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SUMMARY OF THE MESA MODELING RELATED ACTIVITIES DISCUSSED IN VMP8

SUMMARY OF THE MESA MODELING RELATED ACTIVITIES DISCUSSED IN VMP8. VAMOS strategy of Modeling Implementation Plan. Assesment of models ( integration of NAME, MESA, VOCALS) Requires participation/ collaboration from both research groups and operational setor.

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SUMMARY OF THE MESA MODELING RELATED ACTIVITIES DISCUSSED IN VMP8

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  1. SUMMARY OF THE MESA MODELING RELATED ACTIVITIES DISCUSSED IN VMP8

  2. VAMOS strategy of Modeling Implementation Plan • Assesment of models ( integration of NAME, MESA, VOCALS) • Requires participation/ collaboration from both research groups and operational setor. • Need Integration between Field Activities, Research Modeling and Operational Forecasting.

  3. DISCUSSIONS IN PLENARY SESSION • One theme was proposed in the beginning: Diurnal cycle of precipitation and clouds. • Need to focus in a few topics, uniform for both MESA and NAME. • A list of topics was presented, with subjects that appeared on the presentations.

  4. Thematic Approach • Diurnal Cycle • Low Level Jets • PBL Processes • Orographic Effects: Coastal Winds, Precipitation • Mixed-Layer Processes • Low Level Cloudiness • Air-Sea Interactions • Air-Land Interactions • Warm Season Precipitation: Remote vs. Local Impacts • Regional Climate Change Assessment • Resolution Issues • Interactions with SSTs other than ENSO • Extra-Tropical Interactions • Predictability Assessment • Seasonality in Predictability • Low Frequency Modes • Prediction Assessment • Fresh Water Flux/Salinity Issues • Hemispheric Interactions • Scale Interactions: Temporal and Spatial (Transients…) • Convergence Zone Processes (SACZ, ITCZ) • Impact of Land Use Changes • Seasonal Predictability in a Changing Climate • Extreme Events • Intraseasonal Variability • Interactions with ENSO

  5. THEMES DISCUSSED • 1. There was a discussion about the theme of drought prediction in the Americas, that was changed to droughts and floods in the Americas. • 2. Another suggestion : Diurnal cycle • 2.1. In the theme of diurnal cycle, incorporate hydrological component , Cumulus convection and surface heating budgets. Maybe the cumulus convection parameterization is a subject that cant be achieved in a short time, then it is better to analyse the diurnal cycle of convection, rather than to test different schemes. • 3. There is still need to improve prediction of onset of monsoon and intraseasonal variability. • 4. Suggestion for a theme: Life cycle of SAMS. • 4.1 There are metrics that are important: Onset monsoon, Simulating nocturnal precipi. related to diurnal cycle.

  6. THEMES • 5. There is social impacts in the prediction of drought , in SA. We can do this in operational centers. It is important to be able to predict SST in South Atlantic. SACZ, may be elected as a theme. • 5.1. But the theme needs to be uniform in NAME and MESA. • 6. Suggestion of a theme in environmental problems. (droughts, fire, aerosols) • 6.1. Aerosol is important in the transition season. Look at surface process, deforestation. • 7. Need to link to climate change. Theme? No. This could be in each of other themes. • 8. Prediction of SST surrounding Americas (air sea interaction)

  7. MULTI-MODEL ENSEMBLE • 9. Use of Climate Test Bed (CPC/NCEP) mentioned by Mo. This facility is to climate models use, to model development. There are resources in the CTB to do activities related to modeling. It is important to use this infrastructure, working together to achieve results.(This system will accelerate the experiments, the analysis and the conclusions). (test of different physical processes). /cpc.ncep.noaa.gov/products/ctb • 9.1. The idea is to do several modeling experiments, using several models and a multi-model approach, to improve the predictions. Global Circulation Models and also regional models can be tested. Participation of CPTEC was welcome. • 10. Need to know how to do multi model ensemble, to forecasting and development applications. • 11. Consider different themes and different models. Example of Thorpex in UK that considers a diversity of models.

  8. MODELING AND FIELD EXPERIMENTS • 12. There is a need to have a bridge between weather forecast and seasonal prediction. Looking the model bias, they are similar in weather and climate forecasts. There is a need of interaction of weather community and climate community. • 13. There is a worry about coordination of experiments and design. Normally in the process of experiment design, they don’t take into account the complexity of the models. In VAMOS there is an opportunity to talk more about experimentdesign. Example of Krishnamurty paper of how to explore individual roles of modeling aspects. • 14. Importance of VAMOS of planning field experiments. Suggestion of field experiment over South Atlantic, to understand the ITCZ and SACZ behaviour.

  9. DATA ASSIMILATION • 15. Data assimilation is a topic to be considered. • 15.1. What kind of observation system we need. • 15.2. Discussion of reanalysis. To insert the data from experimental SALLJEX, we need high resolution models. We have problems in simulating convection, and we need data assimilation of other variables, as from satellite data, to improve convection. • 15.3. What should be the strategy of data assimilation. • 16. Large amount of outputs from the model experiments: how to cope with this.

  10. MODELS AND VARIABILITY IN SEVERAL TIMESCALES • 17. How the models represent the interdecadal variability. • 17.1. Interannual variability • 17.2. Intraseasonal variability. OTHER COMMENTS 18. The implementation plan should not limit participation and include hydrologists. 19. There was a comment about the large gap between research and operational group that could be considered in the project. 20. The applications are considered in a regional base, and VAMOS community can help with the applications.

  11. 5 selected themes • Diurnal cycle • Droughts and Floods • Life cycle of Monsoon • Predicting SST surrounding Americas • Data assimilation MESA AND NAME

  12. SOME TOPICS IN VMP8 PRESENTATIONS METRICS TO MODEL DEVELOPMENT : IMPROVE SIMULATION OF MONSOON ONSET IMPROVE TOTAL AMOUNT OF DIURNAL VARIABILITY AFTERNOON CONVECTION MAXIMUM AMOUNT OF NOCTURNAL PRECIPITATION TIME AVERAGE SURFACE FLUX (PRE AND POS ONSET) SPECIAL FOCUS IN SIMULATING DIURNAL CYCLE ISSUES: PERIODS TO SIMULATE, EXAME SUBMONTHLY TRANSIENT VARIABILITY NAMS: Influence of tropical cyclones on humidity flux to the LLJ. • Vertical resolution improves Evap/soil moisture relationships. • Improvement of surface dataset using satellite. • Downscale for regional models and hydrological models : Application of products: Agriculture, water resources.

  13. Hydrological Models: • Importance of local process • Importance of remote process • Dataset needed: topography, vegetation,soil type, • Observation: precipitation, river discharge, flux tower, soil moisture • Satellite: precipi., short wave, soil moiture • VOCALS: • stratus clouds over Pacific close to the South America west coast. • SST: warmer bias in prediction. • How important are eddies related to surface heat fluxes (regional ocean model)

  14. How well coupled models simulate Eastern Tropical Pacific ? • Annual mean, annual cycle, interannual variability of SST • Need to focus on improvement of coupled models • Double ITCZ problem, mix layer too shalow • Warm bias along eastern Pacific • Not enough low stratus clouds near west coast • Resolution of T126 to reproduce the diurnal cycle • Need to reduce uncertainty and increase skill • Need of regional analysis in global models • Charge to Modeling group: • Universal problems, as Resolution, Physics, Prediction, to South Monsoon Region • Using Grell convective scheme improved representation of rainfall for the SACZ all the way to the Amazon. • AGCM CPTEC/COLA : seasonal, interannual, intraseasonal, diurnal cycle. Low predictability in SAMS. • Need of new methods of analysis (cluster, probabilities, I.C,,.,..)

  15. Model resolution seems to play a key role in correctly reproducing intraseasonal variability (20-40 day) over the SAMS. • Causes for night formation of convection. • Conditions at high level. • Predictability of large scale conditions. • Get the right diurnal cycle. • Sensitivity to soil moisture. • Initialization of soil moisture improved precipi. in SACZ. • 3-D structure of MCSs analyzed by applying radar and satellite data • Problems: models are not able to: • 1) reproduce nature of the diurnal cycle of precipitation • 2) deal with the step orography in the region • 3) accurately represent MCSs (low-efficiency systems) • Improvements on radiation/cloud physics are required

  16. Several models that have similar convective schemes result in different diurnal cycles • Perform inter-comparison of mesoscale convection during SALJJEX • Is deforestation going to affect moisture transport? • Question as to whether persistence in soil moisture from previous winter-spring to onset of monsoon is model artifact • Air-sea interaction and mechanisms and predictability issues related to the formation of Convergence Zones (ITCZ and SACZ) that affect climate variability over South America • Distribution of land and sea plays a role in the convective patterns. • Development of tropical cyclones in the eastern Pacific: • 1) Provides air masses of enhanced moisture at low to mid-levels • 2) Direct passage associated with deep convection over the gulf and landfall events in Baja California

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