An Investigation into the Pinnacle of Environment and Measures to Protect it with Special Reference to Renewable Energy as a Benison for Our Planet

Man does harm to the climate, water, ground, the different components of the world, and to nature itself, all round. There is just so much man-made waste and environmental destruction that the uncertainty waiting is sufficiently anxious to wake us up. A few developments are taking place from a climatologically standpoint of the overall scenario. Our national and regional climates are both highly polluted. In the densely developed elevations of the northern latitudes, the defensive ozone layer is fading twice as quickly as scientists assumed several years earlier. The accumulation of greenhouse emissions would contribute in the immediate term to major shifts in climate conditions due to global warming. The consequences of environmental degradation are on not only humans, but also on other living creatures as well as the natural world. The issue of environmental contamination and waste disposal will be discussed in this article. All that surrounds us is linked to the environment knowingly or unknowingly. The author of this paper is expressing in what condition our environment is now. What measures can be taken to preserve our environment? Furthermore, he discusses how renewable energy is a boon for our planet that may be proven to be a boon if individuals use it effectively.

Cushion plants as critical pioneers and engineers in alpine ecosystems across the Tibetan Plateau

Cushion plants are widely representative species of the alpine ecosystem due to their vital roles in the abiotic and biotic environments, ecological succession processes, and ecosystem engineering. Importantly, Cushion plants, such as Androsace L. and Arenaria L., can be regarded as critical pioneers of ecosystem health, restoration and sustainability across the Tibetan Plateau because these plants (i) exhibit tenacious vitality, regulate regional climates, substrates and soil nutrients and keep warmth in extreme regions; (ii) facilitate relationships with surrounding and maintain the diversity of above- and below-ground communities; and (iii) have high sensitivity to environmental changes, which can indicate grassland ecosystem health and resilience in the context of global change.

Generating Projections for the Caribbean at 1.5, 2.0, and 2.5 °C from a High-Resolution Ensemble

Six members of the Hadley Centre’s Perturbed Physics Ensemble for the Quantifying Uncertainty in Model Predictions (QUMP) project are downscaled using the PRECIS (Providing Regional Climates for Impact Studies) RCM (Regional Climate Model). Climate scenarios at long-term temperature goals (LTTGs) of 1.5, 2.0, and 2.5 °C above pre-industrial warming levels are generated for the Caribbean and six sub-regions for annual and seasonal timescales. Under a high emissions scenario, the LTTGs are attained in the mid-2020s, end of the 2030s, and the early 2050s, respectively. At 1.5 °C, the region is slightly cooler than the globe, land areas warmer than ocean, and for the later months, the north is warmer than the south. The far western and southern Caribbean including the eastern Caribbean island chain dry at 1.5 °C (up to 50%). At 2.0 °C, the warming and drying intensify and there is a reversal of a wet tendency in parts of the north Caribbean. Drying in the rainfall season accounts for much of the annual change. There is limited further intensification of the region-wide drying at 2.5 °C. Changes in wind strength in the Caribbean low-level jet region may contribute to the patterns seen. There are implications for urgent and targeted adaptation planning in the Caribbean.

Analog Models for Empirical-Statistical Downscaling

Global climate models (GCM) are fundamental tools for weather forecasting and climate predictions at different time scales, from intraseasonal prediction to climate change projections. Their design allows GCMs to simulate the global climate adequately, but they are not able to skillfully simulate local/regional climates. Consequently, downscaling and bias correction methods are increasingly needed and applied for generating useful local and regional climate information from the coarse GCM resolution. Empirical-statistical downscaling (ESD) methods generate climate information at the local scale or with a greater resolution than that achieved by GCM by means of empirical or statistical relationships between large-scale atmospheric variables and the local observed climate. As a counterpart approach, dynamical downscaling is based on regional climate models that simulate regional climate processes with a greater spatial resolution, using GCM fields as initial or boundary conditions. Various ESD methods can be classified according to different criteria, depending on their approach, implementation, and application. In general terms, ESD methods can be categorized into subgroups that include transfer functions or regression models (either linear or nonlinear), weather generators, and weather typing methods and analogs. Although these methods can be grouped into different categories, they can also be combined to generate more sophisticated downscaling methods. In the last group, weather typing and analogs, the methods relate the occurrence of particular weather classes to local and regional weather conditions. In particular, the analog method is based on finding atmospheric states in the historical record that are similar to the atmospheric state on a given target day. Then, the corresponding historical local weather conditions are used to estimate local weather conditions on the target day. The analog method is a relatively simple technique that has been extensively used as a benchmark method in statistical downscaling applications. Of easy construction and applicability to any predictand variable, it has shown to perform as well as other more sophisticated methods. These attributes have inspired its application in diverse studies around the world that explore its ability to simulate different characteristics of regional climates.

Hydropower impact on the river flow of a humid regional climate

Land use and water management have considerable impacts on regional climates. This paper proposes that in humid regions with low wind patterns the construction of hydropower storage reservoirs contributes to the increases in the probability of precipitation in the regional climate. This observation has been tested with a methodology that calculates the cumulative influence of reservoir construction in the basins surrounding with a proposed index named Cumulative Impact of Existing Reservoirs, and compares this index with the historical flow of the rivers. It was found that the construction of reservoirs in Brazil had a considerable impact on its river flows.

The Value of Ocean Decadal Climate Variability Information to United States Agriculture

Ocean-related decadal climate variability (ODCV) has the potential to influence regional climates and, in turn, crop yields. ODCV event forecasts with associated climate and crop yield implication information can provide farmers with the opportunity to alter their crop mixes and input usage to adapt to the forecast conditions. We investigate the value of ODCV information and the nature of adaptations. This is done by estimating the changes in welfare under differing information scenarios using a nonlinear dynamic optimization model. We find evidence that both perfect forecasts and the use of forecasts permitting a conditional probability of future phase combinations can significantly increase agriculture consumer and producer welfare. This is a new result that is an estimate of the US national value of releasing ODCV forecasts and accompanying yield information.