Testing E-OBS European high-resolution gridded data set of daily precipitation and surface temperature

Gridded data sets derived through interpolation of station data have a number of potential inaccuracies and errors. These errors can be introduced either by the propagation of errors in the station data into derived gridded data or by limitations in the ability of the interpolation method to estimate grid values from the underlying station network. Recently, Haylock et al. (2008) reported on the development of a new high-resolution gridded data set of daily climate over Europe (termed E-OBS). E-OBS is based on the largest available pan-European data set, and the interpolation methods used were chosen after careful evaluation of a number of alternatives, yet the data set will inevitably have errors and uncertainties. In this paper we assess the E-OBS data set with respect to: (1) homogeneity of the gridded data; (2) evaluation of inaccuracies arising from available network density, through comparison with existing data sets that have been developed with much denser station networks; and (3) the accuracy of the estimates of interpolation uncertainty that are provided as part of E-OBS. We find many inhomogeneities in the gridded data that are primarily caused by inhomogeneities in the underlying station data. In the comparison of existing data with E-OBS, we find that while correlations overall are high, relative differences in precipitation are large, and usually biased toward lower values in E-OBS. From the analysis of the interpolation uncertainties provided as part of E-OBS, we conclude that the interpolation standard deviation provided with the data significantly underestimates the true interpolation error when cross validated using station data, and therefore will similarly underestimate the interpolation error in the gridded E-OBS data. While E-OBS represents a valuable new resource for climate research in Europe, users of the data need to be aware of the limitations in the data set and use the data appropriately

Designing for Digital Reading

Reading is a complex human activity that has evolved, and co-evolved, with technology over thousands of years. Mass printing in the fifteenth century firmly established what we know as the modern book, with its physical format of covers and paper pages, and now-standard features such as page numbers, footnotes, and diagrams. Today, electronic documents are enabling paperless reading supported by eReading technologies such as Kindles and Nooks, yet a high proportion of users still opt to print on paper before reading. This persistent habit of "printing to read" is one sign of the shortcomings of digital documents -- although the popularity of eReaders is one sign of the shortcomings of paper. How do we get the best of both worlds?The physical properties of paper (for example, it is light, thin, and flexible) contribute to the ease with which physical documents are manipulated; but these properties have a completely different set of affordances to their digital equivalents. Paper can be folded, ripped, or scribbled on almost subconsciously -- activities that require significant cognitive attention in their digital form, if they are even possible. The nearly subliminal interaction that comes from years of learned behavior with paper has been described as lightweight interaction, which is achieved when a person actively reads an article in a way that is so easy and unselfconscious that they are not apt to remember their actions later.Reading is now in a period of rapid change, and digital text is fast becoming the predominant mode of reading. As a society, we are merely at the start of the journey of designing truly effective tools for handling digital text.This book investigates the advantages of paper, how the affordances of paper can be realized in digital form, and what forms best support lightweight interaction for active reading. To understand how to design for the future, we review the ways reading technology and reader behavior have both changed and remained constant over hundreds of years. We explore the reasoning behind reader behavior and introduce and evaluate several user interface designs that implement these lightweight properties familiar from our everyday use of paper.We start by looking back, reviewing the development of reading technology and the progress of research on reading over many years. Drawing key concepts from this review, we move forward to develop and test methods for creating new and more effective interactions for supporting digital reading. Finally, we lay down a set of lightweight attributes which can be used as evidence-based guidelines to improve the usability of future digital reading technologies. By the end of this book, then, we hope you will be equipped to critique the present state of digital reading, and to better design and evaluate new interaction styles and technologies