Precipitation science : measurement, remote sensing, microphysics and modeling /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Michaelides, Silas
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam : Elsevier, [2022]
Temas:
Precipitation (Meteorology)
Precipitation forecasting.
Pr�ecipitations (M�et�eorologie)
Pr�ecipitations (M�et�eorologie) > Pr�evision.
precipitation.
Precipitation forecasting
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover
  • Precipitation Science
  • Copyright Page
  • Dedication
  • Contents
  • List of contributors
  • Foreword
  • Preface
  • Related titles by Silas Michaelides
  • References
  • Credits
  • 1 Precipitation Measurement
  • 1 Accuracy assessment and intercomparison of precipitation measurement instruments
  • 1.1 Introduction
  • 1.2 Precipitation measurement biases
  • 1.2.1 Instrumental biases and calibration procedures for catching gauges
  • 1.2.1.1 Field calibration device
  • 1.2.2 Calibration of non-catching gauges
  • 1.3 Wind-induced bias of catching gauges
  • 1.3.1 Computational fluid dynamic simulations
  • 1.3.2 Particle tracking model and collection efficiency curves
  • 1.4 Intercomparison of precipitation measurement instruments
  • 1.5 Concluding remarks
  • References
  • 2 Application of underwater passive acoustic measurements of ocean sound in precipitation estimation
  • 2.1 Introduction
  • 2.2 Passive aquatic listening technology, methods, and data collection
  • 2.3 Acoustic data analysis
  • 2.3.1 Data collection
  • 2.3.2 Acoustic data and quality control processing
  • 2.3.2.1 Electronic filter correction
  • 2.3.2.2 Residual sensitivity correction
  • 2.3.2.3 Time series of acoustic parameters
  • 2.3.2.4 Classification analysis
  • 2.3.2.5 Acoustic wind speed measurement
  • 2.4 Acoustic precipitation analysis
  • 2.5 Case studies
  • 2.5.1 The Ionian Sea rainfall experiment
  • 2.5.1.1 Classification and validation procedure
  • 2.5.1.2 Assessment results: case study on March 12, 2004
  • 2.5.1.3 Spatial averaging of the rainfall signal
  • 2.5.2 The Aegean Sea experiment
  • 2.5.2.1 Marine mammal detection
  • 2.5.2.2 Shipping detection
  • 2.5.2.3 Sound budgets and acoustic summaries
  • 2.6 Concluding remarks
  • References
  • 3 Quality control and verification of precipitation observations, estimates, and forecasts
  • 3.1 Introduction.
  • 3.2 Quality control of observations from a rain gauge network
  • 3.2.1 Rain gauge errors
  • 3.2.2 Rain gauge data quality control
  • 3.2.3 Examples of implementation of procedures for quality control of rain gauge data
  • 3.2.4 Increasing rain gauge network density by applying other techniques
  • 3.3 Quality control of weather radar data
  • 3.3.1 Quality characterization of radar data
  • 3.3.2 Quality control of 3D radar data
  • 3.3.3 Quality control of 2D surface precipitation estimates
  • 3.3.4 Quality-based composition of 2D surface precipitation products
  • 3.4 Quality control of satellite observations
  • 3.4.1 Observations of precipitation from meteorological satellites
  • 3.4.2 Quality control of precipitation estimates based on satellite products
  • 3.5 Quality control of multisource surface precipitation estimates
  • 3.5.1 Multisource precipitation estimates
  • 3.5.2 Quality-based multisource precipitation estimation
  • 3.5.3 Example of merging
  • 3.6 Methods of evaluating the skill of forecasts
  • 3.6.1 Precipitation forecasts
  • 3.6.1.1 Introduction
  • 3.6.1.2 Errors in NWP modeling of precipitation
  • 3.6.1.3 Observational data
  • 3.6.1.4 Verifying models using observational data: synoptic stations, radars, and satellites
  • 3.6.1.5 Verification measures and methods
  • 3.6.2 Standard methods of forecast verification
  • 3.6.3 Spatial methods of forecast verification
  • 3.7 Conclusion
  • References
  • 4 Insights on a global Extreme Rainfall Detection System
  • 4.1 Introduction
  • 4.2 The Extreme Rainfall Detection System: input data
  • 4.2.1 Near real-time
  • 4.2.2 Forecast
  • 4.3 Extreme rainfall detection methodology
  • 4.4 Case studies
  • 4.5 Conclusion
  • Acknowledgments
  • References
  • 2 Precipitation Remote Sensing
  • 5 Evaluation of high-resolution satellite precipitation data over the Mediterranean Region
  • 5.1 Introduction.
  • 5.2 Study area
  • 5.3 Data and methodology
  • 5.3.1 TRMM/GPM data
  • 5.3.2 GSMaP data
  • 5.3.3 E-OBS data
  • 5.3.4 Methods
  • 5.4 Results and discussion
  • 5.4.1 Mean annual precipitation maps
  • 5.4.2 Average difference maps
  • 5.4.3 Correlation maps
  • 5.5 Conclusion
  • Acknowledgments
  • References
  • 6 Fundamental satellite precipitation data records
  • 6.1 Introduction
  • 6.2 Satellite precipitation estimates
  • 6.3 Satellite observational records
  • 6.4 Precipitation climate data records
  • 6.5 Key questions
  • 6.6 Conclusion
  • Acknowledgments
  • References
  • 7 The potential of using satellite-related precipitation data sources in arid regions
  • 7.1 Arid regions
  • 7.2 Challenges of arid regions
  • 7.2.1 Water scarcity
  • 7.2.2 Data scarcity
  • 7.3 The water cycle in arid regions
  • 7.3.1 Precipitation
  • 7.3.2 Infiltration
  • 7.3.3 Runoff
  • 7.3.4 Evapotranspiration
  • 7.4 Storage
  • 7.4.1 Aquifers
  • 7.4.2 Soil moisture
  • 7.4.3 Rivers and lakes
  • 7.5 Water consumption
  • 7.6 Satellite-based precipitation data sources
  • 7.7 Performance of satellite-related precipitation estimations in an arid region
  • 7.7.1 The study site
  • 7.7.2 Rain-gauge network and in situ measurements
  • 7.7.3 TMPA and IMERG precipitation data
  • 7.7.4 Statistical metrics
  • 7.7.4.1 Statistical tests with TMPA and IMERG
  • 7.7.4.2 Compatibility of TMPA and IMERG data to rain-gauge measurements
  • 7.7.4.3 TMPA and IMERG data in detecting rainfall
  • 7.7.5 Discussion of results
  • 7.8 Concluding remarks
  • Acknowledgments
  • References
  • 8 Monitoring precipitation from space: progress, challenges, and opportunities
  • 8.1 Introduction
  • 8.2 Progress in satellite-based precipitation monitoring
  • 8.3 Gaps, challenges, and opportunities
  • 8.3.1 Challenges
  • 8.3.2 Downscaling
  • 8.3.3 Error correction
  • 8.3.4 Satellite-based precipitation applications.
  • 8.3.5 Water resource management
  • 8.3.6 Drought prediction
  • 8.3.7 River flow forecast
  • 8.3.8 Landslide forecast
  • 8.3.9 Numerical weather forecast
  • 8.4 Conclusion
  • References
  • 9 Satellite hail detection
  • 9.1 Introduction
  • 9.2 Physical basis underpinning hail remote sensing
  • 9.2.1 Radar remote sensing
  • 9.2.2 Radiometer remote sensing
  • 9.3 State-of-the-art satellite microwave methods for hail detection
  • 9.3.1 Satellite radar-based detection of hail
  • 9.3.2 Satellite radiometer-based detection of hail
  • 9.4 Satellite observations: July 17, 2019 case study
  • 9.5 Satellite climatology of hail: status, pitfalls, and ways forward
  • 9.5.1 Champion storms
  • 9.5.2 Hail climatologies
  • 9.6 Conclusion and future perspectives
  • Acknowledgments
  • References
  • 10 Development of a precipitation-retrieval scheme for cross-track passive microwave sounding instruments
  • 10.1 Introduction
  • 10.2 Precipitation retrievals
  • 10.3 Development of the Precipitation Retrieval and Profiling Scheme
  • 10.3.1 The PRPS-SAPHIR a priori scheme
  • 10.3.2 Algorithm design
  • 10.3.3 The PRPS DPR-SAPHIR database
  • 10.3.4 PRPS retrieval
  • 10.4 Evaluation and validation
  • 10.5 Future directions
  • References
  • 11 Evaluation of high-resolution satellite precipitation over the global oceans
  • 11.1 Introduction
  • 11.2 Datasets
  • 11.2.1 OceanRAIN dataset
  • 11.2.2 IMERG dataset
  • 11.2.3 Matched dataset
  • 11.3 Evaluation procedure
  • 11.4 Discussion of evaluation results
  • 11.4.1 IMERG-OceanRAIN comparison
  • 11.4.2 Evaluation of error sources
  • 11.5 OceanRAIN applications
  • 11.6 Conclusion
  • References
  • 12 Recent advances and challenges in satellite-based snowfall detection and estimation
  • 12.1 Introduction
  • 12.2 Spaceborne radars and snowfall
  • 12.2.1 CloudSat Cloud Profiling Radar
  • 12.2.2 The GPM-CO dual-frequency precipitation radar.
  • 12.3 Passive microwave radiometry and snowfall
  • 12.3.1 GMI and ATMS snowfall observation capabilities
  • 12.3.1.1 GMI high-frequency channels and 166-GHz polarization signal
  • 12.3.1.2 Impact of background surface conditions
  • 12.3.1.3 Analysis of ATMS snowfall observation capabilities
  • 12.4 PMW snowfall retrieval techniques
  • 12.4.1 GPROF and SLALOM snowfall retrieval algorithms for GMI
  • 12.5 Ground-based snowfall observations
  • 12.6 Conclusion and recommendations
  • Acknowledgments
  • References
  • 13 Errors and uncertainties associated with quasiglobal satellite precipitation products
  • 13.1 Introduction
  • 13.2 Sensor errors and uncertainties
  • 13.3 Retrieval scheme errors and uncertainties
  • 13.3.1 Information from observations
  • 13.3.2 Incorporating ancillary data
  • 13.4 Product errors and uncertainties
  • 13.5 Conclusion
  • References
  • 14 Performance assessment of merged multisatellite precipitation datasets over diverse climate and complex topography
  • 14.1 Introduction
  • 14.2 Data and methodology
  • 14.2.1 Study area
  • 14.2.1.1 Glacial zone
  • 14.2.1.2 Humid zone
  • 14.2.1.3 Arid zone
  • 14.2.1.4 Hyper-arid zone
  • 14.2.2 Spatial distribution of precipitation across all climate zones of Pakistan
  • 14.3 Performance assessment of satellite precipitation products across Pakistan
  • 14.3.1 Introduction to available assessment results
  • 14.3.2 Limitations, controversies, and intercomparison of zonal errors in evaluated satellite precipitation products
  • 14.4 Merged precipitation datasets: advancements and imperfections
  • 14.4.1 Glacial zone
  • 14.4.2 Humid zone
  • 14.4.3 Arid zone
  • 14.4.4 Hyperarid zone
  • 14.5 Conclusion
  • Acknowledgments
  • References
  • 3 Precipitation Microphysics
  • 15 Melting of atmospheric ice particles
  • 15.1 Introduction.

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