Quick overview of ATM 419/563 ATM 419/563 Spring 2019 Fovell

Goal How to use WRF in support of scientific experimentation with an appreciation of its capabilities, an understanding of its strengths, and an awareness of its limitations The goal is to open up the “black box” You need to be skeptical about what you see I will provide compiled (often customized) executables of the WRF model and supporting programs, and scripts for running model and analyzing output You can use these materials as learning examples and starting points Later in course, if you want to compile your own, I can help Control the degrees of freedom

Overview WRF model simulations Model physics and numerics topics 1D, 2D, and 3D idealized Real-data runs Model physics and numerics topics Planetary boundary layer and surface layer schemes There are 13 PBL schemes in WRF. How do they work? How do they differ? Cloud microphysics There are 26 microphysics schemes in WRF. Which to choose for the problem at hand? Cumulus parameterizations When and why do we need both microphysics and cumulus schemes? How and when do they cooperate and conflict? 15 cumulus schemes in WRFV4.0 Sources of model error Diagnosing linear and nonlinear instability Give people a lot of options, they tend NOT to explore

Simulations Idealized simulations may include Boundary layer evolution Downslope windstorms Sea-breeze circulations Squall line thunderstorms Splitting supercell storms Real-data cases may include Convective outbreaks at various resolutions Extratropical cyclones Tropical cyclones Snowstorms Windstorms Fog cases

Real-data WRF topics Designing and placing a domain Selecting topographic and landuse databases Map projections and map factors Creating telescoping grids Initializing real-data simulations Combining different initialization data sources Model verification against surface and upper air observations Altering model vertical levels from default Modifying topography and other landscape features Model diffusers and dampers – what/when/where/why Stochastic perturbations Analysis nudging Moving nests Bogussing tropical cyclones Adaptive time stepping Nestdown and 1-way nesting WRF restart capability Creating and/or archiving extra model fields Implementing passive tracers

Tools WRF model WRF Preprocessing System (WPS) NetCDF ncview read_wrf_nc program GrADS (Grid Analysis and Display System) wrf_to_grads NCL (NCAR Command Language) RIP (Read-Interpolate-Plot) package IDV (Integrated Data Viewer) UPP (Universal Pre-Processor) MET (Model Evaluation Tools) ImageMagick convert and display Python

Initialization data sources GFS FNL (GFS Final Analysis) NAM RAP and/or HRRR NARR (North Americal Regional Reanalysis) CFSR (Climate Forecast System Reanalysis) NNRP (NCEP/NCAR Reanalysis Project) ERA-interim [others]

Data sources NCEP NOMADS archive NCDC/NCEI NOMADS archive NCAR Research Data Archive (RDA) MADIS archive Other NCDC/NCEI archives [more]

Grading Common complaint: I don’t give indication of grade before semester ends

Tasks Attendance In-class demonstrations Experiments Final project No exams (probably)

Final project Identify a topic of interest to YOU Discuss it with me sooner rather than later (especially for viability) Formulate testable hypotheses Design an experiment using WRF Use tools, insights, and strategies learned from this class in your experiments and analyses Produce a final project in presentation format It doesn’t have to be “publishable”, just new to you, so you gain something from this

From the syllabus A key component of the course grade is the final project. An “A” level project will have identified a viable topic, constructed thoughtful hypotheses and designed a reasonable experiment to test them, analyzed the results thoroughly and with care, crafted figures that are useful, clear, and attractive, and have produced a presentation that is well-organized, coherent, and displays what you did, how you did it, and what you learned. The “B” level is high quality work that shows thoughtfulness and effort but reaches the “A” standards less fully or consistently.

Snapshots from some past student final projects

Tropical cyclone: 10 m wind sensitivity to PBL parameters Control Mod1 Mod2 Mod3 Time [hours] Lugo 2017 – Hurricane vary PBL parameters Distance from center [km] Color shaded indicates maximum wind intensity (every 5 ms^-1). Black (red) contours indicate the isotachs at 10, 20 and 30 ms^-1 for control run (each individual run)

Terrain set to 50% of normal Terrain set to 100% of normal Simulations of TC Matthew Terrain set to 50% of normal Terrain set to 100% of normal Terrain set to 150% of normal Davis 2017 Real-data simulation of TC Matthew & variation of topo height October 2nd 12Z

Simulated Reflectivity 02Z (18th): sensitivity to microphysics McGuinnes 2017 – Vary microphysics for lake effect case

Heavy precipitation case: one vs. two domains Conway & Gallagher 2016 – Heavy rain event, illustrates issues w/ nesting

6Z Observation (radar) The best simulation for intensity Pryzyblo – 2018 – just a small part of this analysis/comparison

Effect of topography and surface roughness change on landfalling hurricane RUN1 RUN2 RUN3 RUN4 Zhou – 2-18 Fig 7. Maximum radar reflectivity at 41 h for (a) RUN1, (b) RUN2, (c) RUN3 and (d) RUN4, shaded semi–transparent grey area stands for land surface in model, while white area represents water surface.

Three month mean OLR Obs WRF (fix SST) WRF (vary SST) WRF tropical channel outgoing longwave radiation (OLR), with and without time-varying sea-surface temperature (SST), vs. analysis OLR (presumed truth) Numerous differences from observation, many of which not mitigated by varying SST WRF (fix SST) WRF (vary SST) Shabaan - 2018

Final thoughts You will get out of this course precisely what you put into it You are in this course for your sake, not for mine This will sometimes be hard, other times quite tedious, but ultimately it should be fun

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