1 st Chimere workshop USE OF LOKAL MODELL

1 st Chimere workshop USE OF LOKAL MODELL FOR THE METEOROLOGICAL INPUT OF CHIMERE Palaiseau, France March 21 -22, 2005 Enrico Minguzzi, Giovanni Bonafè, Marco Deserti, Suzanne Jongen, Michele Stortini Hydro. Meteorological Service of Emilia Romagna Region (SIM), Bologna, Italy 1 st Chimere workshop

Overview Objectives: • Use Lokal Modell (our operational meteorological model) as input for Chimere • Analysis (and, wherever possible, verification) of LM outputs relevant for this application • Tuning Chimere implementation for simulations over Northern Italy Summary: (work in progress) • LM and how we plan to use it • LM verification (how LM errors will impact on Chimere performance? ) • PM underestimation: testing erosion/resuspension scheme (analysis of Qsoil and U*) - Choice of operational time-step - New scheme for nucleation routine Future work/Open questions • Looking for advices… 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Lokal Modell The model: • Non-hydrostatic, limited area model (same class as MM 5, Aladin, …) • First designed by the German Weather Service, presently developed by the COSMO consortium (weather services of Germany, Switzerland, Italy, Greece, Poland) • Used for operational forecasts and research programs (see: www. cosmo-model. org) Implementation at ARPA-SIM: • 7 km horizontal resolution • 35 vertical levels (first levels: 35, 110, 200 m) • Two daily forecasts, lasting 72 hours • Initial and boundary conditions by GME (German GCM) • Data assimilation: 12 hours nudging of GTS data Operational domain of LM @ ARPA-SIM 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Lokal Modell “re-analysis” A “re-analysis” dataset is being built by storing LM fields during assimilation cycle. Applications: • Long-term and scenario simulations • Simulations whit simple dispersion models • Meteorological characterisation of areas where no measurements are available Features • Available from April 2003 • 10 parameters on model levels + 26 surface fields included; hourly resolution - to prevent model drift, some surface fields are updated from GCM every 12 hours (so this is no exactly a continuous assimilation) - presently only GTS data are included in assimilation cycle (i. e. relatively low resolution) 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

LM – Chimere interface (1) It does exactly the same job as interf-mm 5 • Input: GRIB archive. Output: input for diagmet. f • All “questionable” calculations are left to diagmet Interface steps: • Extraction form archive • Horizontal interpolation (rotated coordinates) • Temporal interpolation and de-cumulation • Calculation of pressure and mixing ratio, units conversions This is NOT a general GRIB-to-Chimere interface!! (sorry for that) • GRIB format is very general – and not as standard as it pretends to be. It is very difficult (and probably not worth) to handle all possibilities: - a lot of different options for validation times, geographic projections, vertical levels… - different models store different parameters (ex. Humidity, pressure…) • We have substantially modified the structure of Chimere calling scripts, to make it possible to prepare input files prior to model integration 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

LM – Chimere interface (2) Chimere implementation at ARPA-SIM • Input preparation split from model run • All user modifications are in a single command file (keywords) Command file (keywords) • All programs making calculations unchanged • Prevent duplication of data • When testing different model configurations, input files can be prepared only once • Easier analysis of inputs 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

LM verification Background: • Meteorological fields are a very critical input, especially In Po valley • LM has hardly ever been used to drive a chemical model Objectives • Verification of operational forecasts focused on environmental applications (routinely LM verifications concentrated on precipitation) • Find the best way to produce the input (select the most reliable parameters) • How will LM errors affect Chimere performance? Are they common to most LAMs? Some systematic errors found in LM output • Temperature profiles • 10 meters wind 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

LM verification: winter temperature Day (12 Z) Night (00 Z) Examples of winter Temperature profiles at S. P. Capofiume (rural site) Observations (black) and short term LM forecasts at different resolutions (colours) • PBL looks always too cold in LM • During night, LM strongly underestimates the strength of surface inversion (a 6 to 8 degrees inversion is frequent in Po valley) • Possible causes: surface fluxes (sensible vs latent heat? ), turbulent diffusion in PBL… • Effects on Chimere: wrong vertical mixing, high level emissions (stacks) not being considered above inversion… 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

LM verification: summer temperature T, night T, day Examples of summer Temperature profiles at S. P. Capofiume Observations (black) and short term LM forecasts at different resolutions (colours) • Temperature in the PBL is underestimated also in summer (known problem of LM), both in the diurnal mixed layer and in the nocturnal residual layer. • No night-time inversion in LM (which often occurs in Po valley) • Possible cause: LHF overestimated, SHF underestimated (errors in soil moisture, soil type…) • Effects on Chimere ? ? 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

LM verification: 10 m wind Wind speed, Bias (left) and MAE (right) as a function of validation time. Stations on plains (blue), hills (purple) and mountains (green) Verification dataset: • 74 stations in Po valley (46 plain, 10 hills, 18 mount. ) • Hourly values, 1 year (apr 2003 – mar 2004) Wind speed: • Overestimated on plain and hills, esp. during night • MAE similar in plains/hills errors are more systematic • Errors do not grow with validation time Wind direction: • Plains slightly better than mountains (MAE 60° vs 75°) 1 st Chimere workshop Wind direction, MAE E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

PM 10 underestimation (1) The most pressing problem is PM 10 underestimation activate erosion/resuspension scheme • Forced by u* and Soil Humidity (Qsoil) - Qsoil from LM - u* (and u*salt) estimated by Chimere (diagmet. f) starting form LM values of wind, q, … (Note: thermal mixing is taken into account through a term proportional to w *) • Note: in the following, LM re-analysis were used Erosion emissions: (negligible in this case) • Increase with u salt * • Decrease with Qsoil • Switched off over sea and if Qsoil > 0. 3 m 3/m 3 Resuspension emissions: 1. Proportional to u 1. 43 * 2. Decrease with Qsoil if Qsoil > 0. 15 m 3/m 3 3. Switched off over sea and if Qsoil > 0. 3 m 3/m 3 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

PM 10 underestimation (1) The most pressing problem is PM 10 underestimation activate erosion/resuspension scheme • Forced by u* and Soil Humidity (Qsoil) - Qsoil from LM - u* (and u*salt) estimated by Chimere (diagmet. f) starting form LM values of wind, q, … (Note: thermal mixing is taken into account through a term proportional to w *) • Note: in the following, LM re-analysis were used Erosion emissions: (negligible in this case) • Increase with u salt * • Decrease with Qsoil • Switched off over sea and if Qsoil > 0. 3 m 3/m 3 Resuspension emissions: 1. Proportional to u 1. 43 * 2. Decrease with Qsoil if Qsoil > 0. 15 m 3/m 3 3. Switched off over sea and if Qsoil > 0. 3 m 3/m 3 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

PM 10 underestimation (2) Resulting additional emissions are not exactly what we expected: • “biogenic” PM emissions are comparable to anthropogenic in mountain areas • but much smaller (at least 2 orders of magnitude) in Po valley Analysis of Soil Moisture and Friction Velocity: 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Soil moisture: analysis • Horizontal distribution dominated by soil type (low resolution!) • Little time variability (except annual cycle and precipitation events) • May be sistematically overestimated • No measurements available (at this time) Erosion/resusp often switched off, especially in winter days with no precipitation (where PM concentrations are higher!) 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Friction velocity: analysis 0. 5 0. 3 0. 2 0. 15 0. 10 0. 05 Chimere with LM input (wind, q, qv…) LM direct output (momentum flux) • Pattern is similar • LM values are almost double (0. 2 vs 0. 1) • Chimere much lower during night • Chimere diurnal cycle much stronger Note: u* affects also dry deposition, Kz, Zi… 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Friction Velocity: validation (1) Metodology (preliminary…): • U* measurements (sonic anemometer) available from a campaign held in winter 2002 at S. P. Capofiume (rural site in eastern Po Valley) • U* estimated by meteorological pre-processor Calmet (forced by surface observations and radiosoundings; Holtslag and Van Ulden 1983) is available for both 2002 and 2004 • Calmet output for 2002 is in good agreement with observations; we suppose that it is a good estimate also for 2004 data. Note: • In winter 2004 surface wind speed is significantly different from 2002, especially in afternoon hours • Routine measurements of soil humidity and turbulence parameters at S. P. Capofiume will begin in the next months… 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Friction velocity: “validation” (2) 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Friction velocity: “validation” (3) • During night: - Chimere underestimates; very low in specific days (0. 01) - LM overestimates (by a factor of 2) • During day: 1. Chimere (probably) underestimates; very strong diurnal cycle because of W* term (this will be even stronger in summer) - LM looks good • Further work required… 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

PM 10 underestimation Possible solutions: • Retuning the scheme in order to get higher additional emissions (soil type, salt. u*. . . ) • if erosion/resuspension is really not important, try something else (ex. multiplying SOA) • Take into account urban areas: - Approximately 10% of Po valley is urbanized (see pictures) - PM underestimation may not so large in “real” rural stations… A parameterisation for urban erosion/resuspension could be useful Urbanized areas in Northern Italy (according to Corine 1990) 1 st Chimere workshop Nocturnal illumination in Northern Italy (satellite view) E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Time step 10’ We have a problem with computer time looking for the longest possible time-step • Chimere suggestion: - 60’ (step=1) for resolution > 0. 25° - 15’ (step=4) for resolution 5 -10 km • If we could use 20’ (step=3): - CPU time reduced from 1 h 15’ to 55’ per day - 1 hour saved in a 3 days forecast • Test with 20’ and comparison with 10’ (control) - Model did not explode - Errors are usually negligible - Errors do not accumulate during the simulation - Some differences in secondary species (PM 10, PM 25), where high concentrations predicted - Local differences in primary pollutants (NH 3, H 2 SO 4, NO) close to strong emitting sources Promising results; test with strong wind required 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Nucleation scheme Surface PM 10 concentration, g/m 3, 18/02/2004 h 22 Z. Old (left) and new (right) nucleation scheme A new nucleation scheme is being tested Difference new-old • Different formulation (Kulmala et. al 2002 instead of 1998) • Allows description of very dry conditions (RH<10%) • First test: there are some differences, but rather small • Further investigations required… 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Recap. LM-Chimere interface has been built LM output looks promising, but it shows some systematic errors • Wind speed overestimation • Surface inversions The erosion/resuspension scheme needs to be adapted to Northern Italy • Either tune the scheme • Or improve inputs (soil water) • Or change approach (urban) • Friction velocity deserves further investigations (it also affects dry deposition, Kz, PBL height, . . . ) 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Future work “Near future” work • Test on a summer episode • Operational simulations over Northern Italy • Long-term verification of our regional forecasts (GEMS project) • Extend LM verification (surface inversion, micromet. station at S. P. Capofiume. . . ) • Test direct use of other optional meteorological parameters (Zi, surf. fluxes, cloud water…) • Analysis of wet/dry deposition (we have a monitoring network for wet dep. ) • Improve soil type dataset “Far future” work (looking for advices, cooperation, common interest…) ? Treatment of point sources (stacks…) ? PM verification with satellite data ? Urban parameterisation for erosion/resuspension ? Measuring campaign for PM speciation ? Data assimilation of air quality monitoring data to initialize Chimere runs 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

References Vehkamäki, H. ; Kulmala, M. ; Napari, I. ; Lehtinen, K. E. J. ; Timmreck, C. ; Noppel, M. ; Laaksonen, A, 2002. : An improved parameterization for sulfuric acid-water nucleation rates for tropospheric and stratospheric conditions; Journal of Geophysical Research (Atmospheres), Volume 107, Issue D 22, pp. AAC 3 -1. Kulmala, Markku; Laaksonen, Ari; Pirjola, Liisa, 1998: Parameterizations for sulfuric acid/water nucleation rates; Journal of Geophysical Research, Volume 103, Issue D 7, 8301 -8308. Holtslag, Van Ulden, 1983: A simple scheme for daytime estimates of the surface fluxes from routine weather data; Journal of Climate and Applied Meteorology, Volume 22, 517 -529 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Extra 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

LM verification: 2 m Temperature • LM operational forecasts, 1 year (apr 2003 – mar 2004), 284 stations in Northern Italy • Plains (blue lines): - diurnal cycle underestimated (positive bias in min, negative in max) - annual variability overestimated (positive bias in summer max, negative in winter) - RMS 2 -3 °C, better than in mountains • Mountains (green lines): - Night and winter are too cold - A lot of possible sources of errors (altitude difference, extrapolation form 1 st model level BIAS 1 st Chimere workshop RMSE E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

LM verification: 3 D temperature evolution LM forecast Observations (twice daily radiosoundings) Examples of time evolution of Temperature profile, winter (left) and summer (right) • Although the surface daily temperature excursion is underestimated, in the 200 -1500 m layer this could be correct or even overestimated… • Further analysis required 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005

Time step (2) Sensitivity to time step doubling: NH 3 surface concentrations, in an area of large emissions. This is one of the largest differences observed between 10’ and 20’ time-step simulations 1 st Chimere workshop E. Minguzzi, G. Bonafe, M. Deserti, S. Jongen, M. Stortini, ARPA-SIM Palaiseau, March 21 -22, 2005