Browsing by Author "Lennard, Chris"

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    Open Access
    Assessing the representation of teleconnective drivers of rainfall over Eastern Africa in global and regional climate models and projected future changes
    (2017) Endris, Hussen Seid; Hewitson, Bruce; Lennard, Chris
    Climate variability is an important characteristic of regional climate, and a subject to significant control from teleconnections. An extended diagnosis of the capacity of climate models to represent remote controls of regional climate (teleconnections) is vital for assessing model-based predictions of climate variability, understanding uncertainty in climate projections and model development. An important driver of climate variability for Africa is the sea surface temperature (SST) - rainfall teleconnection, such as the El Ni˜no/Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). In this study, an assessment of the teleconnection between tropical SSTs and Eastern African rainfall in global and regional climate models is presented, with particular attention paid to the propagation of large-scale teleconnection signals (as represented by model reanalyses and Coupled Global Climate models (CGCMs)) into the domain of the Regional Climate Models (RCMs). The teleconnection-rainfall relationship with the Eastern Africa region is assessed in two rainfall seasons (June-July-August-September and October-November- December) under present and future periods. Evaluation runs (RCMs driven by reanalysis datasets) and historical simulations (RCMs driven by CGCMs) are assessed to quantify the ability of the models to capture the teleconnection relationship. The future analysis is performed for two Representative Concentration Pathway scenarios (RCP4.5 and RCP8.5) to assess future change in this relationship as a result of global warming. Using ERA-interim reanalysis as perfect boundary conditions, the RCMs adequately simulate the spatial and temporal distribution of rainfall in comparison with observations, although the model performance varies locally and seasonally within the region. Furthermore, the RCMs correctly capture the magnitude and spatial extent regional-scale seasonal rainfall anomalies associated with large-scale oceanic modes (ENSO and IOD). When the lateral boundary conditions are provided by CGCMs, RCMs barely capture the regional teleconnection patterns associated with large-scale modes, and mostly depend on the selection of the driving CGCM. Comparison of the CGCM-driven RCM simulations with the reanalysis-driven RCM simulations revealed that most of the errors in teleconnection found in the RCM simulations are inherited from the host CGCMs. The ERA-Interim driven downscaled results show better agreement with observed spatial teleconnection patterns than the CGCM driven downscaled results. Analysis of the CGCMs and corresponding downscaled results showed that in most cases both the CGCM and the corresponding downscaled simulations had similar teleconnection patterns, but in some cases the RCM results diverge to those of the driving CGCM results. It has been demonstrated that similarities in SST-rainfall teleconnection patterns between the RCM simulations and respective driving CGCM simulations are noted over the equatorial and southern part of the region during OND season, where the rainfall is primarily controlled by large-scale (synoptic-scale) features, with the RCMs maintaining the overall regional patterns from the forcing models. Di↵erences in RCM simulations from corresponding driving simulations are noted mainly over northern part of the domain during JJAS, which is most likely related to mesoscale processes that are not resolved by CGCMs. Looking at the model projections of the future, although the spatial pattern of teleconnections between ENSO/IOD and rainfall still persist, important changes in the strength of the teleconnection have been found. During JJAS, ENSO is an important driver of rainfall variability in the northern parts of the region where dry anomalies are associated with El Ni˜no and wetter anomalies with La Ni˜na. Both regional and global ensemble projections show higher rainfall during La Ni˜na and lower rainfall during El Ni˜no over the northern part of the region compared to the present period. During OND, the teleconnection between ENSO/IOD and rainfall is projected to strengthen (weaken) over Eastern horn of Africa (southern parts of the region) compared to the present period. This implies heavy seasonal rains associated with positive phases of ENSO and IOD will increase in future across the Eastern horn of Africa. The change OND rainfall teleconnections are stronger and also more consistent between the models and scenarios as compared to the change in JJAS teleconnections. These findings have an important implication for the water and agricultural managers and policies in the region to tackle the anticipated droughts and floods associated anthropogenic climate change. Finally, the analysis demonstrated that the largest source of uncertainty in the regional climate model simulations in the context of teleconnective forcing of rainfall over Eastern Africa is the choice of CGCM used to force the RCMs, reinforcing the understanding that the use of a single GCM to downscale climate predictions/projections and using the downscaled product for assessment of climate change projections is insufficient. Simulations from multiple RCMs nested in more than one GCM, as is undertaken in the Coordinated Regional Downscaling Experiment (CORDEX), are needed to characterize the uncertainty and provide estimates of likely ranges of future regional climate changes.
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    Future changes in extreme rainfall events and circulation patterns over southern Africa
    (2015) Pinto, Izidine S de Sousa; Lennard, Chris; Tadross, Mark; Hewitson, Bruce
    Changes in precipitation extremes are projected by many global climate models as a response to greenhouse gas increases, and such changes will have significant environmental and social impacts. These impacts are a function of exposure and vulnerability. Hence there is critical need to understand the nature of weather and climate extremes. Results from an ensemble of regional climate models from the Coordinated Regional Downscaling Experiment (CORDEX) project are used to investigate projected changes in extreme precipitation characteristics over southern Africa for the middle (2036-2065) and late century (2069-2098) under the representative concentration pathway 4.5 (RCP4.5) and 8.5 (RCP8.5). Two approaches are followed to identify and analyze extreme precipitation events. First, indices for extreme events, which capture moderate extreme events, are calculated on the basis of model data and are compared with indices from two observational gridded datasets at annual basis. The second approach is based on extreme value theory. Here, the Generalized Extreme Value distribution (GEV) is fitted to annual maxima precipitation by a L-moments method. The 20-year return values are analyzed for present and future climate conditions. The physical drivers of the projected change are evaluated by examining the models ability to simulate circulation patterns over the regions with the aid of Self-Organizing Maps (SOM).
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    A historical perspective on wind data: time, space and vector relationships between ship log data and Cape Royal Astronomical Observatory wind data between 1834 and 1854
    (2017) Brown, Alexa; Lennard, Chris; Grab, Stefan
    This dissertation assesses the extent to which data from the Climatological Database for the World's Oceans (CLIWOC) reflect newly digitized historical wind data captured at the Royal Astronomical Observatory (RAO) in Cape Town, South Africa from 1834-1854. This follows the historical precipitation reconstructions for Southern Africa by Hannaford et al. (2015), using wind data from the CLIWOC database. This project also forms part of a bigger project that is recovering and digitising historical instrumental meteorological data for Southern Africa that have never been analysed before. For Southern Africa, the opportunity to compare historical instrumental data seldom arises due to the paucity of reliable data. However, there is an opportunity to analyse and compare two different wind data sources for a twenty-one year cross over period for south western Africa. Wind, as an indicator of atmospheric conditions, has not been assessed extensively in South African, therefore this project fills an academic gap in historical climatology for the region, and provides newly digitised historical data. Digitisation and pre-processing steps ensure that the RAO dataset is comparable to the CLIWOC dataset. This is done by replicating wind direction and speed measurement conversions and formatting (Garcia-Herrera et al., 2005), and by mirroring the available time steps of data in each dataset (eliminating data were the other dataset has erroneous or missing data). Spatially scattered data recorded over the sea compared to data recorded at a fixed position introduces inherent limitations, error and noise into the data comparison. Therefore, to eliminate as many uncertainties as possible and minimise the noise in the data, the CLIWOC data are refined further by a) a single observation per day, b) separating three regions of differing seasonal synoptic air flow regimes (west coast, south west peninsula and south coast) and c) all analyses based on seasonally grouped data. Temporal, spatial and vector relationships are established for each season using scatter plot graphs and Pearson correlations. The different relationships between the data are derived from corresponding wind data (i.e. data of the same day and time), in each dataset for wind speed and wind direction separately. No significant correlation (all p values>0.05) or signal is evident over time, or as the difference in distance changes. However, seasonality is represented consistently in the wind vector distribution heat maps. Significant findings include the observations of anomalous north westerly winds in summer at the RAO, where the CLIWOC data did not pick up similar data for the corresponding region on the west coast. Historical wind data used herein prove to be reliable by the expected seasonal synoptic flow patterns and characteristics seen in each study region. There is no correlation between the datasets over time and space and the data do not present any clear signals or return events over time. Although corresponding data do not show any correlations, there are typical synoptic flow regimes in each study region which prove that wind data was recorded correctly. Therefore, the datasets are mutually exclusive, but accurate in their intrinsic value. It is only the anomalous summer north westerlies at the RAO which question the reliability of the data, as the same wind regimes were not identifiable in the corresponding CLIWOC data. This anomaly was noted but not studied further. This project highlights the major inconsistencies and limitations in the CLIWOC data. Researchers in the future should use CLIWOC data appropriately to suit the research question and be aware of the inconsistencies that may introduce noise.
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    Spatio-temporal effects of projected climate on future crop suitability over West Africa
    (2020) Egbebiyi, Temitope Samuel; Crespo, Olivier; Lennard, Chris
    Future climate is projected to deviate from present-day by unprecedented measure, hereafter climate departure, with direct consequences on food security. West Africa, one of the hotspots for climate departure globally, has suffered significantly from climate change impacts via extreme events with large impacts on food production. A better understanding of the impact of climate departure on crop growth suitability and planting season is still unknown and is highly needed in West Africa, owing to its high vulnerability and low adaptive capacity. This thesis developed a methodology aimed at defining the cropping system to investigate the projected timing of climate departures from historical variability and their impact on crop growth suitability over West Africa. For the study we used 4 statistically downscaled Global Climate Models, GCMs at station level for the period 1951- 2100 under RCP8.5 across the three AgroEcological Zones (AEZs) of West Africa for eight crops, cassava, maize, mango, orange, pearl millet, plantain, pineapple and tomato. Climate variables minimum mean monthly temperature and total monthly precipitation were used as input crop suitability model, Ecocrop to develop a new approach to define and characterise cropping systems departure from their normal regime, called crop-climate departure (CCD), to better understand the timing of future changes in crop suitability. Also, the concept of CCD was defined, tested and applied in West Africa for five different crops types, using 10 GCMs downscaled by regional climate model, RCA4 as input into crop suitability model Ecocrop. The downscaled GCMs were also employed to examine the impact at the different global warming levels, 1.5, 2.0 and 3.0oC on crop suitability over West Africa. Using the GCMs at station level, we develop the concept of crop-climate used in characterizing the suitability of different crop across the three AEZs of West Africa. The result highlights the constraint, a reduction in suitable area, of growing cassava and pineapple only in the Guinea zone by mid and end of century. In contrast, there is an observed and projected opportunity, increase in suitable areas, of growing maize in southern Sahel by the end of the century while mango remains suitable across the three West African AEZs. The application applying the concept crop-climate departure on different crop types showed in decrease suitable areas for most crops by the end of century with horticultural, cassava and cereals respectively are the crops mostly affected. The changes in crop-climate relationship suggests a future constraint in crop suitability could be detrimental to future food security over West Africa. Finally, our findings from the impact of different global warming levels, 1.5. 2.0 and 3.0oC highlights the potential of sustained suitability for all the crops and improved food security under 1.5oC global warming for all the six crops but a contrast under 3oC over West Africa except for cowpea and groundnut. Our findings for cowpea and groundnut showed an increase suitable area into the southern Sahel with increasing global warming level. The study holds great value at regional scale where improved preparedness and regional cohesion could make the difference in making decision for a food secure Africa. Further studies to explore associated short and long-term adaptation options to changes in crop-climate relationship are recommended.
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    The synoptic drivers of extreme rainfall in South Africa
    (2013) Morison, David; Hewitson, Bruce; Lennard, Chris
    A number of studies have shown an increase in the intensity of extreme rainfall over many regions of South Africa during the last 50 to 100 years. However, the weather of a region at any given time is a direct function of the synoptic state of the atmosphere at that particular time. This thesis identifies synoptic states associated with extreme rainfall at a regional scale over South Africa and also investigates trends in extreme rainfall characteristics. Using 31 years of rainfall station data across South Africa, days which experienced extreme rainfall events, defined as the 95th and 99th percentile, were identified. These were then matched against mean sea-level pressure and 500hPa geopotential height circulation patterns obtained from the Climate Forecast System Reanalysis (CFSR) dataset to investigate the driving synoptics of extreme rainfall. Self-organizing maps (SOMs) were used to characterize the synoptic circulations on a general country-wide scale as well as for 8 different regional rainfall regimes at a seasonal scale. Synoptic circulations associated with extreme rainfall events often involved an interaction between more than one synoptic feature such as a linkage between a sub-tropical low pressure system and a mid-latitude cyclone or a ridging high pressure and a continental low pressure. Some features known for contributing towards a significant amount of extreme rainfall events such as cut-off lows in the south-western parts of the country were poorly characterized by the regional SOMs. This may be attributed to the spatial boundaries adopted in this study and suggests general rainfall regimes developed for South Africa are not appropriate for extreme rainfall analyses. Trends in extreme rainfall were assessed in the observed station data with the RClimDex software package and used ten extreme rainfall indices. Apart from the Simple Daily Intensity Index (SDII), which identified a number of significantly increasing trends amongst various stations throughout the country, very few significant trends were identified in the remaining indices. This may be attributed to the infrequent nature of extreme rainfall events and the relatively short 31 year study period. It was, however, discovered that 4 stations with significantly increasing trends in extreme rainfall were paired with synoptic circulations associated with extreme rainfall in the summer rainfall regime that had also experienced significantly increasing trends. Thus the characteristics of extreme rainfall identified in the station data have been associated with the driving synoptic scale circulations and their changing characteristics. However, the generalized regional rainfall regimes identified across South Africa are not appropriate for the study of extreme rainfall synoptic drivers. Here an event-based analysis would provide better insight to the attributes of specific extreme rainfall driving synoptics as well as providing an improved assessment of regional extreme rainfall.
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    Verification of gridded seasonal wind speed forecasts over South Africa.
    (2013) Nchaba, Teboho; Marquard, Andrew; Lennard, Chris
    The Climate System Analysis Group (CSAG) at the University of Cape Town produces provisional global and Southern African seasonal wind forecasts generated using the United Kingdom Meteorological Office Atmospheric General Circulation Model (AGCM) HadAM3P (non-standard version of HadAM3). This study examines the quality of the seasonal wind speed forecasts through a forecast verification process for continuous variables using reanalysis products of the National Centers for Environmental Prediction and the Department of Energy (NCEP-DOE) as observations data. The verification analyses are performed using summary measures Mean Error (ME), Mean Absolute Error (MAE), Mean Squared Error (MSE), correlation coefficients, Linear Error in Probability Space (LEPS) and exploratory methods, scatter and conditional quantile plots. These methods are used to determine the aspects of forecast quality namely, bias, accuracy, reliability, resolution, and skill over a 20 year period (1991 to 2010). The results of the study have determined that the use of both accuracy and skill measures for the verification analyses provide more information about the quality of the forecasts, as opposed only one of these. In all provinces, the highest quality seasonal wind speed forecasts are made at 500 hPa and the lowest quality forecasts at 1000 hPa. Furthermore regions, pressure levels, and seasons with the highest forecast quality share the common characteristic that their wind speeds are relatively high. The forecasts add value to the climatology and thus are a useful tool for wind assessment at a seasonal scale. It is suggested that adding spatial resolution to the forecasts through downscaling may prepare them for use in applications such as wind power output forecasting.