Effect of non-spherical dust aerosol on its direct radiative forcing

Atmospheric Research 120–121 (2013) 112–126

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Effect of non-spherical dust aerosol on its direct radiative forcing Zhili Wang a, Hua Zhang b,⁎, Xianwen Jing a, b, Xiaodong Wei c a b c

Chinese Academy of Meteorological Sciences, Beijing 100081, China Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081, China Meteorological Center, East China Bureau of Air Control, Shanghai 201702, China

a r t i c l e

i n f o

Article history: Received 27 April 2012 Received in revised form 13 August 2012 Accepted 17 August 2012 Keywords: Dust Spherical/non-spherical particles IRF AF

a b s t r a c t The optical properties of spherical and non-spherical dust aerosols are calculated using the Lorenz–Mie theory and the combination of T-matrix method and an improved geometric optics method. The resulting optical properties are then applied in an interactive system that coupled a general circulation model with an aerosol model to quantitatively analyze the effect of non-spherical dust aerosol on its direct radiative forcing (DRF). Our results show that the maximum difference in dust instantaneous radiative forcing (IRF) between spherical and non-spherical particles is 0.27 W m−2 at the top of the atmosphere (TOA) and appears over the Sahara Desert due to enhanced absorption of solar radiation by non-spherical dust. The global annual means of shortwave (longwave) IRFs due to spherical and non-spherical dust aerosols at the TOA for all sky are − 0.62 (0.074) W m−2 and − 0.61 (0.073) W m−2, respectively, and the corresponding values for clear sky are − 1.16 (0.092) W m −2 and − 1.14 (0.093) W m−2, which indicates that the non-spherical effect of dust has almost no effect on their global annual mean IRFs. However, non-spherical dust displays more evident influences than above on its atmosphericand land-temperature adjusted radiative forcing (AF) at the TOA over the Saharan Desert, West Asia, and northern China, with an approximate maximum increase of 3.0 and decrease of 0.5 W m −2. The global annual means of shortwave (longwave) AFs due to spherical and non-spherical dust aerosols are − 0.55 (0.052) W m−2 and − 0.48 (0.049) W m−2 at the TOA for all sky, respectively, and the corresponding values for clear sky are − 1.07 (0.066) W m−2 and − 0.95 (0.062) W m−2. All AFs of dust become much weaker than their corresponding IRFs. The absolute values of annual mean AF for non-spherical dust are approximately 13% (11.2%) and 6% (6%) less than those of spherical dust for the shortwave and longwave for all sky (clear sky), respectively. The results indicate that the non-spherical effect of dust can reduce their AFs more obviously than do their IRFs. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Dust aerosols are a major contributor to aerosol loading on a global scale and play a crucial role in the radiative processes of the earth-atmosphere system. An estimated 1–3 billion tons of dust particles are emitted into the atmosphere globally each year, accounting for more than half of the total atmospheric particles (IPCC, 2001, 2007). Dust aerosols originate largely ⁎ Corresponding author. Tel./fax: +86 10 68400070. E-mail address: [email protected] (H. Zhang). 0169-8095/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.atmosres.2012.08.006

from deserts and semi-desert areas (e.g., the Sahara in Africa and deserts of Central and West Asia). There are also a large number of dust aerosols emitted in the western USA and northwestern China. Anthropogenic dust sources have been increasing since industrialization, largely because of desertification in some areas (Zhang et al., 2008). Dust aerosols can scatter and absorb solar radiation, as well as absorb and emit longwave radiation, thereby directly disturbing the energy balance of the earth-atmosphere system (Haywood et al., 2003; Wang, 2010; Zhang et al., 2010; El-Metwally et al., 2011). Moreover, dust can change the

Z. Wang et al. / Atmospheric Research 120–121 (2013) 112–126

optical properties of clouds by acting as cloud or ice condensation nuclei, thus indirectly affecting climate (Carrió et al., 2007; Hendricks et al., 2011; Rosenfeld et al., 2011). Therefore, dust is regarded as an important climate-forcing factor. IPCC (2007) reported that the global annual mean direct radiative forcing (DRF) of dust aerosols due to anthropogenic contributions is −0.3–+0.1 W m −2. However, there are still many uncertainties, primarily in terms of emission sources and the optical properties of dust. For example, multiple observation results have shown that the single scattering albedo of dust particles in the Sahara Desert ranged from 0.95 to 0.99 at 550 nm wavelength (Haywood et al., 2003; McFarlane et al., 2009). However, corresponding values for a desert in northwestern China ranged between 0.73 and 0.85, the value much smaller than that for the African Sahara region and with stronger absorptivity (Ge et al., 2010). The single scattering albedo depends on the refractive index, particle shape, particle size distribution, thus varying from region to region (Sokolik and Toon, 1996; Claquin et al., 1999; Yi et al., 2011). Most studies have assumed spherical dust particles and used the Lorenz-Mie theory to obtain the optical properties of dust particles when calculating the radiative forcing of dust aerosols in either a general circulation model (GCM) or a radiative transfer model. However, investigations using both scanning electron microscopes and field observations have shown that most dust particles have non-spherical shapes (Nakajima, 1989; Gao and Anderson, 2001; Okada et al., 2001). Several studies have also reported that the optical properties of dust vary significantly depending on whether the particles are considered spherical or non-spherical (Yang et al., 2000; Zhao et al., 2003; Barnaba et al., 2004; Kalashnikova and sokolik, 2004). Yang et al. (2007) compared the optical properties of spherical and spheroidal dust particles using the Lorenz-Mie theory and a combination of the T-matrix method and improved geometric optics method (IGOM) and found that the effects of non-spherical shape were large at short wavelengths but essentially negligible at infrared wavelengths. Fu et al. (2009) calculated the single-scattering properties of dust aerosols with both spheroidal and spherical shapes at the 550 nm wavelength and found that the relative errors of the spheres used to approximate the spheroids were b1% for the extinction efficiency and single-scattering albedo, and less than b2% for the asymmetry factor. Wei and Zhang (2011) found that the difference of phase function between non-spherical and spherical dust was significant, especially in the visible region, and the extinction to backscattering ratio in the so-called lidar equation was affected by the shape of dust greatly in shortwave region. Yi et al. (2011) investigated the non-spherical effect of dust particles on DRF through prescribing the solar zenith and azimuthal angles to be 45° and 0°, respectively, and the dust AOD and surface albedo to be 0.5 and 0.1, respectively, and assuming the shape of dust to be tri-axial ellipsoidal, using a 32-stream DISORT-based radiative transfer model. They found that the non-spherical effect was an important source of dust DRF uncertainties, which were particularly large over water surfaces and capable of causing a 30% difference in dust forcing calculated at the TOA. Satellite observations have also shown that the scattering properties of aerosols assumed to be spheres differ greatly from those of actual dust particles. Thus, it is important to consider the non-spherical effect when estimating the optical depth and

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micro-physical properties of dust aerosols (Wang et al., 2003; Herman et al., 2005; Dubovik et al., 2006). Several recent studies have examined the different optical properties of dust particles arising from their spherical and non-spherical shapes (e.g., Yang et al., 2007; Fu et al., 2009; Wei and Zhang, 2011; Yi et al., 2011). However, none of these studies quantified the effect of non-spherical dust on global DRF. In this study, we calculated the optical properties of spherical and non-spherical dust particles using the LorenzMie theory and a combination of the T-matrix method and IGOM. The resulting optical properties were then applied in an interactive system coupling GCM and an aerosol model to analyze the effects of non-sphericity on dust instantaneous radiative forcing (IRF) and adjusted radiative forcing (AF). The IRF is defined as the change in net irradiance at the TOA with surface and atmospheric temperatures and state held fixed at the unperturbed values. The AF is defined as the change in net irradiance at the TOA after allowing for atmospheric and land temperatures, water vapor, clouds and land albedo to adjust, but with sea surface temperatures (SSTs) and sea ice cover unchanged (Hansen et al., 2005). In the following section, we introduce basic model information, the methods for calculating the optical properties of spherical and non-spherical dust particles, and our experimental design. We then present results from our comparisons of the various optical properties of dust particles calculated by the two methods and analyze the differences between simulated optical properties, IRF, and AF for spherical and non-spherical dust aerosols. 2. Model description and methods 2.1. Basic model information An interactive system for coupling a GCM (BCC_AGCM2.0.1) with the Canadian Aerosol Module (CAM) is developed by Zhang et al. (2012a) and used here to study the non-spherical effect of dust. The BCC_AGCM2.0.1 is developed by the National Climate Center of the China Meteorological Administration (NCC/CMA) based on the Community Atmosphere Model Version 3 (CAM3) developed by the US National Center for Atmospheric Research. The model uses horizontal triangular truncation at wavenumber 42 (T42, approximating 2.8° ×2.8°) and vertical hybrid σ-pressure coordinates to include 26 vertical layers with the top layer having a pressure of 2.9 hPa. Some improvements in dynamics, convection scheme, dry adiabatic adjustment, turbulent fluxes over the ocean, and snow cover fraction parameterization have been implemented in BCC_AGCM2.0.1 in comparison to CAM3, allowing for better performance in climate simulations (Wu et al., 2010). The CAM, a size-segregated multi-component aerosol algorithm, is developed by Gong et al. (2002, 2003a). The algorithm includes processes for the emission, transport, chemical transformation, cloud interaction, and deposition of atmospheric aerosols. Five aerosol species were included: sulfate, black carbon (BC), organic carbon (OC), soil dust, and sea salt. The emissions of sulfate, BC and OC are derived from AeroCom data (Dentener et al., 2006). The emissions of soil dust and sea salt are calculated online using the scheme developed by Marticorena and Bergametti (1995) and Gong et al. (2002), respectively. In this model, the aerosol size is divided into 12 bins with radii between 0.005–0.01, 0.01–0.02, 0.02–0.04, 0.04–0.08, 0.08–

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0.16, 0.16–0.32, 0.32–0.64, 0.64–1.28, 1.28–2.56, 2.56–5.12, 5.12–10.24, and 10.24–20.48 μm. Three lognormal population distributions for dust in China are used, and the mass median diameters and standard deviations of these three populations are determined by considering the soil features in China and source region dust size-distribution measurements (Gong et al., 2003b; Zhang et al., 2003b). Out of China, the two-mode size distribution for dust from the observation by Chatenet et al. (1996) is used (Marticorena and Bergametti, 1995). Finally, the dust emissions are distributed into each size bin by using the above-mentioned size distributions. The refractive indices of aerosols are adopted from D'Almeida et al. (1991). BCC_AGCM2.0.1 and CAM have achieved complete online coupling and can simulate the mass concentration, optical properties, and DRF of typical aerosols with a high level of accuracy (Zhang et al., 2012a). Detailed information on the simulation performance of this interactive system has been provided by Zhang et al. (2012a). In this study, the cloud overlap processing developed by Collins (2001) for the above-mentioned version is replaced with a new method developed by Jing and Zhang (2012) that simulates cloud overlap using a Monte Carlo independent column approximation (McICA). We also replace the primary radiative parameterization from Briegleb (1992) with the correlated k-distribution radiation scheme developed by Zhang et al. (2003a, 2006a, 2006b). These two modifications allow for improved representations of gas absorption and of the structure and radiative transfer of subgrid-scale clouds. Under the new radiation scheme, wavelengths are classified into 17 bands (eight for longwave radiation and nine for shortwave radiation) which are 10–250, 250–550, 550–780, 780–990, 990–1200, 1200–1430, 1430–2110, 2110–2680, 2680–5200, 5200–12,000, 12,000–22,000, 22,000–31,000, 31,000–33,000, 33,000–35,000, 35,000–37,000, 37,000–43,000, and 43,000–49,000 cm − 1, respectively, and the absorption of five main greenhouse gases: H2O, CO2, O3, N2O, CH4, and CFC (CFC11, CFC12, CCL4 and CFC22), and O2 continuum absorption are included. The new scheme also allow for the simulation of the scattering and absorbing processes of clouds and aerosols. The optical properties of aerosols are calculated by Wei and Zhang (2011) and Zhang et al. (2012b). The optical properties of water clouds are taken from Nakajima et al. (2000). The optical properties of ice clouds are obtained by incorporating data on ice cloud particle shapes and spectral distribution by Fu (1996), phase function data by Yang et al. (2005), and the hybrid method of different shapes of ice cloud particles by Baum et al. (2005).

shape and composition of particles in the T-matrix method without considering the orientation of particles. For particles much larger than the wavelength of light, the IGOM is adopted to calculate the single scattering properties of particles, which is developed by Yang and Liou (1996) based on the principles of geometric optics, and the ray-tracing technique has been used in the method (Please see Yang et al. (2007) for detail calculation). It is shown that the optical properties of dust calculated by the spheroidal approximations are similar to those of actual dust (Mishchenko and Travis, 1994; Gobbi et al., 2002). Moreover, the size distributions of dust particles are provided by the online BCC_AGCM2.0.1_CAM. The optical properties of corresponding spherical dust particles are calculated using Wiscombe's (1980) algorithm based on Lorenz-Mie theory. Two groups of experiments are designed for this work, each of which includes two experiments. In the first group of experiments (EXPIRF), the two simulations calculate the IRFs of dust aerosols using the optical properties of spherical (EXPIRF_sphere) and non-spherical (EXPIRF_nonsphere) dust particles, respectively. This method calls on the radiation scheme twice at each radiative time step in each simulation. The effect of dust on radiation is taken into account only in the first call, in which the simulated radiative fields are used to diagnose the dust radiative forcing rather than feedback into the GCM climate. Thus, the difference between the two simulated forcings only results from the difference between two kinds of optical properties of dust particles. In the second group of experiments (EXPAF), the two simulations calculate the AF of spherical (EXPAF_sphere) and non-spherical (EXPAF_ nonsphere) dust aerosols, respectively. The method also calls on the radiation scheme twice, but the radiative effect of dust is only considered in the second call. The radiative fields are fed back into the atmospheric fields, and the model evolution is modified by the radiative effect of dust, whereas SST is fixed (Hansen et al., 2005). Therefore, the difference between the two simulated forcings results from not only the two kinds of dust optical properties, but also changed temperature profiles after responding to the radiative feedback of spherical and non-spherical dust. The AF has been shown to provide a better estimate than IRF of the eventual temperature change (Hansen et al., 2005).

2.2. Methods and experimental design

Fig. 1 shows the relative differences of the extinction efficiency factor, single scattering albedo, and asymmetry factor between non-spherical and spherical dust particles calculated by the Lorenz-Mie theory and the combination of T-matrix method with IGOM. The effect of non-spherical dust particles on extinction efficiency exists across nearly the entire wavelength spectrum. There are obvious differences in extinction of nuclei mode dust from the two shapes. The fluctuations of extinction efficiency factor with the increase of size parameter (2πr/λ) for small spherical and non-spherical dust particles are larger than those for larger particles, so the non-spherical effect on the extinction efficiency factor of small particles is more obvious than that of larger particles. However,

The optical properties of non-spherical dust aerosols including the extinction coefficient, single scattering albedo, and asymmetry factor are calculated by combining the T-matrix method and an IGOM, where the shape of non -spherical dust particles is approximated using a rotational symmetric spheroid (Wei and Zhang, 2011). The T-matrix code developed by Mishchenko and Travis (1994) is used to compute the single scattering properties of spheroidal particles with size parameters (specified in terms of the radius of volume-equivalent sphere) less than 50. For randomly oriented particles, the optical properties are determined by the size,

3. Results 3.1. Comparison between the optical properties of spherical and non-spherical dust particles

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Differences (%)

15 10 5 0 -5 -10 -15 2

Qe

MINM MICM

115

MIAM MITR

a)

ω

b)

0 -2 -4 10 5

g

c)

0 -5 -10 0.2

10

1

40

Wavelength (um) Fig. 1. The relative differences of (a) extinction efficiency factor, (b) single scattering albedo and (c) asymmetry factor between non-spherical and spherical dust particles. MINM, MIAM, MICM and MITR represent the nuclei mode, accumulation mode, coarse mode and transported mode, respectively. The mode radii and standard deviations for the four modes are (0.07 μm, 1.95), (0.39 μm, 2.0), (1.90 μm, 2.15) and (0.50 μm, 2.2), respectively.

the mass concentration of nuclei mode dust is small, so the effect on radiation flux caused by different particle shapes is also small. For accumulation mode and transported mode dust, the relative deviation of extinction efficiency factors is within ±10% between the non-spherical and spherical dust. The difference between non-spherical and spherical dust extinctions for the coarse mode is smaller, with a relative deviation of less than ±5% (Fig. 1a). The relative deviations of single scattering albedo due to non-spherical and spherical dust are within ±4% for the four modes across all wavebands, with a primarily focus on wavebands larger than 3 μm. The relative difference between the two particle shapes is within ±2% in the shortwave band where scattering plays a major role (Fig. 1b). The relative deviation of asymmetry factors between non-spherical and spherical dust particles is within ±8%, concentrating in the wavebands smaller than 2 μm and between approximately 10 and 40 μm (Fig. 1c). In Fig. 2, the band-mean relative differences in optical properties between non-spherical and spherical dust particles are shown for the 17-band radiation scheme used in BCC_AGCM2.0.1. Generally, differences in the extinction coefficient, single scattering albedo, and asymmetry factor are less than 15%. As can be seen from Fig. 2, the nonspherical effect of dust primarily affects the dust extinction and asymmetry factor, and only has small impact on the single scattering albedo except the medium sized dust particles in the 13–17 wavebands (Fig. 2b and c). The differences of dust extinction mainly concentrate in the 1–5 and 11–17 wavebands, with the highest value exceeding 10%. The differences of dust asymmetry factor are located in the 3–9 and 13–15 wavebands, but the asymmetry factor of large dust particles is affected less due to dust non-spherical effect (Fig. 2d).

3.2. Difference in IRF between non-spherical and spherical dust aerosols The IRFs of dust aerosols are calculated in EXPIRF, and the difference between the two simulated dust radiative forcings is due only to the differing optical properties of spherical and non-spherical dust. Fig. 3 shows the global distribution of annual mean column burden for dust aerosol simulated in EXPIRF. The dust column burdens are found to be located mainly in the North African Sahara region and in West Asia, with maximum values exceeding 1000 mg m −2, due to year-round dry air and little vegetation that increase dust emissions in these areas. The second highest values of more than 100 mg m −2 are located in Inner Mongolia and the Xinjiang region of China. There is also an extended distribution of dust aerosol in central and western areas of North America. The simulated global annual mean dust column burden is 57.8 mg m −2. Table 1 compares the global load, lifetime, and optical depth of dust simulated in this study with a number of reference models. We note that the dust load and optical depth in our model is comparative with those in most of other models, but the simulated dust lifetime is shorter than others. This is because that the range of dust size in our model is larger (from 0.005 to 20.48 μm) than those in other models and the larger particles tend to have shorter lifetimes. Fig. 4 shows the global annual mean distributions of simulated dust optical depth from EXPIRF_sphere and the difference between dust optical depths from EXPIRF_nonsphere versus EXPIRF_sphere at 550 nm. The simulated optical depth of non-spherical dust aerosols is greater than that of spherical dust aerosols at 550 nm, due to an increase in the extinction coefficient of dust in both the coarse and transported modes,

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20.0

20.0 Radius = 0.06 um

10.0 5.0 0.0 -5.0

1

-10.0

Radius = 0.24 um

15.0

3 5 7 Extinction SSA Asymmetry factor

9

11

13

15

17

Difference (%)

Difference (%)

15.0

10.0 5.0 0.0 -5.0

1

-10.0

a)

3 5 7 9 Extinction SSA Asymmetry factor

17

b)

20.0 Radius = 0.5 um

10.0 5.0 0.0 1

3

5

Radius = 1.9 um

15.0

7

9

11

Extinction SSA Asymmetry factor

13

15

17

c)

-15.0

Difference (%)

15.0

Difference (%)

15

Waveband

Waveband 20.0

-10.0

13

-15.0

-15.0

-5.0

11

10.0 5.0 0.0 -5.0 -10.0

1

3 5 7 9 Extinction SSA Asymmetry factor

11

13

15

17

d)

-15.0

Waveband

Waveband

Fig. 2. The band-mean relative differences of extinction coefficient, single scattering albedo (SSA) and asymmetry factor between non-spherical and spherical dust for 17-band radiation scheme when particle radius equals to 0.06, 0.24, 0.5 and 1.9 μm.

the principal modes for dust modeling. The dust optical depths are increased by over 2% in most regions. The greatest increase, nearly 4%, appears over the Sahara Desert near 15°N as a result of a high loading of coarse dust in the atmosphere. The dust optical depth also increases by about 3% over northern China. The relative differences in the simulated aerosol single scattering albedo and asymmetry factor between EXPIRF_sphere and

EXPIRF_nonsphere at 550 nm are not obvious, approximately less than 1% (Figures not shown). Dust aerosols not only absorb and scatter solar radiation but also absorb and emit infrared radiation, leading to both positive and negative radiative forcings simultaneously at the TOA under different atmospheric conditions. As can be seen from the simulated global distribution of annual mean shortwave

Fig. 3. The global annual mean distribution of simulated dust column burden in EXPIRF (unit: mg m−2).

Z. Wang et al. / Atmospheric Research 120–121 (2013) 112–126 Table 1 Summary of the global load, lifetime and optical depth at 550 nm (OD550) of dust. Model

Load (Tg)

Lifetime (days)

OD550 dust

References

CAM ECMWF GISS SPRINTARS MOZGN ECHAM5-HAM MIRAGE This study EXPIRF_sphere EXPIRF_nonsphere EXPAF_sphere EXPAF_nonsphere

25.7 54.7 29.0 17.2 21.1 8.2 22.0

4.6 3.3 7.1 1.6 3.3 4.4 3.9

0.035 0.027 0.034 0.024 0.022 0.01 0.053

Huneeus et al. (2011)

29.5 – 25.8 23.4

1.5 – 1.5 2.8

0.038 0.039 0.033 0.031

IRF at the TOA for all sky from EXPIRF_sphere (Fig. 5a), the largest forcing occurs over West Asia, north China, and especially over northern and western Africa. In these regions, maximum forcing exceeds −12 W m −2 due to the multiple scattering of solar radiation caused by the considerable dust loading above the abundant large-scale stratus clouds (Schumacher and Houze, 2006). Dust aerosols produce an apparent positive forcing over the Tibetan Plateau with the maximum exceeding +5 W m−2 owing to a high surface albedo there. Surface albedo is a key factor to control dust radiative forcing. Fig. 6 shows the comparisons of simulated annual mean surface albedo with the MODIS data. As can be seen from the Fig. 6, the distribution of simulated surface albedo is basically consistent with the observation in most of regions. However, the simulated values are slightly lower in northern Africa and larger in the snow cover regions of boreal high latitudes than those observed. Especially, the simulated surface albedo is obviously larger than the observed in the Tibetan Plateau due to the simulated more snow cover and

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depth and the differences of snow properties in model (grain size especially), which possibly results in the larger positive forcing over these areas. The forcing becomes weaker when non-spherical particles are used, because they are effectively more absorbing (Figs. 1b and 5c). Compared to the spherical dust IRF, the IRF by non-spherical dust is weakened by 1–4%. Regions of larger weakening appear in areas with larger dust radiative forcing. For example, the forcing is weakened by up to 0.27 W m −2 over the Sahara Desert and by 0.12 ~ 0.18 W m −2 over West Asia and the Tibetan Plateau. The effect of non-spherical dust on longwave IRF also represents an increase in longwave radiation absorption; however, this increase is small, having a relative difference of about 1% (Fig. 5b and d). The global annual means of simulated dust shortwave (longwave) IRFs at the TOA for all sky in EXPIRF_sphere and EXPIRF_nonsphere are −0.62 (0.073) W m −2 and −0.61 (0.074) W m −2, respectively. Non-spherical dust shape has little influence on IRF (Table 2) because the differences between non-spherical and spherical dust optical properties are relatively small, especially in the solar wavebands, in the coarse (primary dust) mode. Furthermore non-spherical effects can cancel each other for some bands and particle sizes (Fig. 2). It can be noted that the dust has a weak longwave radiative forcing in our results. We find that the mass median diameter of dust particles used in our model given by Marticorena and Bergametti (1995) is smaller than those in other models, which may be the primary reason that leads to the weak longwave effects. In order to get rid of cloud effect in above comparison of spherical and non-spherical dust, Fig. 7 shows the global distributions of simulated dust shortwave and longwave IRF at the TOA for clear sky in EXPIRF_sphere and the differences of forcing in EXPIRF_nonsphere versus EXPIRF_sphere. The strength and range of dust absolute shortwave IRF and longwave IRF for clear sky are larger than those for all sky because of reduction effects of clouds to dust IRF (Zhang et al., 2010), and the absolute changes of IRF due to non-spherical

Fig. 4. The global annual mean distributions of simulated dust optical depth in EXPIRF_sphere (contour line) and the difference in dust optical depths in EXPIRF_nonsphere versus EXPIRF_sphere (shaded) at 550 nm.

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a)

b)

c)

d)

Fig. 5. The global annual mean distributions of simulated dust (a) shortwave and (b) longwave IRF at the TOA in EXPIRF_sphere and the differences in dust (c) shortwave and (d) longwave IRF in EXPIRF_nonsphere versus EXPIRF_sphere for all sky (units: W m−2).

effect of dust for clear sky are more extensive and stronger than those for all sky. The global annual means of simulated dust shortwave (longwave) IRFs at the TOA for clear sky in EXPIRF_sphere and EXPIRF_nonsphere also become larger with values of −1.16 (0.092) W m−2 and −1.14 (0.093) W m−2, respectively (Table 2), each of which is stronger than the corresponding value for all sky, while non-spherical effect of dust on their IRFs is also very small with relative difference of 1.7% and 1.1% reduction for shortwave and longwave, respectively, almost similarly to those of all sky case. 3.3. Difference in AF between non-spherical and spherical dust aerosols The AFs of spherical and non-spherical dust aerosols are simulated in EXPAF. The simulated dust burdens change due to the adjustment of atmospheric and land temperatures to reflect the different radiative effects of non-spherical and spherical dust. Fig. 8 gives the global distributions of the annual mean column burden of simulated dust aerosols in EXPAF_ sphere and EXPAF_nonsphere, respectively. The simulated distributions of dust aerosol column burden in EXPAF_sphere and EXPAF_nonsphere are very similar, but the magnitudes of the annual mean column burden of dust in the two simulations are different: 50.6 mg m −2 and 45.8 mg m−2 for EXPAF_ sphere and EXPAF_nonsphere, respectively. The simulated column burdens of dust aerosols decrease in West Asia, south of African Sahara Desert and near its western ocean, with

maximum value over 200 mg m−2, but the column burdens increase in north of African Sahara Desert, middle North America and northern China, with maximum value exceeding 150 mg m −2, in EXPAF_nonsphere compared with EXPAF_ sphere (Fig. 8c). This is mainly due to the difference in optical and radiative properties between the two shapes of dust aerosols. The adjustment of atmospheric and land temperatures effectively results in differences in the atmospheric heating rate, thereby altering the dust aerosol emission, deposition, and load. It can be seen from the simulated global annual averaged budget of dust that the dust emission is reduced obviously in EXPAF_nonsphere which contributes most to be the change in burden. Fig. 9 indicates that the changes of solar and longwave heating rate due to the nonspherical effect of dust may cause the atmosphere to be more and less stable in the south and north of 25°N, respectively, which suppress and facilitate the dust transport and deposition in corresponding regions, thereby resulting in the changes of dust burden (Fig. 8). A change in simulated dust column burden caused by the optical properties of spherical and non-spherical dust particles will inevitably alter the dust optical depth, which is consistent with changes seen in dust column burden (Figs. 10 and 8c). The simulated optical depth of non-spherical dust aerosols at 550 nm over the north of the Sahara Desert and northern China is 5–20% higher than that of spherical dust aerosols. The dust optical depth in the south Sahara Desert and West Asia also decreases distinctly more for spherical aerosols than for

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a)

b)

Fig. 6. The global annual mean distributions of (a) simulated and (b) MODIS retrieval surface albedo.

non-spherical aerosols by up to 30%. The differences between the two simulations in the single scattering albedo, and asymmetry factor at 550 nm are also small, varying by less

than 1% (figures not shown). Table 3 gives the comparisons of simulated annual mean total AODs in EXPAF with those measured at 550 nm at some sites that are located in the dust

Table 2 Global annual means and differences of simulated dust optical properties and DRF between different experiments. AODD

SSA

g

(λ = 550 nm) EXPIRF_sphere EXPIRF_nonsphere DIFIRF EXPAF_sphere EXPAF_nonsphere DIFAF

0.038 0.039 +2.6% 0.033 0.031 −6.1%

RFS (units: W m

0.98 0.98 – 0.98 0.98 –

0.74 0.74 – 0.74 0.74 –

−0.62 −0.61 +2.0% −0.55 −0.48 +13%

RFL

RFCSs

RFCSL

−2

) 0.073 0.074 +1.4% 0.052 0.049 −6%

−1.16 −1.14 +1.7% −1.07 −0.95 +11%

0.092 0.093 +1.1% 0.066 0.062 −6%

AODD represents the dust optical depth; SSA and g represent the single scattering albedo and asymmetry factor of aerosol, respectively; RFS, RFL, RFCSs and RFCSL represent the dust shortwave and longwave IRF in EXPIRF and AF in EXPAF at the TOA for all sky and clear sky, respectively; DIFi represents the differences of each variable due to dust spherical and non-spherical in EXPIRF and EXPAF ((EXPi_nonsphere − EXPi_sphere) / EXPi_ sphere, i = IRF, AF).

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a)

b)

c)

d)

Fig. 7. Same as in Fig. 5, but for clear sky.

source regions. The measurements are from the AERONET Level 2.0 products except the Dunhuang and Ejinaqi sites that are from the CARSNET (China Meteorological Administration Aerosol Remote Sensing NETwork) (Che et al., 2009). Dailyaveraged aerosol optical depths are acquired at the AERONET and CARSNET sites, from which monthly-mean values and standard deviations are computed weighted by the daily number of observations. Then, the corresponding yearly-mean values equal to the averages of 12 months. The four-point interpolation scheme is used to match the locations of model grids with the measured sites. It can be seen that the simulated AODs are more consistent with the observations at most of sites except the Saada, Dhadnah, Kuwait sites when dust particles are assumed to be non-spherical. However, the improvements due to non-spherical particles on the comparison are difficult to assess, since standard deviations on observations are large. Fig. 11 shows global distributions of annual mean shortwave and longwave AF for simulated dust aerosols at the TOA for all sky in EXPAF_sphere, as well as the differences in dust shortwave and longwave AF in EXPAF_nonsphere versus EXPAF_sphere. The simulated distributions of annual mean shortwave and longwave AF of dust aerosols in EXPAF_sphere are consistent with those in EXPIRF_sphere. Shortwave and longwave AFs of non-spherical dust are weaker than those of spherical dust at the TOA over West Asia, south of the Sahara Desert, and along Africa's west coast. The largest decrease in shortwave forcing exceeds 3 W m−2, accounting for over 20% of the non-spherical dust shortwave AF, resulting from a

distinct decrease in dust column burden and optical depth in these areas, when dust particles are assumed to be nonspherical. The dust column burden and optical depth in northern China increased, but the shortwave AF in these areas decreased, when dust particles are considered nonspherical. This suggests that the absorption of radiation by dust in these regions has obviously increased and the negative AF of dust has been offset by non-spherical aerosol influences. Non-spherical dust intensifies AF in north of the Sahara Desert by 0.1–0.5 W m −2. The global annual means of simulated dust shortwave (longwave) AFs at the TOA are − 0.55 (0.052) W m − 2, and − 0.48 (0.049) W m − 2 in EXPAF_sphere and EXPAF_nonsphere, respectively. The absolute values of annual mean AF for non-spherical dust are approximately 13% and 6% less than those of spherical dust for shortwave and longwave radiation, respectively (Table 2). We also find that the absolute values of dust AF are smaller than those of IRF primarily due to the decrease in dust column burden after temperature adjustment, which is consistent with the results of Hansen et al. (2005). In order to get rid of cloud effects on dust AFs, Fig. 12 shows the global distributions of simulated dust shortwave and longwave AF at the TOA for clear sky in EXPAF_sphere and the differences of forcing in EXPAF_nonsphere versus EXPAF_ sphere. Similar to the IRF, the strength and range of dust negative shortwave AF and positive longwave AF for clear sky are larger than those for all sky, and the absolute changes of AF due to non-spherical effect of dust for clear sky are more

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a)

b)

c)

Fig. 8. The global annual mean distributions of simulated dust column burdens in (a) EXPAF_sphere and (b) EXPAF_nonsphere and (c) the difference in dust column burdens in EXPAF_nonsphere versus EXPAF_sphere (units: mg m−2).

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a)

b)

Fig. 9. The changes of zonally averaged (a) solar and (b) longwave heating rate due to the non-spherical effect of dust (units: 10−7 K s−1).

Fig. 10. Same as in Fig. 4, but for the experiment EXPAF.

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Table 3 Comparisons of simulated annual mean total AODs in EXPAF with those measured at 550 nm at some sites that are located in the dust source regions. The measurements are from the AERONET except the Dunhuang and Ejinaqi sites that are from the CARSNET (China Meteorological Administration Aerosol Remote Sensing NETwork) (Che et al., 2009). Site

Location

Sphere

Nonsphere

Obs.

Obs. years

Blida Malaga Saada La_Laguna Dahkla IER_Cinzana Agoufou Kuwait Hamin SEDE_BOKER Issyk-Kul Dunhuang Ejinaqi

2.9E, 36.5 N 4.5 W, 36.7 N 8.2 W, 31.6 N 16.3 W, 28.5 N 16.0 W, 23.7 N 5.9 W, 13.3 N 1.5 W, 15.3 N 48.0E, 29.3 N 54.3E, 23.0 N 34.8E, 30.9 N 77.0E, 42.6 N 94.7E, 40.2 N 101.1E, 42.0 N

0.12 0.11 0.21 0.25 0.42 0.54 0.64 0.27 0.388 0.184 0.14 0.25 0.17

0.14 0.13 0.26 0.23 0.37 0.49 0.58 0.25 0.307 0.181 0.12 0.28 0.18

0.21 ± 0.13 0.14 ± 0.08 0.22 ± 0.14 0.14 ± 0.13 0.29 ± 0.21 0.47 ± 0.30 0.51 ± 0.35 0.54 ± 0.32 0.345 ± 0.15 0.18 ± 0.11 0.12 ± 0.08 0.35 ± 0.31 0.22 ± 0.19

2003–2009 2009–2011 2004–2009 2006–2009 2002–2003 2004–2009 2003–2009 2007–2010 2004–2007 1996–2010 2007–2010 2003–2008 2002–2008

extensive and stronger than those for all sky, especially in northern Africa and Arabia. Clouds can greatly reduce AFs of dust too. The global annual means of simulated dust shortwave (longwave) AFs at the TOA for clear sky in EXPAF_sphere and EXPAF_nonsphere are −1.07 (0.066) W m −2 and −0.95 (0.062) W m−2, respectively (see Table 2), while nonspherical effect of dust on their AFs become larger with relative difference of 11.2% and 6.0% reduction for shortwave and longwave, respectively, almost the same as the results of all sky case too.

In our experiments, the non-spherical dust effects on radiative forcing are larger in EXPAF than in EXPIRF. This is because the temperature profiles are the same for both shapes of dust particles in EXPIRF, and the differences in dust forcing result from the differences in optical properties between the two simulations. However, there are two factors affecting dust radiative forcing in the two simulations of EXPAF: one is the optical properties of the dust, and the other is the atmospheric profiles that are altered in fast response to radiative feedback from spherical and non-spherical dust (Fig. 9). The net

a)

b)

c)

d)

Fig. 11. Same as in Fig. 5, but for the AF in experiment EXPAF.

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a)

b)

c)

d)

Fig. 12. Same as in Fig. 11, but for clear sky.

radiation flux at the TOA is more affected by non-spherical dust in EXPAF than it is in EXPIRF (0.14 W m −2 versus 0.02 W m −2 for the global annual mean, respectively), which indicates that these fast responses act collectively to increase the effect of non-spherical dust on AF. 4. Conclusions We calculate the optical properties of spherical and nonspherical dust aerosols using the Lorenz-Mie theory and a combination of the T-matrix method with an IGOM. We use the resulting optical properties in an interactive system coupling GCM and an aerosol model (BCC_AGCM2.0.1_CAM) to calculate the IRF and AF of spherical and non-spherical dust aerosols and to discuss the effect of non-spherical dust on radiative forcing. The simulated optical depths at 550 nm for non-spherical are greater than those for spherical dust particles, usually greater than 2%. The increase in dust optical depth due to non-spherical particles is the most distinct (about 4%) over the Sahara Desert, and is about 3% over northern China. The effects of non-spherical dust on aerosol single scattering albedo and asymmetry factor at 550 nm are more limited, and the relative deviations are less than 1%. These effects intensified the absorption of shortwave and longwave radiation by dust by 1 ~ 4% and less than 1%, respectively. Non-spherical dust causes the largest change in dust IRF at the TOA for all sky over the Sahara Desert, with a maximum increase of 0.27 W m −2, due to enhanced absorption of solar

radiation. The global annual means of shortwave (longwave) IRF for spherical and non-spherical dust at the TOA for all sky are − 0.62 (0.074) W m −2 and − 0.61 (0.073) W m −2, respectively. The non-spherical effect of dust has little influence on their IRFs. The global annual means of shortwave (longwave) IRF for spherical and non-spherical dust at the TOA for clear sky are − 1.16 (0.092) W m −2 and − 1.14 (0.093) W m −2, respectively, each of which is stronger than those for all sky. However, the non-spherical effect of dust on their IRFs for clear sky is similar to those for all sky. When atmosphere and land temperatures are adjusted to reflect the radiative effect of spherical and non-spherical dust, the simulated global annual mean column burdens of both dusts respond differently and become 50.6 mg m −2 and 45.8 mg m −2 for spherical and non-spherical dust, respectively. Compared to spherical dust aerosols, the simulated column burdens of non-spherical dust aerosols in West Asia, south of the Sahara Desert, and the west coast of Africa are decreased; whereas column burdens are increased in north of the Sahara Desert, over the middle of North America, and over northern China. Non-spherical dust leads to a 5~20% increase in simulated dust optical depth at 550 nm over areas north of the Sahara Desert and northern China, but up to 30% decrease in south of the Sahara Desert and over West Asia, changing the corresponding shortwave and longwave AFs of dust at the TOA. The greatest change in dust AF at the TOA for all sky also occurs over the Sahara Desert, where shortwave forcing increases as much as 3 W m−2. The global annual means of shortwave (longwave) AF of spherical and non-spherical dust at the TOA for

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all sky are −0.55 (0.052) W m−2 and −0.48 (0.049) W m−2, respectively. The absolute values of non-spherical dust AF are about 13% and 6% less than spherical dust AF for shortwave and longwave radiation, respectively. Similar to the IRF, the absolute changes of AF due to non-spherical effect of dust for clear sky are more extensive and stronger than those for all sky, especially in northern Africa and Arabia. The global annual means of shortwave (longwave) AF of spherical and non-spherical dust at the TOA for clear sky are − 1.07 (0.066) W m − 2 and − 0.95 (0.062) W m − 2, respectively. It is found in this work that non-spherical effect of dust on their AFs become larger with relative difference of 11.2% and 6.0% reduction for shortwave and longwave, respectively, almost the same as the results of all sky case. The effects of non-spherical dust on both IRF and AF that we find here are far less than the uncertainties that exist in dust emission source data. It should be noted that the two-stream approximation scheme is applied in current modeling. Most of studies indicate that non-spherical effect of dust has a significant impact on the phase function, but the two-stream approximation only requires the asymmetry factor which is the first moment of the Legendre expansion of the phase function. This may impact on the non-spherical effect of dust to some extent. Therefore, the non-spherical effect of dust may be considered in the higher stream radiative transfer scheme in future climate models. Acknowledgements This work was financially supported by National Basic Research Program of China (2012CB955303 and 2011CB403405), CAMS Basis Research Project (2012Y003) and the Public Meteorology Special Foundation of MOST (Grant No. GYHY200906020). References Barnaba, F., De Tomasi, F., Gobbi, G.P., Perrone, M.R., Tafuro, A., 2004. Extinction versus backscatter relationships for lidar applications at 351 nm: maritime and desert aerosol simulations and comparison with observations. Atmos. Res. 70, 229–259. Baum, B.A., Heymsfield, A.J., Yang, P., Bedka, S.T., 2005. Bulk scattering properties for the remote sensing of ice clouds. Part I: microphysical data and models. J. Appl. Meteorol. 44, 1885–1895. Briegleb, B.P., 1992. Delta-Eddington approximation for solar radiation in the NCAR Community Climate Model. J. Geophys. Res. 97, 7603–7612. Carrió, G.G., van den Heever, S.C., Cotton, W.R., 2007. Impacts of nucleating aerosol on anvil-cirrus clouds: a modeling study. Atmos. Res. 84, 111–131. Chatenet, B., Marticorena, B., Gomes, L., Bergametti, G., 1996. Assessing the size distribution of desert soils erodible by wind. Sedimentology 43, 901–911. Che, H., et al., 2009. Instrument calibration and aerosol optical depth validation of the China Aerosol Remote Sensing Network. J. Geophys. Res. 114, D03206. http://dx.doi.org/10.1029/2008JD011030. Claquin, T., Schultz, M., Balkanski, Y., 1999. Modeling the mineralogy of atmospheric dust sources. J. Geophys. Res. 104, 22243–22256. Collins, W.D., 2001. Parameterization of generalized cloud overlap for radiative calculations in general circulation models. J. Atmos. Sci. 58, 3224–3242. D'Almeida, G.A., Koepke, P., Shettle, E.P., 1991. Atmospheric aerosols: global climatology and radiative characteristics. A. Deepak Publishing, Virginia, p. 561. Dentener, F., Kinne, S., Bond, T., Boucher, O., Cofala, J., Generoso, S., Ginoux, P., Gong, S., Hoelzemann, J.J., Ito, A., Marelli, L., Penner, J.E., Putaud, J.P., Textor, C., Schulz, M., van der Werf, G.R., Wilson, J., 2006. Emissions of primary aerosol and precursor gases in the years 2000 and 1750 prescribed data-sets for AeroCom. Atmos. Chem. Phys. 6, 4321–4344.

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Zhang, H., Wang, Z.L., Wang, Z.Z., Liu, Q., Gong, S., Zhang, X., Shen, Z., Lu, P., Wei, X., Che, H., Li, L., 2012a. Simulation of direct radiative forcing of aerosols and their effects on East Asian climate using an interactive AGCM-aerosol coupled system. Clim. Dyn. 38, 1675–1693. Zhang, H., Shen, Z., Wei, X., Zhang, M., Li, Z., 2012b. Comparison of optical properties of nitrate and sulfate aerosol and the direct radiative forcing due to nitrate in China. Atmos. Res. 113, 113–125. Zhao, T.X.-P., Laszlo, I., Dubovik, O., Holben, B.N., Sapper, J., Tanre, D., Pietras, C., 2003. A study of the effect of nonspherical dust particles on the AVHRR aerosol optical thickness retrievals. Geophys. Res. Lett. 30 (6), 1317. http://dx.doi.org/10.1029/2002GL016379. Dr. Zhili Wang is an assistant researcher at Chinese Academy of Meteorological Sciences. His main research interests are aerosol direct and indirect radiative forcings and their effect on climate; and development of physical process in aerosol-cloud interaction in GCM. Education Ph. D., 2011, Chinese Academy of Meteorological Sciences, China M. Sc., 2008, College of Atmospheric Science, Nanjing University of Information Science and Technology, China B. Sc., 2005, College of Atmospheric Science, Nanjing University of Information Science and Technology, China Dr. Hua Zhang is a professor at Laboratory for Climate Studies, National Climate Center, China Meteorological Administration. Her research interests are development and improvement of radiation scheme in GCM; cloud overlapping treatment in GCM; and GHGs and aerosol radiative forcings and their effects on climate. Education Ph. D., 1999, Institute of Atmospheric Physics, Chinese Academy of Sciences, China M. Sc., 1989, Department of Atmospheric physics, Nanjing Institute of Meteorology, China B. Sc., 1986, Department of Atmospheric physics, Nanjing Institute of Meteorology, China Xianwen Jing is an engineer at National Climate Center, China Meteorological Administration. His research topic is cloud and radiation processes in GCM. Education Ph. D., 2012, Chinese Academy of Meteorological Science, China M. Sc., 2009, College of Atmospheric Science, Nanjing University of information Science and Technology, China B. Sc., 2006, College of Applied Meteorology, Nanjing University of Information Science and Technology, China Xiaodong Wei took the master degree from Chinese Academy of Meteorological Sciences in 2011. His M. Sc. study is aerosol optical properties. Education M. Sc., 2011, Chinese Academy of Meteorological Sciences, China B. Sc., 2008, College of Atmospheric Physics, Nanjing University of Information Science and Technology, China