© Crown copyright Met Office Developments in UM Microphysics Jonathan Wilkinson Reading and Met Office Collaboration, 17 November 2009.

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Presentation transcript:

© Crown copyright Met Office Developments in UM Microphysics Jonathan Wilkinson Reading and Met Office Collaboration, 17 November 2009

© Crown copyright Met Office Contents This presentation covers the following areas Progress in improving drizzle Why we should care about fog microphysics Aerosol-cloud interactions Generic Ice PSD progress Summary, conclusions, future work

© Crown copyright Met Office Progress in Improving Drizzle Forecasters have been complaining about widespread spotty drizzle in high pressure systems for a number of years. We would like to fix this ‘model characteristic’ and improve drizzle rates in the UM. Of particular nuisance is a land-sea split that occurs in the model. Autoconversion (water turning from liquid cloud into rain) largely determined by droplet number. SEA LAND Global (40 km); NAE (12 km) UK4 (4 km); UKV (1.5 km) UKV Forecast for 14Z 06/11/09 UK4 Forecast for 14Z 06/11/09 Drops Per cc

© Crown copyright Met Office Attempts to remove the sea- land split. Steve Abel & Phil Brown’s WINTEX results show that in UK4, the 600 per cc assumption over land is too high. However, reducing droplet number to allow it to rain more will not pass verification trials unless either the surface observations and UM rain rates agree better, or evaporation is increased between the cloud and the ground. This can be done with Abel & Shipway (2007) rain fall speeds-more later. Various connections with tracer aerosol in development to generate a droplet number.

© Crown copyright Met Office Linking Aerosol to autoconversion We have a ‘MURK’ aerosol variable in the UM, which is used to detemine visibility measurements. We’ve tried using this to provide cloud droplet number, but it’s resulted in an increase in fog in the model (more later). Droplet numbers produced by the aerosol tend to be too high. Working on a few ideas to remove sea-land split (e.g. dirty-clean split, very restrained Ndrop determined from aerosol, linear variation between limits set). What are sensible limits of droplet number? MURK mixing ratio ( µg kg -1 ) Droplet Number per cc 5.0 (very clean, sea air) (clean land) (Dirty land, clean urban area) (extreme, but not uncommon value) > 4000

© Crown copyright Met Office Over-production of drizzle. Several sources (our verification, Ewan O’Connor’s work, Wyant et al, 2007) suggest the UM over- produces drizzle. Can reduce autoconversion by increasing droplet number as described earlier but may not allow model to drizzle enough (Abel & Brown, WINTEX). Abel & Shipway (2007) rain fall speeds in development to allow slower rain fall speeds for light rain rates and more evaporation NAE minus obs (mm/day) Thanks to Marion Mittermaier Log 10 v D (logarithmic scale) Blue: Present UM Black: Beard (1976) Red: Abel & Shipway (2007)

© Crown copyright Met Office Why we should care about Fog microphysics Although we can probably fix the sea land-split, fixing the drizzle rate problem is trickier. Fog drizzles in the UM! (But at a very low rate) Excess drizzle can only be transferred into cloud (qcl) or vapour (qv) – we can’t just get rid of it as we need to maintain a closed water budget. 20 m 80 m180 m 320 m500 m NAE 16/12/08 08Z Fog Fraction Pink: Rain rates mm/hr White > mm/hr

© Crown copyright Met Office Why we should care about Fog microphysics Fog fraction calculations are done with qt (=qcl+qv) in a similar method to the Smith (1990) scheme. Reducing the drizzle increases qcl and/or qv, hence qt increases and fog increases- forecasters complain about this so if we want a drizzle change in, we need to ensure fog doesn’t increase. Critical relative humidity is much higher at low model levels ( ), hence a small increase in qt can lead to a fog fraction rapidly going to 1.0 for that model grid box. Fog generally tends to be pretty stable- should not be autoconverting and drizzling! qtqt cf P(q t ) qsqs Long term aim- move the fog- generated precipitation from drizzle into a droplet settling category- much more realistic!

© Crown copyright Met Office Aerosol-Cloud interactions: Friend or Foe? Despite problems with the MURK aerosol- we are continuing some aerosol work. In reality, MURK is a very crude representation, so will look towards better aerosol schemes. ECMWF are planning to link aerosol to microphysics (Angela Benedetti’s seminar at Met Office, November 2009). We have a similar idea in our research plan: Jun 2011 Develop aerosol dependent UM microphysics. Report on results of tests in 1-D framework Jun 2012 Report on analysis of case studies with aersol-dependent microphysics in LEM and UM at variety of scales. Jun 2013 Report on whether representing aerosol-cloud interactions could improve the accuracy of NWP.

© Crown copyright Met Office Field et al (2005, 2007) Generic Ice Particle Size Distributions Now available in the UM for both mid-latitude (2005 paper) and global (2007 paper). Without PC2 cloud scheme, both schemes tend to reduce high cloud fractions in the model by around 30%- so will not get accepted! Results with PC2 appear better. 5 Feb 2009 snow case – high cloud fractions. Control (left), Field PSD 2005 (centre), difference (right). Thanks to Robert Lee

© Crown copyright Met Office Field et al 2007: Climate Validation Note Generally much better. Fallspeeds tend to convert more ice cloud into liquid- needs examination (with cloudnet radar data?) Would be good to use Alejandro’s CloudSat simulator to look at how this performs for some global model data- on our to-do list! Relative humidity our most major issue: Investigation needed to put this in UM

© Crown copyright Met Office Suggested ways that we can collaborate Droplet numbers over Chilbolton Testing of Field PSD on small sample of Cloudnet data (e.g. a few days). Compare fall speeds with Cloudnet data (and Chris’s work). Help identify Field PSD issues and recify them. Testing of other 3D options that are not yet operational: Hallet-Mossop Processes, 2 nd Ice prognostic, prognostic graupel. Identify days when forecasts weren’t that good and use Cloudnet/Cloudsat data to identify model issues.

© Crown copyright Met Office Summary and Conclusions Options are available to improve UM drizzle rates and to remove the land-sea split. However, these must be implemented carefully to avoid issues with fog. Improvements to fog microphysics and how we represent fog should be considered. However, we should at least be able to remove the land-sea split. Field’s generic ice particle size distribution is available in the mid-lat (2005) and global (2007) versions. Fine-tuning is needed to allow them to be accepted in the NWP and HadGEM models. There are lots of exciting ways we can collaborate- which should be exploited more. We can discuss this in our break-out sessions.

© Crown copyright Met Office Questions and answers