Andy Wood – författare

Things that are good for the planet are also good for business. Numerous studies from the likes of the Economist Intelligence Unit, Harvard, MIT Sloan, and others indicate that organizations that commit to goals of zero waste, zero harmful emissions, and zero use of nonrenewable resources clearly outperform their competition.Like lean thinking, greening your business is not just a ‘nice to have’; at least not anymore. It is now a key economic driver for many forward looking firms. This book is packed with case studies and examples that illustrate how leading firms use lean and green as simultaneous sources of inspiration in various sectors of industry - from automotive and retail to textile and brewing. Take Toyota as an example, the holy grail of economic efficiency for decades. This book, shows that Toyota tops the green chart too, describing Toyota’s notion of Monozukuri: sustainable manufacturing.Creating a Lean and Green Business System: Techniques for Improving Profits and Sustainability offers opportunities for innovation that can simultaneously reduce dependence on natural resources and enhance global prosperity. It explores less understood aspects of lean and green – discussing their evolution independently as well as the opportunities that exist in their integration, highlighting the importance of a cultural shift across the whole company.Outlining a systematic way to eliminate harmful waste while generating green value, the book explains how to:

Creating a Lean and Green Business System: Techniques for Improving Profits and Sustainability supplies a new way of thinking that will allow you to boost improvement efforts and create a positively charged work environment – while contributing to the long-term well-being of the environment.

Hydrometeorological prediction involves the forecasting of the state and variation of hydrometeorological elements -- including precipitation, temperature, humidity, soil moisture, river discharge, groundwater, etc.-- at different space and time scales. Such forecasts form an important scientific basis for informing public of natural hazards such as cyclones, heat waves, frosts, droughts and floods. Traditionally, and at most currently operational centers, hydrometeorological forecasts are deterministic, “single-valued” outlooks: i.e., the weather and hydrological models provide a single best guess of the magnitude and timing of the impending events. These forecasts suffer the obvious drawback of lacking uncertainty information that would help decision-makers assess the risks of forecast use. Recently, hydrometeorological ensemble forecast approaches have begun to be developed and used by operational hydrometeorological services. In contrast to deterministic forecasts, ensemble forecasts are a multiple forecasts of the same events. The ensemble forecasts are generated by perturbing uncertain factors such as model forcings, initial conditions, and/or model physics. Ensemble techniques are attractive because they not only offer an estimate of the most probable future state of the hydrometeorological system, but also quantify the predictive uncertainty of a catastrophic hydrometeorological event occurring. The Hydrological Ensemble Prediction Experiment (HEPEX), initiated in 2004, has signaled a new era of collaboration toward the development of hydrometeorological ensemble forecasts. By bringing meteorologists, hydrologists and hydrometeorological forecast users together, HEPEX aims to improve operational hydrometeorological forecast approaches to a standard that can be used with confidence by emergencies and water resources managers. HEPEX advocates a hydrometeorological ensemble prediction system (HEPS) framework that consists of several basic building blocks. These components include:(a) an approach (typically statistical) for addressing uncertainty in meteorological inputs and generating statistically consistent space/time meteorological inputs for hydrological applications; (b) a land data assimilation approach for leveraging observation to reduce uncertainties in the initial and boundary conditions of the hydrological system; (c) approaches that address uncertainty in model parameters (also called ‘calibration’); (d) a hydrologic model or other approach for converting meteorological inputs into hydrological outputs; and finally (e) approaches for characterizing hydrological model output uncertainty. Also integral to HEPS is a verification system that can be used to evaluate the performance of all of its components. HEPS frameworks are being increasingly adopted by operational hydrometeorological agencies around the world to support risk management related to flash flooding, river and coastal flooding, drought, and water management. Real benefits of ensemble forecasts have been demonstrated in water emergence management decision making, optimization of reservoir operation, and other applications.