Developing government policies for distance education: lessons learnt from two Sri Lankan case studies

Education, especially higher education, is considered vital for maintaining national and individual competitiveness in the global knowledge economy. Following the introduction of its “Free Education Policy” as early as 1947, Sri Lanka is now the best performer in basic education in the South Asian region, with a remarkable record in terms of high literacy rates and the achievement of universal primary education. However, access to tertiary education is a bottleneck, due to an acute shortage of university places. In an attempt to address this problem, the government of Sri Lanka has invested heavily in information and communications technologies (ICTs) for distance education. Although this has resulted in some improvement, the authors of this article identify several barriers which are still impeding successful participation for the majority of Sri Lankans wanting to study at tertiary level. These impediments include the lack of infrastructure/resources, low English language proficiency, weak digital literacy, poor quality of materials and insufficient provision of student support. In the hope that future implementations of ICT-enabled education programmes can avoid repeating the mistakes identified by their research in this Sri Lankan case, the authors conclude their paper with a list of suggested policy options.

Toward seamless prediction: calibration of climate change projections using seasonal forecasts

The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979– 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.