1. Toward a Mesoscale Modeling-Observations Plan for NAME
Mitchell W. Moncrieff,
NCAR/MMM, Boulder CO
NAME 3rd Science Working Group Meeting,
Oct 25th 2002, George Mason University, VA.

2. The context
Recommendation: The U.S. CLIVAR SSC has recommended that NAME organizes a Mesoscale Modeling-Observations (MM-OBS) team aimed at interlinking the mesoscale modeling community (especially physical parameterization interests) and NAME field measurements. 
Motivation: Contribute to a ramp-up strategy for the NAME Field Campaign; provide guidance on needs and priorities for NAME observations; identify sustained observational requirements; identify additional process studies necessary to reduce uncertainties; and develop partnerships between observations and modeling.
Focus: Parallel to the Atmospheric Global Circulation Model–Observations (AGCM-OBS) team focus on the warm-season diurnal cycle over the US and Mexico in AGCM’s.  

3. Basic points
Physical processes on scales order 1 km-100 km are fundamental to the diurnal cycle of convection.
Diurnal cycle and the organization of convection on mesoscales cannot be legitimately separated.
Mesoscale processes are not resolved in GCMs, not resolved or distorted in NWP models and RMMs (the scale-separation issue).
Mesoscale processes measured by the NAME Tier 1 observing facilities are represented explicitly by cloud-system-resolving models (CSRMs) over a similar dynamic range (1 km – 100’s km).
Gives prospect for understanding the diurnal cycle and the large-scale role of organized convection in complex coastal terrain and addressing convective parameterization aspects.

4. Parameterization
NAME Tier 1 observations
Regional mesoscale modeling
Cloud-system-resolving models
(CSRM)
CSRMs interlink Tier 1 observations, regional mesoscale modeling and parameterization goals of the NAME

5. MM-OBS tasks <linkages>
Develop a research strategy complementary to the AGCM-OBS Team <diurnal cycle of convection in complex coastal terrain>
Define how MM-OBS will complement on-going regional mesoscale modeling <explicit convection, mesoscale observations of surges, etc.>
Contribute to NAME needs for weather/climate prediction  <parameterization of convection, cloud-radiation interaction, effects of terrain>

6. NAME Tier-1 observations, Cloud-System- Resolving Models
Cross-scale linkages
NAME Tier-1 observations, Cloud-System- Resolving Models
Regional Mesoscale Models
General Circulation (Climate) Models
Global NWP Models

7. Over-arching objectives of MM-OBS
To describe, model and understand the processes that determine the diurnal cycle of convection and the attendant distribution of precipitation in the core region of the NAME.
To use the explicit cloud-system-resolving model approach to improve the representation of convection in prediction models, with focus on the effects of complex coastal terrain.

8. Specific objectives of MM-OBS
To describe, model and understand the processes that determine the diurnal cycle of convection and the mesoscale organization of convection in the core region of the NAME.
To address convective parameterization issues in the NAME locale using cloud-system-resolving models (CSRM).
To describe, model and understand the mechanisms responsible for the generation of southerly surges and low-level jets in the Gulf of California.
To quantify far-field relationships between organized convection in the mid-US continent and convective cloud systems in NAME Tier 1 region in regard to tropical easterly waves and mid-latitude westerly troughs.

9. Diurnal cycle and convective organization in NAME
Processes:
- sea- and land-breeze circulations
- orographically and convectively generated gravity waves
- propagating, organized convection (non-local dynamics)
- lee vortices in low-Froude-number mean flow
- ITCZ and easterly wave ‘flaring’
- Gulf-surge dynamics
- far-field influences
Parameterization:
- convective triggering, transport, closure
- convective organization, scale-separation

10. Processes in complex coastal terrain
Interaction between convectively generated gravity waves, terrain and the diurnal cycle of convection.
Lee-effects of thermally forced low Froude number flow past complex terrain on the location/life-cycle of convection.
Role of local forcing (surface fluxes, quasi-stationary convergence zones, sea-breeze and land-breeze circulations).
Processes that organize convection on the mesoscale.
Dynamics of southerly surges, LLJ in Gulf of California in the context of easterly waves and convection.
Far-field influence of the monsoon moisture and dynamics on precipitating systems that form over Colorado, mod-continental US.

11. Convective triggering: sea-breeze dynamics
Crook (2001)

12. Convective triggering: low-level flow and shear
Moncrieff and Liu (1999)

13. Orographically and convectively coupled gravity waves
Mapes et al. (2002)

14. Low-Froude-number lee vortices
Reisner and Smolarkiewicz (1994)

15. Easterly waves and ITCZ ‘flares’
TRMM
GOES

16. Gulf surges
Adams and Comrie (1997)

17. Interlinking NAME Tier 1 observations, CSRMs and parameterization: The GATE legacy

18. NAME domains

19. Soundings, radar networks and CSRM simulations
GATE
NAME Tier 1

20. Squall system
Deployment Issues

21. Convection and easterly waves: the GATE simulation
CSRMs have simulated convection over tropical oceans and in association with major multiscale field-programs: GATE and TOGA COARE.
Large-scale forcing prescribed from objectively analyzed data from network of tropospheric soundings.
Results used for evaluation/development of physically based parameterization of convection and cloud-interactive radiation.
This multiscale cloud-system simulation is feasible for the NAME Tier 1 domain – in the challenging physical setting of complex coastal terrain.

22. Easterly-wave-modulated convection
Synoptic-scale baroclinic variability (large-scale forcing, shear) by easterly waves controlled the organization of convection in GATE over a 1-week period.
CSRM used to study this aspect and attendant parameterization issues using large-scale forcing derived from GATE sounding network.
Similar strategy could be used for NAME Tier 1, complex coastal terrain an extra challenge.

24. Convection and GATE easterly waves: A snapshot

25. CSRM convective mass fluxes
Grabowski et al. (1998)

26. CSRM clouds and radiation

27. Interlinking RMMs and CSRMs: Hierarchical modeling
Kain-Fritsch
In the hierarchical approach, CSRM & parameterizations are run using the same non-hydrostatic dynamical core but at different resolution.
Left: CSRM run at 2-km grid resolution.
Right: Kain-Fritsch (K-F) parameterization at 15-km grid-resolution.
Liu et al. (2000)

28. CSRM-derived parameterization issues
Overly deep convection and extensive cirrus a result of excessive detrainment of condensate.
Sensitivity to grid-scale moisture feedback from convective parameterization.
Parameterized overshoot-generated adiabatic cooling at cloud tops too strong, resulting in cold bias.
Over-prediction of low-level moisture attributed to parameterized downdrafts.
These shortcomings stem from the single-plume model used in the parameterization, which does not represent the trimodal distribution of cumulonimbus, congestus, and shallow convection observed by Johnson et al. (1999) and simulated by the CSRM.

29. Easterly waves, ITCZ ‘moist flares’ in TRMM monthly composites

30. Far-field influences
Saleeby and Cotton (manuscript)

31. Liu and Moncrieff (2003)

32. Total condensate 18 UTC 12 MDT 00 UTC 18 MDT 06 UTC 00 MDT 12 UTC

33. Conclusion
Key point: CSRMs can integrate the observational and parameterization objectives and the mesoscale and large-scale objectives of the NAME.
Use of CSRMs in convective parameterization development developed over a number of years by international GEWEX Cloud System Study (GCSS) and also by individual efforts.
Field-observation/CSRM collaboration a legacy of GATE and TOGA COARE field programs.
Complex coastal terrain of NAME a challenging next step in collaborative observational-modeling efforts.
Evaluation of CSRMs an intensive activity, relying on the NAME Field Program design (e.g., sounding network, radar, lidar) and post-field analysis (mesoscale, cloud-scale)