1 / 27

Justin Glisan Iowa State University Department of Geological and Atmospheric Sciences

RACM Project Update: ISU Atmospheric Modeling Component: Part 1. Justin Glisan Iowa State University Department of Geological and Atmospheric Sciences. Presentation Outline. Update since Boulder Research Methodology and Development North American Observational Study

curt
Download Presentation

Justin Glisan Iowa State University Department of Geological and Atmospheric Sciences

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. RACM Project Update: ISU Atmospheric Modeling Component: Part 1 Justin Glisan Iowa State University Department of Geological and Atmospheric Sciences Justin Glisan, Iowa State University

  2. Presentation Outline • Update since Boulder • Research Methodology and Development • North American Observational Study • Proposed PAW Simulations • PAW CORDEX Ensemble Simulation • PAW RACM Spectral Nudging • Model Validation and Analysis • Some results

  3. Update Since Boulder…

  4. CORDEX Arctic Domain

  5. Key research questions 3. RESEARCH METHODOLOGY AND DEVELOPMENT

  6. Key Research Questions • The underlying premise of this research is the study/analysis of extreme atmospheric behavior • Temperature and precipitation • Large-scale, quasi-stationary flow regimes • Do extremes produced in PAW represent real-world occurrences? • Does spectral nudging act to filter out extreme events? • Do quasi-stationary persistent flows affect downstream extremes?

  7. NCDC North American stations Precipitation and Temperature 4. NORTH AMERICAN OBSERVATIONAL STUDY

  8. Domain of Interest • Arctic CORDEX Domain • NCDS Global Summary of the Day • Around 150 stations • Daily Precipitation and Temperature • Four analysis boxes • Based on the climatological record, weather patterns • Geographical and topographical characteristics

  9. Analysis Boxes Selection • Is station located within forcing frame? • Does station data exhibit a significant degree of temporal continuity (20% threshold)? • Four boxes: • Canada A: The Canadian Archipelago • Canada B: Sub-Arctic Canadian Plains • Alaska A: North of the Brooks Range, Arctic Sea • Alaska B: South of Brooks Range, Gulf of Alaska

  10. Observation Analysis • Each station is considered an individual realization within each box; each realization has a large number of samples =>DoF • Observations are ordered and ranked by precipitation amount and temperature • Using the 95th percentile, extreme values are extracted from the data • Further analysis will be performed to determine extreme temporal and spatial regimes

  11. Analysis of extreme and persistent model behavior as manifested in: Short-term spectrally-nudged PAW simulations on the RACM domain Long-term non-nudged PAW simulations on the CA domain Large-scale quasi-stationary atmospheric flow regimes Development of the Baseline Arctic System Climatology (BASC) Pan-Arctic SIMULATIONS

  12. PAW CORDEX Ensembles • Long-term simulations spanning E-I period • Six-members created via 1-day stagger • Simulations run over CORDEX Arctic domain • Used to study large, quasi-persistent flows and associated temperature and precip. extremes

  13. PAW CORDEX Ensembles (con’t) • Study how PAW produces large-scale atmospheric flows in the Arctic • Associated T and precip. events • Are extremes evolving with sea ice changes? • Determine if PAW replicates historic events • Baseline Arctic System Climatology • Diagnostic for extreme events • Used in fully-coupled RACM

  14. PAW RACM Spectral Nudging • Spectral nudging constrains the model to be more consistent with observed behavior • Usually activated at a specific level • Adds nudging terms to largest waves • What strength of nudging is ideal/efficient without smoothing extreme behavior? • Strong nudging may push PAW to a smooth, large-scale state while keeping mean behavior intact • Weak nudging may not correct RACM anomalies

  15. PAW RACM Spectral Nudging • WRFV3.1.1 w/ CU physics • Full spectral nudging options • Six-member ensemble (one day stagger) • Two cases: • Winter case: January 2007 (initialized in Dec.) • Summer case: July 2007 (initialized in June) • Eight nudging coefficients • Full (WRF default) • Triple, Double, 1/2, 1/4, 1/8, 1/16, 1/128 • Baseline cases

  16. SN Namelist Settings

  17. Differencing and Statistical Analysis Temporally Persistent Extreme Analysis PAW VALIDATION AND ANALYSIS

  18. Bias and Statistical Analysis • Data sets used in model validation: • ECMWF Era-Interim Reanalysis • NCDC Global Summary of the Day • Washington gridded 50-km Arctic Station data • HARA* • Analysis tools: • NCL (plotting, climatology) • JMP (statistics) • Excel (statistics, binning)

  19. Temporally Persistent Extreme Analysis • Large-scale quasi-stationary flows located by: • Blocking Index (strength) • Sum of Lyapunov Exponents (episode duration) • These features have been shown to influence weather and extremes: • Downstream of system • For multiple seasons after episode

  20. Blocking Index • The BI has a scale from 1 to 10 • Proportional to the height gradients in the blocking region • Can be use to diagnose the strength of large-scale circulations

  21. Lyapunov Exponents • Analog to flow stability • Best used as a diagnostic for locating quasi-persistent anticyclones • Decreasing positive values indicate flow stabilization • Significant shifts in planetary-scale flow • Found prior to block initiation

More Related