract

The 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.

Open access
Rachel James, Richard Washington, and David P. Rowell

Abstract

The importance of investigating regional climate changes associated with degrees of global warming is increasingly being recognized, but the majority of relevant research has been based on multimodel ensembles (MMEs) from the Coupled Model Intercomparison Project (CMIP). This has left two important questions unanswered: Are there plausible futures which are not represented by the models in CMIP? And, how would regional climates evolve under enhanced global warming, beyond 4°C? In this paper, two perturbed physics ensembles (PPEs) are used to address these issues with reference to African precipitation. Examination of model versions that generate warming greater than 4°C in the twenty-first century shows that changes in African precipitation are enhanced gradually, even to high global temperatures; however, there may be nonlinearities that are not incorporated here due to limited model complexity. The range of projections from the PPEs is compared to data from phases 3 and 5 of CMIP (CMIP3 and CMIP5), revealing regional differences. This is partly the result of implausible model versions, but the PPE dataset can be justifiably constrained given its size and systematic nature, highlighting an additional advantage over MMEs. After applying constraints, the PPEs still show changes that are outside the range of CMIP, most prominently strong dry signals in west equatorial Africa and the Sahel, implying that MMEs may underestimate risks for these regions. Analysis of African precipitation changes therefore demonstrates that regional assessments that rely on CMIP3 and CMIP5 may overlook uncertainties associated with model parameterizations and pronounced warming. More systematic approaches are needed for conservative estimates of danger.

Full access
Neil C. G. Hart, Richard Washington, and Ross I. Maidment

Abstract

Africa is one of the three key regions of deep convection in the global tropics. There is a wealth of information on the intensity, variability, and change of convection and associated rainfall in regions across the continent but almost all of this literature is regionally focused and confined to specific seasons. This fragmented approach precludes a continent-wide view of deep convection leaving the following key issues unanswered: When is deep convection the most widespread across Africa? Where on the continent is deep convection most active? Where does widespread convection have the most interannual variability? This paper confronts these questions using a satellite-derived integral of deep convection. At the continental scale, March exhibits the most extensive deep convection whereas the West African monsoon during June–July exhibits the least. El Niño generally suppresses pan-African convective activity while La Niña enhances this activity. These pan-African signals are largely determined by regional hotspots: the eastern Congo hosts the most persistent widespread deep convection, southeastern southern Africa displays the highest interannual variability, and regional highlands maintain local convective activity hotspots. Furthermore, pan-African annual mean convective activity has increased ~10% between 1983 and 2015 with increases of >20% recorded in local hotspots. Results in this study provide a climatological baseline for both observational and model-based studies of African climates and offer insights into when African convection has the greatest potential impact on the general circulation.

Open access
Randall V. Martin, Richard Washington, and Thomas E. Downing

Abstract

Seasonal maize water-stress forecasts were derived for area averages of the primary maize-growing regions of South Africa and Zimbabwe. An agroclimatological model was used to create a historical record of maize water stress as a function of evapotranspiration for 1961–94. Water stress, the primary determinant of yield in water-limited environments such as southern Africa, was correlated with two well-known indices of the El Niño– Southern Oscillation: the Southern Oscillation index (SOI) and the Niño-3 region of the equatorial Pacific. Forecasts for South Africa using only the SOI at a 4-month lead yielded a hindcast correlation of 0.67 over 17 seasons (1961–78) and a forecast correlation of 0.69 over 16 seasons (1978–94). Forecasts for Zimbabwe were less remarkable.

Full access
Neil C. G. Hart, Richard Washington, and Chris J. C. Reason

Abstract

The Southern Hemisphere subtropical convergence zones are important regions of rainfall in the subtropics. The south Indian Ocean convergence zone (SICZ) has the strongest seasonality and exhibits substantial interannual variability in strength and position during austral summer. On synoptic time scales, the SICZ is a preferred region for the formation of tropical–extratropical (TE) cloud bands with local maxima over the southern African mainland and Madagascar. This study investigates how the seasonality in satellite-observed cloud band frequency emerges from the interplay between the asynchronous seasonal cycles in convective instability and upper-level flow, as represented by reanalysis data. These atmospheric mean states are diagnosed with a gross convective instability metric and a method to distinguish between subtropical and eddy-driven jet axes. Month-by-month analysis of these diagnostics elucidates how mean-state perturbations during ENSO events modify cloud band likelihood. Typically, 150%–200% more cloud bands develop during La Niña seasons supported by 5°–10° latitudinal separation between the local subtropical and eddy-driven jets and higher values of convective instability, especially in semiarid parts of mainland southern Africa. During El Niño events, fewer cloud bands develop over southern Africa in a more convectively stable environment without a distinct subtropical jet. However, east of Madagascar cloud bands are 150% more likely. Plausible teleconnection pathways based on these ENSO-related perturbations are discussed. The paper concludes with a conceptual framing of the seasonal cycle in the mean-state pertinent to TE cloud band likelihood.

Open access
Rachel James, Neil C. G. Hart, Callum Munday, Chris J. C. Reason, and Richard Washington

Abstract

There are increasing efforts to use climate model output for adaptation planning, but meanwhile there is often limited understanding of how models represent regional climate. Here we analyze the simulation in global coupled climate models of a key rainfall-generating mechanism over southern Africa: tropical temperate troughs (TTTs). An image-processing algorithm is applied to outgoing longwave radiation data from satellites and models to create TTT event sets. All models investigated produce TTTs with similar circulation features to observed. However, there are large differences among models in the number, intensity, and preferred longitude of events. Five groups of models are identified. The first group generates too few TTTs, and relatively dry conditions over southern Africa compared to other models. A second group generates more TTTs and wet biases. The contrast between these two groups suggests that the number of TTTs could explain intermodel variations in climatological rainfall. However, there is a third group of models that simulate up to 92% more TTTs than observed, but do not have large rainfall biases, as each TTT event is relatively weak. Finally, there are a further two groups that concentrate TTTs over the subcontinent or the ocean, respectively. These distinctions between models are associated with the amount of convective activity in the Congo Basin, the magnitude of moisture fluxes into southern Africa, and the degree of zonal asymmetry in upper-level westerly flow. Model development focused on tropical convection and the representation of orography is needed for improved simulation of TTTs, and therefore southern African rainfall.

Open access