Conclusion

Author(s):  
Huug van den Dool

In this book we have reviewed empirical methods in short-term climate prediction. We devoted a whole chapter to the design of two of these methods, Empirical Wave Propagation (EWP, Chapter 3) and Constructed Analogue (CA Chapter 7). Other methods of empirical prediction were listed in Chapter 8, with brief descriptions and examples and references. One chapter is devoted to EOFs, as such a diagnostic topic, but widely used in both prediction and diagnostics, and thoroughly debated for a few decades. Two brief chapters, written in support of the subsequent chapter, Teleconnections (Chapter 4), should make the discussion on EOFs more interesting, and the topic of effective degrees of freedom (Chapter 6) is indispensable when one wants to understand why and when natural analogues would work (or not), or how an analogue is constructed, or how any method using truncation works. Most chapters can be read largely in isolation, but connections can be made of course between chapters. EWP is claimed to be useful, if not essential, in understanding teleconnections. Dispersion experiments, featuring day-by-day time-scales, link the CA and EWP methods. Examples of El Nino boreal winter behavior can be found in (a) the examples of EOFs on global SST and 500 mb streamfunction (Chapter 5), (b) specification of surface weather from 500 mb streamfunction (Chapter 7), and (c) the ENSO correlation and compositing approach (Chapter 8). The noble pursuit of knowledge may have been as important in the choice of some material as any immediate prediction application. Chapter 9 is different, less research oriented, and more an eyewitness description of what goes on in the making of a seasonal prediction. This eyewitness account style spills over into Chapter 8 here and there, because in order to understand why certain methods have survived to this day some practicalities have to be understood. The closeness to real-time prediction throughout the book creates a sense of application. However, the application in this book does not go beyond the making of the forecast itself; we completely shied away from such topics as a cost/benefit analysis or decision-making process by, for example, a climate sensitive potato farmer or reservoir operator.

Author(s):  
Huug van den Dool

How many degrees of freedom are evident in a physical process represented by f(s, t)? In some form questions about “degrees of freedom” (d.o.f.) are common in mathematics, physics, statistics, and geophysics. This would mean, for instance, in how many independent directions a weight suspended from the ceiling could move. Dofs are important for three reasons that will become apparent in the remaining chapters. First, dofs are critically important in understanding why natural analogues can (or cannot) be applied as a forecast method in a particular problem (Chapter 7). Secondly, understanding dofs leads to ideas about truncating data sets efficiently, which is very important for just about any empirical prediction method (Chapters 7 and 8). Lastly, the number of dofs retained is one aspect that has a bearing on how nonlinear prediction methods can be (Chapter 10). In view of Chapter 5 one might think that the total number of orthogonal directions required to reproduce a data set is the dof. However, this is impractical as the dimension would increase (to infinity) with ever denser and slightly imperfect observations. Rather we need a measure that takes into account the amount of variance represented by each orthogonal direction, because some directions are more important than others. This allows truncation in EOF space without lowering the “effective” dof very much. We here think schematically of the total atmospheric or oceanic variance about the mean state as being made up by N equal additive variance processes. N can be thought of as the dimension of a phase space in which the atmospheric state at one moment in time is a point. This point moves around over time in the N-dimensional phase space. The climatology is the origin of the phase space. The trajectory of a sequence of atmospheric states is thus a complicated Lissajous figure in N dimensions, where, importantly, the range of the excursions in each of the N dimensions is the same in the long run. The phase space is a hypersphere with an equal probability radius in all N directions.


2011 ◽  
pp. 57-78
Author(s):  
I. Pilipenko

The paper analyzes shortcomings of economic impact studies based mainly on input- output models that are often employed in Russia as well as abroad. Using studies about sport events in the USA and Olympic Games that took place during the last 30 years we reveal advantages of the cost-benefit analysis approach in obtaining unbiased assessments of public investments efficiency; the step-by-step method of cost-benefit analysis is presented in the paper as well. We employ the project of Sochi-2014 Winter Olympic and Paralympic Games in Russia to evaluate its efficiency using cost-benefit analysis for five accounts (areas of impact), namely government, households, environment, economic development, and social development, and calculate the net present value of the project taking into account its possible alternatives. In conclusion we suggest several policy directions that would enhance public investment efficiency within the Sochi-2014 Olympics.


2007 ◽  
pp. 70-84 ◽  
Author(s):  
E. Demidova

This article analyzes definitions and the role of hostile takeovers at the Russian and European markets for corporate control. It develops the methodology of assessing the efficiency of anti-takeover defenses adapted to the conditions of the Russian market. The paper uses the cost-benefit analysis, where the costs and benefits of the pre-bid and post-bid defenses are compared.


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