A simultaneous analysis of 13 years of remotely sensed data of land cover, fires, precipitation, and aerosols from the MODIS, TRMM, and MISR satellites and the AERONET network over Southeast Asia is performed, leading to a set of robust relationships between land-use change and fire being found on inter-annual and intra-annual scales over Southeast Asia, reflecting the heavy amounts of anthropogenic influence over land-use change and fires in this region of the world.

Anthropogenic aerosols are a key factor governing Earth’s climate, and play a central role in human-caused climate change. However, because of aerosols’ complex physical, optical, and dynamical properties, aerosols are one of the most uncertain aspects of climate modeling. Fortunately, aerosol measurement networks over the past few decades have led to the establishment of long-term observations for numerous locations worldwide.

Sustainable development of Indian cities is an essential pre-requisite for India to establish itself as a major economic power. Smart cities dwell on energyefficient urban centres. The National Action Plan on Climate Change and the recently formulated plan for Smart Cities emphasize the need for energy efficiency. However, inadequate domestic finance and lack of public support impose sizeable constraints. (Scientific Correspondence)

There is an ongoing debate on whether the observed decadal variations in surface solar radiation, known as "dimming and brightening", are a global or just local phenomenon. We investigated this issue using a comprehensive set of long-term sunshine duration records from China, which experienced a rapid growth in urbanization during past decades. 172 pairs of urban and nearby rural stations were analyzed over the period 1960–1989 ("dimming phase") and 1990–2013 ("brightening phase").

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming.