Note: 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 -- 7.2. Systematic bias for regional means -- 7.3. Autocorrelation -- 7.4. Cyclical components -- 7.5. Threshold distance for spatial comparisons -- 7.6. Synchronous and semi-synchronous inhomogeneities -- 7.7. Short-term inhomogeneities -- 7.8. Weather dependent inhomogeneities -- 7.9. Homogenization of probability distribution -- 7.10. Temporal resolution of homogenization results -- 7.11. Wide applicability of additive inhomogeneity model -- References -- Chapter 8: A selection of statistical homogenization methods -- 8.1. Methods using accumulated anomalies -- 8.2. SNHT (Standard Normal Homogeneity Test) -- 8.3. RHtests (Relative Homogenization Tests) -- 8.4. MASH (Multiple Analysis of Series for Homogenization) -- 8.5. PHA (Pairwise Homogenization Algorithm) -- 8.6. Climatol -- 8.7. PRODIGE. , 8.8. HOMER (HOMogenization softwarE in R) -- 8.9. ACMANT (Applied Caussinus-Mestre Algorithm for homogenizing Networks of climatic Time series) -- 8.10. Homogenization methods for particular climatic elements -- References -- Chapter 9: Accuracy of homogenization results -- 9.1. Concepts of benchmarking -- 9.2. Construction of benchmark datasets -- 9.3. Efficiency measures -- 9.4. Limitations of the reliability of test results -- 9.5. Tests for break detection methods -- 9.6. HOME benchmark experiments -- 9.7. MULTITEST benchmark experiments -- 9.8. Tests for the accuracy of homogenized daily data -- 9.9. Tests with observed data -- 9.10. Tasks for the future -- References -- Chapter 10: Use of quality controlled and homogenized data -- 10.1. Weather forecast and weather alarms -- 10.2. Climate modeling -- 10.3. Use of homogenized data: For which purposes is it advantageous? -- 10.4. Climate research -- 10.5. Climate services -- 10.6. Adaptation to climate change -- References -- Appendix: Basic statistical concepts -- Reference -- Further reading -- Index.