Skill and economic benefits of dynamical downscaling of ECMWF ENSEMBLE seasonal forecast over southern Africa with RegCM4

2015 ◽  
Vol 36 (2) ◽  
pp. 675-688 ◽  
Author(s):  
Gulilat Tefera Diro
Keyword(s):  
Southern Africa ◽  
Dynamical Downscaling ◽  
Seasonal Forecast ◽  
Economic Benefits

scholarly journals A Policy Review of Green Hydrogen Economy in Southern Africa

2021 ◽  
Vol 13 (23) ◽  
pp. 13240
Author(s):  
Katundu Imasiku ◽  
Fortunate Farirai ◽  
Jane Olwoch ◽  
Solomon Nwabueze Agbo
Keyword(s):  
Renewable Energy ◽  
Energy Policy ◽  
Southern Africa ◽  
Energy Transition ◽  
Clean Energy ◽  
Economic Benefits ◽  
Energy Resources ◽  
Policy Framework ◽  
Hydrogen Energy ◽  
Renewable Energy Resources

Renewable energy and clean energy have been on the global agenda for energy transition for quite a long time but recently gained strong momentum, especially with the anticipated depletion of fossil fuels alongside increasing environmental degradation from their exploitation and the changing climate caused by their excessive carbon emissions. Despite this, Africa’s pursuit to transition to a green economy using renewable energy resources still faces constraints that hamper further development and commercialization. These may include socio-economic, technical, political, financial, and institutional policy framework barriers. Although hydrogen demand is still low in Southern Africa, the region can meet the global demands for green hydrogen as a major supplier because of its enormous renewable energy resource-base. This article reviews existing renewable energy resources and hydrogen energy policies in the Southern African Development Community (SADC). The significance of this review is that it explores how clean energy technologies that utilize renewable energy resources address the United Nations sustainable development goals (UN SDGs) and identifies the hydrogen energy policy gaps. This review further presents policy options and recommends approaches to enhance hydrogen energy production and ramp the energy transition from a fossil fuel-based economy to a hydrogen energy-based economy in Southern Africa. Concisely, the transition can be achieved if the existing hydrogen energy policy framework gap is narrowed by formulating policies that are specific to hydrogen development in each country with the associated economic benefits of hydrogen energy clearly outlined.

Dynamical Downscaling of Austral Summer Climate Forecasts over Southern Africa Using a Regional Coupled Model

2013 ◽  
Vol 26 (16) ◽  
pp. 6015-6032 ◽  
Author(s):  
J. V. Ratnam ◽  
S. K. Behera ◽  
S. B. Ratna ◽  
C. J. de W. Rautenbach ◽  
C. Lennard ◽  
...  
Keyword(s):  
South Africa ◽  
Mixed Layer ◽  
Southern Africa ◽  
General Circulation ◽  
Dynamical Downscaling ◽  
Wrf Model ◽  
Ocean Model ◽  
Seasonal Forecasts ◽  
Climate Forecasts ◽  
Precipitation Anomalies

Abstract The prediction skill of dynamical downscaling is evaluated for climate forecasts over southern Africa using the Advanced Research Weather Research and Forecasting (WRF) model. As a case study, forecasts for the December–February (DJF) season of 2011/12 are evaluated. Initial and boundary conditions for the WRF model were taken from the seasonal forecasts of the Scale Interaction Experiment-Frontier Research Center for Global Change (SINTEX-F) coupled general circulation model. In addition to sea surface temperature (SST) forecasts generated by nine-member ensemble forecasts of SINTEX-F, the WRF was also configured to use SST generated by a simple mixed layer Price–Weller–Pinkel ocean model coupled to the WRF model. Analysis of the ensemble mean shows that the uncoupled WRF model significantly increases the biases (errors) in precipitation forecasted by SINTEX-F. When coupled to a simple mixed layer ocean model, the WRF model improves the spatial distribution of precipitation over southern Africa through a better representation of the moisture fluxes. Precipitation anomalies forecasted by the coupled WRF are seen to be significantly correlated with the observed precipitation anomalies over South Africa, Zimbabwe, southern Madagascar, and parts of Zambia and Angola. This is in contrast to the SINTEX-F global model precipitation anomaly forecasts that are closer to observations only for parts of Zimbabwe and South Africa. Therefore, the dynamical downscaling with the coupled WRF adds value to the SINTEX-F precipitation forecasts over southern Africa. However, the WRF model yields positive biases (>2°C) in surface air temperature forecasts over the southern African landmass in both the coupled and uncoupled configurations because of biases in the net heat fluxes.

DYNAMICAL DOWNSCALING OF SEASONAL CLIMATE IN SOUTHERN AFRICA

2015 ◽  
pp. 265-279
Author(s):  
J. VENKATA RATNAM ◽  
SATYABAN B. RATNA ◽  
SWADHIN K. BEHERA ◽  
C. J. deW. RAUTENBACH ◽  
KEIKO TAKAKASHI ◽  
...  
Keyword(s):  
Southern Africa ◽  
Dynamical Downscaling ◽  
Seasonal Climate

Understanding TQM implementation barriers involving construction companies in a difficult environment

2019 ◽  
Vol 36 (7) ◽  
pp. 1137-1158 ◽  
Author(s):  
Richard Stuart Dilawo ◽  
Zahra Salimi
Keyword(s):  
Southern Africa ◽  
Construction Projects ◽  
Road Construction ◽  
Business Environment ◽  
Economic Benefits ◽  
Implementation Barriers ◽  
Content Type ◽  
Construction Companies ◽  
Implementation Practices

Purpose The purpose of this paper is to identify the factors that affect TQM implementation in construction companies and it suggests solutions for TQM implementation in a difficult environment. Design/methodology/approach Studies were carried out at six large construction companies who ply their trade in Southern Africa and in-depth investigations were conducted to assess TQM implementation practices and associated TQM barriers. Interviews were conducted on directors and key personnel that play important roles in TQM implementation in their respective organisations. The empirical study also utilised a number of organisational documents which added rigour to the findings. Findings This study identified three core categories and ten main barriers affecting TQM implementation in Southern Africa construction companies. The core categories are motivation, infrastructure and penchants and tendencies while the factors are lack of quality support, poor TQM knowledge and TQM awareness, poor information sharing, temporary workers, overdependence on contract document, poor data collection measurement, undefined TQM roles and responsibilities, award to lowest bidder tendency, poor business environment and corruption. Research limitations/implications The study was conducted based on companies plying their trade in Southern Africa and mostly around Malawi, Zambia and Mozambique. It does not study companies in Namibia, Zimbabwe, Angola, South Africa and Botswana. Practical implications TQM cannot be exported wholly from another region to a new setting without taking into consideration the local factors associated with that setting. For successful TQM implementation in construction in Southern Africa, characteristics of this region have to be known. This study illuminates a number of TQM implementation barriers associated with construction especially applied to this difficult environment. Application of this knowledge would enhance TQM and heighten competitive advantage initiatives. The proportions highlighted in this study therefore help build up the TQM implementation awareness. Social implications At society level, the findings of this study indicate societal problems such as corruption and business environment which require wide level approaches to deal with these barriers. In addition, if TQM applied in road construction projects, the quality of the roads will be improved, this in turn will have direct impact on quality of life in the society, better roads means easier access to hospitals, schools and public places, better transport and movements of goods and services, etc. It can also save money for the country in long run and economic benefits to the society. Originality/value The factors identified in this study are based on current TQM implementation practices at established construction companies in Southern Africa. They provide a practical basis for guiding TQM in construction companies operating in difficult environments.

scholarly journals Toward a Regional-Scale Seasonal Climate Prediction System over Central Italy based on Dynamical Downscaling

Climate ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 120 ◽  
Author(s):  
Sangelantoni ◽  
Ferretti ◽  
Redaelli
Keyword(s):  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Scale ◽  
Central Italy ◽  
Seasonal Forecast ◽  
Added Value ◽  
Seasonal Forecasts ◽  
Adaptation Measures ◽  
Seasonal Climate ◽  
Forecast Lead Time

Anticipating seasonal climate anomalies is essential for defining short-term adaptation measures. To be actionable, many stakeholders require seasonal forecasts at the regional scale to be properly coupled to region-specific vulnerabilities. In this study, we present and preliminarily evaluate a regional-scale Seasonal Forecast System (SFS) over Central Italy. This system relies on a double dynamical downscaling performed through the Regional-scale Climate Model (RCM) RegCM4.1. A twelve-member ensemble of the NCEP-CFSv2 provides driving fields for the RegCM. In the first step, the RegCM dynamically downscales NCEP-CFSv2 predictions from a resolution of 100 to 60 km over Europe (RegCM-d1). This first downscaling drives a second downscaling over Central Italy at 12 km (RegCM-d2). To investigate the added value of the downscaled forecasts compared to the driving NCEP-CFSv2, we evaluate the driving CFS, and the two downscaled SFSs over the same (inner) domain. Evaluation involves winter temperatures and precipitations over a climatological period (1982–2003). Evaluation for mean bias, statistical distribution, inter-annual anomaly variability, and hit-rate of anomalous seasons are shown and discussed. Results highlight temperature physical values reproduction benefiting from the downscaling. Downscaled inter-annual variability and probabilistic metrics show improvement mainly at forecast lead-time 1. Downscaled precipitation shows an improved spatial distribution with an undegraded but not improved seasonal forecast quality.

Enhancing climate resilience using stress-tolerant maize in conservation agriculture in southern Africa.

2022 ◽  
pp. 230-245
Author(s):  
Peter Setimela ◽  
Isaiah Nyagumbo ◽  
Walter Mupangwa ◽  
Munyaradzi Mutenje
Keyword(s):  
Southern Africa ◽  
Smallholder Farmers ◽  
Conservation Agriculture ◽  
Growing Season ◽  
Economic Benefits ◽  
Maize Germplasm ◽  
Maize Cultivars ◽  
Climate Resilience ◽  
Drought Tolerant ◽  
Smart Agriculture

Abstract Recurrent and widespread droughts in southern Africa (SA) reduce agricultural productivity and increase food insecurity among smallholder farmers. The average growing-season temperatures are expected to increase by 2.5°C. In SA maize is a staple food, accounting for more than 30% of total calories. The crop is mostly grown by smallholder farmers with limited inputs of fertilizers and improved seed. Most of the maize cultivars grown by farmers are susceptible to heat and drought. Multi-stress-tolerant maize germplasm is one of the climate smart agriculture (CSA) components and, when used in combination with others, can sustainably increase production and resilience of agricultural systems. In this paper we review the performance and economic benefits of drought-tolerant maize cultivars under conventional monocropping practice, under conventional intercropping and in Conservation Agriculture (CA) as part of sustainable intensification to ensure food security for smallholder farmers.

scholarly journals A review of the main drivers and variability of Central America’s Climate and seasonal forecast systems

2018 ◽  
Vol 66 (1-1) ◽  
pp. 153 ◽  
Author(s):  
Tito Maldonado ◽  
Eric J. Alfaro ◽  
Hugo G. Hidalgo
Keyword(s):  
Climate Change ◽  
Natural Disasters ◽  
Central America ◽  
Natural Hazards ◽  
Dynamical Downscaling ◽  
Southern Oscillation ◽  
Human Life ◽  
Seasonal Prediction ◽  
Seasonal Forecast ◽  
The Impact

Central America is a region susceptible to natural disasters and climate change. We reviewed the literature on the main atmospheric and oceanographic forces and climate modulators affecting Central America, for different spatial and time scales. We also reviewed the reported correlation between climate variability, natural hazards and climate change aspects (in the past and future). In addition, we examined the current state of seasonal prediction systems being applied to the region. At inter-annual scales, El Niño/Southern Oscillation is the main climate modulator; however, other indices such as the Tropical North Atlantic, Atlantic Multi-Decadal Oscillation and Pacific Decadal Oscillation, have shown a correlation with precipitation anomalies in the region. Current seasonal forecast systems in the region have shown a constant development, including incorporation of different approaches ranging from statistical to dynamical downscaling, improving prediction of variables such as precipitation. Many studies have revealed the need of including –in addition to the climatic information– socio-economic variables to assess the impact of natural disasters and climate change in the region. These studies highlight the importance of socio-economic and human life losses associated with the impacts caused by natural hazards for organizations and governments. Rev. Biol. Trop. 66(Suppl. 1): S153-S175. Epub 2018 April 01. 

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