Climate observations : data quality control and time series homogenization

Climate observations : data quality control and time series homogenization /

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Bibliographic Details
Main Authors: Domonkos, Péter (Author), Tóth, Róbert (Author), Nyitrai, László (Author)
Corporate Author: ProQuest (Firm)
Format: Electronic eBook
Language:English
Published: Amsterdam ; Cambridge, MA : Elsevier, [2023]
Series:Developments in weather and climate science
Subjects:
Climatology > Observations.
Climatology > Statistical methods.
Online Access:Connect to this title online (unlimited simultaneous users allowed; 325 uses per year)
Table of Contents:
  • Intro
  • Climate Observations: Data Quality Control and Time Series Homogenization
  • Copyright
  • Contents
  • About the authors
  • Introduction
  • Chapter 1: Land surface observations
  • 1.1. Global system of weather and climate observations
  • 1.2. Site selection and installation of instruments
  • 1.3. Manual and automated observations
  • 1.4. Temperature
  • 1.5. Humidity
  • 1.6. Precipitation
  • 1.7. Wind direction and wind speed
  • 1.8. Atmospheric pressure
  • 1.9. Sunshine duration and radiation
  • 1.10. Cloudiness
  • 1.11. Other climate variables
  • 1.12. Calibration of instruments and maintenance
  • References
  • Chapter 2: Upper air observation and remote sensing
  • 2.1. Upper air observations: Climatic characteristics and tools for their observation
  • 2.2. Radiosondes I. Technology and performance of observations
  • 2.3. Radiosondes II. Spatial and temporal density of observations
  • 2.4. Remote sensing
  • 2.5. Weather radars
  • 2.6. Satellites in the observation of weather and climate
  • 2.7. Space-based observations
  • 2.8. Other upper air observations
  • 2.9. Closing notes to Chapter 1 and this chapter
  • References
  • Chapter 3: Data quality control and dataset development
  • 3.1. Error sources
  • 3.2. Kinds and indications of data errors
  • 3.3. Phases of quality control
  • 3.4. Elimination of data errors
  • 3.5. Quality control of extreme values
  • 3.6. Data rescue and digitation
  • 3.7. Data gaps and gap filling
  • 3.8. Data gridding
  • 3.9. Dataset development
  • References
  • Chapter 4: Homogenization task and its principal approaches
  • 4.1. Time series homogenization in the system of scientific fields
  • 4.2. Basic concepts of time series homogenization
  • 4.3. Kinds of inhomogeneities
  • 4.4. Kinds of homogenization tasks
  • 4.5. Spatial representativeness of homogenized climatic data
  • 4.6. Relation with general quality control
  • 4.7. Use of documented information (metadata)
  • 4.8. Homogeneity test
  • 4.9. Homogenization without neighbor series
  • References
  • Chapter 5: Relative homogenization: The basis
  • 5.1. Concept of relative homogenization
  • 5.2. Traditional approach
  • 5.3. Revolution of methodology from the 1990s
  • 5.4. Time series comparison
  • 5.5. Detection of trend inhomogeneities
  • 5.6. Detection of multiple break points
  • 5.7. Correction of inhomogeneities
  • References
  • Chapter 6: Relative homogenization: Optional tools
  • 6.1. Multistep procedures
  • 6.2. Iteration
  • 6.3. Parameterization
  • 6.4. Relative time series of daily resolution
  • 6.5. Ensemble homogenization
  • 6.6. Transformation of probability distribution
  • 6.7. Infilling data gaps within homogenization procedures
  • 6.8. Pairwise detection in automatic homogenization
  • 6.9. Multivariate detection
  • 6.10. Combination of homogenization methods
  • References
  • Chapter 7: Relative homogenization: Special problems
  • 7.1. Signal-to-noise ratio

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