Effect of Currency Fluctuations on the Economic Growth Potential of Nigeria

The exchange rate is one of the most important determinants of a country's relative level of economic health. This study examines the effect of currency fluctuations on the economic growth potential of Nigeria using the World Bank Development Indicators data from 1970-2012. The study through the Augmented Dickey Fuller (ADF)/ unit root test found that the variables used in the model are integrated of the order one while export and interest rate are integrated of the order zero. Using the Johansen co integration tests shows the presence of long run relationship between variables. The Error Correction Model (ECM) results suggest that exchange rate has a negative significant impact on GDP in the short run and long run. The study therefore recommends that the competitiveness and stability of the exchange rate should be given due consideration as this will increase economic growth through increased investment. Keywords: Exchange rate, Economic growth, ADF, ECM, Nigeri

Sensitivity of Surface Urban Energy and Water Balance Scheme (SUEWS) to downscaling of reanalysis forcing data

Often the meteorological forcing data required for urban hydrological models are unavailable at the required temporal resolution or for the desired period. Although reanalysis data can provide this information, the spatial resolution is often coarse relative to cities, so downscaling is required prior to use as realistic forcing. In this study, WATCH WFDEI reanalysis data are used to force the Surface Urban Energy and Water Balance Scheme (SUEWS). From sensitivity tests in two cities, Vancouver and London with different orography, we conclude precipitation is the most important meteorological variable to be properly downscaled to obtain reliable surface hydrology results, with relative humidity being the second most important. Overestimation of precipitation in reanalysis data at the three sites gives 6-21% higher annual modelled evaporation, 26-39% higher runoff at one site and 4% lower value at one site when compared to modelled values using observed forcing data. Application of a bias correction method to the reanalysis precipitation reduces the model bias compared to using observed forcing data, when evaluated using eddy covariance evaporation measurements. (c) 2017 Elsevier B.V. All rights reserved.Often the meteorological forcing data required for urban hydrological models are unavailable at the required temporal resolution or for the desired period. Although reanalysis data can provide this information, the spatial resolution is often coarse relative to cities, so downscaling is required prior to use as realistic forcing. In this study, WATCH WFDEI reanalysis data are used to force the Surface Urban Energy and Water Balance Scheme (SUEWS). From sensitivity tests in two cities, Vancouver and London with different orography, we conclude precipitation is the most important meteorological variable to be properly downscaled to obtain reliable surface hydrology results, with relative humidity being the second most important. Overestimation of precipitation in reanalysis data at the three sites gives 6-21% higher annual modelled evaporation, 26-39% higher runoff at one site and 4% lower value at one site when compared to modelled values using observed forcing data. Application of a bias correction method to the reanalysis precipitation reduces the model bias compared to using observed forcing data, when evaluated using eddy covariance evaporation measurements. (c) 2017 Elsevier B.V. All rights reserved.Often the meteorological forcing data required for urban hydrological models are unavailable at the required temporal resolution or for the desired period. Although reanalysis data can provide this information, the spatial resolution is often coarse relative to cities, so downscaling is required prior to use as realistic forcing. In this study, WATCH WFDEI reanalysis data are used to force the Surface Urban Energy and Water Balance Scheme (SUEWS). From sensitivity tests in two cities, Vancouver and London with different orography, we conclude precipitation is the most important meteorological variable to be properly downscaled to obtain reliable surface hydrology results, with relative humidity being the second most important. Overestimation of precipitation in reanalysis data at the three sites gives 6-21% higher annual modelled evaporation, 26-39% higher runoff at one site and 4% lower value at one site when compared to modelled values using observed forcing data. Application of a bias correction method to the reanalysis precipitation reduces the model bias compared to using observed forcing data, when evaluated using eddy covariance evaporation measurements. (c) 2017 Elsevier B.V. All rights reserved.Peer reviewe

Key Parameters for Urban Heat Island Assessment in A Mediterranean Context: A Sensitivity Analysis Using the Urban Weather Generator Model

Although Urban Heat Island (UHI) is a fundamental effect modifying the urban climate, being widely studied, the relative weight of the parameters involved in its generation is still not clear. This paper investigates the hierarchy of importance of eight parameters responsible for UHI intensity in the Mediterranean context. Sensitivity analyses have been carried out using the Urban Weather Generator model, considering the range of variability of: 1) city radius, 2) urban morphology, 3) tree coverage, 4) anthropogenic heat from vehicles, 5) building’s cooling set point, 6) heat released to canyon from HVAC systems, 7) wall construction properties and 8) albedo of vertical and horizontal surfaces. Results show a clear hierarchy of significance among the considered parameters; the urban morphology is the most important variable, causing a relative change up to 120% of the annual average UHI intensity in the Mediterranean context. The impact of anthropogenic sources of heat such as cooling systems and vehicles is also significant. These results suggest that urban morphology parameters can be used as descriptors of the climatic performance of different urban areas, easing the work of urban planners and designers in understanding a complex physical phenomenon, such as the UHI

Low-cost wind resource assessment for small-scale turbine installations using site pre-screening and short-term wind measurements

A two-stage approach to low-cost wind resource assessment for small-scale wind installations has been investigated in terms of its ability to screen for non-viable sites and to provide accurate wind power predictions at promising locations. The approach was implemented as a case study at ten UK locations where domestic-scale turbines were previously installed. In stage one, sites were pre-screened using a boundary-layer scaling model to predict the mean wind power density, including estimated uncertainties, and these predictions were compared to a minimum viability criterion. Using this procedure, five of the seven non-viable sites were correctly identified without direct onsite wind measurements and none of the viable sites were excluded. In stage two, more detailed analysis was carried out using 3 months onsite wind measurements combined with measure-correlate-predict (MCP) approaches. Using this process, the remaining two non-viable sites were identified and the available wind power density at the three viable sites was accurately predicted. The effect of seasonal variability on the MCPpredicted wind resource was considered and the implications for financial projections were highlighted. The study provides a framework for low-cost wind resource assessment in cases where long-term onsite measurements may be too costly or impractical