THE RELATIONSHIP BETWEEN CLOUD DROPLET AND AEROSOL NUMBER CONCENTRATIONS FOR CLIMATE MODELS

Transcription

1 INTERNATIONAL JOURNAL OF CLIMATOLOGY, VOL. 16, (1 996) l(4) THE RELATIONSHIP BETWEEN CLOUD DROPLET AND AEROSOL NUMBER CONCENTRATIONS FOR CLIMATE MODELS 1. GULTEPE and G. A. ISAAC Cloud Physics Research Division, Atmospheric Environment Service, Downsview, Ontario M3H 5T4, Canada Received 31 May 1995 Accepted 3 October 1995 ABSTRACT Aerosols have an effect on cloud droplet size and concentration, and thus affect the radiative properties of clouds. The purpose of this study is to develop parameterized equations between droplet number concentration (Nd) and total aerosol number concentration (N,) for use in numerical weather prediction models and global climate models. In situ observations of droplet and aerosol number concentrations collected during four field projects are used. Variables Nd and N, for stratus and stratocumulus clouds are averaged over 1-km lengths to represent scales close to those used in these models. The Nd value is added to the interstitial aerosol number concentration (Ni) to obtain in cloud N,. The relationships generated are compared with current parameterizations. The results suggest that parameterized equations obtained from three field projects, representing clouds formed over land, are similar. The fourth one, representing clouds over ocean, is found similar to the other three for lower concentration of N,, but different for higher values of N,. The value of Nd in clouds generally increases with N,. This suggests that the relationship between Nd and N, may be universal. However, local variability can be very important. W.Y WORDS: maritime and continental clouds over North America; microphysical parameterization and statistical analysis; aircraft observations; aerosol and droplet concentrations; radiative fluxes. INTRODUCTION Clouds in the atmosphere play an important role in weather and climate. Size, concentration, and the distribution of the cloud droplets are influenced by aerosols (Leaitch et al., 1992; Gultepe et al., 1996). Aerosols, which have a net cooling effect, can play two important roles: (i) a direct effect where they scatter solar radiation back to space; and (ii) an indirect effect where they change the number density and concentration of cloud droplets and thus affect cloud albedo. Some of these issues have been discussed by Wigley (1 99 1, 1994), Kaufman et al. (1 99 l), Charlson et al. (1992), and Leaitch and Isaac (1994). Recently, Jones et al. (1994) noted that the global annual mean radiative forcing through the direct effect of sulphate aerosols is about -.3 to -.9 W m- 2, and about W m- through the indirect effect. The result of Jones et al. indicates that aerosol radiative forcing effect can balance green house heating effects but the exact magnitude of the aerosol effect cannot be quantified easily. The aerosol effect on climate change has been studied by Taylor and Penner (1994). They did not, however, consider the indirect effect. Based on the studies of Martin and Johnson (1992), and Martin et al. (1 994), the Jones et al. (1994) study used a relationship between Nd and N, as Nd = 375(1 - exp(-2*5 X w3na)). They also compared equation (1) with one obtained from the study of Leaitch et al. (1992), which is log(nd) =.2571g(*122Na) -I Equation (2) is obtained assuming the same aerosol composition and size distribution as in Leaitch et al. (1 992), and that cloud water and particulate sulphate concentrations are equal; the original equation relates Nd to sulphate CCC /96/ by the Royal Meteorological Society (1) (2)

2 942 I. GULTEPE AND G. A. ISAAC concentration. The difference between equations (1) and (2) is significant, but the trend is in the same direction for both lines. Raga and Jonas (1993) suggested the following equation be used for cumulus clouds over the sea: Nd = 14.N,26, (3) where N, is the subcloud aerosol concentration, with an upper limit of about lo4 ~ m-~, and cloud droplet concentration Nd represents measurements made near the cloud top. The correlation coefficient (R) for the above equation was estimated as.95. Martin et al. (1994) suggested equations for over land and over ocean, respectively, as: and Nd = O-963Na X w3n: (4) Nd = O.568Na x (5) where N, for continental clouds ranges between 375 cmp3 and 15 cmp3. For maritime clouds, its value is between 36 and 28 ~ m-~. The standard deviation of the points from the best-fit line is f 19 cm-3 for maritime clouds and f 68 cm-3 for continental clouds. It is important to note that, except for the Raga and Jonas (1993) study, all other studies, including this study, used observations from mainly stratus and stratocumulus cloud types. OBSERVATIONS Observations during four field projects were collected by either the National Research Council of Canada DHC-6 Twin Otter or the Convair-58 aircraft. Table I denotes the project name, date, location, cloud type, and temperature. The Syracuse project was performed in New York State during The Eulerian Model Evaluation Field Study was conducted in southern Ontario during 1988 (EMEFS I) and 199 (EMEFS 11). The North Atlantic Regional Experiment (NARE) was conducted in Nova Scotia during Observations are obtained from mainly stratus and stratocumulus cloud types. Some of the observations during EMEFS I were collected in cumuliform clouds (Leaitch et al., 1992). However, cloud segments are included in the analysis only if for 95 per cent of the flying time along a segment the droplet number concentration is greater than approximately 5 ~ m-~. Consequently, cumulus clouds are taken out of the analysis, because their size is much smaller than the analysis length of about 1-15 km. Cloud droplet number concentration (Nd) and diameter were obtained from a Particle Measuring Systems (PMS) Forward Scattering Spectrometer Probe (FSSP-1) operated in 15 channels in the p diameter range. The FSSP measurements are corrected for probe dead time and coincidence as recommended by Baumgardner et al. (1985). Interstitial aerosol number concentration (Ni) during EMEFS I1 and NARE was obtained with a PMS Passive Cavity Aerosol Spectrometer Probe (PCASP-IOOX), which samples in 15 channels in the.13-2 pm diameter range (Liu et al. 1993). Outside of cloud, this instrument measures the dry aerosol concentration in the given size interval. Inside of cloud, there is an uncertainty in Ni owing to evaporation of small cloud droplets in the PCASP, which cannot be separated completely from the dry aerosols. Owing to the generally lower droplet concentration seen, this uncertainty will not be significant. Table I. Shows the date, location, cloud type, and temperature range for each field experiment used in this study. Experiment Year Month Location Clouds over Temperature range ("C) Syracuse October-I4 November 43'4" 7" 11'W Land - 15 to 15 EMEFS I July-29 August 44'58" 79"18'W Land - 1 to 2 EMEFS I March-29 April 46'2" 79"3'W Land - 1 to 1 NARE August4 September 43"5'N 65"3'W Ocean - to 2

3 CLOUD DROPLETS AND AEROSOL CONCENTRATIONS 943 The PCASP probe had an internal flow problem for most of the time during EMEFS I1 and this may affect the scatter of the data but not N,. The data from the Syracuse and EMEFS I field projects were collected by an ASASP probe that operated in the diameter range from.17 to 2 pm (Liu et af., 1993). Because of a lower limit in the PCASP, N, from this probe can be larger than that of the ASASP. The ratio of the lowest two channels (.135 pm to.165 pm) of the PCASP to total N, is found to be from 8 to 3 per cent for NARE and EMEFS 11. There is no way to estimate the particle concentration for sizes less than.17 pm when using the ASASP probe. Therefore, based on the other field data, N, during Syracuse and EMEFS I is underestimated by approximately 8-3 per cent. The uncertainty in counting is about 12 per cent for both the ASASP and the PCASP. ANALYSIS AND RESULTS Observations from stratiform clouds at a 1Hz sampling rate during constant altitude flight legs are used in the analysis. Figure 1 illustrates the importance of the relationship between Nd and Ni (or N, outside the cloud). In box a, representing a cloud segment, the dots are for PCASP aerosol number concentrations and the solid line is for FSSP droplet number concentration for 2 September 1993 during NARE. Smoothed lines are drawn through the values of Nd and Ni. In the smoothing, a running average method is applied to each 15 data points. It can be easily seen from box a that increasing Ni about 1 cm-3 results in a decrease in Nd of approximately the same amount. This result is similar to that obtained for stratiform clouds by Isaac et al. (199). In box b, aerosol concentration within and outside the cloud are shown. The N, value within cloud is equal to Nd + N, and outside cloud is equal to the aerosol concentration. Outside the cloud, average aerosol concentration is about 441 f447 ~m-~, and it is shown with a solid horizontal line. The average total aerosol concentration within the cloud is approximately 491 f 51 cm-3, and it is also shown by a solid horizontal line. This shows that aerosol number concentration N, outside the cloud is approximately equal to Ni + Nd within the cloud. This result is also found to be similar to that r rj t' I I I I I I I I I I I I I 8 1 Rnn L '_.."" L TIME [sec] Figure 1. Time series of PCASP interstitial aerosol number concentration Ni (or N. in cloud-free segments), and FSSP droplet number concentration Nd are shown in box a. Smoothed lines represent a 15 point running average value of both parameters. Total aerosol number concentration N. is shown by solid lines in box b. Both boxes are for 2 September Horizontal thin lines in box b are for mean values of N. for in-cloud and out of cloud. Cloud is approximately between and 1 s.

4 944 I. GULTEPE AND G. A. ISAAC E 6 4 z" 2 n r) I E U 2" I & 6 L-l 4 z" N, [~rn-~] Figure 2. Relationship between Nd and N,: (a) for Syracuse, (b) for EMEFS I, (c) for EMEFS 11, and (d) for NARE field projects. Bars are for standard deviation along 2 s legs. The solid line represents the best fit. of Isaac et al. (199) and indicates the importance of the relationship between aerosols and droplet number concentrations. The Nd and N, observations for the clouds are averaged over 2 s (about 1-15 km) flight legs for each field experiment. The mean and standard deviation of both parameters are obtained and plotted in Figure 2. Figures 2% 2b, 2c, and 2d are for Syracuse, EMEFS I, EMEFS 11, and NARE, respectively. Each figure shows all the data points with the associated error bars. The solid lines are for the best fit, and their equations, chosen on the basis of higher R values, are respectively given as Nd = log(n,) + R =.66, Nd = log(na) + R =.76, (6) (7)

5 CLOUD DROPLETS AND AEROSOL CONCENTRATIONS N, [~rn-~] Figure 3. Best fits representing equations given in text. The dashed lines are from the present study. Others are for earlier studies. Equation numbers are shown next to the lines. Nd = g(Na) + R =.6, (8) Nd = g(Na) + R =.59. (9) In the above equations, R represents the correlation coefficient. The upper limit for N, from equations (6) to (9) is 1, 8, 15, and 15, respectively. The curves are particularly steep for N, < 5 cmp3. The variability in Nd for a given N, is approximately 2-3 cmp3. This variability may be attributed to localized aerosol sources, but it may also be due to non-local inhomogeneities in the aerosol field, different cloud types, and cloud dynamical and thermodynamical conditions. The effect of these conditions on aerosol number concentrations are explained by Gultepe et al. (1996). The curves obtained from equations (1) to (9) are shown in Figure 3. The best fits from the three continental sites of this study (6, 7, and 8) showed similar results, which are different from the maritime NARE case (9). This suggests that the relationship between Nd and N, is different for maritime and continental locations. Based on these results, it would be difficult to use only one curve (e.g. l), as suggested by Jones et al. (1994). The results from the present studies were different in detail but remarkably similar to equations (l), (2), (4), and (5). Only equation (3) from Raga and Jonas (1993) showed a substantial deviation from the other results. The reason for thls can be due to the use of observations from cumuliform clouds in their study as opposed to stratiform cloud data used in this study. It is also important to note that the curve of equation 2 is curtailed at approximately Nd = 2 ~m-~, and this lower limit is chosen to stop predicting more droplets than aerosol particles (possibly an artifact of the equation being based on just sulphate concentrations). Many studies (McFarlane et al., 1992; Treut et al., 1994) have used constant droplet concentrations over ocean (e.g. 1 cmp3) and over land (e.g. 5 ~ m-~). Figure 3 shows that Nd is a strong function of N,. Assuming a constant value over oceans and land is probably not the best approximation. CONCLUSIONS This study used in situ observations of droplet and aerosol concentrations over ocean and land to determine relationships between these variables. Relationships between total aerosol and droplet concentrations are important in developing better parameterizations of cloud microphysics. However, it should be noted that most of the present climate studies under development are centred around predicting sulphate aerosol mass, which is not the same thing as N,. Because of the presently limited data set on marine stratus clouds, future field projects will be used to further refine the analysis of N,,, N,, and aerosol chemistry relationships. The results suggest that parameterized equations obtained from three field projects, representing stratiform clouds formed over land, are similar. The

6 GULTEPE AND G. A. ISAAC fourth one, representing stratiform clouds over ocean, is found similar to the other three for lower concentration of N,, but different for higher values of N,. The values of N, near 15 cm-3 for equation (9) indicate that cloud droplets during NARE were likely activated on aerosols which originated from both land and ocean surfaces. The value of Nd in clouds generally increases with N,, with the rate of increase being less at higher concentrations, in a similar manner to other studies (excluding equations (4) and (5)). This suggests that the relationship between Nd and N, may be universal. However, strong local influences on aerosol concentration do exist and they may significantly affect the radiative properties of the atmosphere. ACKNOWLEDGEMENTS The authors would like to thank M. Couture, and D. Kellow of the Cloud Physics Research Division of the Atmospheric Environment Service (AES), for assistance in the data analysis. The authors would particularly like to thank W. R. Leaitch and J. W. Strapp. Many other scientists and technicians from AES and the National Research Council (NRC) are also acknowledged for their effort to gather data during five field experiments, and for datarelated discussions. The aircraft data were obtained with the assistance of NRC. REFERENCES Baumgardner, D., Strapp, J. W. and Dye, J. E Evaluation of the forward-scattering spectrometer probe. 11: corrections for coincidence and deat-time losses, 1 Atmos. Ocean. Technol., 2, Charlson, R. J., Schwartz, S. E., Hales, J. M., Cess, R. D., Coakley, J. A,, Hansen, J. E. and Hofmann, D. J Climate forcing by anthropogenic aerosols, Science, 255, Gultepe, I., Isaac, G. I., Leaitch, W. R. and Banic, C. M Parameterizations of marine stratus microphysics based in in situ observations: implications for GCMs. 1 Climate, 9, Isaac, G. A. Leaitch, W. R. and Strapp, J. W The vertical distribution of aerosols and acid related compounds in air and cloudwater, Atmos. Envimn., 24A, Jones, A., Roberts, D. L. and Slingo, JA A climate model study of indirect radiative forcing by anthropogenic sulphate aerosols, Nature, 37, Kaufman, Y. J., Fmer, R. S. and Mahoney, R. L Fossil fuel and biomass burning effect on climate - heating or cooling?, 1 Climate, 4, Leaitch, W. R., Isaac, G. A., Strapp, J. W., Banic, C. M. and Wiebe, H. A The relationship between cloud droplet number concentrations and anthropogenic pollution: observations and climatic implications, 1 Geophy Res., 97, Liu, P. S. K., Leaitch, W. R., MacDonald, A. M., Isaac, G. A. and Strapp, J. W Sulphate production in summer cloud over Ontario, Canada, Tellus, 45B, Martin, G. M. and Johnson, D. W The measurement and parameterization of effective radius of droplets in stratocumuls clouds, Proceedings of the 11th International Conference on Clouds and Precipitation, Montreal, published by AES, Downsview, Ontario, Canada, pp Martin, G. M., Johnson, D. W. and Spice, A The measurement and parameterization of effective radius of droplets in warm stratocumulus clouds, 1 Ahos. Sci., 51, McFarlane, N. A,, Boer, G. J., Blanchet, J.-I? and Lazare, M The Canadian Climate Center second generation general circulation model and its equilibrium climate, 1 Climate, 5, Raga, G. B. and Jonas, I? R On the link between cloud-top radiative properties and sub-cloud aerosol concentrations, Q. 1 R. Meteoml. SOC., 119, Taylor, K. E. and Penner, J. E Response of the climate system to atmospheric aerosols and greenhouse gases, Nature, 369, Treut, H. L., Li, Z. X. and Morichon, M Sensitivity of the LMD general circulation model to greenhouse forcing associated with two different cloud water parameterimtions, 1 Climate, 7, Wigley, T. M. L Cloud reducing fossil-fuel emissions cause global warming?, Natum, 349, Wigley, T. M. L Outlook becoming hazier, Nature, 369,79-71.