Justin GlisanIowa State University

Department of Geological and Atmospheric Sciences

RACM Project Update: ISU Atmospheric Modeling Component: Part 1

7th DOE/RACM Meeting: Ames, IA 1Justin Glisan, Iowa State University

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

Update Since Boulder…

CORDEX Arctic Domain

3. RESEARCH METHODOLOGY AND DEVELOPMENT

Key research questions

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?

4. NORTH AMERICAN OBSERVATIONAL STUDY

NCDC North American stationsPrecipitation and Temperature

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

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

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

Pan-Arctic SIMULATIONSAnalysis 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)

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

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

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

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

SN Namelist Settings

PAW VALIDATION AND ANALYSIS

Differencing and Statistical AnalysisTemporally Persistent Extreme Analysis

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)

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

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

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