Presentation is loading. Please wait.

Presentation is loading. Please wait.

Reading – Met Office collaboration Reading RAP University: R Hogan, P-J van Leeuwen, K Shine, A ONeill, R Sutton, S Gray, J Methven Met Office: R Kershaw,

Similar presentations


Presentation on theme: "Reading – Met Office collaboration Reading RAP University: R Hogan, P-J van Leeuwen, K Shine, A ONeill, R Sutton, S Gray, J Methven Met Office: R Kershaw,"— Presentation transcript:

1 Reading – Met Office collaboration Reading RAP University: R Hogan, P-J van Leeuwen, K Shine, A ONeill, R Sutton, S Gray, J Methven Met Office: R Kershaw, D Barker, P Stott Science themes 1.From processes to parameterisation to future models 2.Advanced data assimilation 3.High-resolution convective- and urban-scale modelling 4.Multi-scale predictability and ensembles 5.Attribution and seasonal-to-decadal prediction of climate through observation and process understanding 6.Application of the science of climate and its application in adaptation and mitigation decision-making 7.Space weather

2 Diabatic influences on mesoscale structures in extratropical storms What is the origin, structure, and dynamical consequence of diabatically-generated flow anomalies in cyclonic storms and what are their consequences for rainfall and surface winds? A. Observations and detailed modelling –Observational campaign in four phases (aircraft and radar) –Doug Parker, Sue Gray, Peter Knippertz, Dave Schultz –Roy Kershaw, Phil Brown, Jon Taylor, Malcolm Kitchen B. Parametrization of physical processes –Convection in cyclones, ocean & BL fluxes, latent heat release in clouds –Bob Plant, Ian Renfrew, Tom Choularton –Humphrey Lean, Paul Field C. Predictability at the mesoscale –Ensembles and DA, balances at small scales, link to precipitation –John Methven, Peter Jan van Leeuwen, Ross Bannister –Sue Ballard, Nigel Roberts, Richard Swinbank, Dale Barker

3 Data Assimilation Confronting atmospheric models with observations –Kelly/Migliorini/Lean - Improving the use of satellite atmospheric motion vectors in high resolution NWP (EUMETSAT fellow) –Eyre/Pavelin/Migliorini - improved methods for presenting satellite radiance information to NWP systems – EUMETSAT/CASE Land data assimilation –May workshop - Mason/Garcia-Pintado/Gurney - Macpherson/Barker –Reading recently hired new Lecturer Tristan Quaife Coupled ocean-atmosphere-land data assimilation –Haines integrating project + Lawless, van Leeuwen, Matthews/Barker Convective-scale data assimilation –Balance, ensembles, covariances: Dance/Bannister/Ballard Opportunities for expanded collaboration –COPE – convection field campaign and DA –Space weather – assimilating STEREO obs. into a solar wind model © Crown copyright Met Office

4 Improving radar assimilation & nowcasting Radar attenuation is the big problem in quantitative estimates of rainfall Can lead to substantial underestimates in severe flooding events –Anthony Illingworth, Rob Thompson, John Nicol –Malcolm Kitchen, Tim Darlington, Sue Ballard, Jacqueline Sugier New idea: attenuating targets also emit microwaves and total attenuation can be estimated from increased receiver noise Met Office shortly to fund Rob Thompson to evaluate this Future work: assimilation Wimbledon storm 28 June 2011 –Emission indicates total attenuation up to 7 dB –Corresponds to a factor of 3 underestimate in rainfall which can now be corrected Also collaboration on assimilation of refractivity and insect winds

5 Forecast 3D storm structure 3D structure observed by Chilbolton DYMECS Dynamical and Microphysical Evolution of Convective Storms Robin Hogan (PI), Bob Plant, Thorwald Stein, Kirsty Hanley, Humphrey Lean, Emilie Carter –Gathering statistics on hundreds of storms and tracking their evolution with radar –Will statistically evaluate the evolution of storm size, rain rate, ice water content, updraft strength in UM, plus testing new configurations and higher resolutions –Application successful to use mOnSoOn Met Office 1.5 km model National radar network rainfall on 26 August 2011 Rain rate (mm h -1 ) Radar observations Forecast plan-view of rainfall

6 Process Studies Predictive tools Strengths and weaknesses Atmospheric Science Questions Urban meteorology (Reading – Met Office) –Heat balance and BL depth Evolution of particulate matter –Size, composition & processing Evolution of gas phase –Emission, oxidation & processing Health Drivers Particulate matter Ozone and NOx Heat waves Measurement strategy Establish infrastructure Long-term measurements to investigate seasonal variations IOPs for process studies Link to ACTUAL Urban Atmospheric Laboratory obs NERC consortium led by Reading (Stephen Belcher) with 11 other institutes including the Met Office Atmospheric Science for Health Impacts of Urban Air Quality

7 AMDAR profiles Model development Joint development of MORUSES urban scheme now introduced into JULES/UM Collaboration using mOnSoOn service Evaluation Long-term UKV being evaluated using Doppler lidar and other ACTUAL obs Large opportunity for evaluation of AQUM at high resolution over London with the huge ClearfLo dataset Process studies Boundary layer structure & depth over London Sea breezes & air quality Urban heat island Diurnal cycle London urban heat island effect modelled using high resolution UK (Sylvia Bohnenstengel) Urban meteorology Janet Barlow, Stephen Belcher, Sylvia Bohnenstengel, Sian Lane, Humphrey Lean…

8 Volcanic Ash Predictions and Observations Doppler lidars measurements at Chilbolton and Exeter have been used to evaluate the NAME model Dacre et al. (2011), JGR Devenish et al. (2011), Atmos. Env. Marenco and Hogan (2012), JGR Doppler lidars measurements at Chilbolton and Exeter have been used to evaluate the NAME model Dacre et al. (2011), JGR Devenish et al. (2011), Atmos. Env. Marenco and Hogan (2012), JGR The FAAM aircraft in-situ measurements of volcanic ash have been used to evaluate the NAME model Grant et al (2012), in prep. Dacre et al. (2012), in prep. The FAAM aircraft in-situ measurements of volcanic ash have been used to evaluate the NAME model Grant et al (2012), in prep. Dacre et al. (2012), in prep. Volcanic Ash The Eyjafjallaj ö kull volcano erupted in April 2010 emitting a plume of ash into the atmosphere. The Met Office and the University of Reading collaborated in providing urgently needed model simulations of the ash plume The MO and UoR have collaborated on a NERC proposal (PURE) to quantify the uncertainty of volcanic ash forecasts using a variety of statistical and physical models. Helen Dacre, Alan Grant, Robin Hogan, Dave Thompson, Jim Haywood, Franco Marenco, Ben Devenish

9 collaborations with Met Office High-res global modelling and applications (e.g. tropical and mid-latitude cyclones (P-L Vidale, L Shaffrey) - JWCRP post Attribution (R Sutton, J Gregory) including Changing Water Cycle - Joint posts & PhD student Asian summer monsoon (A Turner) - JWCRP post Ocean heat uptake and sea level (J Gregory) Atmosphere-land surface interactions (P-L Vidale) Convection (S Woolnough) – including CASCADE project Monthly to decadal variability, predictability and prediction (R Sutton, E Hawkins, L Shaffrey, E Guilyardi) – joint NERC & EU projects e.g. VALOR, THOR, SPECS Mid-latitude storms, storm tracks & blocking (L Shaffrey, T Woolings) Radiation and the water cycle in models and obs (R Allan)

10 Development of process-based fingerprints for attribution Changing water cycle (Beena Sarojini, jointly funded post-doc) –GCM experiments to unpick the competing role of CO2 rise and aerosols More thoroughly account for role of natural internal variability (Vikki Frith, PhD student with Peter Stott, Rowan Sutton and Ed Hawkins) Improved understanding of ocean heat content and sea level rise (Proposed PhD studentship with Jonathan Gregory, Matt Palmer) Zonal mean precipitation changes as observed (coloured lines) and modelled (MM) © Crown copyright Met Office

11 Improved decadal predictions through better use of observational constraints Ed Hawkins and Peter Stott Weight future model predictions by their agreement with previous observational constraints (ASK) to get better decadal predictions –Figure for AR5 Chapter 11 © Crown copyright Met Office

12 Space weather Coronal mass ejections have potential to knock out satellites, kill astronauts, overload power grids… –Met Office is developing new forecasting system Reading has strong expertise in this area –Lots of scope for collaboration (modelling, assimilation…) –Several proposals pending with Met Office involvement Matt Owens (Lecturer) –Numerical modelling –CME observations Chris Davis (Reader) –STEREO mission PI –Ionospheric physics Prof Mike Lockwood –Long-term solar variations –Magnetosphere –energetic particles

13 Some key challenges to address by theme 1.From processes to parameterisation to future models Boundary-layer clouds, deep convection, ocean mixing, radiative transfer New dynamical core development (GUNG-HO project) 2.Advanced data assimilation Convective-scale data assimilation (e.g. FLOOD opportunity) Making use of new observations (clouds, refractivity, radar polarization…) 3.High-resolution convective- and urban-scale modelling Enabling COPE science to go ahead Collaboration on AQUM at 1.5 km in urban areas 4.Multi-scale predictability and ensembles Strat-trop interaction, convective-scale ensembles, exploiting DIAMET obs… 5.Attribution and seasonal-to-decadal prediction of climate through observation and process understanding Process-based model evaluation, also involving NCEO, NCAS 6.Application of the science of climate and its application in adaptation and mitigation decision-making Enhance impacts prediction (e.g. flooding/crops) via better links to Walker Institute 7.Space weather Data assimilation and space weather collaboration at Reading Met Office investment: 1.5 FTEs – enough to build new capability?


Download ppt "Reading – Met Office collaboration Reading RAP University: R Hogan, P-J van Leeuwen, K Shine, A ONeill, R Sutton, S Gray, J Methven Met Office: R Kershaw,"

Similar presentations


Ads by Google