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E-raamat: Spatial Interpolation for Climate Data: The Use of GIS in Climatology and Meteorology

Edited by (Institute of Alpine Geography, Joseph Fourier University, Grenoble, France), Edited by (Institute of Meteorology and Water Management of Krakow), Edited by (Institute of Meteorology and Geodynamics of Vienna)
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  • Ilmumisaeg: 01-Mar-2013
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781118614990
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Spatial Interpolation for Climate Data: The Use of GIS in Climatology and MeteorologySuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 01-Mar-2013
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781118614990
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The 2001-06 COST 719 European research program was charged with establishing interfaces between GIS (geographical information systems) and data in climatology and meteorology. Here are most of the presentations made at the final conference, in Grenoble in July 2006. After looking generally at the three fields and interactions between them, and at the spatialization of meteorological and climatological elements, they describe demonstration projects and suggest climate-related applications. Topics include the daily mapping of fire risk, winter road maintenance, and assessing population exposure to odorous pollution from a landfill over complex terrain. Annotation ©2007 Book News, Inc., Portland, OR (booknews.com)

This compilation of papers—presented during the COST European program entitled “The Use of GIS in Climatology and Meteorology”—focuses on the applications of geographic software and data to interpolate climate and meteorology parameters. Issues such as spatial interpolation of climate parameters, environmental problems, and national meteorology institutes’ current demo projects are detailed and supplemented by practical application illustrations.


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.
Preface xv
Part
1. GIS to Manage and Distribute Climate Data
1(70)
GIS, Climatology and Meteorology
3(22)
Antonio Perdigao
GIS technology and spatial data (working group 1)
3(4)
Introduction
3(1)
Weather and GIS
4(1)
Geographical data, environmental data and weather data
5(1)
A GIS approach to access weather data
6(1)
Data and metadata
7(8)
Introduction
7(1)
Important datasets
7(2)
Metadata
9(1)
Dpen Geospatial Consortium
10(1)
EU strategies for data handling and standards
10(2)
Meteorological datasets, important projects and programs
12(1)
Projects using Earth Observation satellites
13(2)
Interoperability
15(8)
Introduction
15(1)
Technology for service-oriented architectures
16(1)
Interoperability in GIS
17(1)
Open Geospatial Consortium foundation ideas
18(1)
Standardized geospatial Web services
19(2)
GIS and AS interoperability potential: data model and formats
21(1)
Atmospheric data model
21(2)
Support from GIS for atmospheric data formats
23(1)
Conclusions
23(1)
Bibliography
24(1)
SIGMA: A Web-based GIS for Environmental Applications
25(10)
Carlos Frederico Angelis
Fabiano Morelli
Luiz Augusto Toledo Machado
Cintia Pereira De Freitas
Introduction
25(1)
CPTEC-INPE
26(1)
SIGMA
27(2)
Basic functions
29(1)
Impacts of weather conditions on the economy
29(1)
Severe Weather Observation System (SOS)
29(2)
Tracking of convective clouds
30(1)
Risk of lightning occurrence
30(1)
SOS interface
31(2)
Conclusions
33(1)
Acknowledgements
34(1)
Bibliography
34(1)
Web Mapping: Different Solutions using GIS
35(10)
Pawel Madej
Malgorzata Barszczynska
Danuta Kubacka
Introduction
35(1)
Examples of Web mapping based on the usage of GIS technology in offline mode
36(2)
Examples of Web mapping using GIS tools in online mode
38(5)
Conclusion
43(1)
Bibliography
44(1)
Comparison of Geostatistical and Meteorological Interpolation Methods (What is What?)
45(12)
Tamas Szentimrey
Zita Bihari
Sandor Szalai
Introduction
45(1)
Mathematical statistical model of spatial interpolation
46(2)
Statistical parameters
46(1)
Linear meteorological model for expected values
47(1)
Linear regression formula
47(1)
Geostatistical interpolation methods
48(2)
Ordinary kriging formula
48(1)
Universal kriging formula
49(1)
Modeling of unknown statistical parameters in geostatistics
50(1)
Meteorological interpolation
50(2)
Meteorological interpolation formula
50(1)
Possibility of modeling unknown statistical parameters in meteorology
51(1)
Difference between geostatistics and meteorology
52(1)
Software and connection of topics
52(2)
Example of the MISH application
54(2)
Bibliography
56(1)
Uncertainty from Spatial Sampling: A Case Study in the French Alps
57(14)
Pierre Dumolard
Introduction
57(1)
The sample as a whole
58(3)
Looking in detail where the sample is not representative
61(2)
Summarizing the sampling uncertainty
63(6)
2D simplification
63(1)
3D generalization
64(2)
Geographic homogenous sub-regions of the sample
66(2)
Interpolation of a climate parameter
68(1)
Conclusion
69(1)
Bibliography
70(1)
Part
2. Spatial Interpolation of Climate Data
71(68)
The Developments in Spatialization of Meteorological and Climatological Elements
73(14)
Ole Einar Tveito
Introduction
73(1)
Spatialization
74(1)
Why Spatialization?
74(1)
The role of GIS in developing Spatialization within climatology
75(1)
Methodology
76(1)
Data representativity, quality and reliability
77(3)
Applications
80(2)
Spatialization of temperature
81(1)
Spatialization of precipitation
81(1)
Climate indices
82(1)
Gridded datasets
83(1)
Recommendations and future outlook
84(2)
Choose the right method
84(1)
Correct use of the method
84(1)
Test several methods
84(1)
Validation
84(1)
The future
85(1)
Bibliography
86(1)
The Spatial Analysis of the Selected Meteorological Fields in the Example of Poland
87(10)
Izabela Dyras
Zbigniew Ustrnul
Introduction
87(2)
Spatialization problems using standard observation data
89(2)
Spatialization using remote sensing data
91(4)
Conclusions
95(1)
Acknowledgements
95(1)
Bibliography
96(1)
Optimizing the Interpolation of Temperatures by GIS: A Space Analysis Approach
97(12)
Jean-Christophe Loubier
Limits of the interpolation in a heterogenous space
97(1)
Optimizing the spatial distribution of the stations
98(1)
Underlying space assumptions
98(1)
Theoretical structure of our model
99(1)
Information management in GIS
99(1)
The process of linear modeling for the selected factors
100(1)
Determination of the optimal positioning of P
101(1)
An example of implementation
101(1)
Consequences and spatial/structural understanding
102(1)
Determination of authorized spaces
103(1)
Constraints
103(1)
Factors
103(1)
Taking uncertainty into account: a choice/given couple
104(1)
The standardization process
105(1)
Results for the addition of stations
105(1)
Authorized interpolators
106(1)
Conclusion
106(1)
Bibliography
107(2)
Daily Winter Air Temperature Mapping in Mountainous Areas
109(12)
Remi Lhotellier
Introduction
109(1)
GIS and climatic data
110(2)
Spatialization of air temperature on a daily scale
112(5)
Temperature maps (local scale)
117(2)
Conclusion
119(1)
Bibliography
119(2)
Aspects Concerning the Spatialization of Radiation balance Components
121(18)
Cristian Valeriu Patriche
Introduction
121(7)
Comparison of the models
128(8)
Bibliography
136(3)
Part
3. Demo Projects
139(74)
The Use of GIS Applications in Meteorology and Climatology: A Need for the Application of Regional Ecological Modeling Approaches
141(14)
Martin Wegehenkel
Introduction
141(1)
Overview of the actual state of the art of GIS applications in meteorology and climatology
142(1)
GIS applications in meteorology and climatology and regional ecological modeling approaches
143(8)
Quality check of meteorological data
144(3)
Regional application of an ecological model
147(4)
Conclusions
151(2)
Acknowledgements
153(1)
Bibliography
153(2)
GIS Application to Daily Fire Risk Mapping
155(10)
Alvaro Silva
Introduction
155(1)
Methodology
156(2)
Conjuncture Fire Index (CFI)
156(1)
Fire Weather Index (FWI)
156(2)
Fire risk mapping
158(1)
Results: some examples
158(1)
FWI map
158(1)
CFR map
158(1)
Adding spatial statistics
159(1)
Conclusion
159(5)
Bibliography
164(1)
Application of GIS Technology on the Comparisons of Climatological Databases: An Overview of Winter Precipitation over Spain
165(14)
M.Y. Luna
M.L. Martin
M.G. Sotillo
C. Almarza
F. Valero
J. De La Cruz
Introduction
165(1)
Data and methodology
166(2)
Results
168(1)
Summary and conclusions
169(1)
Acknowledgements
170(1)
Bibliography
171(8)
Drought Sensitivity Research in Hungary and Influence of Climate Change on Drought Sensitivity
179(10)
Sandor Szalai
Szabolcs Bella
Akos Nemeth
Introduction
179(2)
The climate of Hungary
181(1)
Method
182(5)
Soil parameters
182(1)
Mineral content
183(1)
Soil texture
183(1)
Water management
183(1)
Topsoil thickness
184(1)
Organic content
184(1)
Type of rock
184(1)
Precipitation
184(1)
Groundwater
184(1)
Land use
185(1)
Slope and aspect
185(2)
Conclusion
187(1)
Acknowledgements
188(1)
Bibliography
188(1)
First Steps Towards a New Temperature Climatology of the Greater Alpine Region (GAR)
189(10)
Wolfgang Schoner
Ingeborg Auer
Reinhard Bohm
Introduction
189(1)
Data
190(4)
Spatialization
194(1)
Summary and outlook
194(2)
Acknowledgements
196(1)
Bibliography
197(2)
XRWIS: A New GIS Paradigm for Winter Road Maintenance
199(14)
John E. Thornes
Lee Chapman
Steve White
Introduction
199(1)
The current RWIS paradigm in the UK
200(2)
Next generation road weather information systems: XRWIS
202(1)
Verification
203(1)
Conclusion
204(1)
Bibliography
205(8)
Part
4. Climate-related Applications
213(64)
The Use of GIS in Climatology: Challenges in Fine Scale Applications: Examples in Agrometeorological and Urban Climate Studies
215(12)
Claude Kergomard
Aim and context
215(1)
GIS challenges in fine scale applications
216(1)
First challenge: handle, homogenize and archive ``atmospheric information''
216(1)
Second challenge: handle, synthesize and prepare ``geographical information''
216(1)
Third challenge: spatial interpolation of climatological/air quality data
216(1)
Fourth challenge: GIS-based spatial interpolation
217(1)
Examples of application in agrometeorology
217(4)
Spring frost hazard in the Champagne vineyard
218(2)
Towards interpolation in a fruit orchard at the scale of pieces of land
220(1)
Urban studies examples
221(3)
Urban heat island in the Lille metropolitan area
221(1)
GIS-based analysis of urban fabric for use in urban climatology
222(2)
Acknowledgements
224(1)
Bibliography
224(3)
Climate Impact on the Winter Land Use and Land Cover Management in Brittany
227(16)
S. Corgne
H. Quenol
O. Planchon
T. Corpetti
Introduction
227(1)
Climate characteristics of the study area
228(5)
Site description
228(1)
Meteorological information
229(1)
Meteorological data
229(1)
Space-time variability analysis of precipitation on the Scorff watershed using the three reference stations
230(1)
Relationships between precipitation space-time variability and land cover management
231(2)
Impact of the climate characteristics in the land cover prediction model
233(6)
Presentation of the land cover prediction model
233(1)
Presentation of the DST and DSmT
233(2)
Change prediction design and results of the land cover prediction with DST and DSmT
235(2)
Integration of the climate variable in the land cover prediction model
237(1)
Mass function affectation of the climatic factor
237(1)
Results of the land cover prediction with the integration of the climate variable
238(1)
Conclusion
239(1)
Acknowledgements
240(1)
Bibliography
240(3)
A Tool for the Integrated Use of Remote Sensing with Ground Truth Data: DEMETER Project
243(10)
A. Perdigao
A. Jochum
A. Calera
L. Pessanha
A. Chinita
J. Maia
Introduction
243(1)
Methodology used on the project
244(1)
Product line methodology
245(3)
Report and data from the field campaigns
248(3)
Conclusion
251(1)
Acknowledgements
251(1)
Bibliography
251(2)
Assessing Population Exposure to Odorous Pollution from a Landfill over Complex Terrain
253(12)
Caroline Riesenmey
Charles Chemel
Herve Vaillant
Mireille Batton-Hubert
Introduction
253(1)
Model set-up
254(6)
Description of the landfill area
254(1)
Meteorological modeling
254(2)
Terrain data
256(1)
Orography
256(2)
Land use
258(2)
Model results
260(2)
Case study: 17 August 2002
260(1)
Map of the population exposure
260(2)
Conclusion
262(1)
Acknowledgements
262(1)
Bibliography
263(2)
Disaggregated Estimation of N2O Fluxes from Agricultural Soils of the Italian Region by Modelization in GIS Environment
265(12)
Anna Carfora
Simona Castaldi
Marco Vigliotti
Riccardo Valentini
Introduction
265(2)
Data sources and methods
267(4)
Methods applied for N2O flux calculation
267(1)
Applied models
267(4)
Results and discussion
271(4)
Bibliography
275(2)
List of Authors 277(6)
Index 283


Hartwig Dobesch is a Professor at the Institute of Meteorology and Geodynamics of Vienna, specializing in meteorology and climatology. He is also President of the COST European research program "The use of GIS in climatology and meteorology". Pierre Dumolard is a Professor at the Institute of Alpine Geography, Joseph Fourier University, Grenoble, France.

Izabela Dyras is the leader of the Satellite Research Department in the Institute of Meteorology and Water Management of Krakow. She is the Vice-President of the COST European research program "The use of GIS in climatology and meteorology".
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