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Climate change is today's news, but it isn't a new phenomenon. Centuries-long cycles of heating and cooling are well documented for Europe and the North Atlantic. These variations in climate, including the Medieval Warm Period (MWP), AD 900 to 1300, and the early centuries of the Little Ice Age (LIA), AD 1300 to 1600, had a substantial impact on the cultural history of Europe. In this pathfinding volume, William C. Foster marshals extensive evidence that the heating and cooling of the MWP and LIA also occurred in North America and significantly affected the cultural history of Native peoples of the American Southwest, Southern Plains, and Southeast. Correlating climate change data with studies of archaeological sites across the Southwest, Southern Plains, and Southeast, Foster presents the first comprehensive overview of how Native American societies responded to climate variations over seven centuries. He describes how, as in Europe, the MWP ushered in a cultural renaissance, during which population levels surged and Native peoples substantially intensified agriculture, constructed monumental architecture, and produced sophisticated works of art. Foster follows the rise of three dominant cultural centers-Chaco Canyon in New Mexico, Cahokia on the middle Mississippi River, and Casas Grandes in northwestern Chihuahua, Mexico-that reached population levels comparable to those of London and Paris. Then he shows how the LIA reversed the gains of the MWP as population levels and agricultural production sharply declined; Chaco Canyon, Cahokia, and Casas Grandes collapsed; and dozens of smaller villages also collapsed or became fortresses.

This book goes to the heart of the unfolding reality of the twenty-first century: international efforts to reduce greenhouse gas emissions have all failed, and before the end of the century Earth is projected to be warmer than it has been for 15 million years. The question \"can the crisis be avoided?\" has been superseded by a more frightening one, \"what can be done to prevent the devastation of the living world?\" And the disturbing answer, now under wide discussion both within and outside the scientific community, is to seize control of the very climate of the Earth itself. Clive Hamilton begins by exploring the range of technologies now being developed in the field of geoengineering--the intentional, enduring, large-scale manipulation of Earth's climate system. He lays out the arguments for and against climate engineering, and reveals the extent of vested interests linking researchers, venture capitalists, and corporations. He then examines what it means for human beings to be making plans to control the planet's atmosphere, probes the uneasiness we feel with the notion of exercising technological mastery over nature, and challenges the ways we think about ourselves and our place in the natural world.

The West without Water documents the tumultuous climate of the American West over twenty millennia, with tales of past droughts and deluges and predictions about the impacts of future climate change on water resources. Looking at the region’s current water crisis from the perspective of its climate history, the authors ask the central question of what is “normal” climate for the West, and whether the relatively benign climate of the past century will continue into the future. The West without Water merges climate and paleoclimate research from a wide variety of sources as it introduces readers to key discoveries in cracking the secrets of the region’s climatic past. It demonstrates that extended droughts and catastrophic floods have plagued the West with regularity over the past two millennia and recounts the most disastrous flood in the history of California and the West, which occurred in 1861–62. The authors show that, while the West may have temporarily buffered itself from such harsh climatic swings by creating artificial environments and human landscapes, our modern civilization may be ill-prepared for the future climate changes that are predicted to beset the region. They warn that it is time to face the realities of the past and prepare for a future in which fresh water may be less reliable.

This Intergovernmental Panel on Climate Change Special Report (IPCC-SREX) explores the challenge of understanding and managing the risks of climate extremes to advance climate change adaptation. Extreme weather and climate events, interacting with exposed and vulnerable human and natural systems, can lead to disasters. Changes in the frequency and severity of the physical events affect disaster risk, but so do the spatially diverse and temporally dynamic patterns of exposure and vulnerability. Some types of extreme weather and climate events have increased in frequency or magnitude, but populations and assets at risk have also increased, with consequences for disaster risk. Opportunities for managing risks of weather- and climate-related disasters exist or can be developed at any scale, local to international. Prepared following strict IPCC procedures, SREX is an invaluable assessment for anyone interested in climate extremes, environmental disasters and adaptation to climate change, including policymakers, the private sector and academic researchers.

Global warming skeptics often fall back on the argument that the scientific case for global warming is all model predictions, nothing but simulation; they warn us that we need to wait for real data, \"sound science.\" In A Vast Machine Paul Edwards has news for these doubters: without models, there are no data. Today, no collection of signals or observations--even from satellites, which can \"see\" the whole planet with a single instrument--becomes global in time and space without passing through a series of data models. Everything we know about the world's climate we know through models. Edwards offers an engaging and innovative history of how scientists learned to understand the atmosphere--to measure it, trace its past, and model its future. Edwards argues that all our knowledge about climate change comes from three kinds of computer models: simulation models of weather and climate; reanalysis models, which recreate climate history from historical weather data; and data models, used to combine and adjust measurements from many different sources. Meteorology creates knowledge through an infrastructure (weather stations and other data platforms) that covers the whole world, making global data. This infrastructure generates information so vast in quantity and so diverse in quality and form that it can be understood only by computer analysis--making data global. Edwards describes the science behind the scientific consensus on climate change, arguing that over the years data and models have converged to create a stable, reliable, and trustworthy basis for the reality of global warming.

This study examines environmental disasters in the Levant. The data is drawn from contemporary sources. The main aim is to determine the long and short-term repercussions of environmental disasters on the regional affairs during the Crusader, Ayyubid and Mamluk periods.

An autonomous vehicle must accurately detect its surrounding environment to operate reliably. Adverse weather conditions (ADWC) are snow, rain, sand, and haze, badly affect the quality of vehicle detection (VD) in an autonomous environment. Most existing techniques focused on VD under various weather effects such as signal control, travel pattern, traffic volume variations and collision risk. Only a limited number of works of literature were focused on VD under ADWC at different automation scales. In this paper, a novel deep learning (DL) model, Optimized You Look Only Once Version 5 (OYOLOV5), is proposed for autonomous VD (AVD) in ADWC. The proposed model consists of three phases: data collection, data preprocessing, feature extraction and classification. Initially, the data is collected from the DAWN and COCO dataset to perform VD, which is openly available. The augmentation of the data is carried out on the collected input data by including hue, saturation, blur, brightness, and noise, which helps to get a clear view of vehicles. After data augmentation, feature extraction and classification of the preprocessed images are done using the OYOLOV5 framework, which uses Resnet-50 as the backbone network and Feature Pyramid Network (FPN) for detecting the vehicles at multi-scales. Experiments are conducted, and the outcomes demonstrated the proposed OYOLOV5 model achieves better performance with the state-of-art methods in terms of precision (PRC), recall (RC), f-measure (FMS), accuracy (ACU), average IoU (AI), processing speed (PS), and training time (TTI). Also, the system attains good mean average precision (mAP) than the conventional methods.

The past 15 years have seen marked progress in observing, understanding, and predicting weather.At the same time, the United States has failed to match or surpass progress in operational numerical weather prediction achieved by other nations and failed to realize its prediction potential; as a result, the nation is not mitigating weather impacts.