Cyclones and Changes in the Thermodynamic Environment

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1 Cyclones and Changes in the Thermodynamic Environment Gary Lackmann Dept. of Marine, Earth, & Atmospheric Sciences North Carolina State University With collaborators: Walt Robinson, Kevin Hill, Megan Mallard, Jeff Willison, and Michelle Cipullo

2 Motive Cyclone dynamics affected by condensational heating Climate warming: Increased water vapor (~7% C -1 ), potential for increased condensation How do large-scale thermodynamic changes alter cyclone characteristics and intensity? Implications for high-impact weather: wind & flooding events, severe convection, storm track dynamics, etc.

3 Questions For cyclonic systems with strong condensational heating: - Which cyclone characteristics respond to changes in the thermodynamic environment? - How large must thermodynamic changes be to significantly alter cyclone dynamics? 1.) Extratropical cyclone (ETC) a.) Low-level jet (LLJ) c.) Precipitation b.) Diabatic contribution to intensity d.) Changes in storm track 2.) Tropical cyclone (TC) sensitivity to thermodynamic environment a.) Size b.) Intensity c.) Precipitation d.) Frequency

run with modified thermodynamics Utilize WRF-ARW model in conjunction with GCM output Simulated composite

4 Methods High resolution required for isolation of moist mesoscale dynamics and their response to thermodynamic change (< ~20km x) Strategy: Use idealized or real-case events, control run + experimental run with modified thermodynamics Utilize WRF-ARW model in conjunction with GCM output Simulated composite reflectivity for squall line, 2-km grid length (WRF) WRF simulated composite reflectivity, Hurricane Ivan (2004), 2-km grid

Analyses or Reanalyses: Initial, lateral BC to simulate recent season or event WRF Simulated future season/event, current synoptic

5 Methods: Future Replication of Current Events After control simulation, apply GCM-derived thermodynamic change to initial, lateral BCs; uniform (tropics) or spatially varying (higher latitude) Run simulation with current pattern but future thermodynamics Analyses or Reanalyses: Initial, lateral BC to simulate recent season or event WRF Simulated future season/event, current synoptic pattern, future thermo Pseudo Global Warming ; e.g., Schär et al. 1996; Hara et al T q GCM IPCC AR4 Ensemble derived changes (A1B, A2)

6 Thermodynamic changes: IPCC AR4 GCM ensemble (2090s) (1990s), tropical area Temperature Change B1 A1B A2 Water Vapor Change Temperature profile: more stable Increased lower moisture: less stable

7 Methods: Potential Vorticity (PV) & Heating Diabatic PV tendency: projection of heating gradient on absolute vorticity vector d PV dt = s r ( &) -1 h q + s k F -1 ˆ diabatic term friction term r PV =- g V aq q p Rich get richer: Diabatic PV growth favored where PV, vorticity large Anticyclonic PV tendency Absolute vorticity vector Cyclonic PV tendency Heating maximum

8 In a PV framework, how would extratropical cyclones change in response to a warming and moistening environment?

9 PV features in idealized extratropical cyclone Stratospheric extrusion (cyclonic, dry) Upper-tropospheric anomaly, partly diabatic (anticyclonic) L Diabatic lowertropospheric anomaly (cyclonic) Surface warm anomaly (cyclonic)

10 Moisture Transport, Low-Level Jet (LLJ) Low-level jets accompanying cyclonic systems can strengthen via latent heat release (e.g., Lackmann and Gyakum 1999) Positive feedback with moisture transport and diabatic LLJ suggested by PV inversion studies Gray shading: Water Vapor Blue shading: mb PV (measure of diabatic contribution to low-level jet)

11 1-4 May 2010 Tennessee Flood Event Damage exceeded $2B USD (Durkee et al. 2012) 3-day precipitation exceeded 250 mm over substantial area Impressive low-level jet, tropical moisture plume, persistence >250 mm 3-Day total rainfall (mm) Maximum: 523 mm

Moisture Transport & Quasi-Stationary MCSs 12Z 1

(2011) Important features: 12Z 2 May 2010 -

east - Lee trough east of Mexican plateau:

12 Moisture Transport & Quasi-Stationary MCSs 12Z 1 May 2010 Moore et al. (2011) Important features: 12Z 2 May Persistent longwave pattern- trough west, ridge east - Lee trough east of Mexican plateau: Southerly LLJ, moisture transport - Stationary front, lift, repeated MCS events to north

13 Question If synoptic pattern of 1-4 May 2010 were repeated in late 21 st century, how would strength of low-level jet (and moisture transport/precipitation) compare? Hypothesis: Increased vapor, heavier rain, & stronger latent heating: - Stronger diabatic PV generation - Stronger low-level jet - Enhanced vapor-transport feedback

spacing, 1-way nesting BMJ convection outer two domains, explicit inner - WSM6

14 Methods: Control Simulation GFS analyses for initial, lateral boundary conditions (1.0 ) Initialize 00 UTC 30 April 2010, run 96h to 00 UTC 4 May /18/6 km grid spacing, 1-way nesting BMJ convection outer two domains, explicit inner - WSM6 microphysics - YSU PBL, surface layer - NOAH LSM 18 km Spatially varying GCM change 6 km 15N 45N z 54 km

15 Control Simulation Comparison Subjective impression: Control simulation credible Higher resolution runs, additional verification work forthcoming Observed Radar, 00Z 5/1-23Z 5/3 WRF 6-km control simulation

16 Current versus future composite reflectivity (contours), precipitable water (shaded) Current Future (A2)

17 Current versus future CAPE Increased lower-tropospheric vapor outweighs lapserate stabilization Current Hour 21 Future (A2) More CAPE, potential increase in dynamical precipitation due to increased updraft velocity

Current Hour 70 Future (A2) Area-averaged 900-hPa vapor

18 Current versus future composite reflectivity (red contours), 850-mb mixing ratio (shaded), wind > 25 kt Current Hour 70 Future (A2) Area-averaged 900-hPa vapor increase over Gulf of Mexico: ~21%, consistent with ~3 C warming

72-h Precipitation Total: Current vs Future D3 (6

Current) Maximum difference > + 500 mm, due mostly

19 72-h Precipitation Total: Current vs Future D3 (6 km) Current D3 (6km) A2 Future Max = mm, Q2 max: 523 mm Max = mm ~35% increase D3 (6 km) Difference (Future Current) Maximum difference > mm, due mostly to south/eastward shift Area-averaged precipitation increase: 36% for northern flooding region

20 Spatial & Temporal Average Comparison Future: Stronger latent heating to north, less difference to south Expect insignificant diabatic PV tendency difference over Gulf of Mexico (LLJ location) Latent Heating: (N) N Latent Heating: (S) S

21 Spatial & Temporal Average Comparison PV tendency: Stronger cyclonic lowertropospheric tendency to north expected! Stronger negative tendency above 500 hpa Weak differences in southern region Diabatic PV tendency (N) N Diabatic PV tendency (S) S

22 Spatial & Temporal Average Comparison Future: PV generally larger below 200- hpa in both regions, smaller above Higher dynamic tropopause in future PV increase apparently not directly due to diabatic processes PV (N) N PV (S) S

23 Averaged PV Budget Comparison Why is PV larger in future throughout most of troposphere? Lapse-rate stabilization below 200 hpa matches cross-over point Back-of-envelope computation supports ~.1 PVU increase in future PV (N) Temp (N)

24 Spatial & Temporal Average Comparison V-wind component slightly stronger aloft (N), slightly weaker near surface in north In southern region, V-wind component generally weaker in future simulation Little evidence for future LLJ strengthening for this case V wind (N) Why not? V wind (S)

25 mb PV (shaded) SLP (contours)

800-900 mb PV (shaded) SLP (contours) Control D01 No Terrain D01

weaker LLJ and southerly flow Suggests orographic effects, lee

26 mb PV (shaded) SLP (contours) Control D01 No Terrain D01 Removing terrain results in higher pressure in western Gulf, weaker LLJ and southerly flow Suggests orographic effects, lee trough more important than condensational heating for southern portion of LLJ

800-900 mb PV (shaded) SLP (contours) Control D01 No Terrain D01 H 304

no-terrain simulation (304 mm versus 96 mm for Domain 1) Lee trough,

27 mb PV (shaded) SLP (contours) Control D01 No Terrain D01 H 304 Much heavier precipitation in flood zone in control relative to no-terrain simulation (304 mm versus 96 mm for Domain 1) Lee trough, Mexican terrain critical during this event, but no climate change for this aspect

28 Tropopause Differences (θ, wind) Current Future Fut-Curr Fut-Curr Wind Stronger southwesterly flow in future on tropopause perhaps related to slightly faster trough progression (Rossby wave)

29 Summary: LLJ Future A2 simulations: Heavier precipitation, as expected with increased vapor content Despite this, do not see systematically stronger low-level jet Reasons? - Topographic role in LLJ enhancement (western Gulf) less affected by climate change than latent-heat driven LLJ - Stronger convective ascent, low stability- lessen dynamical response of LLJ (also limited stratiform precipitation) Future work: Examine cases with condensation-driven LLJ Additional diabatic strengthening of upper ridge, upper jet downstream of heavy precipitation in future simulation

30 Tropical Cyclones (i) Environmental humidity & TC size (ii) Climate change and TC intensity, frequency PV isosurface (grey) in idealized tropical cyclone simulation

31 Tropical Cyclones: Size TC size important for: Storm surge, storm duration, evacuation area, timing of onset of TC winds, precipitation amount, etc. Despite importance, we have limited understanding of processes that control TC size, and limited predictive ability

32 Tip, 11 October 1979 Supertyphoon Tip (1979) Max Wind: 85 m/s Gale diameter: 2200 km Gale area: ~3,800,000 km 2 Tracy Cyclone Tracy (1974) Max Wind: 65 m/s Gale diameter: 100 km Gale area: ~7,900 km 2

33 Hypothesis Extent of outer-core precipitation influences TC size via diabatic PV generation TC size sensitive to environmental humidity All else equal: Dry environments will exhibit less spiral band activity, narrower PV distribution, smaller TCs Moist environments favor spiral banding, broader PV distribution & larger TCs

34 Simulated composite radar, hour 168

35 Discrete Jumps in RMW (only in 80% run) RH 04RH 06RH 08RH Radius of Maximum Wind (km) RMW (km) \ Hour Simulation hour

36 Summary: TC Size Breadth of PV distribution related to outer-core precipitation, sensitive to environmental RH Feedbacks? Wind field expansion: Favors outer-core moistening Increases efficiency of diabatic PV production Likely that several factors influence observed TC size Alberto, in dry midlevel environ, 20 May 2012

37 TCs and Climate Change An Inconvenient Truth Webster et al GRL

TCs and Climate Change Favorable Increased SST, MPI Increased vapor content, precipitation, latent heating Increased convective available potential energy (CAPE) Unfavorable Lapse rate stabilization,

38 TCs and Climate Change Favorable Increased SST, MPI Increased vapor content, precipitation, latent heating Increased convective available potential energy (CAPE) Unfavorable Lapse rate stabilization, reduced thermodynamic efficiency Increased convective inhibition Weakening of tropical circulation Increased vertical wind shear (basin dependence) Larger mid-level saturation deficit A1B Atlantic MPI Difference: 5 to 20 mb increase in potential TC intensity

39 TCs and Climate Change Previous experiments illustrate TC structural sensitivity to the thermodynamic environment Can use same idealized model design to run storm to quasisteady intensity with constant SST, no shear environment Compare equilibrium strength using analyzed current environment versus future projections from GCM ensemble Examine: TC Precipitation Intensity Frequency

40 Thermodynamic Changes 20-member IPCC AR4 GCM ensemble Change: Difference in 10- year spatial averages (September) over tropical N. Atlantic, 1990s & 2090s Apply to initial, boundary conditions, re-run WRF B1 A1B A2 Δ mixing ratio ΔT Moisture: Constant relative humidity (RH), calculate mixing ratio at modified temperature

41 TC Precipitation and Climate Change Simulation name Min SLP (hpa) Increase in SLP deficit (%) Precipitation (R < 250 km) MPI change (% relative to control) Ctrl 2km 919 B1 2km % +8 % 6.5% A1B 2km % +20 % 9.0% A2 2km % +27 % 10.7% MPI increase: 6-11% Intensity increase: 11-19% Rainfall increase: tied to vapor more than updraft, in eyewall Rain Rate (in/hr) Current Future Eye

steady-state PV tower related to precipitation rate 8 km

42 TC Intensity and Climate Change Lapse-rate stabilization, but more CAPE Heavier precipitation for future TCs: Strength of steady-state PV tower related to precipitation rate 8 km Current A1B up PVU PVU Time-averaged PV cross sections

43 TC Frequency and Climate Change WRF-ARW, version 3.2 KF convective scheme (CP) On 54- & 18-km grids Initial & boundary conditions: 1 GFS FNL analyses 0.5 RTG SST (24 h) Mini-physics ensemble (PBL, microphysics) Δx=54 km Δx = 6 km Δx=18 km Ocean mixed layer model (OML) for TC cold wakes TC wake Modified to combine SST update with OML

Future Replication of Current Season Apply horizontally uniform

with future thermodynamics Preserves synoptic pattern, initial

recent season or event WRF Simulated future season/event, current

44 Future Replication of Current Season Apply horizontally uniform thermodynamic changes to current analyses Replicate current season with future thermodynamics Preserves synoptic pattern, initial disturbances & ~ wind shear GFS analysis data: IC, BC to simulate recent season or event WRF Simulated future season/event, current synoptic pattern, future thermo T q GCM IPCC AR4 Ensemble derived changes (A1B, A2)

45 High-Resolution Basin Simulations Side-by-Side Ensemble Member E3 September 2005 A1B Modified Future simulations: Reduced TC activity with same synoptic pattern

46 High-Resolution Basin Simulations Side-by-Side Ensemble Member E3 September 2005 A1B Modified Future simulations: Reduced TC activity with same synoptic pattern

Future TC Activity Change Ensemble mean activity change Accumulated Cyclone Energy (ACE) reduced in future (both resolutions, 2005 + 2009) Storm count decreases at

47 Future TC Activity Change Ensemble mean activity change Accumulated Cyclone Energy (ACE) reduced in future (both resolutions, ) Storm count decreases at both 18 and 6 km grid length Fewer storms, longer time to genesis, shorter duration 2005: -45% 6 km ACE 6km Sept. 2005: Count -18% -19% 2009: -23% Current Future -17%

48 Prior Work: Projected TC Changes Knutson et al. (2010) review: Of 8 modeling studies reporting global results: All 8 report TC frequency decrease (8-34%) Strong TCs: Suggested frequency increase in high resolution studies Why does TC frequency decrease? Several proposed mechanisms Here: Experimental design allows comparison

49 Causes of future TC frequency reduction? Past work: Frequency decrease in warming due to: Increased stability, decreased TC efficiency (e.g., Sugi et al. 2002; Yoshimura et al. 2006; Oouchi et al. 2006; Bengtsson et al. 2007; Gualdi et al. 2008; Hill & Lackmann 2010) Weakening vertical motion in tropics (e.g., Sugi et al. 2002; Bengtsson et al. 2007; Murakami and Wang 2010; Lavender and Walsh 2011) Increased vertical wind shear (e.g., Gualdi et al. 2008; Garner et al. 2009) Increased TC sensitivity to shear (Nolan and Rappin 2010) Increased mid-level saturation deficit (Emanuel 2008, Rappin et al. 2010)

50 TC Incubation Parameter Emanuel et al. 2008; Rappin et al. 2010: c m = s - s c b mid mid * s0 - sb c flux Proportional to time until TC genesis * s 0 s mid * s mid s b Larger c mid & TC frequency: - Larger midlevel saturation deficit: more subsaturated downdrafts - Near saturation necessary condition for TC genesis - Delayed TC genesis, reduced TC frequency Lq v s cplnt - Rd ln p + - Rv q ln RH T See Emanuel 1989, 1995, Emanuel et al. 2008, Rappin et al. 2010

51 Comparison: Developing & Non-Developing Current & Future Cases # 1 to 4 (D/ND) Develops (D) in current simulation, corresponding disturbance non-developing (ND) in future simulation Cases # 5 & 6 (D/D) Genesis occurs in similar timeframe for both current/future Focus on representative D/ND events, use matching ensemble members (physics choices)

52 Case 1: D/ND Initial disturbance appears as closed low, convection to east, south Current Current: convection persists, TC genesis Future Future: convection dissipates Model simulated radar & sea-level pressure (every 2 hpa) 7 Sept. 12 UTC to 11 Sept. 12 UTC 2005, 1 st ensemble member

53 Initial disturbances enter marginal humidity environment Current: Convection moistens environment, reduces saturation deficit Future: large deficits persist, convection eventually dissipates Case 1: D/ND Current Same RH in each Future c mid Incubation (c m )

54 Case 5: D/D Current For favorable moisture environments, genesis occurs in both simulations Future c mid Incubation (c m )

55 Summary: TC Frequency Reduced future peak season TC frequency, even with same synoptic pattern, shear environment Comparison: several incipient TCs in marginal humidity environments fail to develop in future, but able to develop in current Why don t future TCs develop? Increased mid-level saturation deficit (c mid ), Increase in incubation parameter: Longer time to genesis Increased CIN, less convective triggering? Results: thermodynamic effect alone can explain TC frequency decrease; changes robust across GCMs

56 Summary: TC Frequency Results consistent with Emanuel et al. (2008, 2010), Rappin et al. (2010); contrast with Garner et al. (2009), Lavender & Walsh (2011) Basin dependence? Do more TCs currently form in marginal humidity environments in Atlantic relative to other basins? Caveat: Did not examine shoulder month activity; some indication of more vortex-like development in future runs for off-peak events

57 Overall Summary Tropical & extratropical cyclones are sensitive to changes in larger-scale thermodynamic environment Analysis of sensitivity demands high resolution (e.g., 2-20 km x for mesoscale, diabatic processes: Downscaling Thermodynamic changes derived from GCM ensembles are sufficient to produce significant changes, quite robust Dynamic changes only partially represented with these experiments; need global downscaling with coupled model Joint meetings of this type are beneficial for interactions between climate & weather research communities

58 Thanks to CMOS & WAF/NWP Committees for the honor of this invitation and Thank You

59 Acknowledgements Thanks to CMOS & WAF/NWP organizing committees for the honor of this invitation U.S. National Science Foundation (NSF) grant AGS and U.S. Department of Energy (DOE) grant ER64448 awarded to North Carolina State University; WRF model is made available through NCAR, sponsored by the NSF Grant RPI From Bermuda Institute of Ocean Sciences, awarded to North Carolina State University ( High-resolution modeling studies of the changing risks of damage from extratropical storms ) Model simulations were performed at the Renaissance Computing Institute (RENCI), which is supported by UNC Chapel Hill, NCSU, Duke University, and the state of North Carolina. The Program for Climate Model Diagnosis and Intercomparison (PCMDI) for collecting and archiving the CMIP3 model output The WCRP s Working Group on Coupled Modeling (WGCM) for organizing the model data analysis activity. The WCRP CMIP3 multimodel dataset is supported by the Office of Science, U.S. Department of Energy. This research represents a portion of Megan Mallard s and Kevin Hill s PhD dissertations Kevin Hill, Megan Mallard, Jeff Willison, Michelle Cipullo, Anantha Aiyyer, Walt Robinson, and Fred Semazzi all contributed to this work

60 Overall Summary Tropical & extratropical cyclones are sensitive to changes in larger-scale thermodynamic environment Analysis of sensitivity demands high resolution (e.g., 2-20 km x for mesoscale, diabatic processes: Downscaling Willison, Robinson, and Lackmann (2012, in prep): storm track EAPE generation at 120, 20 km x

61 Overall Summary Thermodynamic changes derived from GCM ensembles are sufficient to produce significant changes Dynamic changes only partially represented with experimental design employed here; global downscaling underway However, GCM-ensemble thermodynamic changes quite robust, higher confidence in this aspect Joint meetings of this type are beneficial for interactions between climate & weather research communities

62 Extras

63 Overall Summary Response of cyclonic systems to changes in thermodynamic environment not restricted to climate change problem Low-level jet case presented here (May 2010) did not exhibit significant strengthening: dominance of terrain effect Other notable changes include increased CAPE, higher dynamic tropopause, stronger upper westerlies Understanding cyclone response to changes in thermodynamic environment helpful in storm-track change context

64 Steady Growth of Hurricane Wind Radius 02RH 04RH 06RH 08RH Radius of Hurricane Force Wind (km) RHFW (km) Simulation Hour hour RHFW growth during RMW growth, & when RMW not increasing RMW controlled by inner-core PV, RHFW by outer

65 Growth period 850 hpa PV, wind radii 20RH 80RH Radius of Tropical Storm force wind (18 m/s) Radius of Hurricane force wind (33 m/s) hpa PV

66 Experimental design allows comparison of same initial disturbances in current, future environment Vrel difference domain 3 hour mb, fut-curr

67 How Would Climate Change Affect the LLJ? Warming climate: Roughly 7% specific humidity increase per C warming Condensational heating with cold-frontal precipitation strengthens LLJ Climate change: Potentially more condensation, stronger LLJ? Implications: Precipitation amount, wind damage, convective environ A B N A L B

68 Summary: LLJ Several additional experiments underway: - Extratropical transition event (Nicole, 2010) - Extratropical cyclone Xynthia - Composite-based simulations Xynthia case, February 2010 Nicole case, November 2010

Spatial shift of LLJ complicates comparison Need to compute temporal,

69 Low-Level Jet Strength Comparison D 850 mb wind speed, 48 h D 700 mb wind speed, 66 h Systematic changes weak in lowertropospheric wind speed Spatial shift of LLJ complicates comparison Need to compute temporal, spatial averages of wind, PV, PV tendency Averaged over areas below, hours S N

Climate Change: Mesoscale and Synoptic- Scale Precipitation Events

Climate Change: Mesoscale and Synoptic- Scale Precipitation Events Gary Lackmann, North Carolina State University Collaborators: M. Cipullo, J. Willison, M. Mallard, W. Robinson CLIVAR Workshop on LSMPs