H115
Utilizing Precipitation Datasets and Quantifying Associated Uncertainties in Hydrometeorological and Climate Impact Applications
Session ID#: 156627
Session Description:
This session seeks contributions from the research, operational, and user communities that utilize precipitation datasets in applications that address scientific and societal needs from flood forecasts to climate impact studies. Uncertainties in precipitation data have a significant impact on the usefulness of these applications. This session also seeks contributions that present advances in error characterization and uncertainty quantification in diverse precipitation datasets and to enhance our understanding on how the uncertainties propagate to hydrological processes and thus affecting the modeling and data-assimilation in these applications. The session can host broad topics including evaluation efforts. Presentations that present precipitation applications and various error components in precipitation datasets are welcome.
Index Terms:
1807 Climate impacts [HYDROLOGY]
1840 Hydrometeorology [HYDROLOGY]
1854 Precipitation [HYDROLOGY]
3354 Precipitation [ATMOSPHERIC PROCESSES]
Primary Convener: Paul A Kucera, University Corporation for Atmospheric Research, COMET, Boulder, CO, United States
Conveners: Emad Habib, University of Louisiana at Lafayette, Department of Civil Engineering, Lafayette, LA, United States and Ali Behrangi, University of Arizona, Hydrology and Atmospheric Sciences, Tucson, AZ, United States
Student/Early Career Convener: Paul A Kucera, NCAR, Boulder, CO, United States
Comparative Evaluation of Gridded and Point Datasets for Drought Analysis for a Semi-arid Basin of Peninsular India (1057986)
Ajay Gupta, Indian Institute of Technology, Roorkee, Hydrology, Roorkee, India, Manoj Kumar Jain, Indian Institute of Technology Roorkee, Hydrology, Roorkee, India and Rajendra Prasad Pandey, National Institute of Hydrology, Roorkee, Environmental Hydrology Division, Roorkee, India
Assessing the performance of quantitative precipitation estimates to support the development of user-driven applications. From TMPA to IMERG V06 in western Peru. (1069281)
Vasco Manuel Mantas, University of Coimbra, Department of Earth Sciences, Coimbra, Portugal, Zhong Liu, NASA GSFC GES DISC (CSISS, George Mason University), Greenbelt, MD, United States, Yixin Wen, University of Florida, Department of Geography, Ft Walton Beach, FL, United States, George John Huffman, NASA Goddard Space Flight Center, Greenbelt, MD, United States and Claudia Caro, La Molina National Agrarian University, Lima, Peru
Spatiotemporal Characteristics of Heavy Precipitation Systems in the Upper Midwestern United States (1071994)
Yichen Tao, University of Wisconsin Madison, Madison, WI, United States, Daniel Wright, University of Wisconsin-Madison, Madison, United States and Yuan Liu, University of Wisconsin-Madison, Civil and Environmental Engineering, Madison, United States
Understating the Uncertainty in Global Rainfall Erosivity Estimated Using Multiple Satellite Precipitation Datasets (1077494)
Subhankar Das1, Manoj Kumar Jain1, Vivek Gupta2 and Aniruddha Saha1, (1)Indian Institute of Technology Roorkee, Hydrology, Roorkee, India, (2)Indian Institute of Technology Mandi, School of Civil and Environmental Engineering, Mandi, India
Multi-satellite Precipitation Estimates Can Improve Irrigation Water Decisions (1089111)
Sunil Bista1, Rocky Talchabhadel2, Sanjib Sharma3, Ganesh R Ghimire4, Jeeban Panthi Sr5, Rupesh Baniya1, Rajaram Prajapati6 and Bhesh Raj Thapa7, (1)Pulchowk Campus, Institute of Engineering, Tribhuvan University, Lalitpur, Nepal, (2)Texas A&M University, Texas A&M AgriLife Research, Texas, United States, (3)Pennsylvania State University Main Campus, Earth and Environmental Systems Institute, University Park, PA, United States, (4)Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, United States, (5)The Small Earth Nepal (SEN), Kathmandu, Nepal, (6)University of Pittsburgh, Pittsburgh, United States, (7)Universal Engineering and Science College, Lalitpur, Nepal
Overview of the 39 years of the Regional Surface and Precipitation Reanalysis System (1111596)
Milena Dimitrijevic, Environment and Climate Change Canada, Environmental Numerical Prediction Research, Dorval, QC, Canada, Vincent Fortin, Environment and Climate Change Canada, Meteorological Research Division, Dorval, QC, Canada, Nicolas Gasset, Environment and Climate Change Canada, National Prediction Development, Dorval, QC, Canada, Dikra Khendhaouiria, Environment and Climate Change Canada, Meteorological Research Division, Quebec, Canada, Juliane Mai, University of Waterloo, Department of Civil and Environmental Engineering, Waterloo, ON, Canada and Maxim Bulat, Environment and Climate Change Canada, Meteorological Service of Canada, Dorval, QC, Canada
Evaluating RDRS Quantitative Precipitation Estimates (QPEs): Hydrologic Modelling Perspective (1115130)
Dayal Wijayarathne1, Sopan Kurkute1, Tricia Stadnyk1, Alain Pietroniro2 and Vincent Fortin3, (1)University of Calgary, Department of Geography, Calgary, AB, Canada, (2)University of Calgary, Department of Civil Engineering, Calgary, AB, Canada, (3)Environment and Climate Change Canada, Meteorological Research Division, Dorval, QC, Canada
Gauge-enhanced Satellite Precipitation Estimates - Challenges and Opportunities (1118399)
Pete Peterson1, Chris C Funk2, Austin Sonnier1, Tamuka Magadzire3 and Gregory J Husak4, (1)University of California Santa Barbara, Geography, Santa Barbara, CA, United States, (2)USGS, Sioux Falls, SD, United States, (3)FEWS NET, Gaborone, Botswana, (4)University of California Santa Barbara, Climate Hazards Center, Santa Barbara, CA, United States
Preliminary Analysis for Radar-based Precipitation Frequency Estimation: Radar Product Evaluation and Conditional Error Modeling (1123134)
Bong Chul Seo1, Witold F Krajewski2, Gabriele Villarini3, Riley Post1 and Hanbeen Kim4, (1)University of Iowa, Iowa City, IA, United States, (2)University of Iowa, Iowa City, United States, (3)University of Iowa, IIHR—Hydroscience & Engineering, Iowa City, IA, United States, (4)Yonsei University, Department of Civil & Environmental Engineering, Seoul, South Korea
An Investigation of Reforecast Thinning as a Strategy to Support Calibration and Validation of the Hydrologic Ensemble Forecast Service at Reduced Cost (1126939)
Sunghee Kim1,2, James D. Brown3, Mark A Fresch1 and Ernie Wells4, (1)NOAA/NWS/OWP, Silver Spring, United States, (2)Lynker Technologies, Leesburg, United States, (3)Hydrologic Solutions Limited, Southampton, United Kingdom, (4)NOAA/NWS, Analyze, Forecast and Support Office, Silver Spring, United States
Near-real Time Daily Drought Monitoring Using Remotely Sensed and In-situ Gridded Precipitation Datasets (1147424)
Olivier P Prat1, David Coates2, Scott Wilkins1, Denis Willet3, Ronald Leeper2, Brian R Nelson4, Rocky Bilotta5, Steve Ansari6 and George John Huffman7, (1)North Carolina Institute for Climate Studies, North Carolina State University, Asheville, United States, (2)North Carolina Institute for Climate Studies, North Carolina State University, Asheville, NC, United States, (3)North Carolina Institute for Climate Studies, Asheville, United States, (4)NOAA Asheville, NCEI/CWC, Asheville, NC, United States, (5)ISciences, LLC/NIDIS, Asheville, NC, United States, (6)NOAA Asheville, NCEI/NIDIS, Asheville, United States, (7)NASA Goddard Space Flight Center, Greenbelt, MD, United States
Characterizing Hydrology for Tropical Cyclone Precipitation using Satellite, Radar-blended and Gauge-based Precipitation Products. (1158477)
Alka Tiwari, Purdue University, West Lafayette, IN, United States, Keith Aric Cherkauer, Purdue University, Agricultural & Biological Engineering, West Lafayette, IN, United States, Frank Marks, NOAA/AOML/Hurricane Research Division, Key Biscayne, FL, United States, Wen-wen Tung, Purdue Univ, West Lafayette, IN, United States and Dev Niyogi, University of Texas Austin, Jackson School of Geosciences, Austin, TX, United States
Evaluation of Uncertainty in Medium-Range Precipitation Forecasts from Different Sources and Assessing the Usefulness in Crop Irrigation Water Management (1159825)
Kirthiga SM, Indian Institute of Technology Madras, Chennai, India, Chakravarthi Balaji Dr, Professor, Mechanical Department, Chennai, India and Narasimhan Balaji, Indian Institute of Technology Madras, Civil, Chennai, India
Identification of Critical Stream Gauge Locations in the Ganga River Basin (1165856)
Akshay Singhal1, Muhammed Jaseem2, Ankit Singh3 and Sanjeev Jha2, (1)Indian Institute of Science Education and Research Bhopal, Bhopal, India, (2)Indian Institute of Science Education and Research Bhopal, Earth and Environmental Sciences, Bhopal, India, (3)Indian Institute of Science Education and Research Bhopal, Earth and Environmental Sciences, Bhopal, India
NowCasting-Nets: Representation Learning to Mitigate Latency Gap of Satellite Precipitation Products Using Convolutional and Recurrent Neural Networks (1173071)
Mohammad Reza Ehsani1, Ariyan Zarei2, Hoshin Gupta3 and Ali Behrangi3, (1)University of Arizona, Department of Hydrology and Atmospheric Sciences, Tucson, AZ, United States, (2)University of Arizona, Department of Computer Science, Tucson, AZ, United States, (3)University of Arizona, Hydrology and Atmospheric Sciences, Tucson, AZ, United States
How dry is “dry” lightning? A multi-dataset assessment of precipitation amounts associated with lightning-caused wildfire ignition across the western United States. (1179709)
Dmitri Alexander Kalashnikov1, John Abatzoglou2, Paul C Loikith3, Nicholas J. Nauslar4 and Deepti Singh1, (1)Washington State University Vancouver, School of the Environment, Vancouver, WA, United States, (2)University of California Merced, Management of Complex Systems, Merced, United States, (3)Portland State University, Geography, Portland, OR, United States, (4)Bureau of Land Management, Boise, United States
Characterisation and evaluation of error components in observational gridded precipitation datasets. (1181077)
Santiago Begueria1, J. Carlos González-Hidalgo2, Dhais Peña-Angulo3 and Victor Trullenque2, (1)Consejo Superior de Investigaciones Científicas (CSIC), Aula Dei Experimental Station, Zaragoza, Spain, (2)Universidad de Zaragoza, Dept. of Geography, Zaragoza, Spain, (3)Consejo Superior de Investigaciones Científicas (CSIC), Instituto Pirenaico de Ecología, Zaragoza, Spain
Hierarchical Weather Generators: A Comparison of Different Design Structures on Precipitation Simulation Performance (1185440)
Chinedum Eluwa1, Campbell Watson2, Jorge Luis Luis Guevara Guevara Diaz3, Bianca Zadrozny3 and Maria Julia De Castro Villafranca Garcia3, (1)University of Massachusetts Amherst, Amherst, MA, United States, (2)Organization Not Listed, Washington, DC, United States, (3)IBM Research, Rio de Janeiro, Brazil
