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George Kallos With contribution from S. Solomos, I. Kushta, M. Astitha, C. Spyrou, I. Pytharoulis Key Processes in Regional Atmospheric.

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Presentation on theme: "George Kallos With contribution from S. Solomos, I. Kushta, M. Astitha, C. Spyrou, I. Pytharoulis Key Processes in Regional Atmospheric."— Presentation transcript:

1 George Kallos With contribution from S. Solomos, I. Kushta, M. Astitha, C. Spyrou, I. Pytharoulis Key Processes in Regional Atmospheric Modeling in the Mediterranean Region UNIVERSITY OF ATHENS SCHOOL OF PHYSICS, DIVISION OF ENVIRONMENT AND METEOROLOGY ATMOSPHERIC MODELING AND WEATHER FORECASTING GROUP

2 Physiographic characteristics are partially responsible for the formation of particular climatic conditions in the Mediterranean Region. Regional climatic patterns are defined as a result of balancing between large scale flow and mesoscale circulations. The resulted circulation has a general trend from North to South (pressure gradient and differential heating between land and water). Air masses reaching the Mediterranean region are not clearly defined as pure maritime or continental because their characteristics are modified relatively fast. The air masses in the area have a mixture of natural and anthropogenic origin aerosols with varying optical and hygroscopic properties. Therefore, cloud formation is a complicated process. MOTIVATION

3 Desert dust and sea salt are major sources of PM in the atmosphere. Their impacts in the atmosphere are many and of course the feedbacks are considerable. The impacts are ranging from modification of the radiative forcing to cloud formation and precipitation. Therefore, perturbations in dust and/or sea salt particle production can have impacts on radiative properties, cloud formation and water budget. These links are not one way but there are feedbacks that are critical for both meteorological and climatological – scale phenomena. The links and feedbacks become more complicated because of the coexistence of anthropogenically-produced aerosols and chemical transformations. MOTIVATION

4 By scattering and absorbing solar radiation modifies the planetary albedo and reduces the amount of radiation reaching the surface By absorbing part of the IR radiation causes atmospheric heating By acting as CCN modifies the microphysical, micro-chemical and hence optical and radiative properties of clouds Aerosols can also decrease the cloud precipitation efficiency In combination with certain anthropogenic pollutants can work towards the formation of heavy rainfall Changes features on the terrestrial ecosystems (Reichholf,1986) Neutralizes acid rains (Hedin and Likens, 1996) It reduces visibility It affects air quality in urban areas (and not only) Dust deposition provides considerable quantities of bioavailable nutrients to ocean surface waters and the seabed Saharan dust aerosols influence the nutrient dynamics and biogeochemical cycling of both terrestrial and oceanic ecosystems There is evidence that dust may cause ocean cooling (Schollaert and Merrill, 1998) Dust contains appreciable quantities of iron, the addition of which to ocean waters may increase plankton productivity ……………. Some Effects of Soil Dust in the Atmosphere

5 Discuss the: Long range transport of naturally (mainly Saharan dust and sea-salt) and anthropogenically - produced aerosols. Aerosol-cloud interaction processes Other processes needed to be taken in the account New modeling tools OBJECTIVES

6 Kallos et al JAMC, 46(8), pp. 1230–1251. SUMMER SEASON TRANSITION SEASONS Paths and scales of transport

7 STRATOSPHERE LOWER TROPOSPHERE SO 2 HCl ash SO 2 H 2 SO 4 precipitation warming hv & OH cooling of the surface LW radiation Cloud Modifications Nucleation Deposition Dust NaCl UPPER TROPOSPHERE Heterogeneous reactions SO 2 + O 3 DSO 4 (dust+sulfate) NO 2 DNO 3 (dust+nitrate) HNO 3 DNO 3 (dust+nitrate) dust PM AND GASEOUS POLLUTANTS IN THE ATMOSPHERE PROCESSES AFFECTING AIR QUALITY AND CLIMATE incoming-outgoing SW radiation

8 AEROSOLS AND CLOUDS Aerosols in general act as CCN and IN in the cloud formation processes according to their physicochemical properties. As it is known, high concentrations of aerosols result in haze and small-cloud droplet formation that do not necessarily lead in precipitation. Although, this is not always the case. Under certain conditions and mixture of naturally and anthropogenically-produced aerosols, gigantic CCNs and/or IN formation with enhanced hygroscopicity may lead in stormy weather conditions (Levin et al., 2006; Rosenfeld et al., 2008)

9 activation drop growth (collision, coalescence) Condensates (cloud,rain,ice,graupel,hail, pristine ice,aggregates) Natural particle emissions – transport Aerosol AEROSOLS AND CLOUDS

10 SEM analysis Izaña Sta. Cruz de Tenerife (Alastuey et al. 2005) clay particles (around 1 µm) clay particles (>10 µm) general aspect of dustrounded quartz fresh water diatomspore particles natural marine aerosols spongy carbonaceous anthropogenic particles typical large and plate natural gypsum particles potassium sulphate particles covering clay aggregates <5 µm Ca sulphates with crystalline habit COEXISTENCE OF MINERAL DUST, SULFATES AND CLOUD DROPLETS

11 A photomicrograph of drops and aerosol particles collected inside clouds D: drops, P: dry interstitial particles (Levin et al. 1996, 2006) A photomicrograph of desert mineral dust with small sulfate particles on its surface. COEXISTENCE OF MINERAL DUST, SULFATES AND CLOUD DROPLETS


13 Mechanical Processes Molecular Processes DUST + SEA SALT + SODIUM AEROSOL + CHLORIDE AEROSOL sedimentation rain Chemical transformation of gases, coalescence, condensation, homogeneous nucleation SULFATES NITRATES FINE PARTICLES COARSE PARTICLES PARTICLE DIAMETER (μm) SULFATES FORMED ON DUST NITRATES FORMED ON DUST Interaction MASS-SIZE DISTRIBUTION OF PM

14 Aerosol-Cloud Interaction (Rosenfeld, 2008)

15 Aerosol effects on precipitation (Rosenfeld, 2008) Aerosol concentration Dry unstable situation Maritime & moderate (wet) continental clouds Accumulated rain

16 Precipitation GAIN (condensation+deposition) Precip = - LOSS (evaporation+sublimation) Precipitation is often a small difference of large values Aerosols affect both generation and loss of hydrometeor mass Aerosol effects on precipitation

17 WHY WE NEED NEW MODELING TOOLS? To study such complicated processes there is a need for advanced modeling tools that include physical and chemical properties directly coupled.

18 The Integrated Community Limited Area Modeling System – ICLAMS – has been developed (still under development) at the framework of CIRCE project (RL8) It has been designed to be able to simulate links and feedbacks between air quality and regional climate ICLAMS development is on RAMS.6 modeling system RAMS is a multi-scale modeling system and can be configured to run with resolution from a few meters to tens of kilometers on a two-way interactive nesting mode It has detailed cloud microphysical scheme with 8 microphysical categories, detailed surface parameterization and many other features that make it the most advanced limited area meteorological model The cloud microphysical scheme includes prognostic equations for mass mixing ratios of the various forms of water species ICLAMS

19 The new model development includes the following features: Full dust cycle module following the formulation used in SKIRON/Dust with 8 dust particle bins following lognormal distribution Kallos et al., (2005, 2007). Sea salt production mechanism with 2 size bins following Gong et al., (1999). Gas and aqueous phase chemistry (SAPRC mechanism as implemented in CAMx). Gas to particle conversion and heterogeneous chemistry following the ISOROPIA scheme and additional interactions with desert dust, sea salt and sulfates. Impacts of aerosols and PMs on radiative transfer of the photochemically active bands. Visible and Infrared corrections due to aerosols and PMs. Treatment of CCN and GCCN as predictive quantities (4-D). All these new elements are directly coupled and executed together with the meteorological modules. ICLAMS

20 BASIC MODULES OF ICLAMS The development is carried out on the RAMS ver. 6 It has two-way interactive nesting capabilities Explicit cloud microphysical scheme It can be nested inside of global systems It can run with configurations from a few meters horizontal resolution up to hemispheric It also includes: Detailed soil surface and water interaction processes Detailed dust cycle description Detailed sea salt cycle Gas phase chemistry module with photochemical processes Aqueous phase chemistry Gas to particle conversion and heterogeneous chemical reactions Dry and wet deposition modules Aerosol-cloud-radiative transfer interaction module It can be used mainly for case studies and scenario development related to aerosol cloud interaction

21 The modeling system handles dust, sea salt and three-generation particle formation on a direct way. CCN, GCCN and IN are predictive quantities. Links and feedbacks between the direct and indirect aerosol effects are described. Currently the following model components have been developed and tested : Cloud effects: Prognostic CCN calculation based on aerosol number density and chemical composition. Three different approaches are used. 1.All fine aerosols and 33% coarse are efficient CCN (Levin et al., 2005) 2.A parameterization based on Koehler theory (Nenes et al., 2007) is used to calculate the number of natural particles that can be active CCNs and the number of cloud droplets nucleated based on the chemical composition of the aerosols, their size (lognormal distribution) and ambient conditions (temperature, updraft velocity). 3.Cloud droplets spectrum is obtained by previously (offline) generated lookup tables from detailed parcel-bin model as a function of CCN and GCCN number concentration, updraft velocity and temperature. (Cotton et al., 2007). Prognostic cloud droplets spectrum is then used by the explicit microphysical scheme of RAMS (Meyers et al. 1997) to forecast the rest of the microphysical species (rain, pristine ice, snow, aggregates, graupel, hail) and precipitation. Radiative transfer : Calculation of the heating rates based on aerosol load and type. Two different options are available. 1. Harrington radiation scheme 2. Rapid Radiative Transfer Model (RRTM) ICLAMS Aerosol – Meteorology feedback

22 MEIDEX experiment MEIDEX TEST CASE On 28 January 2003, a dust storm passed over the north east Mediterranean region. On 29 JAN 2003 heavy rain and hail dispersed over the Middle East coastline and a few km inland. Flood events and agricultural disasters were reported. Airborne measurements of this episode were obtained during the Mediterranean Israeli Dust Experiment (MEIDEX) Two cases have been considered: 1st case: Natural particles are treated as passive tracers. User specified constant CCN #. 2nd case: Dust plume and sea-salt sprayed interact with clouds. CCN and GCCN prognostic (from dust and sea salt concentrations and size distribution.

23 MODEL SETUP RAMS6.0 with: DUST MODULE (Zender at al., Marticorena and Bergameti) 8 Bin lognormal dust particles distribution - Dust cycle SEASALT MODULE (Gong et al.) 2 Bin lognormal salt particles distribution - Seasalt cycle DOMAIN SETUP 3 grids (36km-12km-4km), 31 vertical levels, 120 hours run Initial and boundary conditions – NCEP 1deg GFS analysis data REFERENCE RUN (1 st case) ICLOUD=5 (Constant # of CCN) Dust and Salt particles do not interact with the rest of the model TEST RUN (2 nd case) ICLOUD=7 (3-D prognostic CCN and GCCN field) Particles serve as efficient cloud condensation nuclei (CCN).

24 On 28 Jan 2003 a cold cyclone moved from Crete through Cyprus accompanied by a cold front. A second air mass transported dust particles from NE Africa over the sea towards Israeli coastline. Wind speed 28JAN UTC Dust load 28JAN UTC 3h accumulated precipitation 28JAN UTC LARGE SCALE FEAUTURES

25 DUST CONCENTRATION at 1500UTC (all bins) 27JAN UTC 28JAN UTC 29JAN UTC 1071 m 6 th model level 2087 m 9 th model level 3440 m 12 th model level

26 SEA SALT CONCENTRATIONS at 1500 UTC (both bins) 27JAN JAN JAN m 2 nd model level 530 m 4 th model level 1071 m 6 th model level

27 Case 1 - CONSTANT CCN (ICLOUD=5) 1hr accumulated precip. 29JAN UTC1hr accumulated precip. 29JAN UTC1hr accumulated precip. 29JAN UTC1hr accumulated precip. 29JAN UTC Case 2 - PROGNOSTIC CCN (ICLOUD=7) 1hr accumulated precip. 29JAN UTC1hr accumulated precip. 29JAN UTC1hr accumulated precip. 29JAN UTC1hr accumulated precip. 29JAN UTC PRECIPITATION PATTERN

28 3hr accumulated hail 29JAN UTC3hr accumulated hail 29JAN UTC3hr accumulated hail 29JAN UTC3hr accumulated hail 29JAN UTC Case 2 - PROGNOSTIC CCN (ICLOUD=7) Case 1 - CONSTANT CCN (ICLOUD=5) 3hr accumulated hail 29JAN UTC3hr accumulated hail 29JAN UTC3hr accumulated hail 29JAN UTC3hr accumulated hail 29JAN UTC HAIL PATTERN

29 Total Particles have been measured at 15 locations along the aircraft flight (11:27–13:40 UTC 28JAN2003) aircraft altitude particle concentration MEIDEX OBSERVATIONS (Levin et al.)

30 For each one of the 15 measuring locations of MEIDEX experiment a time / height plot of modelled total particles (dust & salt) concentration is created. Maximum particles concentration during the flight period (10:00 – 13:00 UTC) are ranging from 1000 #/cm 3 near the ground to below 50#/cm 3 above 3 Km. These numbers compare well with the aircraft observations. MEIDEX experimental flight ICLAMS PARTICLE CONCENTRATIONS

31 Time – Height cross sections at each measuring location

32 During the dust storm simulation the concentration profile for coarse particles (d>1 μm) ranged from 40 (#/cm 3 ) near the ground to less than 5(#/cm 3 ) above 2km The simulated concentration for fine particles (d<1 μm) ranged from 1000 (#/cm 3 ) near the ground to less than 100 above 3km. Fine particles – ICLAMS - 28JAN2003 Coarse particles – ICLAMS - 28JAN2003 COARSE & FINE PARTICLES

33 2 nd CASE: Aerosols serve as efficient CCN For simplicity we assume that all particles produced (dust and sea salt) are efficient CCN. However the CCN field will not retain the lognormal characteristics of aerosol size distribution. Dust and sea salt - born CCN will be added on the background value (400 #/cm3) in order to enhance the effect of the dust storm in cloud processes. The rest of the RAMS microphysics scheme remains unchanged.

34 Constant CCN field CCN concentration (#/cm 3 )CCN concentration 28JAN UTCCCN concentration 29JAN UTC CCN concentration 29JAN UTCCCN concentration 30JAN UTC Prognostic 3D CCN field ICLAMS CCN VERTICAL DISTRIBUTION

35 Constant CCN field prognostic CCN field Cloud concen. (#/cm3) 28JAN UTCCloud concen. (#/cm3) 29JAN UTC Cloud concen. (#/cm3) 28JAN UTC Cloud concen. (#/cm3) 29JAN UTC CLOUD CONCENTRATION VERTICAL CROSSECTION

36 Prognostic CCN field constant CCN field Total condensates (#/cm3) 29JAN UTCTotal condensates (#/cm3) 29JAN UTC Total condensates (#/cm3) 29JAN UTCTotal condensates (#/cm3) 29JAN UTC TOTAL CONDENSATES VERTICAL CROSSECTION

37 Prognostic CCN field Constant CCN field Ice mix ratio (gr/kgr) 28JAN UTCIce mix ratio (gr/kgr) 28JAN UTC Ice mix ratio (gr/kgr) 28JAN UTC Ice mix ratio (gr/kgr) 28JAN UTC ICE MIXING RATIO VERTICAL CROSSECTION

38 MAXIMUM UPDRAFT VELOCITY Significant delay on the updraft velocity maximum during cloud development and also increase in maximum value in 2 nd mode run (yellow line ) CCN Condensation Latent heat Updrafts

39 MAXIMUM UPDRAFT VELOCITY FeatureConstant CCN fieldAll particles are effective CCN All fine particles and 33% from the coarse are effective CCN Max updraft Time and height10:00 UTC at 4km13:00 UTC at 4km14:00 UTC at 4km

40 OTHER PROCESSES THAT NEED SPECIAL ATTENTION Surface properties and energy partitioning: SST Soil thermophysical and hydraulic properties How useful is the high resolution SST on regional scale modeling in the Mediterranean Region? Energy partitioning on the sea surface What is the role on soil texture on the accuracy of the models?

41 Two different resolution SST data sets were used to study to study the atmospheric model response

42 SEP 2004 OCT 2004 NOV 2004 HiRes SSTs (1/16 deg) Coarse SSTs (1/2 deg

43 T+12 Case of 13/10/04 Cyclone formation over Central Mediterranean

44 T+24 Front over the Ionian Sea



47 T+24

48 RED: 1/16 x 1/16 SSTs BLUE: 0.5 x0.5 SSTs 2-m Temperature and 6-hr accumulated precipitation

49 Sea-surface energy partitioning The SKIRON/Eta model calculates the surface parameters using a viscous sublayer scheme (Janjic 1994, MWR) The SKIRON/Eta model calculates the surface parameters using a viscous sublayer scheme (Janjic 1994, MWR) The viscous sublayer over the ocean is assumed to operate in 3 regimes: (i) smooth and transitional, (ii) rough, (iii) rough with spray, depending on the Reynolds number which is a function of u *

50 Mean Differences in Heat Fluxes in Jan 2003 (VISCOUSyes-VISCOUSno) Stronger latent and sensible heat fluxes over the water without the use of the viscous sublayer. Higher precipitation amounts and stronger winds over the water without the use of the viscous sublayer. This is in agreement with theory

51 Soil Characteristics - Thermophysical and Hydraulic Properties

52 Effects of Soil Thermophysical Properties on Saharan ABL RMSERocky soilSand Α Β C D AVG

53 Dust, sea salt and anthropogenically-produced aerosols are key players in radiation, cloud and precipitation formation. The links and feedbacks are important on defining forcing and therefore studying regional climate. In the new system - ICLAMS - such capabilities have been implemented: Cloud formation through the treatment of CCN, GCCN and IN as predictive quantities. Aerosol-cloud-radiation interactions. Treatment of naturally and anthropogenically-produced particles with different properties. Simulation of cloud-scale phenomena. The sensitivity tests carried out clearly showed that the CCN originated mainly from desert dust. The storm generation and evolution is highly related to spatiotemporal distribution of CCNs. In general, high concentrations of natural particles tend to delay rainfall but can have higher amounts of precipitation in certain locations. More development (production of CCG, GCCN and IN from anthropogenic sources) and testing efforts are under way at the framework of CIRCE project. Some Concluding Remarks

54 This work is funded by European Union FP6 project CIRCE ACKNOWLEDGEMENTS

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