Direct and semi-direct radiative effects of absorbing aerosols in Europe: Results from a regional model
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1 GEOPHYSICAL SEARCH LETTERS, VOL. 39,, doi: /2012gl050994, 2012 Direct and semi-direct radiative effects of absorbing aerosols in Europe: Results from a regional model J. Meier, 1 I. Tegen, 1 B. Heinold, 2 and R. Wolke 1 Received 17 January 2012; revised 8 March 2012; accepted 15 March 2012; published 5 May [1] The influence of absorbing aerosol on atmospheric conditions in Europe is simulated for a summer and a winter period with a regional model. Depending on the fraction of elemental carbon the effects of radiation are determined. Absorbing aerosol increases the average solar heating rate for the summer case by Ks 1 (20% 46%) within the boundary layer. Due to the heating by absorbing substances an average decrease of the total cloud cover (summer: %, winter: 0.7%) is found. This semidirect radiative effect causes mainly positive forcing near the surface and at the top-of-atmosphere (TOA). Significant negative correlations (summer: 0.7, winter: 0.4) between the aerosol optical depth and the direct radiative forcing () are determined at the surface. At the TOA the pattern is influenced by the surface albedo and the cloud fraction. A general decrease of 2m temperatures is simulated when using absorbing aerosol compared to an aerosol-free troposphere (summer: 0.14 K, winter: 0.10 K) over land surface. Citation: Meier, J., I. Tegen, B. Heinold, and R. Wolke (2012), Direct and semi-direct radiative effects of absorbing aerosols in Europe: Results from a regional model, Geophys. Res. Lett., 39,, doi: /2012gl Introduction [2] The global and annual average direct radiative forcing () by anthropogenic (including reflecting material) aerosols is currently estimated from observations and models to be in the range of W m 2 [Intergovernmental Panel on Climate Change, 2007]. The analysis of the by Cook and Highwood [2004] showed that the influence of aerosol absorption can be much larger regionally than the influence of carbon dioxide. Further, the caused by absorbing aerosol can result in positive and negative values at the TOA depending on the cloud fraction [Chand et al., 2009]. Large uncertainties also exist in the so-called semidirect radiative effect (S) where warming of the air by black carbon (BC) could offset the cooling due to indirect aerosol effect [Lohmann and Feichter, 2001]. Absorption of solar radiation by elemental carbon (EC) or BC can cause increased atmospheric heating and thus a decrease of the cloud fraction [e.g., Ackerman et al., 2000]. A comprehensive study regarding the determination of the S depending on the location (above, below or near clouds) of absorbing aerosol is done by Koch and Del Genio [2010]. For instance, absorbing aerosol located within a cloud layer cause a decrease of the cloud cover whereas absorbing particles 1 Leibniz-Institute for Tropospheric Research, Leipzig, Germany. 2 School of Earth and Environment, University of Leeds, Leeds, UK. Copyright 2012 by the American Geophysical Union /12/2012GL above a cloud yield to stabilization of the underlying atmosphere and can cause an increase of stratocumulus clouds. Regarding this stratocumulus clouds Johnson et al. [2004] performed some studies at marine environment and the S. The S was found to be positive or negative depending on whether the absorbing aerosol was located below or above marine stratocumulus clouds. Sakaeda et al. [2011] studied the as well as the S caused by biomass burning aerosol over Africa. Over the ocean the authors found negative S at the TOA, while over land surface a positive S was estimated. Aerosols are often combinations of several compounds. Their resulting radiative impact can therefore be strongly dependent on their mixing state [Chandra et al., 2004]. [3] Here we study the and S of anthropogenic absorbing aerosols within Europe. A regional transport model was used for simulations of two time periods. The main focus is the effect of the absorbing aerosol on solar fluxes, cloud cover and temperature. Both simulation periods were already described in detail by Meier et al. [2012]. The summer period (19 26 July 2006) was characterized by relatively constant meteorological conditions. A few rainfall events occurred during this time. Within the entire model domain the wind speed was high only during thunderstorms. Thus a strong accumulation of atmospheric particles within Europe occurred during this time. A domain-average aerosol optical depth (AOD) of 0.19 is simulated for July In contrast, the winter period (16 26 February 2007) was characterized by several rain- and snowfall events. Additionally, high wind speeds occurred during this time period within the entire model domain. These events caused a significant removal of particles out of the atmosphere and thus a domain-average AOD of 0.14 for the entire winter period. 2. Model Setup [4] Model simulations for two time periods were performed with the regional transport model COSMO MUSCAT (Consortium for Small-scale Modeling MultiScale Atmospheric Transport Model). The COSMO MUSCAT model system consists of the weather forecast model (COSMO), provided by the German Weather Service (DWD) [Steppeler et al., 2003], and a 3-dimensional chemistry transport model (MUSCAT) [Wolke et al., 2004]. Meier et al. [2012] explained in detail how aerosol distributions, extinction coefficients and AOD are determined in the model, and describes model evaluation with observed AOD as well as with ground- and space-based lidar observations and aerosol composition at the surface. The radiative transfer for short- and longwave radiation for different atmospheric conditions is computed with a d-two-stream radiative solver 1of5
2 Figure 1. Average solar heating rate [Ks 1 ] (solid line: AEROSOL, dashed line: NoAEROSOL) and extinction profile [m 1 ] (blue line) during July 2006 simulated over land surface and cloud-free grid boxes. (with three solar and five thermal bands) taking into account scattering and absorption by, e.g., aerosols [Ritter and Geleyn, 1992]. COSMO prescribes the optical properties of five different aerosol types (continental, urban, maritime, volcanic and stratospheric) according to Tanré et al. [1984]. Here the focus is on continental and urban aerosol types. The spatio-temporally varying distribution of both aerosol types is calculated in COSMO MUSCAT based on the fraction of EC on PM 2.5 (primary particulate matter up to 2.5 mm diameter). A fraction of EC larger than 20% classifies the aerosol mass as urban; otherwise it is classified as continental. The 20% limit is at the upper end of the range found during observations [e.g., Weijers et al., 2011]. Thus, the model simulates more continental aerosol type than urban aerosol type. Based on the mass of the simulated urban and continental aerosol the optical thickness for both types is computed and considered by the radiative scheme [Tanré et al., 1984] of COSMO. Depending on their mass, distribution and optical properties both aerosol types contribute to the radiative effects. [5] The model simulations are performed with a horizontal resolution of 28 km 28 km with horizontal grid cells (South-West corner: 10.1 W, 27.5 N) and 40 vertical layers with a model top of MUSCAT at 8 km. Model simulations are performed as cycles. In the beginning of each cycle COSMO calculations are performed for 24 hours before MUSCAT is started, using the aerosol distribution of the previous cycle and run in parallel with COSMO for 24 hours. [6] Three different model setups are realized: [7] 1. AEROSOL: Urban and continental aerosol distributions are simulated within MUSCAT; their influence on solar radiation as well as on dynamical parameters is calculated within COSMO. [8] 2. NoAEROSOL: The impact of urban and continental aerosol on solar radiation is not computed by COSMO MUSCAT. [9] 3. AEROSOLNoFB: Urban and continental aerosol influence the solar radiation only, without any influence on further processes and therefore without feedback. For this computation the radiation routine of the COSMO model is called twice: at first to compute the aerosol forcing and secondly without the forcing. Thus dynamical processes are equal to NoAEROSOL. [10] The differences of radiation flux densities between the individual simulations provide the following information: [11] 1. : Radiative effect including the direct radiative effect of the aerosol and the effect of changes due to the impact of the direct forcing, e.g., on cloud cover, computed as differences of radiation flux densities of AEROSOL and NoAEROSOL. The sea surface temperature (SST) is held constant and therefore not influenced by the. [12] 2. : Direct radiative forcing, the effect of aerosols on the radiation fluxes without including effects of changed atmospheric dynamics, computed as difference between AEROSOLNoFB and NoAEROSOL. Nevertheless the determination of the also depends on clouds. [13] 3. S: The radiative effect of changes on atmospheric dynamics, e.g., due to cloud changes, without considering the aerosol, computed as difference between AEROSOL and AEROSOLNoFB. 3. Results [14] The presence of absorbing aerosol influences atmospheric solar heating rates. Figure 1 represents the average solar heating rates (based on 67 individual profiles) for the entire summer simulation period over land surface for cloud-free grid cells; simulated with the AEROSOL and the NoAEROSOL model setup (the profile of the AEROSOLNoFB is equal to the NoAEROSOL profile). Additionally, the average vertical profile of extinction coefficients is shown, calculated with the AEROSOL setup for the same conditions. Distinct differences between the individual solar heating rate profiles are found. The absorption of the solar radiation by the urban and the continental aerosol causes a stronger heating especially within the boundary layer between the surface and 2 km altitude. Here, the average difference between both model setups range from 20% to 46%. The extinction values range from m 1 to m 1 with highest values near the surface and a relatively constant decrease with increasing altitude. During the winter period the determination of an average solar heating rate for cloud-free grid cells was not possible since cloud cover was always higher than 0% in one of the simulations. [15] Except for the southern part of the model domain, clouds are present in the entire domain during July 2006 (Figure 2, left). [16] During the winter period the entire model domain is covered with clouds (not shown). For both time periods a general decrease of the total cloud cover is found when taking the absorption of solar radiation by the urban and continental aerosol and the increase in atmospheric heating rates into account (Figure 2, right and Table 1). [17] An average decrease of % in total cloud cover during the entire summer period and of 0.7% during the 2of5
3 Figure 2. (left) Total cloud cover, simulated with the AEROSOL setup and (right) the difference of the total cloud cover between the AEROSOL and the NoAEROSOL setup during July winter period is simulated. A slightly lower decrease of the average total cloud cover occurs during night then during day for the entire simulation period (Table 1). [18] The of the absorbing aerosol (Figure 3, left for the summer case; Table 1) is determined by the aerosol (Figure 3, right) together with the S (Figure 3, middle). [19] The S reflects the change of the total cloud cover. At the surface the is negative over the model domain (Figure 3, top right). The urban and continental aerosol types force a domain-average attenuation of the solar flux of 16.3 W m 2 during the summer period and of 6.3 W m 2 during the winter period (Table 1). The negative is stronger in those regions with high AOD (Figure 3) [Meier et al., 2012]. A significant negative correlation between AOD and surface (Pearson coefficient PC) of 0.7 during the summer and a weaker negative correlation of PC = 0.4 during the winter simulation period is determined. The at the TOA for the entire model domain is shown in Figure 3 (bottom right) and in Table 1. On average a value of W m 2 (19 26 July 2006) and of 2.7 W m 2 (16 26 February 2007) is determined. The at TOA is distinctly related to cloud cover for the summer case. A positive forcing occurs at total cloud covers larger than 43% (PC = 0.8). During this time the cloud fraction dominates the forcing over the Atlantic Ocean. The value of 43% agrees well with the cloud fraction limit of 0.4 which was determined by Chand et al. [2009] based on satellite observations. In the winter period such a distinct correlation between cloud cover and at the TOA was not found (PC = 0.2), probably due to the specific meteorological conditions. Whereas a high accumulation of particles and therefore of absorbing material within the atmosphere was possible during the summer simulation period, several precipitation events within the entire European model domain caused a strong removal of particles from the atmosphere during February But the determination of the influence of cloud cover fraction on the at the TOA is highly sensitive to the amount of solar radiation which is absorbed by the aerosol and by the albedo of the underlying surface [Chand et al., 2009]. Thus the removal of particles as well as of absorbing material during the winter could be one reason that it is difficult to determine a certain cloud cover limit when shifts between positive and negative values. Additionally, the sign of the forcing depends on surface albedo and clouds underlying the aerosol. The surface albedo of a relatively dark surface like the cloudfree ocean (e.g., Mediterranean Sea) results in a negative at the TOA. During both time periods the above the sea surface indicates a stronger negative or less positive forcing than over the land surface. During July 2006 the at TOA over sea surface is 1.3 W m 2 and over land surface 0.3 W m 2. In contrast, a of 1.5 W m 2 over sea surface and of 3.6 W m 2 over land surface at the TOA for the entire winter simulation period is calculated (Table 1), because of the high cloud fraction. Table 1. Average Differences of Total Cloud Cover and 2 m Temperatures Between AEROSOL and NoAEROSOL Simulation for Both Time Periodsa July 2006 entire period 00 UTC 12 UTC entire period 00 UTC 12 UTC February 2007 Total Cloud Cover Difference [%] m Temperature Difference [K], Land Surface Radiative Forcing [W m 2], Surface, Entire Domain, Entire Period S S Radiative Forcing [W m 2], TOA, Entire Domain, Entire Period S Radiative Forcing [W m 2], TOA, Sea Surface, Entire Period Radiative Forcing [W m 2], TOA, Land Surface, Entire Period S a Average values of, and S at the surface and the TOA are presented for July 2006 and February 2007, respectively. 3 of 5
4 Figure 3. (left), (middle) S and (right) (top) near the surface and (bottom) at the TOA for the whole summer period (19 26 July 2006). [20] The simulated S near the surface is positive especially in regions with high cloud fraction (compare with Figure 2, left). The absorption of incoming solar radiation by atmospheric particles decreases the average cloud fraction (Figure 2, right and Table 1) and results in a mainly positive S near the surface (summer: 2.6 W m 2, winter: 0.7 W m 2) for the entire model domain. At the TOA the S is mainly positive over the entire domain and with a stronger effect during the summer than during the winter time (summer: 2.4 W m 2, winter: 0.9 W m 2). In contrast to the at the TOA the S is equal over land and sea surfaces (Table 1). [21] Finally, the effect of and S results in negative aerosol near the surface with a domain-average value of 13.7 W m 2 during July 2006 and of 5.6 W m 2 during February At the TOA lower values are simulated (summer: 1.5 W m 2, winter: 3.6 W m 2) for the entire model domain (Table 1) due to the constellation of positive and negative local radiative effects. [22] The influence of the absorbing aerosol is also evident in changes in the 2 m temperatures, which are summarized in Table 1 for both simulation periods. Recently, Sakaeda et al. [2011] indicated that strong cooling is closely connected with strong negative radiative effects near the surface. When considering the at the surface (Figure 3) during the summer case, significantly lower temperatures are expected over the continent (SST remains constant during the model simulations). Here an average decrease of 0.14 K is simulated. In case of February 2007 this average values are slightly lower ( 0.1 K) but nevertheless distinct. For both periods the effect on the 2 m temperature over land surface is particularly evident during daytime (average over all 12 UTC model simulations), when aerosol cooling is at 0.24 K and 0.25 K, respectively (Table 1). 4. Conclusion [23] For a summer as well as for a winter period forcing effects of absorbing aerosol are studied by a model simulation for the European domain. The aerosol effect on the radiative fluxes and meteorological parameters is described by the regional transport model COSMO MUSCAT. At the TOA the of the absorbing aerosol depends on its AOD, surface albedo and total cloud cover. The presence of absorbing particles within the atmosphere causes a significant impact on solar heating rates especially within the boundary layer. In addition to the direct aerosol forcing the heating effect of the aerosol results in a decrease of the total cloud cover. On average a cloud cover decrease by % (summer period) and by 0.7% (winter period) is found. This reduced cloud cover influences the solar flux at the surface and the TOA. The increase of solar flux at the surface caused by the absorbing aerosol S counteracts the decrease by its. However, as it was referred by Johnson et al. [2004] the determination of S may be problematic when using models with a coarse resolution. Thus using smaller model scale could provide a more accurate understanding of S processes. [24] Over land surface a distinct decrease of the 2 m temperatures during both simulation periods is found; during daytime the average decrease is estimated to be 0.24K (summer) and 0.25K (winter). The high limit of 20% EC 4 of 5
5 fraction results in the formation of more reflecting aerosol. Assuming a lower EC threshold, implying more absorbing aerosol, would lead to more cloud reduction and thus to a higher S. Thus the results on S presented here can be interpreted as lower limit. While the results presented here are characteristic for only two relatively short time periods and the study does not take into account the indirect effect of aerosol particles on microphysical cloud properties, it indicates the importance of taking into account the semi-direct effects of absorbing aerosol on cloud cover in studies of interactions of clouds, aerosol and radiation. Further studies will consider model simulations of longer time periods. [25] Acknowledgments. The Editor thanks two anonymous reviewers for assisting in the evaluation of this paper. References Ackerman, A. S., O. B. Toon, D. E. Stevens, A. J. Heymsfield, V. Ramanathan, and E. J. Welton (2000), Reduction of tropical cloudiness by soot, Science, 288, Chand, D., R. Wood, T. L. Anderson, S. K. Satheesh, and R. J. Charlson (2009), Satellite-derived direct radiative effect of aerosols dependent on cloud cover, Nat. Geosci., 2, Chandra, S., S. K. Satheesh, and J. Srinivasan (2004), Can the state of mixing of black carbon aerosols explain the mystery of excess atmospheric absorption?, Geophys. Res. Lett., 31, L19109, doi: / 2004GL Cook, J., and E. J. Highwood (2004), Climate response to tropospheric absorbing aerosols in an intermediate general-circulation model, Q. J. R. Meteorol. Soc., 130, Intergovernmental Panel on Climate Change (2007), Climate Change 2007: The Physical Science Basis. Contribution to Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by S. Solomon et al., 996 pp., Cambridge Univ. Press, Cambridge, U. K. Johnson, B. T., K. P. Shine, and P. M. Forster (2004), The semi-direct aerosol effect: Impact of absorbing aerosols on marine stratocumulus, Q. J. R. Meteorol. Soc., 130, Koch, D., and A. D. Del Genio (2010), Black carbon semi-direct effects on cloud cover: review and synthesis, Atmos. Chem. Phys., 10, Lohmann, U., and J. Feichter (2001), Can the direct and semi-direct aerosol effect compete with the indirect effect on a global scale?, Geophys. Res. Lett., 28, Meier, J., et al. (2012), A regional model of European aerosol transport: Evaluation with sun photometer, lidar and air quality data, Atmos. Environ., 47, Ritter, B., and J. F. Geleyn (1992), A comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations, Mon. Weather Rev., 120, Sakaeda, N., R. Wood, and P. J. Rasch (2011), Direct and semidirect aerosol effects of southern African biomass burning aerosol, J. Geophys. Res., 116, D12205, doi: /2010jd Steppeler, J., G. Doms, U. Schättler, H. W. Bitzer, A. Gassmann, U. Damrath, and G. Gregoric (2003), Meso-gamma scale forecasts using the nonhydrostatic model LM, Meteorol. Atmos. Phys., 82, Tanré, D., J.-F. Geleyn, and J. M. Slingo (1984), First results of the introduction of an advanced aerosol-radiation interaction in the ECMWF low resolution global model, in Aerosols and Their Climatic Effects, edited by H. E. Gerber and A. Deepak, pp , A. Deepak, Hampton, Va. Weijers, E. P., M. Schaap, L. Nguyen, J. Matthijsen, H. A. C. D. van der Gon, H. M. ten Brink, and R. Hoogerbrugge (2011), Anthropogenic and natural constituents in particulate matter in the Netherlands, Atmos. Chem. Phys., 11, Wolke, R., O. Knoth, O. Hellmuth, W. Schröder, and E. Renner (2004), The parallel model system LM-MUSCAT for chemistry-transport simulations: Coupling scheme, parallelization and applications, Parallel Comput., 13, B. Heinold, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK. J. Meier, I. Tegen, and R. Wolke, Leibniz-Institute for Tropospheric Research, Permoserstrasse 15, D Leipzig, Germany. (jessica. meier@tropos.de) 5of5
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