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Simulation of radar reflectivities in the UK Met Office model: comparison with CloudSat Data

Simulation of radar reflectivities in the UK Met Office model: comparison with CloudSat Data. Alejandro Bodas-Salcedo, M.E. Brooks and M. Webb GERB Science Team Meeting, Abingdon, 3 May 2007. Outline. Introduction The A-Train and CloudSat Our approach

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Simulation of radar reflectivities in the UK Met Office model: comparison with CloudSat Data

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  1. Simulation of radar reflectivities in the UK Met Office model: comparison with CloudSat Data Alejandro Bodas-Salcedo, M.E. Brooks and M. Webb GERB Science Team Meeting, Abingdon, 3 May 2007

  2. Outline • Introduction • The A-Train and CloudSat • Our approach • Description of the simulator: subcomponents • Global forecast model: comparison with observations • Conclusions and future work

  3. Relevance of clouds in the ARB ATM Radiation Budget ATM CRFs • The vertical distribution and overlap of cloud layers determine the magnitude and vertical profile of radiative heating, which then exerts an influence in the large-scale circulation.

  4. Impact on ocean heat transport • By modulating the distribution of heating between the atmosphere and the surface, clouds influence the circulation of the oceans. (Glecker, GRL, 2005)

  5. Feedback loop These large-scale impacts are connected to cloud physical properties through a feedback loop. (Stephens et al., BAMS, 2002) This loop involves a wide range of spatio-temporal scales => the Unified Model appears to be an adequate framework to link interactions at different scales

  6. A new perspective on clouds and the SARB (http://cloudsat.atmos.colostate.edu/mission/formation_flying)

  7. Synergy between active and passive sensing (ESA SP-1257(1), 2001)

  8. CloudSat - Launch April 28th 2006. Operations began on June 2nd. - Nadir pointing, 94GHz radar. - 500m vertical resolution, oversampled at 240m. - 1.4km x 2.5 km horizontal resolution - Sensitivity ~-28 dBZ - Dynamic range: 80 dBZ - Calibration: 2 dBZ

  9. Our approach • To facilitate the exploitation of CloudSat and CALIPSO data in numerical models, we are developing a system that allows to simulate the signal that CloudSat/CALIPSO would see in a model-generated world. • CFMIP CloudSat/CALIPSO Simulator (C3S): • LMD/IPSL, LLNL, CSU, UW, Met Office • Flexible tool to simulate active instruments in models (climate, forecast, cloud-resolving) • This 'model-to-satellite' approach has proven successful in recent years, with the development of the ISCCP simulator1 and the simulation of satellite channel radiances2. 1: (Klein and Jakob, 1999; Webb et al., 2001) 2: (Ringer et al., 2003)

  10. Subcomponents C3S MAIN SG PRECIP C3S SUB-GRID SCOPS CLOUDSAT CALIPSO SUMMARY STATISTICS

  11. B . A Case study I: analysis chart • 2006/07/07 Transect trough a mature extra-tropical system • Analysis chart valid at 18 UTC • CloudSat overpass from 15:14:38 to 15:21:01

  12. B A Case study I: MSG composite RGB 321 (1.6 m, 0.8 m, 0.6 m) 1330 UTC: turquoise clouds contain ice crystals, whilst white clouds are water clouds (inc. fog). Vegetation creates a green signal and sandy areas are pink. Snow covered ground is turquoise.

  13. Case study I: Ze B A 1/55 1/120

  14. Case study II: analysis chart • 2006/12/09 Transect trough a mature extra-tropical system • Analysis chart valid at 12 UTC • CloudSat overpass from 14:57:10 to 15:03:53 B A

  15. Case study II: MSG composite B A

  16. Case study II: Ze B A

  17. Case study III: analysis chart • 2006/12/14 Transect trough a quasi-stationary front • Analysis chart valid at 18 UTC • CloudSat overpass from 15:12:36 to 15:15:53 B A

  18. Case study III: MSG composite B A

  19. Case study III: Ze B A

  20. Cloud/Precipitation occurrence

  21. North Atlantic statistics

  22. Conclusions and future work • Tool to simulate radar reflectivities in the UM • New perspective on clouds and precipitation • Comparisons with global forecast model: • The overall vertical structure of ML systems is well represented • LS precipitation is also generally well captured in the occluded sector • Cloud top height matches very well the obs. • Indications of too much cirrus/cirrostratus • Indications of too much drizzle production • Need to develop more quantitative, statistically-based approaches • Developing a community simulator: • CFMIP CloudSat/CALIPSO Simulator (C3S) (LMD/IPSL, LLNL, CSU) • Flexible tool to simulate active instruments in models (climate, forecast, cloud-resolving)

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