11th Workshop of International Precipitation Working Group (IPWG-11)
Mon, 15 Jul 2024
| Time | No. | Presentation title | Author Name | Author Affiliation |
|---|---|---|---|---|
| Session 1: Current and Future Satellite Missions and Products (Chair : Christian Kummerow, Takuji Kubota) | ||||
| 9:00 - 9:05 | 1.1 | Introduction of IPWG | Joe Turk | IPWG Rapporter |
| 9:05 - 9:10 | 1.2 | Welcome address from JAXA | Riko Oki | JAXA/EORC |
| 9:10 - 9:15 | 1.3 | Welcome address from Tokyo Tech. | Nobuyuki Utsumi | Tokyo Institute of Technology |
| 9:15 - 9:25 | 1.4 | Logistic information | Nao Yoshida | JAXA/EORC |
| 9:25 - 9:40 | 1.5 | Recent status of the Global Precipitation Measurement (GPM) Mission in Japan and future Japanese Precipitation Measuring Mission (PMM) | Takuji Kubota | Japan Aerospace Exploration Agency |
| 9:40 - 9:55 | 1.6 | Development of the Advanced Microwave Scanning Radiometer (AMSR) Series and its Utilizations | Misako Kachi | JAXA/EORC |
| 9:55 - 10:10 | 1.7 | Status of Himawari-8/9 and their follow-on satellite Himawari-10 | Arata OKUYAMA | Japan Meteorological Agency |
| 10:10 - 10:25 | 1.8 | The in-orbit performance of the first China's Fengyun Rainfall Mission FY-3G | Peng Zhang | CMA Meteorological Observation Centre |
| 10:25 - 10:40 | 1.9 | IMERG: V07 (at Long Last) and What Comes Next | George J. Huffman | NASA Goddard Space Flight Center |
| 10:40 - 10:55 | 1.10 | Status of the Atmosphere Observing System | Scott Braun | NASA Goddard Space Flight Center |
| 10:55 - 11:10 | 1.11 | Overview of the EUMETSAT Polar System - Second Generation (EPS-SG) Passive Microwave Missions | Christophe Accadia | EUMETSAT |
| 11:10 - 11:25 | 1.12 | NOAA Operational Snowfall Rate Product – Recent Developments and Applications | Huan Meng | US National Oceanic and Atmospheric Administration |
| 11:25 - 11:40 | 1.13 | Improving CMORPH2 Real-Time Production | Pingping Xie | NOAA/NWS/NCEP Climate Prediction Center |
| 11:40 - 11:55 | 1.14 | WMO Space-based Weather and Climate Extremes Monitoring (SWCEM) for East Asia and Western Pacific | Yuriy Kuleshov | Royal Melbourne Institute of Technology (RMIT) University |
| 11:55 - 12:00 | Group photo | |||
| 12:00 - 13:30 | Lunch Break | |||
| Session 2: Surface Precipitation Observations (Chair : Pierre Kirstetter, Kazumasa Aonashi) | ||||
| 13:30 - 13:45 | 2.1 | Overview of the gridded daily and monthly precipitation data sets provided by the Global Precipitation Climatology Centre (GPCC) | Zora Schirmeister | Deutscher Wetterdienst |
| 13:45 - 14:00 | 2.2 | Reprocessing R/A precipitation data, their value, and the application to the society | Kenichi Kuma | Research Center for Advanced Science and Technology, The University of Tokyo |
| 14:00 - 14:15 | 2.3 | Calibration Error Estimation of Ground-based Radar by the Global Precipitation Measurement Dual-frequency Precipitation Radar in China | Wang Gang | Guangzhou Meteorological Satellite Ground Station（Guangdong Meteorological Satellite Remote Sensing Center） |
| 14:15 - 14:30 | 2.4 | A Radar-Rain Gauge Data Merging Method using Radial Basis Function Interpolation | Ryu, Soorok | Center for Atmospheric REmote sensing (CARE), Kyungpook National University, Republic of Korea |
| 14:30 - 14:45 | 2.5 | PREVENIR RQPE 1.0: Ground radar qunatitative precipitation estimation development for nowcasting and hydrological aplications. | Paola Salio | CIMA CONICET-UBA / DCAO FCEN-UBA/ IRL 3351 IFAECI CNRS-IRD-CONICET-UBA Buenos Aires, Argentina |
| Session 3: Spaceborne Radar Products (Chair : Ali Behrangi, Daniel Vila) | ||||
| 14:45 - 15:00 | 3.1 | Possible improvement of the Solver module for DPR standard algorithm Version 08 | Shinta Seto | Nagasaki University |
| 15:00 - 15:15 | 3.2 | Evaluation of V7 Products and Developing New Features in V8 of Classification Module in GPM DPR Level-2 Algorithm | V. Chandrasekar | colorado state university |
| 15:15 - 15:30 | 3.3 | The Fengyun rainfall mission FY3G: the scientific products and validation progress | Lin CHEN | National Satellite Meteorological Centre (National Center for Space Weather), China Meteorological Administration |
| 15:30 - 16:00 | Break | |||
| Session 4: Merged Satellite Precipitation Products (Chair : Ali Behrangi, Daniel Vila) | ||||
| 16:00 - 16:15 | 4.1 | High Resolution GSMaP using new Himawari satellite data | Tomoo Ushio | Osaka University |
| 16:15 - 16:30 | 4.2 | Final Calibration Upgrades for IMERG V07 and Future Calibration Challenges for IMERG V08 | Robert Joyce | NASA/GSFC-SSAI |
| 16:30 - 16:45 | 4.3 | Analysis of the GPM and GPCP latest products over the oceans and cold surfaces | Ali Behrangi | University of Arizona |
| 16:45 - 17:00 | 4.4 | Investigating the representation of extremes in high-resolution, long period-of-record precipitation products in the continental US | Janice Bytheway | NOAA Physical Sciences Laboratory |
| 17:00 - 17:15 | 4.5 | An Automated Quality Control Scheme for GPM Satellite Precipitation Products | Jackson Tan | NASA Goddard Space Flight Center & University of Maryland Baltimore County |
| 17:15 - 17:30 | 4.6 | H SAF Precipitation Products Quality Assessment: methodology and results | Marco Petracca | Institute of Atmospheric Sciences and Climate, National Research Council (CNR-ISAC), Rome, Italy |
| 17:30 - 17:45 | 4.7 | Evolution of H SAF near real-time rainfall products derived from soil moisture observations | Luca Ciabatta | CNR-IRPI |
| 17:45 - 18:00 | 4.8 | GIRAFE v1: A global precipitation climate data record from satellite data including uncertainty estimates | Marc Schröder | DWD |
| 18:30 - 20:30 | Ice Breaker | |||
Tue, 16 Jul 2024
| Time | No. | Presentation title | Author Name | Author Affiliation |
|---|---|---|---|---|
| Session 5: Machine Learning (Chair : Simon Pfreundschuh, Tomoo Ushio) | ||||
| 9:00 - 9:15 | 5.1 | Advanced Technologies in monitoring and data management | Kuolin Hsu | Center for Hydrometeorology & Remote Sensing (CHRS), University of California Irvine |
| 9:15 - 9:30 | 5.2 | A global and operational precipitation product from weather satellites: Espresso | Sylvain LE MOAL | Meteo-France – Meteorological Satellite Centre |
| 9:30 - 9:45 | 5.3 | Reconceiving the synergy between LEO and GEO observations for satellite precipitation retrievals in the era of deep learning | Clement Guilloteau | University of California Irvine |
| 9:45 - 10:00 | 5.4 | Evaluation of SVR-Based Rainfall Estimation using Soil Moisture Data Across India's Diverse Climatic Regions | Shuvojit Nath | Department of Civil Engineering, IIT Bombay, India and Department of Civil Engineering, Monash University, Australia |
| 10:00 - 10:15 | 5.5 | The Polarized Submillimeter Ice-Cloud Radiometers (POLSIR): Mission Objectives and Level-2 Product Overview | Jie Gong | NASA Goddard Space Flight Center, United States |
| 10:15 - 10:30 | 5.6 | Deriving Hydrometeor Mass from Images with Machine Learning | Kwo-Sen Kuo | Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA |
| Session 6: Poster flash talks (Session A) (Chair : Shoichi Shige, Viviana Maggioni) | ||||
| 10:30 - 11:00 | 1. min talk by each presenter | |||
| 6.1 | Summary of GPM V07 reprocessing, conversion of OS to RHEL 8 and impact on data of the GPM core satellite boost Poster |
Erich Franz Stocker | NASA/GSFC code 619 | |
| 6.2 | Six Months of Preliminary Calibration Results of the PMR onboard the FY-3G Satellite Poster |
Honggang Yin | National Satellite Meteorological Center/CMA | |
| 6.3 | Validation of FY-3G Precipitation Measurement Radar Poster |
Jian Shang | National Satellite Meteorological Center | |
| 6.4 | The latest Global Precipitation Climatology Project Daily and Monthly products (Version 3.2): Summary and Comparisons Poster |
Ali Behrangi | University of Arizona | |
| 6.5 | Spatiotemporal variability of gridded precipitation information updated by diverse sampling Poster |
Masafumi Hirose | Meijo University | |
| 6.6 | Use of Smallsat-Sized Conical- and Cross-Track Scanning Passive Microwave Sensors to Complement the Precipitation Constellation and Facilitate Oceanic Convection Investigations Poster |
F. Joseph Turk | JPL/Caltech | |
| 6.7 | Spatial partitioning of precipitation in the terrestrial water cycle | Yannis Markonis | Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Czech Republic | |
| 6.8 | Towards Understanding the Uncertainties of PMW-derived Precipitation Regime Trends Poster |
Veljko Petkovic | University of Maryland | |
| 6.9 | Evaluation of the latest version of the Global Satellite Mapping of Precipitation (GSMaP) focused on orographic rainfall Poster |
Munehisa K. Yamamoto | Earth Observation Research Center, Japan Aerospace Exploration Agency | |
| 6.10 | Climatological study of Satellite Sensed Precipitation along the mountainous regions of Nepal
Poster |
Sudip Pandey | Graduate School of Environment Science, Hokkaido University, Sapporo, Japan | |
| 6.11 | A Satellite-Based Analysis of Changes in Extreme Precipitation Over West Africa | Malihe Nasibi | Department of Civil, Environmental, and Infrastructure Engineering, George Mason University | |
| 6.12 | Development of a LSTM-based Seasonal Prediction Model of Rainy Precipitation over Indochina Peninsula | Mai Kurokawa | Chuo University | |
| 6.13 | Evaluating Spatial and Temporal Variability of Precipitation Concentration and Shannon’s Entropy Characteristics in Nigeria: A Study from 1980 to 2023 | Obasi-oma Oluwatosin R. | Lagos State University | |
| 6.14 | Unraveling the Impact of Multi-Layered Precipitation Systems in Satellite-based Quantitative Precipitation Estimates Poster |
Malarvizhi Arulraj | Earth System Science Interdisciplinary Center/Cooperative Institute for Satellite Earth System Studies, University of Maryland, College Park, Maryland, USA | |
| 6.15 | The EUMETSAT Satellite Application Facility in Support to Operational Hydrology and Water Management (H SAF) Project - Status of the Precipitation Cluster | Davide Melfi | Italian Air Force Met Service - CNMCA | |
| 6.16 | Introduction of the observation and prediction technologies by utilizing a localized high-density ground surface meteorological observation network (POTEKA) Poster |
Hisato Iwashita | Meisei Electric Co.,Ltd. | |
| 6.17 | INPE Algorithm for Tracking Precipitating Systems Poster |
Alan Calheiros | Brazilian National Institute for Space Research (INPE) | |
| 6.18 | Using the Jupyter Notebook as an open tool for analyzing the EUMETSAT H SAF precipitation products Poster |
Nicoletta Roberto | Italian Civil Protection Department | |
| 6.19 | Developing New Data Services in Support of NASA's Earth System Observatory | Zhong Liu | NASA GES DISC and CSISS George Mason University | |
| 6.20 | Adaptation of the Precipitation Retrieval and Profiling Scheme to the CM SAF FCDR record of SSM/I and SSMIS. | Chris Kidd | Earth System Science Interdisciplinary Center, University of Maryland, College Park. USA and NASA/Goddard Space Flight Center, Greenbelt, USA | |
| 6.21 | EUMETSAT’s contribution to observation of precipitation from space Poster |
Viju Oommen John | EUMETSAT | |
| 6.22 | Topography-guided Bias Correction Framework to Improve Satellite-based Retrievals over Mountain Regions Poster |
Yashraj Upase | Indian Institute of Technology, Hyderabad, India | |
| 6.23 | Catastrophic Extreme Rain Events observed over the Indian Land region during 1998-2022 in Global Precipitation Mission measurements | Kusuma G Rao | Atmosphere, Ocean and Space Sciences Unit, Institute for Advanced Research in Science, Bengaluru, India | |
| 11:00 - 12:00 | Session 6: Poster Session A | |||
| 12:00 - 13:30 | Lunch Break | |||
| Session 7: Working Group (WG) reports (Chair : Takuji Kubota, Christian Kummerow) | ||||
| 13:30 - 13:45 | 7.1 | The IPWG WGs and benchmarking activity – toward predictable Uncertainties | Christian Kummerow | Colorado State University |
| 13:45 - 14:15 | 7.2 | WG 1: Baseline Surface Precipitation Network | Pierre Kirstetter, Kazumasa Aonashi | |
| 14:15 - 14:45 | 7.3 | WG 2: Merged Satellite Precipitation Products | Ali Behrangi, Daniel Vila | |
| 14:45 - 15:15 | 7.4 | WG 3: Machine Learning | Simon Pfreundschuh and Tomoo Ushio | |
| 15:15 - 15:45 | 7.5 | WG 4: CubeSat/SmallSat | Chris Kidd, Joe Munchak | |
| 15:45 - 16:15 | Break | |||
| Session 8: Breakout session with all the WGs in parallel (Each WG chair) | ||||
| 16:15 - 18:00 | Breakout session by 4 rooms (Multi-Purpose Digital Hall, Collaboration Room, Media Hall) WG1: Baseline Surface Precipitation Network Breakout Session Outline Talks on surface precipitation networks: MRMS(Pierre Kirstetter), Frenchnetwork(Pierre Kirstetter), Japanesenetwork(Takanori Sakanashi), Koreannetwork(Soorok Ryu) WG2: Merged Satellite Precipitation Products WG3: Machine Learning WG4: CubeSat/SmallSat |
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Wed, 17 Jul 2024
| Time | No. | Presentation title | Author Name | Author Affiliation |
|---|---|---|---|---|
| Session 9: Cubesat/Smallsat and Data Assimilation (Chair : Chris Kidd, Joe Munchak) | ||||
| 9:00 - 9:15 | 9.1 | The Tomorrow.io Weather Constellation: Status and Early On-Orbit Results | S. Joseph Munchak | The Tomorrow Companies, Inc. |
| 9:15 - 9:30 | 9.2 | An overview of the EPS Sterna Programme | Christophe Accadia | EUMETSAT |
| 9:30 - 9:45 | 9.3 | Precipitation retrievals from passive microwave cubesat and smallsat sensors. | Chris Kidd | Earth System Science Interdisciplinary Center, University of Maryland, College Park. USA and NASA/Goddard Space Flight Center, Greenbelt, USA |
| 9:45 - 10:00 | 9.4 | Estimation of Surface Rain Rates from TEMPEST STP-H8 Brightness Temperature Observations using a Transfer Learning Model | V. Chandrasekar | Colorado State University |
| 10:00 - 10:15 | 9.5 | Exploring impacts of the Tomorrow.io Microwave Sounder (TMS) constellation | Ryan Honeyager | Tomorrow.io |
| 10:15 - 10:30 | 9.6 | A global Observing System Simulation Experiment to evaluate the impact of the EPS-Sterna constellation of microwave sounders | Philippe Chambon | CNRM, Météo-France & CNRS |
| Session 10: Poster flash talks (Session B) (Chair : Joe Turk, Sarah Ringerud) | ||||
| 10:30 - 11:00 | 1. min talk by each presenter | |||
| 10.1 | Characterizing GPROF Regional Bias Using Radar-Derived Hydrometeor Information Poster |
Eric Goldenstern | Colorado State University | |
| 10.2 | Preliminary results of FY-3G passive microwave precipitation parameters Poster |
Xiaoqing Li | National Satellite Meteorological Center，CMA | |
| 10.3 | Comparison of GSMaP version 8 and long term rain-gauge data in Timor Leste Poster |
YUKI OKADA | IDEA Consultants, Inc. | |
| 10.4 | Development of a precipitation climate record from spaceborne precipitation radar data | Kaya Kanemaru | NICT | |
| 10.5 | The necessity of sufficient perturbation rank for adequately conducting ensemble simulations | Pin-Ying Wu | Postdoctoral Fellow of Japan Society for the Promotion of Science; Meteorology Research Institute | |
| 10.6 | Dynamic Land Surface Emissivity for Global Precipitation Retrieval | Sarah Ringerud | NASA GSFC | |
| 10.7 | Sensitivity analysis of land atmosphere interaction using different parameterization schemes of the WRF model to simulate heavy rainfall events over the Mahi River basin, India | Aditya Sharma | Department of Atmospheric Science, School of Earth Science, Central University of Rajasthan, India | |
| 10.8 | Analysis of long-term trends in global precipitation products Poster |
Nobuhiro Takahashi | Institute for Space-Earth Environmental Research, Nagoya University | |
| 10.9 | Lightning-corrected GSMaP Precipitation Measurements Poster |
Archie Veloria | Department of Electrical, Electronic, and Infocommunications Engineering, Osaka University | |
| 10.10 | Development of retrieval algorithm for the GPM DPR spectral latent heating algorithm in the midlatitudes Poster |
Atsushi Hamada | Faculty of Sustainable Design, University of Toyama, Toyama, Japan / Center for Environmental Remote Sensing, Chiba University, Chiba, Japan | |
| 10.11 | Construction of look-up tables for GPM DPR spectral latent heating algorithm in the midlatitudes | Chie Yokoyama | Earth Observation Research Center, Japan Aerospace Exploration Agency | |
| 10.12 | Three-dimensional classification of precipitation particle types using GPM/DPR Poster |
Taisei Tsuji | University of Toyama | |
| 10.13 | Enhancing GSMaP precipitation tracking algorithm through combined use of high-resolution cloud moving vectors and ForTraCC Poster |
Hitoshi Hirose | Electronic and Information Engineering, Osaka University | |
| 10.14 | Long-term comparison of CHIRPS and GSMaP_ISRO rainfall over India | prashant kumar | EPSA, Space Applications Centre, ISRO, India. | |
| 10.15 | Comparisons between the GSMaP and the IMERG Near-real-time products over the India Poster |
Masato Ito | RESTEC | |
| 10.16 | Quantifying Temporal Sampling Errors for Gulab Cyclone using GPM Constellation Poster |
Ajay Sharma | Indian Institute of Technology Bombay, Powai, India | |
| 10.17 | Impact of satellite data assimilation on the NASA Goddard Earth Observing System (GEOS) precipitation analysis | Min-Jeong Kim | Global Modelling and Assimilating Office (GMAO), NASA Goddard Space Flight Center, Greenbelt, MD, USA | |
| 10.18 | Assessment of Global Satellite Mapping of Precipitation Data for Rainfall Measurement in Bangladesh | M. Rafiuddin | Department of Physics, Bangladesh University of Engineering & Technology, Dhaka-1000, Bangladesh | |
| 10.19 | Characteristics of light rain types determined from GPM/DPR measurements | Seoeun Choi | School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea | |
| 10.20 | Narrowing the Blind Zone of GPM DPR to Improve Precipitation Estimation over Ocean | Riku Shimizu | Kyoto University | |
| 10.21 | Improving Small-scale Tropical Precipitation Forecast by Assimilating Frequent Satellite Microwave Observations Poster |
Konduru Rakesh Teja | Data Assimilation Research Team,RIKEN Center for Computational Science, Kobe, Japan | |
| 10.22 | Extended Triple Collocation for Enhanced Precipitation Analysis: Evaluating and Integrating GSMaP, GSMaP ISRO Rain and IMERG-Final Run Poster |
Abhigyan Chakraborty | Department of Civil Engineering, Indian Institute of Technology, Hyderabad, 502285, India | |
| 11:00 - 12:00 | Session 10: Poster Session B | |||
| 12:00 - 13:30 | Lunch Break | |||
| Session 11: Focus Group (FG) reports (Chair : Christian Kummerow, Takuji Kubota) | ||||
| 13:30 - 14:00 | 11.1 | FG 1: Orographic Precipitation | Shoichi Shige; Yagmur Derin | |
| 14:00 - 14:30 | 11.2 | FG 2: Snowfall | Huan Meng, Giulia Panegrossi | |
| 14:30 - 15:00 | 11.3 | FG 3: Particle Scattering | Guosheng Liu, Nubuyuki Utsumi | |
| 15:00 - 15:30 | 11.4 | FG 4: Data Assimilation | Philippe Chambon, Yasutaka Ikuta | |
| 15:30 - 16:00 | 11.5 | FG 5: Land Surface | Joe Turk, Sarah Ringerud | |
| 16:00 - 16:30 | Break | |||
| Session 12: Breakout session with all the FGs in parallel (Each FG chair) | ||||
| 16:30 - 18:00 | Breaskout session by 5 rooms (Multi-Purpose Digital Hall, Collaboration Room, Media Hall, Additional room) FG 1: Orographic Precipitation Orographic/nonorographic rainfall classification scheme in GSMaP Retrieval uncertainties related to clutter removal inspaceborne precipitation radar data IPWG Orographic Precipitation Focus Group Goals and Expected Outcomes FG 2: Snowfall Snowfall Focus Group Global Snowfall as Revealed by Satellite Precipitation Products Retrieving Snowfall Class from Satellite Passive Microwave Observations NOAA –NESDIS Snowfall Rate Snowfall retrieval activities at CNR-ISAC Six responses with answers to the science questions FG 3: Particle Scattering Particle Scattering Focus Group FG 4: Data Assimilation Focus group on data assimilation FG 5: Land Surface Land Surface Focus Group |
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| 18:30 - 20:30 | Workshop Dinner | |||
Thu, 18 Jul 2024
| Time | No. | Presentation title | Author Name | Author Affiliation |
|---|---|---|---|---|
| Session 13: Data Assimilation (Chair : Philippe Chambon, Yasutaka Ikuta) | ||||
| 9:00 - 9:15 | 13.1 | Progress toward CRTM v4.0: Integrating AI/ML methods for Improved Performance and Accuracy Video |
Benjamin Johnson | UCAR/UCP/JCSDA |
| 9:15 - 9:30 | 13.2 | Advances and applications of satellite data assimilation of clouds, precipitation, and the ocean | Takemasa Miyoshi | RIKEN |
| 9:30 - 9:45 | 13.3 | Using 6 and 10 GHz from Microwave Imagers in an NWP system to improve the analysis of skin and sub-surface temperature and (in the future) precipitation Video |
Tracy Scanlon | ECMWF |
| 9:45 - 10:00 | 13.4 | Preparation for space-based cloud radar assimilation | Kozo Okamoto | JMA/MRI |
| 10:00 - 10:15 | 13.5 | All-sky assimilation of a constellation of passive microwave observation satellites within the regional kilometric scale model AROME | Elisa Chardon--Legrand | CNRM, Météo-France & CNRS, Toulouse, France |
| 10:15 - 10:30 | 13.6 | Assimilation method for clouds and precipitation forecast using background error covariance generated by conditional generative adversarial network | Yasutaka Ikuta | Meteorological Research Institute, Japan Meteorological Agency |
| Session 14: Poster flash talks (Session C) (Chair : Guosheng Liu, Nubuyuki Utsumi) | ||||
| 10:30 - 11:00 | 1. min talk by each presenter | |||
| 14.1 | Simultaneous Multi-Task Learning Strategies for Satellite Precipitation Estimates | Takumi Bannai | LTS, Inc. | |
| 14.2 | Sensitivity analysis of precipitation rate retrieval algorithms for spaceborne precipitation radar Poster |
Qiong Wu | National Satellite Meteorological Center(National Center for Space Weather), China Meteorological Administration | |
| 14.3 | Attention-Based Deep Fusion CNN for Geostationary Satellite Rainfall Estimates over Taiwan. Part 1: Model developing Poster |
Chin-Ya Chang | International Integrated Systems, Inc. | |
| 14.4 | Attention-Based Deep Fusion CNN for Geostationary Satellite Rainfall Estimates over Taiwan. Part 2: Product Evaluation Poster |
Yun-Lan Chen | Central Weather Administration, Taiwan | |
| 14.5 | A Comparative Analysis of Clear-Sky TB Estimation Techniques for snowfall retrieval Poster |
Nobuyuki Utsumi | Tokyo Institute of Technology | |
| 14.6 | Development of Satellite Precipitation in Asia-Pacific Region for Rainfall-Runoff Analysis using CNN with Meteorological Satellite Himawari | Kansei FUJIMOTO | Chuo graduate school of Science and Engineering | |
| 14.7 | The H SAF EPS-SG MWI and MWS precipitation products: machine Learning techniques for snowfall and rainfall retrieval Poster |
Giulia Panegrossi | National Research Council-Institute of Atmospheric Sciences and Climate (CNR-ISAC) | |
| 14.8 | Multi-year precipitation characteristics based on in-situ and remote sensing observations at the Arctic research site Ny-Ålesund, Svalbard Poster |
Kerstin Ebell | University of Cologne, Germany | |
| 14.9 | Satellite precipitation products behavior in cold season conditions in Poland – cases studies analysis Poster |
Bozena Lapeta | IMGW-PIB, Poland | |
| 14.10 | Retrieving Raindrop Size Distribution Parameters and Vertical Air Motion from Micro Rain Radar (MRR) Observations Poster |
Christopher Williams | University of Colorado Boulder | |
| 14.11 | Temporal and Spatial precipitation downscaling in Brazil Poster |
Alan Calheiros | INPE | |
| 14.12 | Progress of MIDAS and Challenges Poster |
Kwo-Sen Kuo | Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA | |
| 14.13 | Enhancing Satellite Quantitative Precipitation Estimation Using Neural Network Algorithms | Vesta Afzali Gorooh | Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California | |
| 14.14 | Representative Precipitation Worldwide | Mijael Rodrigo Vargas Godoy | Czech University of Life Sciences Prague | |
| 14.15 | Validation of satellite precipitation estimates over Japan using the gauge-calibrated ground radar network Poster |
Nao Yoshida | JAXA/EORC | |
| 14.16 | Validation of climate models | Francisco J. Tapiador | UCLM | |
| 14.17 | Satellite Remote Sensing of Precipitation’s Latent Heat: Physical vs. AI-based Algorithms | Rui Li | School of Earth and Space Science, University of Science and Technology of China, Hefei, China | |
| 14.18 | Mitigating False Alarms in Infrared-based Precipitation Estimates: A Multi-task Machine Learning Approach Poster |
Shruti A. Upadhyaya | 1-Department of Civil Engineering, Indian Institute of Technology Hyderabad, Telangana, India 2- Advanced Radar Research Center, University of Oklahoma, Norman, Oklahoma, USA | |
| 14.19 | Cloud phase estimation through machine learning: Applying Gaussian Mixture Models to GEO-KOMPSAT-2A observations | Dong-Cheol Kim | Yonsei university | |
| 14.20 | Simultaneous Vertical Pointing Observation by X-band Doppler Radar and Dual-frequency Wind Profiler for the Coming Era of Doppler Velocity Observation by Space-Borne Radar: Stratiform Precipitation Growth Process near the Bright Bands Poster |
Shoichi Shige | Graduate School of Science, Kyoto University | |
| 14.21 | Evaluation of Machine Learning Based Quantitative Precipitation Estimation from Ground Radar Observations at Different Time Scales Poster |
EunYeol Kim | Colorado State University | |
| 14.22 | Polarimetric Radar QPE Aided by Interpretable AI/ML | Yixin Wen | University of Florida | |
| 14.23 | A Novel Double Machine Learning Strategy for Producing High-precision Multi-source Merging Precipitation Estimates over the Tibetan Plateau | Bin Yong | Hohai University | |
| 11:00 - 12:00 | Session 14: Poster Session C | |||
| 12:00 - 13:30 | Lunch Break | |||
| Session 15: Snowfall, Scattering, Multi-frequency observations (chair : Huan Meng, Giulia Panegrossi) | ||||
| 13:30 - 13:45 | 15.1 | Correcting Snowfall Elevation Gradients by using Sentinel 1 Based Snow Depth Observations | Christian Massari | CNR, Research Institute for the Geo-hydrological Protection |
| 13:45 - 14:00 | 15.2 | Improving Satellite Mountain Snowfall Magnitudes with SWE-Reanlysis Data and GPROF-NN | Ryan Gonzalez | Colorado State University |
| 14:00 - 14:15 | 15.3 | Global Snowfall as Revealed by Satellite Precipitation Products | Lisa Milani | University of Maryland/NASA Goddard Space Flight Center |
| 14:15 - 14:30 | 15.4 | Passive microwave radiative transfer modeling considering spatiotemporal variability of ice particle shapes | Jiseob Kim | Yonsei University, Seoul, South Korea |
| 14:30 - 14:45 | 15.5 | Frozen Precipitation Particle Properties Estimated from DPR and GMI for OLYMPEX Cases | Kazumasa Aonashi | Kyoto University |
| 14:45 - 15:00 | 15.6 | Airborne observations of Arctic mixed-phase clouds, precipitation, and water vapor with state-of-the-art remote sensing instrumentation in the vicinity of Svalbard | Mario Mech | University of Cologne, Germany |
| 15:00 - 15:15 | 15.7 | Closing the drizzle observation gap with CloudSat | Spencer R. Jones | Colorado State University |
| 15:15 - 15:30 | 15.8 | Application of NASA Multi-Frequency Airborne Doppler Radar for Identification of Hydrometeor Phases | Liang Liao | Morgan State university |
| 15:30 - 16:00 | Break | |||
| Session 16: Wrap-up (Chair : Takuji Kubota, Christian Kummerow) | ||||
| 16:00 - 16:05 | 16.1 | WG 1: Baseline Surface Precipitation Network | Pierre Kirstetter, Kazumasa Aonashi | |
| 16:05 - 16:10 | 16.2 | WG 2: Merged Satellite Precipitation Products | Ali Behrangi, Daniel Vila | |
| 16:10 - 16:15 | 16.3 | WG 3: Machine Learning | Simon Pfreundschuh and Tomoo Ushio | |
| 16:15 - 16:20 | 16.4 | WG 4: CubeSat/SmallSat | Chris Kidd, Joe Munchak | |
| 16:20 - 16:25 | 16.5 | FG 1: Orographic Precipitation | Shoichi Shige; Yagmur Derin | |
| 16:25 - 16:30 | 16.6 | FG 2: Snowfall | Huan Meng, Giulia Panegrossi | |
| 16:30 - 16:35 | 16.7 | FG 3: Particle Scattering | Guosheng Liu, Nubuyuki Utsumi | |
| 16:35 - 16:40 | 16.8 | FG 4: Data Assimilation | Philippe Chambon, Yasutaka Ikuta | |
| 16:40 - 16:45 | 16.9 | FG 5: Land Surface | Joe Turk, Sarah Ringerud | |
| 16:45 - 17:30 | 16.10 |
IPWG Early Career Prizes Wrap-up and Adjourn |
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(Last update: 07 Aug 2024)