Spatial Interpolation for Climate Data E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 346

Veröffentlichungsjahr: 2013

Beschreibung

This title gives an authoritative look at the use of Geographical Information Systems (GIS) in climatology and meterology. GIS provides a range of strategies, from traditional methods, such as those for hydromet database analysis and management, to new developing methods. As such, this book will provide a useful reference tool in this important aspect of climatology and meterology study.

Leseprobe

Table of Contents

Preface

Part 1. GIS to Manage and Distribute Climate Data

Chapter 1. GIS, Climatology and Meteorology

1.1. GIS technology and spatial data (working group 1)

1.2. Data and metadata

1.3. Interoperability

1.4. Conclusions

1.5. Bibliography

Chapter 2. SIGMA: A Web-based GIS for Environmental Applications

2.1. Introduction

2.2. CPTEC-INPE

2.3. SIGMA

2.4. Impacts of weather conditions on the economy

2.5. Severe Weather Observation System (SOS)

2.6. SOS interface

2.7. Conclusions

2.8. Acknowledgements

2.9. Bibliography

Chapter 3. Web Mapping: Different Solutions using GIS

3.1. Introduction

3.2. Examples of Web mapping based on the usage of GIS technology in offline mode

3.3. Examples of Web mapping using GIS tools in online mode

3.4. Conclusion

3.5. Bibliography

Chapter 4. Comparison of Geostatistical and Meteorological Interpolation Methods (What is What?)

4.1. Introduction

4.2. Mathematical statistical model of spatial interpolation

4.3. Geostatistical interpolation methods

4.4. Meteorological interpolation

4.5. Software and connection of topics

4.6. Example of the MISH application

4.7. Bibliography

Chapter 5. Uncertainty from Spatial Sampling: A Case Study in the French Alps

5.1. Introduction

5.2. The sample as a whole

5.3. Looking in detail where the sample is not representative

5.4. Summarizing the sampling uncertainty

5.5. Conclusion

5.6. Bibliography

Part 2. Spatial Interpolation of Climate Data

Chapter 6. The Developments in Spatialization of Meteorological and Climatological Elements

6.1. Introduction

6.2. Spatialization

6.3. Why spatialization?

6.4. The role of GIS in developing spatialization within climatology

6.5. Methodology

6.6. Data representativity, quality and reliability

6.7. Applications

6.8. Climate indices

6.9. Gridded datasets

6.10. Recommendations and future outlook

6.11. Bibliography

Chapter 7. The Spatial Analysis of the Selected Meteorological Fields in the Example of Poland

7.1. Introduction

7.2. Spatialization problems using standard observation data

7.3. Spatialization using remote sensing data

7.4. Conclusions

7.5. Acknowledgements

7.6. Bibliography

Chapter 8. Optimizing the Interpolation of Temperatures by GIS: A Space Analysis Approach

8.1. Limits of the interpolation in a heterogenous space

8.2. Optimizing the spatial distribution of the stations

8.3. Underlying space assumptions

8.4. Theoretical structure of our model

8.5. The process of linear modeling for the selected factors

8.6. Determination of the optimal positioning of P

8.7. An example of implementation

8.8. Consequences and spatial/structural understanding

8.9. Determination of authorized spaces

8.10. Taking uncertainty into account: a choice/given couple

8.11. The standardization process

8.12. Results for the addition of stations

8.13. Authorized interpolators

8.14. Conclusion

8.15. Bibliography

Chapter 9. Daily Winter Air Temperature Mapping in Mountainous Areas

9.1. Introduction

9.2. GIS and climatic data

9.3. Spatialization of air temperature on a daily scale

9.4. Temperature maps (local scale)

9.5. Conclusion

9.6. Bibliography

Chapter 10. Aspects Concerning the Spatialization of Radiation Balance Components

10.1. Introduction

10.2. Comparison of the models

10.3. Bibliography

Part 3. Demo Projects

Chapter 11. The Use of GIS Applications in Meteorology and Climatology: A Need for the Application of Regional Ecological Modeling Approaches.

11.1. Introduction

11.2. Overview of the actual state of the art of GIS applications in meteorology and climatology

11.3. GIS applications in meteorology and climatology and regional ecological modeling approaches

11.4. Conclusions

11.5. Acknowledgements

11.6. Bibliography

Chapter 12. GIS Application to Daily Fire Risk Mapping

12.1. Introduction

12.2. Methodology

12.3. Results: some examples

12.4. Conclusion

12.5. Bibliography

Chapter 13. Application of GIS Technology on the Comparisons of Climatological Databases: An Overview of Winter Precipitation over Spain

13.1. Introduction

13.2. Data and methodology

13.3. Results

13.4. Summary and conclusions

13.5. Acknowledgements

13.6. Bibliography

Chapter 14. Drought Sensitivity Research in Hungary and Influence of Climate Change on Drought Sensitivity

14.1. Introduction

14.2. The climate of Hungary

14.3. Method

14.4. Conclusion

14.5. Acknowledgements

14.6. Bibliography

Chapter 15. First Steps Towards a New Temperature Climatology of the Greater Alpine Region (GAR)

15.1. Introduction

15.2. Data

15.3. Spatialization

15.4. Summary and outlook

15.5. Acknowledgements

15.6. Bibliography

Chapter 16. XRWIS: A New GIS Paradigm for Winter Road Maintenance

16.1. Introduction

16.2. The current RWIS paradigm in the UK

16.3. Next generation road weather information systems: XRWIS

16.4. Verification

16.5. Conclusion

16.6. Bibliography

Part 4. Climate-related Applications

Chapter 17. The Use of GIS in Climatology: Challenges in Fine Scale Applications: Examples in Agrometeorological and Urban Climate Studies

17.1. Aim and context

17.2. GIS challenges in fine scale applications

17.3. Examples of application in agrometeorology

17.4. Urban studies examples

17.5. Acknowledgements

17.6. Bibliography

Chapter 18. Climate Impact on the Winter Land Use and Land Cover Management in Brittany

18.1. Introduction

18.2. Climate characteristics of the study area

18.3. Impact of the climate characteristics in the land cover prediction model

18.4. Conclusion

18.5. Acknowledgements

18.6. Bibliography

Chapter 19. A Tool for the Integrated Use of Remote Sensing with Ground Truth Data: DEMETER Project

19.1. Introduction

19.2. Methodology used on the project

19.3. Product line methodology

19.4. Report and data from the field campaigns

19.5. Conclusion

19.6. Acknowledgements

19.7. Bibliography

Chapter 20. Assessing Population Exposure to Odorous Pollution from a Landfill over Complex Terrain

20.1. Introduction

20.2. Model set-up

20.3. Model results

20.4. Conclusion

20.5. Acknowledgements

20.6. Bibliography

Chapter 21. Disaggregated Estimation of N2O Fluxes from Agricultural Soils of the Italian Region by Modelization in GIS Environment

21.1. Introduction

21.2. Data sources and methods

21.3. Results and discussion

21.4. Bibliography

List of Authors

Index

First published in Great Britain and the United States in 2007 by ISTE Ltd

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

ISTE Ltd6 Fitzroy SquareLondon W1T 5DXUK

ISTE USA4308 Patrice RoadNewport Beach, CA 92663USA

www.iste.co.uk

© ISTE Ltd, 2007

The rights of Hartwig Dobesch, Pierre Dumolard and Izabela Dyras to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Cataloging-in-Publication Data

Spatial interpolation for climate data: the use of GIS in climatology and meteorology/edited by Hartwig Dobesch, Pierre Dumolard, Izabela Dyras.

p. cm.

Includes bibliographical references and index.

ISBN 978-1-905209-70-5

1. Climatology--Data processing. 2. Meteorology--Data processing. 3. Geospatial data--Mathematical models. 4. Geographic information systems. 5. Spatial data infrastructures. I. Dobesch, Hartwig. II. Dumolard, Pierre. III. Dyras, Izabela.

QC874.3.S63 2007

551.60285--dc22

2007012743

British Library Cataloguing-in-Publication Data

A CIP record for this book is available from the British Library

ISBN: 978-1-905209-70-5

Preface

The COST 719 European research program (“The use of GIS in climatology and meteorology”) began in 2001 and ended in 2006. 20 European countries participated. Its main objective was to establish interfaces between GIS and data in climatology and meteorology and in order to reach this objective, three working groups were defined:

– working group 1 on “Data access and data availability”;

– working group 2 on “Spatial interpolation”;

– working group 3 on “GIS applications”.

Most of the applications have focused on three climate parameters: temperature, precipitation and energy balance in the fields of climatology, meteorology and environmental sciences.

This book is the proceedings of most of the presentations made during the final conference of the COST 719 action (Grenoble, July 2006). It comprises four parts, each one introduced by a keynote speaker.

Part 1 is devoted to GIS use in meteorology and climatology. It is introduced by a text underlining that GIS is a mature technology to integrate, analyze and display spatial data but is still scarcely used in most Meteorological Services, partly due to the lack of an atmospheric data model (meteorology has its own operational infrastructure). A major concern is the share of terrain data in Europe (INSPIRE initiative) and the definition of a common metadata standard.

Four other contributions complete this first part.

– SIGMA is a currently running GIS (in Brazil) dedicated to real-time information (precipitation, temperature, lightning, NDVI, ozone, etc.) and alerts.

– A paper on webmapping of climatological and meteorological data compares ARC-IMS, open standards and Scalable Vector Graphics approaches.

– MISH (Meteorological Interpolation method) has been developed in Hungary. Geostatistical methods are based on one realization whereas MISH incorporates, in order to model the statistical parameters, climatic spatio-temporal information.

– A simple GIS study of the northern French Alps meteorological network shows that its statistical robustness is not evenly distributed, so that the sample should be stratified and the uncertainty regionalized.

Part 2 is dedicated to the spatial interpolation of climatological parameters. It is introduced by a chapter showing the developments in spatialization of meteorological and climatological parameters. Interpolation methods, which are present in most GIS, make it possible to combine numerous layers to derive estimates of parameters for any place at any time.

– The first application, in Poland, tests several methods for interpolating air temperatures, precipitation and cloudiness. The results for the temperature are correct, whereas the two other ones are in fact much more complicated to interpolate.

– Two following applications deal with the spatialization of (mean or average) temperatures in the northern parts of the French Alps. The measuring network is dense but still not dense enough to derive very good estimates for any place at any time (especially with anticyclonic weather).

– The last application discusses several methods for the spatialization of the radiation balance. It also examines the possibility to derive land surface albedo from satellite images.

Part 3 is devoted to demonstration projects. It is introduced by an overview of ready-to-use demos. The chapter insists on the need for relevant meteorological and climatological data for environmental users, presenting links and connections between simulation models developed by ecologists and hydrologists on the one hand, applications by meteorologists and climatologists on the other hand.

– The first demo deals with daily fire risk mapping in Portugal, combining structural elements (number of fires, burnt areas, vegetation, biomass accumulation, climatic variables) with weather forecasts for the next 24 and 48 hours.

– The second demo compares, in Spain, a high resolution precipitation database with one created by dynamic downscaling; the statistical analysis shows a good similarity in terms of spatiotemporal distribution and total precipitation.

– The third demo is devoted to simulating drought sensitivity in southern Hungary under the hypothesis of climate change and assessing that damages will depend more on vulnerability than on events themselves.

– The fourth demo presents the ALP-IMP project where the monthly temperature fields of the Greater Alpine Region were calculated back to 1760. In the new ECSN-HRT-GAR project, monthly climatology fields are modeled according to quality checked normals for about 1,700 stations. In its final stage, monthly grids (1 km² pixels) will be produced.

– The fifth demo presents the RWIS (Road Weather Information System) for the winter maintenance of roads. Road weather forecasts use sensors, sky view factor analysis and mesoscale weather forecasts. An energy balance model (IceMiser) has been tested on 12,000 locations of 6 roads in England.

Part 4 is dedicated to environmental problems, which are strongly related to climate. It is introduced by a chapter presenting the challenges in fine scale applications, with examples in agrometeorology and urban climatology.

– In regions (like Brittany) with an intensive agriculture, transfer of pollutants into water resources partly depends on land use management during winter (bare or cultivated soils). A predictive model at the piece of land scale, based on the Dezert-Smarandache theory, proved an 82% success rate.

– The DEMETER project has been set up to facilitate the water management (quantity and quality) for irrigated farming in southern Europe. Pilot studies have been carried out using agricultural surveys, satellite images and weather and climate data, showing the possible improved management of cultures in Mediterranean areas.

– Olfactive nuisances around landfill sites are usually associated with certain meteorological situations. To evaluate the population exposure, a metamodel has been built, combining a local meteorological model (ARPS with nested domains), terrain data and a specific Eulerian dispersion model.

– The last application deals with the estimated disaggregation of N2O fluxes due to agricultural soils in Italy (N2O has a warming potential 275 times greater than CO2 and has a very long life). The disaggregation procedure was conducted with land use, environment and climate data.

Hartwig Dobesch

Pierre Dumolard

Izabela Dyras

Part 1

GIS to Manage and Distribute Climate Data

Chapter 1

GIS, Climatology and Meteorology1

1.1. GIS technology and spatial data (working group 1)

1.1.1. Introduction

In the framework of the COST program, COST-719 addresses the spread of knowledge and skills concerning Geographical Information Systems (GIS) or, specifically, spatial data management within the climatological and meteorological community. GIS can offer a practical and relevant working environment for the integration, analysis and visualization of this data together with other spatial data sources. Within most National Meteorological Services (NMS) the acceptance of commercial GIS tools beyond climatology is still a cumbersome process, which is partly caused by the shortcomings underlying the data model (time aspects!) and partly by the lack of knowledge of applicable GIS methods. Another reason is that atmospheric science is more concerned with the question of why phenomena happen and less with the region where they happen [PET 01].