Aerosol modelling : spatial distribution and effects on radiation Citation for published version (APA): Henzing, J. S. (2006). Aerosol modelling : spatial distribution and effects on radiation. Technische Universiteit Eindhoven. https://doi.org/10.6100/IR601939 DOI: 10.6100/IR601939 Document status and date: Published: 01/01/2006 Document Version: Publisher’s PDF, also known as Version of Record (includes final page, issue and volume numbers) Please check the document version of this publication: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. 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If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license above, please follow below link for the End User Agreement: www.tue.nl/taverne Take down policy If you believe that this document breaches copyright please contact us at: [email protected] providing details and we will investigate your claim. Download date: 26. Sep. 2021 Aerosol Modelling Spatial Distribution and Effects on Radiation PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Technische Universiteit Eindhoven, op gezag van de Rector Magnificus, prof.dr.ir. C.J. van Duijn, voor een commissie aangewezen door het College voor Promoties in het openbaar te verdedigen op maandag 6 maart 2006 om 16.00 uur door Jeroen Sebastiaan Henzing geboren te Alkemade Dit proefschrift is goedgekeurd door de promotoren: prof.dr. H.M. Kelder en prof.dr.ir. G.J.F. van Heijst Copromotor: dr. P.F.J. van Velthoven Cover: Photos of various mixtures of atmospheric aerosol taken with an electronic microscope. By courtesy of Olga Mayol-Bracero, Joachim Huth and Günter Helas, MPI for Chemistry, Mainz, Germany. Druk: Universiteitsdrukkerij Technische Universiteit Eindhoven Omslagontwerp: Paul Verspaget, [email protected] CIP- DATA LIBRARY TECHNISCHE UNIVERSITEIT EINDHOVEN Henzing, J.S. Aerosol modelling : spatial distribution and effects on radiation / by J.S. Henzing. – Eindhoven : Technische Universiteit Eindhoven, 2006. – Proefschrift. ISBN-10: 90-386-2431-X ISBN-13: 978-90-386-2431-0 NUR 932 Trefwoorden: aërosolen / klimatologie / atmosferische straling / troposfeer / atmosferische chemie Subject headings: aerosol / climatology / atmosferic radiation / troposphere / atmospheric chemistry Contents Samenvatting 7 1. General introduction 13 1.1 Background and motivation 13 1.2 This thesis 14 2. Aerosols and climate 17 2.1 Radiative forcing 17 2.1.1 Well-mixed greenhouse gases 18 2.1.2 Scattering aerosols 18 2.1.3 Absorbing aerosols 19 2.2 Precipitation – hydrological cycle 22 3. The effect of aerosols on the downward shortwave irradiances at the surface – Measurements versus calculations with modtran4.1 27 3.1 Introduction 27 3.2 Experimental approach 28 3.2.1 Selection of cloudless days 29 3.2.2 Instrumentation 30 3.3 Surface irradiance measurements 32 3.3.1 Direct irradiance 32 3.3.2 Diffuse irradiance 33 3.3.3 Global irradiance 35 3.4 Radiative transfer model and its input data 35 3.4.1 modtran4.1 description 35 3.4.2 Overview of required input data 35 3.4.2.1 Solar irradiance 35 3.4.2.2 Gases and thermal structure 36 3.4.2.3 Surface albedo 36 3.4.2.4 Aerosol characteristics 36 3.4.3 Measurements of model input data 38 3.4.3.1 Spectral aerosol optical thickness 38 3.4.3.2 Aerosol absorption coefficient 38 3.4.3.3 Aerosol scattering coefficient 39 3.4.3.4 Aerosol asymmetry parameter 39 3.4.3.5 Water vapor column 40 3.4.3.6 Ozone column 41 3.4.3.7 Surface albedo 41 3.5 Sensitivity study of model calculations of shortwave irradiances on cloudless days 42 3.5.1 modtran4.1 calculations 42 3.5.2 Sensitivity study 43 3.5.2.1 Sensitivity to aerosol optical thickness errors 44 3.5.2.2 Sensitivity to absorption coefficient errors 45 3.5.2.3 Sensitivity to scattering coefficient errors 48 4 Contents 3.5.2.4 Sensitivity to asymmetry parameter errors 48 3.5.2.5 Sensitivity to water vapor column errors 49 3.5.2.6 Sensitivity to surface albedo errors 49 3.5.3 Total error in the calculated irradiances 49 3.6 Comparison between modeled and measured downward shortwave irradiances on cloudless days 50 3.6.1 Comparison strategy 50 3.6.2 Direct irradiances 50 3.6.3 Diffuse irradiances 50 3.6.4 Global irradiances 50 3.6.5 Discussion of possible sources of the disagreement between calculated and measured irradiances 51 3.6.5.1 Spectral aerosol optical thickness 51 3.6.5.2 Surface albedo 53 3.6.5.3 Zero offset of pyranometer measurements 53 3.6.5.4 Vertical aerosol distribution 53 3.7 Discussion of a possible agreement between modeled and measured diffuse irradiances 54 3.8 Conclusions 57 4. A parameterization of size resolved below cloud scavenging of aerosols by rain 59 4.1 Introduction 59 4.2 Below cloud scavenging coefficient 60 4.2.1 Explicit calculation 60 4.2.1.1 Rain droplet velocity 60 4.2.1.2 Rain droplet size distribution 60 4.2.1.3 Raindrop-aerosol collection efficiency 61 4.2.2 Parameterization 61 4.3 Global chemistry transport model TM4 63 4.3.1 Sea salt source function 63 4.3.2 Aerosol sinks 65 4.3.2.1 Large scale cloud systems 65 4.3.2.2 Dry deposition 66 4.3.2.3 Convective cloud systems 67 4.4 Results 67 4.4.1 Emission, load, and lifetime 67 4.4.2 Partitioning between below-cloud scavenging and other sinks 69 4.5 Remaining uncertainties 70 4.5.1 Rain droplet spectrum 70 4.5.2 Particle humidity growth 71 4.5.3 Precipitation and evaporation 71 4.6 Conclusions 72 5. Global aerosol modeling with TM4 – application to the aerosol optical depth over Europe 75 5.1 Introduction 75 5.2 Transport Model TM4 75 5.2.1 Emissions 75 5.2.2 Chemistry 76 Contents 5 5.3 Aerosol module 76 5.3.1 Aerosol sources 76 5.3.2 Aerosol sinks 77 5.3.2.1 Dry deposition 78 5.3.2.2 In-cloud scavenging and convective scavenging 78 5.3.2.3 Below-cloud scavenging 79 5.3.3 Aerosol optical parameters 80 5.3.3.1 Hydrophobic carbonaceous aerosol 80 5.3.3.2 Internal mixtures of carbonaceous and secondary inorganic aerosols 81 5.3.3.3 Pure secondary inorganic aerosol 82 5.3.3.4 Sea salt aerosol 83 5.4 Application to Europe – comparison to observations 86 5.4.1 Comparison to AERONET observations 89 5.4.2 Sensitivity studies 91 5.4.2.1 Sources 91 5.4.2.2 Water vapor redistribution 92 5.4.2.3 Sources and water vapor redistribution 93 5.5 Discussion and conclusions 95 6. Perspectives on the assimilation of aerosol optical depth – development of an aerosol assimilation system for TM4 and application to Europe 99 6.1 Introduction 99 6.2 Transport model TM4 aerosol module 99 6.3 Assimilation system 99 6.3.1 Satellite observation error 101 6.3.2 Model error 102 6.4 Application of the system 103 6.4.1 Satellite observations 103 6.4.2 Results and discussion 107 6.4.2.1 Case 1: March 2000 107 6.4.2.2 Case 2: May 2000 107 6.4.2.3 General results 107 6.5 Discussion and conclusions 110 7. Summary and conclusions 111 8. Outlook and recommendations 115 References 117 List of acronyms and abbreviations 135 Dankwoord 137 Curriculum vitae 139 6 Samenvatting Verklaring van de titel van dit proefschrift De titel van dit proefschrift laat zich vertalen als: “Aërosolmodellering – de ruimtelijke verdeling en de effecten op straling”. Een aërosol is gedefinieerd als een nevel waarin kleine vaste en vloeibare deeltjes zweven. In de klimaatwetenschap wordt vaker gesproken over aërosolen, aërosoldeeltjes, of worden met het woord “aërosol” alleen de deeltjes bedoeld. In dit proefschrift wordt op twee manieren aan aërosolmodellering gedaan. Op basis van waarnemingen wordt een aërosolmodel gemaakt dat als basis dient voor stralingstransport berekeningen. Met deze berekeningen worden de aërosoleffecten op de instraling van de zon aan de grond onderzocht. Het andere aërosolmodel dat wordt ontwikkeld in dit proefschrift heeft als doel de ruimtelijke verdeling van aërosol te kunnen simuleren op mondiale schaal. Achtergrond en motivatie Weer en klimaat zijn van groot belang voor het leven op Aarde. Het weer beïnvloedt ons leven dagelijks en klimaatveranderingen kunnen onze gezondheid, voedselproductie en het algemeen welbevinden in gevaar brengen. Het is daarom essentieel om het klimaat te begrijpen en om betrouwbare verwachtingen van klimaatveranderingen te kunnen maken.