Satellite Precipitation Measurement: Volume 2 (Advances in Global Change Research, 69)

✍ Scribed by Vincenzo Levizzani (editor), Christopher Kidd (editor), Dalia B. Kirschbaum (editor), Christian D. Kummerow (editor), Kenji Nakamura (editor), F. Joseph Turk (editor)

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 797
• Category: Library

✦ Synopsis

This book offers a complete overview of the measurement of precipitation from space, which has made considerable advancements during the last two decades. This is mainly due to the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM) mission, CloudSat and a carefully maintained constellation of satellites hosting passive microwave sensors. The book revisits a previous book, Measuring Precipitation from Space, edited by V. Levizzani, P. Bauer and F. J. Turk, published with Springer in 2007. The current content has been completely renewed to incorporate the advancements of science and technology in the field since then. This book provides unique contributions from field experts and from the International Precipitation Working Group (IPWG).

The book will be of interest to meteorologists, hydrologists, climatologists, water management authorities, students at various levels and many other parties interested in making use of satellite precipitation data sets.

✦ Table of Contents

Preface
Acknowledgments
Contents of Volume 2
Contents of Volume 1
List of Figures
List of Tables
Contributors
Acronyms
Part IV: Validation
Chapter 25: The IPWG Satellite Precipitation Validation Effort
25.1 Introduction
25.2 Current Validation Work: Data and Methodological Approach
25.3 Examples of IPWG Validation
25.3.1 Regional Analysis Over Japan Region
25.3.2 Seasonal Studies Over South America
25.3.3 Examples of IPWG-Related Studies
25.4 Future Validation Efforts
25.5 Conclusions
References
Chapter 26: The GPM Ground Validation Program
26.1 Overview
26.1.1 GV Measurement Synergy
26.2 Validation Instruments, Data, and Examples
26.2.1 Primary Datasets
26.2.2 Example Applications of VN Datasets
26.2.3 Validation Using GV-MRMS
26.2.4 Application to Verification of GPM L1SRs
26.3 Physical Validation Activities
26.4 Validation of the GPM IMERG Product
26.4.1 Examples of IMERG Validation Over South Korea
26.4.2 Selected Examples of IMERG Validation Over CONUS
26.5 Summary and Moving Forward
References
Chapter 27: The GPM DPR Validation Program
27.1 Introduction
27.2 Calibration
27.3 Ground Ka-Radar Experiment
27.3.1 Measurements
27.3.2 Results
27.4 Comparisons of DPR Products with Ground Observations
27.4.1 GPM/DPR Ground Validation Comparing with Rain Gauge Data Over Japan
27.4.2 GPM/DPR Ground Validation with MRMS/NMQ Data Over the US
27.4.3 Surface Snow Flag in the Latest DPR Product
27.5 Summary
References
Chapter 28: Error and Uncertainty Characterization
28.1 Uncertainty Sources of Satellite Precipitation Products
28.2 Methods for Assessing Satellite Precipitation Products
28.2.1 The Benchmark
28.2.2 Verification Metrics
28.2.3 Triple Collocation Analysis
28.3 Error and Uncertainty Models
28.4 Summary of the Performance of the Main Satellite Precipitation Products
References
Chapter 29: Multiscale Evaluation of Satellite Precipitation Products: Effective Resolution of IMERG
29.1 Introduction
29.2 Data
29.2.1 IMERG
29.2.2 MRMS Gauge-Adjusted Radar QPE
29.3 Method: Spectral Analysis in the Wavelet Domain
29.3.1 Rationale
29.3.2 Implementation
29.3.3 Illustrative Case Study
29.4 Results
29.5 Conclusions
Appendix: Two-Dimensional Discrete Orthogonal Decomposition with the Haar Wavelet
Wavelets Functions in One Dimension and N Dimensions
The Haar Discrete Orthogonal Wavelets in One and Two Dimensions
References
Chapter 30: Remote Sensing of Orographic Precipitation
30.1 Introduction
30.2 Orographic Precipitation Measurement
30.3 Ground-Validation
30.4 Physical-Basis of Retrieval Errors
30.5 Summary
References
Chapter 31: Integrated Multi-satellite Evaluation for the Global Precipitation Measurement: Impact of Precipitation Types on S...
31.1 Introduction
31.2 Spaceborne and Ground-Based Precipitation Datasets
31.2.1 Dual-Frequency Phased Array Radar
31.2.2 GPM Microwave Imager
31.2.3 Integrated Multi-satellitE Retrievals for GPM
31.2.4 Ground-Based Reference Precipitation
31.3 Impact of Precipitation Typology on Satellite-Based Active, Passive and Merged Precipitation Estimation
31.3.1 DPR QPE and Precipitation Typology
31.3.2 GMI QPE and Precipitation Typology
31.3.3 IMERG and Precipitation Typology
31.4 Conclusion
References
Chapter 32: Hydrologic Validation and Flood Analysis
32.1 Introduction
32.2 Space-Time Validation Framework
32.2.1 Point Based Evaluation
32.2.2 River Network Based Multiscale Valuation
32.2.3 River Network Based Error Dependence
32.3 Conclusions
References
Chapter 33: Global-Scale Evaluation of 22 Precipitation Datasets Using Gauge Observations and Hydrological Modeling
33.1 Introduction
33.2 Data and Methods
33.2.1 P Datasets
33.2.2 Performance Evaluation Using Gauge Observations
33.2.3 Performance Evaluation Using Hydrological Modeling
33.3 Results and Discussion
33.3.1 Performance in Terms of Temporal Dynamics
33.3.2 Performance in Terms of Climate Indices
33.3.3 Performance Evaluation Using Hydrological Modeling
33.4 Conclusions
References
Chapter 34: OceanRAIN - The Global Ocean Surface-Reference Dataset for Characterization, Validation and Evaluation of the Wate...
34.1 Introduction
34.2 The OceanRAIN Optical Disdrometer ODM470
34.3 Data Ingest and Data Set Construction
34.4 OceanRAIN Data Sets
34.5 Applications and Validation
34.5.1 Precipitation Characterization
34.5.2 The Point-to-Area Representativeness
34.5.3 IMERG Validation
34.6 Conclusions and Future Outlook
References
Part V: Observed Characteristics of Precipitation
Chapter 35: GPCP and the Global Characteristics of Precipitation
35.1 Introduction
35.2 GPCP Monthly Analysis Technique
35.3 Global Precipitation Climatology
35.4 Variations in Global Mean Precipitation (1979-2017)
35.5 Patterns of Precipitation Variation and Trends
35.6 Trends in Precipitation Intensity at the Monthly Scale
35.7 Summary
References
Chapter 36: Global Snowfall Detection and Measurement
36.1 Introduction
36.2 Global Snowfall: CloudSat´s Recent Contributions
36.3 CloudSat Snowfall Detection and QPE Algorithm
36.4 Global Snowfall Characteristics
36.4.1 CloudSat Sampling
36.4.2 Snowfall Occurrence Statistics
36.4.3 CPR Reflectivity Variability: Snowfall Events
36.4.4 Snowfall QPE
36.5 Concluding Remarks
References
Chapter 37: Snowfall Detection by Spaceborne Radars
37.1 Introduction
37.2 Classical Methods to Determine Surface Precipitation Types
37.3 Vertical Phase Distribution from Spaceborne Radars
37.4 Use of Dual-Frequency Observations
37.5 Future Directions
References
Chapter 38: On the Duration and Life Cycle of Precipitation Systems in the Tropics
38.1 Introduction
38.2 The Climatology and Morphology of the MCS
38.2.1 Background and Robust Features
38.2.2 TOOCAN Specific Features of Tropical MCS
38.3 Precipitation and MCS Duration
38.3.1 The Precipitation Totals and the Degree of Organization of Convection
38.3.2 The Precipitation Totals and the System Duration
38.4 Precipitation and the MCS Life Cycle
38.4.1 The Linear Growth/Decay Model for the Cold Cloud Shield Life Cycle
38.4.2 Compositing GEO and LEO Along the Life Cycle
38.5 Conclusions
References
Chapter 39: Observational Characteristics of Warm-Type Heavy Rainfall
39.1 Introduction
39.2 Data and Analysis Method
39.3 Comparison Between Korea and Oklahoma
39.4 General Features Found Over the East Asian Monsoon Area
39.5 Role of Collision and Coalescence Processes
39.6 Conclusions
References
Chapter 40: Satellite Precipitation Measurement and Extreme Rainfall
40.1 Introduction
40.1.1 Physical Principles of Satellite Rainfall Measurements
40.1.2 Selected Satellite QPE Products
40.2 Statistical Distribution of Rainfall Extremes
40.2.1 Average and Maximum Rainfall
40.2.2 Thresholds, Percentiles and Spatial Distribution of Daily Extremes
40.3 Application of Satellite QPE to Extreme Events
40.3.1 Rainfall Extremes at the Daily Scale
40.3.2 Daily Rainfall Extremes in Relation to Cyclonic Activity
40.3.3 Other Applications of SPPs with Respect to Rainfall Extremes
40.4 Verification of Satellite QPE Extremes with Respect to In-Situ Rain Gauge Observations
40.5 Conclusions and Future Directions in Satellite QPEs for Extreme Events Measurements
References
Chapter 41: Rainfall Trends in East Africa from an Ensemble of IR-Based Satellite Products
41.1 Introduction
41.2 Data and Methods
41.2.1 Satellite Products
41.2.2 Rainfall Indices and Trend Analysis Methodology
41.3 Rainfall Seasonality and Variability
41.4 Trend Results
41.4.1 Trend Analysis of Annual Rainfall Indices
41.4.2 Trend Analysis of Seasonal Rainfall Indices
41.4.2.1 January-February (JF) Season
41.4.2.2 March-April-May (MAM) Season
41.4.2.3 June-July-August-September (JJAS) Season
41.4.2.4 October-November-December (OND) season
41.5 Conclusions
References
Chapter 42: Heavy Precipitation Systems in the Mediterranean Area: The Role of GPM
42.1 Introduction
42.2 Satellite Precipitation Products
42.3 Isolated Deep-Convective Systems
42.4 Mesoscale Convective Systems
42.5 Medicanes
42.6 Final Remarks
References
Chapter 43: Dryland Precipitation Climatology from Satellite Observations
43.1 Introduction
43.2 Background on Dryland Climate
43.3 Accuracy of Satellite Precipitation Estimates for Dryland Regions
43.4 Satellite-Derived Climatological Properties of Dryland Precipitation
43.5 Quasi-Global Dryland Precipitation Climatology from TRMM Observations
43.6 Conclusions and Recommendations
References
Chapter 44: Hailfall Detection
44.1 Physical Basis
44.2 Microwave Imager and Active Radar Retrievals
44.3 Microwave Sounder Retrievals
44.3.1 MicroWave Cloud Classification (MWCC)
44.3.2 Hail Detection with MWCC Method
44.3.3 NOAA AMSU-b/MHS
44.4 Summary
References
Chapter 45: Improving High-Latitude and Cold Region Precipitation Analysis
45.1 Introduction
45.2 Utilizing CloudSat to Assess High Latitude Precipitation
45.2.1 Analysis of Zonal Precipitation Distribution Over Ocean
45.2.2 Regional Analysis and Precipitation Pattern
45.3 Utilizing GRACE to Assess Cold Region Precipitation
45.4 Concluding Remarks
References
Chapter 46: Latent Heating Retrievals from Satellite Observations
46.1 Introduction
46.2 The Spectral Latent Heating (SLH) Algorithm
46.2.1 Latent Heating Retrieval for the Tropical Region
46.2.2 SLH Algorithm for Mid Latitudes
46.2.2.1 Construction of LUTs
46.2.2.2 SLH Retrieval from GPM KuPR: Consistency Check and Performance
46.3 Convective and Stratiform Heating (CSH) Algorithm
46.3.1 CSH Algorithm for Tropical Region
46.3.1.1 Cases for CSH Look-Up Table
46.3.1.2 Updated CSH
46.3.2 CSH for High Latitudes
46.3.2.1 NU-WRF and Cases
46.3.2.2 NU-WRF and Look-Up Tables
46.3.2.3 Consistency Check
46.4 Summary and Future Issues
References
Part VI: Applications
Chapter 47: Operational Applications of Global Precipitation Measurement Observations
47.1 Introduction
47.2 Background and Methods
47.2.1 GPM
47.2.2 Data
47.2.3 Motivation
47.2.4 End User Interaction
47.3 Applications
47.3.1 Landslides/Mudslides
47.3.2 Flooding
47.3.3 Atmospheric Rivers
47.3.4 Rain Gauge Verification
47.3.5 Additional Applications
47.3.5.1 Supporting High Impact Events
47.3.5.2 Precipitation - Applications Related to Snowfall
47.3.5.3 Hurricane Structure and Intensity
47.4 Conclusions
References
Chapter 48: Assimilation of Precipitation Observations from Space into Numerical Weather Prediction (NWP)
48.1 Introduction
48.1.1 Understanding the Remote Sensing of Precipitation
48.1.2 Applications of Space-Borne Precipitation Measurements
48.2 Precipitation Measurement from Space: Sensitivity Assessment
48.2.1 Sensitivity to Microphysical Properties
48.2.2 Sensitivity to the Surrounding Environment
48.3 Important Factors for the Physical Inversion and Data Assimilation of Precipitation Observations
48.3.1 The Theoretical and Mathematical Basis for the Inversion of Satellite Radiances
48.3.2 The Issue of Non-linearities When Assimilating Precipitation Measurements
48.3.3 Uncertainties in Radiative Transfer and Jacobians
48.3.4 Model-Related Limiting Factors in the Assimilation of Precipitation
48.4 The Assimilation of Precipitating Data: Different Methods and Perspectives
48.4.1 A Summary of Previous Efforts
48.4.2 Global Assimilation of Precipitation Affected Radiances at ECMWF
48.4.3 Global Assimilation of Precipitation Affected Radiances at JMA: Impacts on Tropical Cyclones
48.4.4 Assimilation of Precipitation Affected Radiances Using a 1D-Var + 4D-EnVar
48.5 Final Thoughts on Precipitation Data and Data Assimilation for Numerical Weather Prediction
References
Chapter 49: Precipitation Ensemble Data Assimilation in NWP Models
References
Chapter 50: PERSIANN-CDR for Hydrology and Hydro-climatic Applications
50.1 Introduction
50.2 Hydro-climatic Applications
50.2.1 RainSphere for Global Precipitation Analysis and Visualization
50.2.2 Evaluation of PERSIANN-CDR on Extreme Events
50.2.3 Evaluation of CMIP5 Model Precipitation
50.3 Hydrology Applications
50.3.1 Hydrologic Modeling
50.3.2 Rainfall Frequency Analysis Using Satellite-Retrieved Precipitation
50.4 Conclusions
References
Chapter 51: Soil Moisture and Precipitation: The SM2RAIN Algorithm for Rainfall Retrieval from Satellite Soil Moisture
51.1 Introduction
51.2 SM2RAIN Algorithm
51.3 SM2RAIN-Derived Rainfall Products
51.3.1 SM2RAIN-CCI
51.3.2 SM2RAIN-ASCAT
51.4 Flood Modelling in Europe Through SM2RAIN-Derived Rainfall Products
51.4.1 In Situ and Satellite Datasets
51.4.2 MISDc Rainfall-Runoff Modelling
51.4.3 Results
51.5 Limitations and Future Directions
References
Chapter 52: Drought Risk Management Using Satellite-Based Rainfall Estimates
52.1 Introduction
52.2 Rainfall Monitoring for Drought Assessment
52.2.1 Evolution of Rainfall Observation Technology: From Rainfall Observations to Rainfall Estimation
52.2.2 Evaluations and Inter-comparisons of Satellite-Based Rainfall Estimates: Choosing a Rainfall Product
52.3 Drought Risk Management
52.3.1 Rainfall-Based Drought Indicators
52.3.1.1 Single-Variable Indicators: Rainfall Anomalies/Indices
52.3.1.2 Multi-variable Indicators: Anomalies/Indices and Models
52.3.2 Hydrological Models for Drought Assessment
52.3.3 Crop Water Stress and Crop Yield Modelling
52.3.4 Cross-Cutting Approaches
52.3.4.1 Drought and Famine Early Warning Systems (EWS)
52.3.4.2 Weather Index-Based Insurance (WII)
52.4 Summary and Outlook
References
Chapter 53: Two Decades of Urban Hydroclimatological Studies Have Yielded Discovery and Societal Benefits
53.1 Introduction
53.2 The ``Urban Precipitation Effect´´
53.3 Urban Impacts on Winter Precipitation
53.4 Land Surface Hydrological Response and Water Management
53.5 Urbanization and the Energy-Food-Water Nexus
53.6 Concluding Statements
References
Chapter 54: Validation of Climate Models
54.1 The Importance of Validation
54.2 Precipitation: The Privileged Metric for Validation
54.3 Basic Comparisons
54.4 Quality Standards in the Validation of Climate Models
54.5 A Checklist for Validation of Climate Models
References
Chapter 55: Extreme Precipitation in the Himalayan Landslide Hotspot
55.1 Introduction
55.2 Rainfall and Landslide Data
55.2.1 GFDL FLOR
55.2.2 TMPA
55.2.3 Landslide Data
55.3 Methods
55.4 Results
55.4.1 Regional Patterns in Extreme Precipitation
55.4.2 Annual Variability
55.4.3 Seasonal Variability
55.4.4 Monthly Variability
55.5 Discussion
55.6 Conclusions
References
Chapter 56: The Value of Satellite Rainfall Estimates in Agriculture and Food Security
56.1 Introduction
56.2 The Value of Satellite Rainfall Estimates in Agriculture and Food Security
56.2.1 Climate Services in Agriculture
56.2.2 Challenges to Available Climate Data in Africa
56.2.3 The Value of Satellite Data to Overcome Data Availability Challenges
56.3 Specific Applications of Satellite Rainfall Estimates in Agriculture
56.3.1 Enhancing National Climate Services (ENACTS)
56.3.2 Rwanda Climate Services for Agriculture Project
56.3.3 Weather Index Insurance
56.4 Summary
References
Chapter 57: Using Satellite Estimates of Precipitation for Fire Danger Rating
57.1 Introduction
57.2 The Canadian Fire Weather Index System and the Global Fire Weather Database
57.3 The 2017 Fire Season in British Columbia, Canada
57.4 The 2017 Fire Storm in Central Chile
57.5 The 2018 Attica Fires Near Athens, Greece
57.6 Fire Activity Over Western Indonesia, 2015-2018
57.7 Conclusions
References
Chapter 58: Variability of Satellite Sea Surface Salinity Under Rainfall
58.1 Introduction
58.2 Data and Method
58.2.1 Salinity and Wind Speed Data
58.2.2 Rain Rate Data
58.2.3 Method
58.2.3.1 Salinity Anomalies
58.2.3.2 Detection of Rain History
58.2.3.3 Filtering of Non-rainy Processes and DeltaS Versus Instantaneous RR Relationship
58.3 Results
58.3.1 Intercomparison of RR and SSS Products
58.3.2 Which Is the Imprint of Rain History on Salinity Anomalies?
58.3.3 Variability of the Relationship Between Salinity Freshening and Rain Rate as Function of Wind Speed
58.4 Discussion and Conclusion
References