Short Courses

Update July 3, 2019: Short course slidees are available by clicking on the title below or via Google Drive.

There will be several short courses offered on Tuesday, June 18 from 9:00 am to 7:00 pm. If you are interested, please sign up for them when registering. Their descriptions are below:

Title: Quantitative Precipitation Estimation (QPE): observations from radar, gauges and satellites for flood prediction
Instructor:  Pierre Kirstetter - NOAA

Course description: The course focuses on precipitation information that can be obtained from various sensors and specifically from weather radars and satellites. Understanding of the uncertainties and spatial and temporal resolutions in which various techniques can capture precipitation patterns is needed to combine these techniques. Participants will explore the impact of precipitation on watershed response and hydrological modeling at local to continental scales. 


Title: Hands-on workshop on Extreme Value Analysis
Instructor:  Amir AghaKouchack & Charlotte Love - UCI, Mojtaba Sadegh - BSU

Course description: The overarching goal of this hands-on workshop is to introduce stationary and nonstationary extreme value analysis methods used in hydrology and climate research. The intended outcomes include: (a) providing the theoretical foundation for rigorous data analysis and (b) exposing participants to experiential learning through a project-based learning process. The students will need to bring their own laptops and the instructors will share sample codes and data that will be used during the workshop. The topics that will be covered include: Introduction to extreme weather events; Extreme value distributions; Univariate extreme value analysis; Multivariate analysis; Change detection methods; Stationary vs. nonstationary extreme value analysis; Temporal vs. process-based nonstationary analysis; Introduction to ProNEVA. 


Title: CHRS PERSIANN: algorithms, data products and applications
Instructor: Kuolin Hsu & Phu Nguyen - UCI

Course Description: This course provides fundamental knowledge about the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) algorithms, which have been developed at CHRS UC Irvine in collaboration with the UNESCO-IHP G-WADI network over the past two decades. The three main data products namely PERSIANN, PERSIANN-CCS and PERSIANN-CDR will be introduced with utility of each of the datasets.  Participants will also learn how to use the recently developed systems (iRain, RainSphere and Data Portal) to analyze, visualize, subset, and download the data products for their applications.


Title: A deep dive into the configuration and features of the National Water Model
Instructor: David Gochis - UCAR

Course Description: This extended presentation will provide an in depth description of the operational National Water Model (NWM) configuration of the WRF-Hydro modeling system.  The core physics components and model architecture will be discussed as will be the workflow comprising the operational model.  Aspects of foundational dataset development, verification activities and model calibration will be presented in detail.  Version-over-version changes in model configurations and in model simulation performance will be reviewed.  Participants will also get exposed to various output datasets that are generated from the operational model and a few recent and past case studies will be presented.  This forum should provide an excellent opportunity for scientists and data users to ask questions and significantly improve their understanding of the strengths, limitations and future research opportunities around the NWM.