Convective organization and the water cycle: Improving global models

1. Convective organization and the water cycle: Improving global models Mitchell Moncrieff (MMM) Changhai Liu (TIIMES Water Cycle Program & MMM)

2. Introduction • Precipitating convective systems, the atmospheric water cycle, and atmospheric dynamics are intimately interlinked on time scales pertinent to the weather-climate intersection • It is essential to quantify this linkage in order to improve physical representations in advanced prediction systems for weather and climate • Achieved through judicious use of cloud-system resolving models and theoretical-dynamical analogs verified against observations

3. Rationale • Convective organization: dynamical coherence on scales ~ X 10-1000 larger than individual cumulus clouds (a ‘systemic’ and ‘upscale’ property) • Large-scaleeffectsof convective organization: not represented by contemporary parameterizations • Cloud-system Resolving Models (CRM, grid spacing ~ few km): resolveconvective organization but not individual cumulus clouds • Next- generation global models: ( ~ 10 km) : parameterized and explicit convection coexist • Climate models & future earth-system models: convective parameterizations needed for the foreseeable future

4. RESULTS:published, emerging, analysis in progress, new study Expanding Diurnal Cycle of Precip studies to Global Background after Laing and Fritsch 1997

5. Summertime convection over the US continent: TIIMES Water-Cycle Program / MMM collaborative research Organized convection initiated by complex terrain propagating in a sheared environment

6. Vertical shear: Key to organization & propagation Noon Early next morning MCS: a cumulonimbus family Cumulo- nimbus Mesoscale downdraft Elevated solar heating: The starting block for traveling convection About 1500 km

7. Diurnal cycle of clouds and precipitation: non-uniform over the US continent Knievel et al. (2004)

8. IPCC Working Group I Fourth Assessment Report (AR4): Projected precipitation changes in global climate models over regions where people live (+/- 50 latitude) mostly show low confidence (less than 66% of the models agree on the sign of the precipitation change, white region), especially in summer conditions (red outlines) i.e.,regions with coherent patterns of propagating convection, a focus of Water-Cycle research

9. Hierarchical simulation Observed episode (3-10 July 2003, BAMEX field campaign); NEXRAD-derived precipitation provides model evaluation MM5: NCEP MRF boundary layer & surface exchange schemes; Noah LSM; GSFC microphysics; lateral boundary conditions from NCEP global analysis

10. Precipitation: 3-km grid Mountains Plains

11. Orogenesis and subsequent propagation … NEXRAD analysis (Carbone et al. 2002) 3-kmexplicit (CRM) 10-km explicit : no conv. param. 10-km: Betts-Miller Meridionally-averaged precipitation rate

12. Hybrid: Parameterized and explicit Total Parameterized Explicit

13. Resolution dependent systematic error: convective heating rate Systematic warming: Weak mesoscale downdrafts 30 km 3 km 10 km

14. Mesoscale downdraft Simulated organization C

15. Mathematical formalism Environmental shear Steering level latent heating evaporative cooling Propagation Convective Froude number: Hydraulic work-energy principle: Moncrieff-Green Equation Vorticity generated by potential temperature gradient Environmental shear Vorticity

16. Resolution dependence of convective organization 3-km & 10-km grid simulations show similar organization 30-km grid – critically distorted

17. Similarly for convective momentum transport Cumulonimbus region Mesoscale region

18. Mesoscale momentum transport by organized tilted eddies: distinct from turbulent mixing z - Eddy tilt: backward relative to propagation vector C - +

19. Parameterization

20. Early concept of penetrative cumulus ensembles (1958) adopted by mass-flux type convective parameterization community Line Islands 1967 GATE 1974 Houze et al (1980) Leary & Houze (1997) Zipser (1969)

21. ‘Ordinary’ and ‘organized’ convection are fundamentally different ‘Ordinary’convection Organized convection

22. Couple mesoscale convective organization to convective parameterization: Total tendency Coupling method needed

23. The ‘upscale’ problem of multiscale convection… n n = n + 1 + Dynamic triggering Stage 1: onset Stage 2: multicell convection Stratiform heating n n + 1 L n + 2 … Mesoscale downdraft cooling Convective scale Mesoscale Stage 3: mesoscale circulation New: Represent mesoscale heating/momentum transport in terms of the convective scale tendency

24. “Predictor-corrector” hybrid parameterization • Predictor: under-resolved explicit ‘grid-scale’ circulations – approximate mesoscale circulation: but downdraft too weak • Corrector: second baroclinic stratiform heating/mesoscale downdraft couplet strengthens downdraft In models of low horizontal resolution (e.g., climate models) grid-scale circulations are absent (i.e., no predictor), in which case the mesoscale parameterization is solely the “corrector”

25. Stratiform heating & mesoscale downdraft : the “corrector” Apply in shear zones

26. Mesoscale momentum parameterization = parameterized convective momentum transport Apply in shear zones

27. Impact on precipitation & propagation 10 m/s 12 m/s Parameterizedconvection alone Parameterized + mesoscale param (corrector) + grid-scale (predictor) 16 m/s Parameterized + mesoscale param (corrector)

28. 10 m/s 12 m/s 16 m/s a) b) c)

29. Next steps • Next steps being discussed at monthly water cycle meetings focused on convective parameterizations involving MMM, CGD, TIIMES, RAL, visitors (next meeting this afternoon) • Implement organized convection parameterization in CAM • Provides a way to measure impact of mesoscale convective organization in climate models, this ahs been missing in the past • Special interest: Convective momentum transport and mesoscale momentum transport, and their relative contributions • Brian Mapes (U Miami) and Rich Neale (CGD) have ideas on representing mesoscale organization Yaga Richter & Rich Neale (CGD) Changhai Liu & Mitch Moncrieff (TIIMES/ MMM) Brian Mapes (U. Miami)

30. Mean 3-day forecast precip error: CAM3 in weather mode DJF 1992-93 • Largest errors in regions of organized convection, e.g., ITCZ, continents, MJO, monsoons • Similarity between 3-day forecast error and 10-year climate bias Mean precip error DJF 10-year CAM3 run

31. Summary • Organized propagating systems in shear flow over the US continent were numerically simulated, dynamically approximated, and parameterized • A new hybrid parameterization of meso-convective organization for global models was formulated: • Implementation in 60-km-grid MM5 simulation shows strong effect of meso-convective parameterization on precipitation and propagation of convective systems • Plans to implement the new meso-convective parameterization in CAM in a collaborative study involving Yaga Richter (CGD), Rich Neale (CGD), Changhai Liu (TIIMES Water Cycle Program), and Mitch Moncrieff (MMM)

32. Publications Moncrieff, Liu, C., J. Dudhia, and M.W. Moncrieff, 2007: Comparison of two land surface schemes in week-long cloud-system-resolving simulations of warm-season precipitation. J. Appl. Meteor., submitted. H-m Hsu,M.W.,Moncrieff, P. Sullivan, M.J. Dixon and J.D. Tuttle, 2007. Spatial statistical properties of multiscale convective precipitation over North America. J. Climate, submitted. Liu, C., and M.W. Moncrieff, 2007: Sensitivity of explicit simulations of warm-season convection to cloud- microphysics parameterizations. Mon. Wea. Rev, 135, 2854-2868. Moncrieff, M.W., and C. Liu, 2006: Representing convective organization in prediction models by a hybrid strategy. J. Atmos. Sci., 63, 3404–3420. Hsu, H-m., M.W. Moncrieff, W-w.Tung and C. Liu, 2006: Multiscale temporal variability of warm-season precipitation over North America: Statistical analysis of radar measurements. J. Atmos. Sci., 63, 2355-2368. Liu, C.H., M.W. Moncrieff, J.D. Tuttle and R.E. Carbone, 2005: Explicit and parameterized episodes of warm-season precipitation over the Continental U.S. Adv. Atmos. Sci., 23, 91-105. Moncrieff, M.W., 2004: Convective Dynamics Issues at ~10 km Grid-resolution, Proceedings of the Workshop on Representation of Sub-grid Processes using Stochastic-Dynamical Models, ECMWF, 91-105.