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Monthly and seasonal variations of aerosol optical properties and direct radiative forcing over Zanjan, Iran
Accepted Manuscript Monthly and seasonal variations of aerosol optical properties and direct radiative forcing over Zanjan, Iran Maryam Gharibzadeh, Khan Alam, Yousefali Abedini, Abbasali Aliakbari Bidokhti, Amir Masoumi PII:
S1364-6826(17)30425-X
DOI:
10.1016/j.jastp.2017.09.006
Reference:
ATP 4689
To appear in:
Journal of Atmospheric and Solar-Terrestrial Physics
Received Date: 26 July 2017 Revised Date:
6 September 2017
Accepted Date: 7 September 2017
Please cite this article as: Gharibzadeh, M., Alam, K., Abedini, Y., Bidokhti, A.A., Masoumi, A., Monthly and seasonal variations of aerosol optical properties and direct radiative forcing over Zanjan, Iran, Journal of Atmospheric and Solar-Terrestrial Physics (2017), doi: 10.1016/j.jastp.2017.09.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Monthly and seasonal variations of aerosol optical properties and direct radiative forcing over Zanjan, Iran
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Maryam Gharibzadeh1, Khan Alam2*, Yousefali Abedini1, 3, 4, Abbasali Aliakbari Bidokhti5, and Amir Masoumi1 1
Department of Physics, Faculty of Sciences, University of Zanjan, Zanjan, Iran Department of Physics, University of Peshawar, Peshawar, Khyber Pakhtunkhwa, Pakistan 3 Environmental Science Department, University of Zanjan, Zanjan, Iran 4 Center for Research in Climate and Global Warming, IASBS, Zanjan, Iran 5 Institute of Geophysics, University of Tehran, Tehran, Iran 2
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*Corresponding author:
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[email protected]
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Abstract Aerosol optical properties and radiative forcing over Zanjan in northwest of Iran has been
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analyzed during 2010-2013. The aerosol optical and radiative properties are less studied over
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Zanjan, and therefore, require a careful and in depth analysis. The optical properties like
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Aerosol Optical Depth (AOD), Ångström Exponent (AE), ASYmmetry parameter (ASY),
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Single Scattering Albedo (SSA), and Aerosol Volume Size Distribution (AVSD) have been
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evaluated using the ground-based AErosol RObotic NETwork (AERONET) data. Higher
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AOD while relatively lower AE were observed in the spring and summer, which showed the
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presence of coarse mode particles in these seasons. An obvious increase of coarse mode
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particles in AVSD distribution, as well as a higher value of SSA represented considerable
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addition of coarse mode particles like dust into the atmosphere of Zanjan in these two
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seasons. Increase in AE, while a decrease in AOD was detected in the winter and fall. The
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presence of fine particles indicates the dominance of particles like urban-industrial aerosols
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from local sources especially in the winter. The Santa Barbara DISORT Atmospheric
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Radiative Transfer (SBDART) model was utilized to calculate the Aerosol Radiative Forcing
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(ARF) at the Top of the Atmosphere (TOA), earth's surface and within the atmosphere. The
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annual averaged ARF values were -13.47 Wm-2 and -36.1 Wm-2 at the TOA and earth's
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surface, respectively, which indicate a significant cooling effect. Likewise, the ARF
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efficiencies at the TOA and earth's surface were -65.08 Wm-2 and -158.43 Wm-2,
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respectively. The annual mean atmospheric ARF and heating rate within the atmosphere
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were 22.63 Wm-2 and 0.27 Kday-1 respectively, represented the warming effect within the
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atmosphere. Finally, a good agreement was found between AERONET retrieved ARF and
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SBDART simulated ARF.
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Keywords: AOD; Ǻngström Exponent; Single Scattering Albedo; SBDART; ARF
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1. Introduction
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Aerosols are one of the major components of the atmosphere which can affect the radiation
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equilibrium and the energy balance of the earth's atmospheric system (Hansen et al., 1997).
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Aerosols can change the radiative processes and climate, directly by scattering and absorbing the
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solar radiation (McCormick and Ludwig, 1967; Miller and Tegen, 1998). While, indirectly by
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changing the micro-physics of clouds and modifying the precipitation (Gunn and Phillips, 1957;
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Liou and Ou, 1989; Kumar et al., 2011). The influence of aerosols on structure of atmospheric
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temperature, cloud droplets evaporation, liquid water path and cloud cover is a semi direct effect
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(Hansen et al., 1997; Koren et al., 2004). Aerosols can cause many problems and much influence
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on global climate change. However, they are one of the major source of uncertainties in climate
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models (Hansen et al., 1997; Liou, 2002). The lack of detailed studies in regional and global
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scale, as well as the extended spatio-temporal distribution of aerosols leads to large uncertainties.
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Aerosols are generated from a variety of natural and anthropogenic sources. They can be
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classified according to their size, physical and chemical structures.
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The effect of aerosols by absorbing and scattering of radiations are considered as direct Aerosol
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Radiative Forcing (ARF). The analysis of the aerosol optical properties can significantly help in
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understanding the radiative processes and energy budget calculations. Many factors determine
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the sign and magnitude of the ARF including the nature, size, source and distribution of the
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aerosols as well as the surface albedo (Feng and Christopher, 2013; Bhaskar et al., 2015).
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During the last two decades the number and severity of dust storms has increased significantly in
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the West Asia. These storms deteriorated air quality and created climatic and health related
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issues in Iran. In order to carry out detailed analysis on climatic impacts of aerosol, it is crucial to
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analyze aerosol optical and radiative properties over the region. To inquire optical properties of
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aerosols over Iran, limited studies have been conducted by means of remote sensing techniques
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(Bayat et al., 2013; Masoumi et al., 2013; Khoshsima et al., 2014). These studies focused only on
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aerosol optical properties for a limited time period, however, to the best of authors knowledge,
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no study has yet been conducted to focus on aerosol radiative impacts over long time period. The
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analysis of aerosol optical properties and radiative impacts was merely reported during dust
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events over Zanjan by Gharibzadeh et al. (2017). In order to better understand the climatic
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impacts of aerosol over Zanjan, relatively long-term data (2010-2013) has been used. Zanjan is
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the least study location in terms of aerosol readiative properties, therefore, this study has the
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potential to fill scientific and geographic gap of our present knowledge about aerosol optical and
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radiative properties over the region.
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In the present study, monthly ARF has been calculated for a period of four years (2010-2013)
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over Zanjan, Iran. First, the optical properties such as Aerosol Optical Depth (AOD), Ångström
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Exponent (AE), ASYmmetry parameter (ASY), Single Scattering Albedo (SSA) and Aerosol
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Volume Size Distribution (AVSD) were analyzed using AErosol RObotic NETwork
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(AERONET) data. The Santa Barbara Discrete-ordinate Atmospheric Radiative Transfer
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(SBDART) model was utilized to simulate the solar irradiance values at the Top Of the
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Atmosphere (TOA), at the earth’s surface, and within the atmosphere (Ricchiazzi et al., 1998).
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AERONET retrieved parameters (AOD, SSA, ASY) and surface albedo data from Ozone
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Monitoring Instrument (OMI) were used as inputs to SBDART model. The surface albedo values
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were obtained from Aura OMI through the Giovanni online data system. Finally, SBDART
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simulated ARF values were compared with that of AERONET retrieved ARF obtained directly
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from inversion product. Furthermore, ARF efficiency and atmospheric heating rate were also
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calculated.
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Data and methodology
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1.1. Site description
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Iran is located approximately in the middle of a dust belt, the semi-arid to arid area which is
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spread from North Africa to China. Dust storms in the Middle East are active round all the year,
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especially in the spring and summer. When dust storms occur, they cover many parts of Iran,
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particularly the southwest, west and central regions. Zanjan is located in the northwest of Iran
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(36.70° N, 48.50° E, and 1800 m above sea surface). Zagros Mountains separate the city from
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Mesopotamian low-altitude area. Dust aerosols in this region often are derived from some
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important sources like Tigris and Euphrates basins in Iraq, the Arabian Peninsula and west Syria
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during dry months from May to July. Anthropogenic aerosols are also present in the atmosphere
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(Bayat et al., 2013; Masoumi et al., 2013).
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The meteorological situation over Zanjan was analyzed as shown in Fig 1. The daily mean
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temperature and precipitation have been provided by Iran Meteorological Organization from the
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earth’s surface (1805 m above sea level) during 2010-2014 (see Fig.1a). The mean temperature
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ranges from -4 °C to 24 °C with maximum in the summer and minimum in the winter. The mean
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precipitation during spring, winter, fall and summer were 50.7, 28.9, 20.8, and 10.2 mm,
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respectively. To understand the role of the surface wind at 850 mb, wind flow patterns were
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obtained from NCEP/NCAR reanalysis (http://www.cdc.noaa.gov) over west of Iran (see Fig.
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1b) for each year in the study period. The arrows show wind directions and the colours represent
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the wind speeds. As it can be seen, strong winds are almost from the west and southwest. To
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understand what pathway the air mass have been transported from their sources to Zanjan, back-
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trajectory analyses based on the NOAA HYSPLIT model were performed for the selected dusty
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days in each of the four years. The results revealed that the air masses arriving from North
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Africa, Saudi Arabia and Iraq significantly contribute in high aerosol loading over Zanjan
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(Khoshsima et al., 2014).
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1.2. AERONET
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The AERONET is a ground-based remote sensing network of sun photometers which provides
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an aerosol and radiative properties database. The only sunphotometer in Iran is the CIMEL
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Sunphotometer of Zanjan, which takes measurements of the direct sun and diffuses sky
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radiances. AOD data are available for three quality levels: Level 1.0 (unscreened), Level 1.5
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(cloud-screened) and Level 2.0 (cloud screened and quality-assured). The present study utilized
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the Level 2.0 data during the period (2010-2013) to analyze the climatic impacts of aerosol. The
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AERONET automatic filtering algorithm described by Smirnov et al. (2000) filters out a lot of
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AOD values due to very rapid change of aerosol load. Since the majority of the high AOD values
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were considered as ''clouds'' by the Level 2.0 filtering algorithm, when in reality there were
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irregular high dust concentrations. Therefore, it will be vital to use Level 1.0 parallel to Level 2.0
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data for dust or high AOD values, because the dust events may have been screened out of the
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cloud-screened data (Tripathi et al., 2005; Mahler et al., 2006).
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The uncertainty in retrieval under cloud-free conditions for AOD is less than ±0.01 for the
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wavelengths greater than 0.44 nm and for shorter wavelengths it is less than ±0.02. Moreover,
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the uncertainty for the retrieval of sky radiance measurements is less than ±0.05 (Dubovik et al.,
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2000). There are data gaps in this study because data are not available on AERONET site due to
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process of calibration of sunphotometer.
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1.3. SBDART
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SBDART model is a FORTRAN computer code. This model calculates the plane-parallel
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radiative transfer at earth's surface and top of the atmosphere. This software is used in a wide
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variety of studies related to radiative transfer problems. To solve the plane-parallel radiative
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transfer equations, a numerically stable algorithm was used. At most, five different aerosol layers
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with particular radiative characteristics can be recognized. This code is a complex set of
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DISORT (Discrete Ordinate Radiative Transfer), Mie scattering code and atmospheric
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transmission models (Ricchiazzi et al., 1998).
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The daily net fluxes at the earth's surface and TOA were calculated for short wavelengths (0.3–
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4.0 µm) using the SBDART model. Then monthly average of ARF was determined from daily
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averaged values during the study period. The mid-latitude winter atmospheric model was used.
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To improve the accuracy of the estimated ARF, mean values for columnar water vapor were
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utilized. To calculate the radiative forcing in the clear sky conditions, the AERONET data such
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as AOD, SSA, and ASY were used as input in the SBDART model. The surface albedo values
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were obtained from Aura OMI version 3 aerosols level 2 data through the Giovanni online data
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system, developed and maintained by the NASA Goddard Earth Sciences (GES) Data and
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Information Services Centre (DISC), retrieved from https://giovanni.sci.gsfc.nasa.gov/giovanni.
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For other inputs like solar zenith angle, a code was used which is available in SBDART model
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by specifying the values of latitude, longitude, time and date.
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2. Results and discussion
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2.1. Variation in aerosol optical properties
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2.1.1. Aerosol optical depth and Ångström exponent
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AOD represents the amount of solar radiations absorbed or scattered by aerosols. It is a measure
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of the total column extinction of transmitted radiations due to atmospheric aerosols. The amount
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of radiation that reaches the earth's surface, determines the measured voltage by sunphotometer.
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The total optical depth can be calculated using Eq. (1): Vλ = V λd e
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(1)
where V is digital voltage at λ, V0 is extraterrestrial voltage, d is the ratio of the average to the
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actual earth-sun distance, τTot is the total optical depth and m is the optical air mass (Holben et
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al., 1998).
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Wavelength dependence of the AOD determines AE which is a good indicator of aerosol particle
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size which is demonstrated by the Ångström relationship (Ångström, 1964) given as:
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τ λ = βλ
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(2)
where τ λ is AOD at wavelength λ, β is the turbidity coefficient indicating aerosol loading in
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the atmosphere and α is AE.
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There are occasionally dust aerosols in the atmosphere of Zanjan during spring and summer, it is
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due to dryness of soil and high activity of dust sources, therefore, dust particles are more
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dominant in the atmosphere (Bayat et al., 2013; Masoumi et al., 2013; Gharibzadeh et al., 2017).
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Monthly variation of AOD at 500 nm, AE at 440–870 nm and water vapour over Zanjan during
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2010-2013 are shown in Fig. 2. The monthly averaged AOD ranged between 0.051 and 0.57 with
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the lowest in December 2014 and the highest in June 2011 with a mean value of 0.21. The
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monthly variations of AE were in the range from 0.3 to 1.74 with an average value of 0.9.
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Correspondingly, the monthly averaged values of water vapour varied between 0.30-1.37 cm
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having maximum values in August 2011 and minimum in January 2012.
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The behaviour of AOD in response to changes in water vapour revealed that AOD and water
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vapour showed positive correlation of 0.15, 0.05 and 0.56 in the spring, summer and fall,
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respectively, and a negative correlation of -0.21 in the winter. The seasonal averaged AOD, AE
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and water vapour along with their standard deviations are listed in the Table 1. The higher AOD
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in the spring months (March–May) and summer months (June–August) and relatively lower
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AOD in the winter months (December–February) and fall months (September–November) were
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observed. The high AOD values in the spring and summer were due to dust aerosols, which
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originated from external sources like Tigris-Euphrates basin and Arabian Peninsula as well as
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local dust sources such as dried seasonal lakes or rivers during dry months (Bayat et al., 2013;
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Masoumi et al., 2013, Gharibzadeh et al., 2017). During summer high temperature plays an
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important role in heating and lifting lose materials from the ground due to high wind speed, and
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therefore, higher AOD values were observed (Alam et al., 2011). Moreover, the values of water
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vapour were observed to be higher during summer months when the dust particles were
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dominant. During spring and summer water soluble aerosols grow hygroscopically in the
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presence of water vapour, consequently contribute to high AOD values (Alam et al., 2011; Alam
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et al., 2012). The variation of AE was relatively different than that of AOD. The increase in AE
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values were observed in the winter and fall while decreases were found in the summer and
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spring. Low values of AE represent the dominance of coarse mode particles, which were
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indicatives of dust storms in these seasons. AE was high in the fall and winter because of local
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anthropogenic activities such as increase of fossil fuels consumption and the dominance of
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urban/industrial aerosols that were fine mode particles (Singh et al., 2005; Alam et al., 2011).
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Recently, Patel and Kumar (2016) reported the abundance of fine and coarse mode particles,
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which were associated with high AE and low AE, respectively over Dehradun.
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Similarly, Khoshsima et al., (2014) reported high AOD in late spring and early summer with a
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maximum in the month of June over Zanjan, representing the impact of dust storms and regional
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climate. Che et al., (2013) found the same seasonal trend of AOD and AE over Taklimakan
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Desert. They found that low AOD in the fall and winter and high AOD in the summer and
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spring. These findings about the inverse relationship between AOD and AE for dust events are
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similar to the results reported earlier (Kumar et al., 2013; Srivastava et al., 2014). However, the
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high values of AE indicate the dominance of fine particles, when dust particle are not prominent
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in the atmosphere (Alam et al., 2011; Srivastava et al., 2014). Recently, Bibi et al. (2016) found
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the high AOD and low AE for coarse mode particles and high AOD and high AE for the fine
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mode aerosol.
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2.1.2. Asymmetry parameter and Single scattering albedo
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ASY represents a preferred direction in scattering and is one of the important components in
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determining the radiative forcing calculations. ASY is calculated by Eq. (3):
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ASYλ = cos θ Pλ, θ sin θ dθ
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where θ is the angle between the incident and scattered radiation and P (λ,θ) is the phase function
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(angular distribution of scattered light) (Muneer, 2007). ASY is 1 if the scattering is completely
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in the forward direction and is -1 for completely backward scattering.
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Fig. 3 shows the spectral variation of ASY over Zanjan during the study period. In all seasons,
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ASY depicted high values at a wavelength of 440 nm. The ASY values were decreasing with
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increasing wavelengths from 440 to 870 nm (the visible range). The increase in infrared region
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(from 870 to 1020 nm) in summer is due to the dominance of the coarse mode dust aerosols.
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Similar to the results reported by Srivastava et al. (2011), Adesina et al. (2014), and Bibi et al.
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(2016). In the winter ASY decreased with increasing wavelengths. The lowest value of ASY
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occurred at 1020 nm in winter is due to the dominance of anthropogenic aerosol. The decline
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trend was not so prominent in the wavelength range from 870 to1020 nm during the spring and
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fall. Similar results were reported by Bi et al. (2011), Alam et al. (2012) and Adesina et al.
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(2015).
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The ratio of scattering efficiency to total extinction efficiency is called SSA (Steinfeld, 1998).
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SSA is a good indicator showing the type of aerosols, which is 1 and 0 for the totally scattering
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and absorbing types of aerosol, respectively. Spectral variation of the seasonal averaged SSA is
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shown in Fig. 4. The SSA was observed to be strongly wavelength dependent during all seasons
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except during fall. Increase in SSA with increasing wavelength, represented the dominance of
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dust particles with larger size during summer. Similar increasing trend in SSA with increasing
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wavelength was observed to be common during dust episodes as documented by previous
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researchers Eck et al. (2010), Alam et al. (2014) and Yu et al. (2016). But in the winter, the
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decrease in SSA with increasing wavelength was noted due to major contribution of fine
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particles. Zheng et al. (2008) and Bi et al. (2011) also reported the similar spectral dependency
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(decrease in SSA with increasing wavelength) over China. Whereas slightly increase in SSA
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with increasing wavelength between 440 and 675 nm and then smooth decrease till 1020 nm was
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found during spring, which show the possibility of mixed aerosol (Dust and anthropogenic
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aerosols) (Alam et al., 2011; Alam et al., 2012). Recently, Bibi et al. (2016) pointed out that
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SSA sharply increases from 440 to 675 nm and decreases from 675 to 1020 nm. In the fall, the
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SSA value was higher as compared to other seasons showing the presence of dust particles with
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minor contribution of fine particles. Similarly, Bibi et al. (2016) noticed the less spectral
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dependency of SSA during fall season over IGP, but with lower SSA values than the results
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reported in this study.
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2.1.3. Aerosol volume size distribution
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Aerosol distributions are classified in two categories: the fine particles smaller than 0.6 µm and
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the coarse mode particles larger than 0.6 µm (Dubovik et al., 2002) AVSD can be shown as
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follows:
$'(&
=
* ∑/0 +,, -#.
,
exp 3−
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5'(& '(&+,, 6 .7,
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where, σ/ is the standard deviation, r%,/ is the volume median radius and c%,/ is the volume
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concentration for fine and coarse modes (Che et al., 2013). Fig. 5 shows the seasonal averaged
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of AERONET retrieved AVSD for Zanjan during 2010-2013. Both fine and coarse modes are
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seen in the Fig. 5, but significant variations can be found in the coarse mode. The peak values of
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AVSD for fine and coarse mode were observed about radii of 0.11 and 2.24 µm, respectively,
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during all the seasons. The higher amounts of AVSD in the coarse mode in the spring and
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summer could be due to the presence of dust particles (Alam et al., 2012; Adesina et al., 2014;
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Srivastava et al., 2014).
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During winter and fall coarse mode aerosol are also dominant over fine mode due to re-
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suspended road dust. The results are similar to other earlier results (Alam et al., 2012; Adesina et
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al., 2014; Srivastava et al., 2014). The values for coarse mode volume concentrations were
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0.108, 0.149, 0.077 and 0.037 in the spring, summer, fall and winter, respectively. The values of
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0.016, 0.023, 0.015 and 0.011 were obtained for fine mode volume concentrations in spring,
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summer, fall and winter, respectively. The ratio of coarse to fine mode volume concentrations
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increased in the summer and spring and decreased in the fall and winter. As a result of dust
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particles transferred from Mesopotamian sources to Zanjan especially in late spring and summer.
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2.2. Aerosol radiative forcing and atmospheric heating rate
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Further knowledge and extensive research about radiations and their interaction with aerosol and
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cloud are the most important requirements in climate studies. The difference between the net
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solar flux (down minus up) with and without aerosols, either at the TOA or the earth’s surface
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(Jacob, 1999):
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∆F = F↓ − F↑ − F↓ − F↑
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(5)
where ∆F denotes the irradiance (downwelling or upwelling, Wm-2), and (F↓-F↑) denotes the net
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irradiance (downwelling minus upwelling) computed with aerosol (Fa) and without aerosol (Fo)
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at either the TOA or at the earth’s surface (Alam et al., 2012). The ARF at the TOA, surface,
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within the atmosphere from SBDART calculations and atmospheric heating rate during the study
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period of 2010-2013 are shown in Fig. 6.
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In addition to the optical parameters such as AOD, SSA and ASY, few other parameters like
302
surface albedo and meteorological conditions are also used as input in SBDART model for
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calculation of ARF. The calculated values of ARF at the TOA were between -28.45 Wm-2 (in
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April 2011) and 5.7 Wm-2 (in May 2010) having an average annual value of -13.47 Wm-2 for the
305
whole study period. The surface ARF varied between -7.92 Wm-2 in December 2013 and -91.67
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Wm-2 in June 2011 with an average annual of -36.1 Wm-2. Table 2 shows the seasonal averaged
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ARF values at the TOA, surface and within the atmosphere.
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The difference between ARF at the surface and at the TOA indicates the ARF within the
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atmosphere. Positive atmospheric ARF demonstrates heating of the atmosphere which causes a
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reduction in solar radiation flux reaching the earth’s surface. This effect can influence cloud
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formation, precipitation, and hydrological cycle (Ramachandran and Kedia, 2012). The
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atmospheric heating rate calculated by Liou (2002) is given in Eq. (7): ∆=
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=−
? ∆B
@A ∆C
(6)
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where g denotes gravitational acceleration (ms-2), Cp denotes the specific heat of air (JK-1kg-1),
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∆F is the atmospheric irradiance and P denotes the pressure (Pa). Fig. 6 also shows the monthly
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atmospheric heating rate and ARF within the atmosphere during 2010-2013. The variation of
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atmospheric heating rate over Zanjan ranged from 0.01 Kday-1 in December 2013 to 0.87 Kday-1
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in June 2011 with the annual mean of 0.27 Kday-1. Atmospheric ARF values were between 0.91
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Wm-2 in December 2013 and 72.47 Wm-2 in June 2011. The mean value was 22.63 Wm-2 , which
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reveals a warming effect within the atmosphere. Some earlier studies reported higher values than
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our results in different locations (Alam et al., 2012; Adesina et al., 2014; Srivastava et al., 2015),
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while, other reported lower values (Ramachandran and Kedia, 2012).
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The high values of atmospheric heating rate and atmospheric ARF in the spring and summer
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seasons demonstrate net atmospheric absorption due to aerosols. This happened because of the
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higher aerosol concentration and varying characteristics of aerosols (Kumar and Devara, 2012),
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and also due to presence of an elevated aerosol layer during spring and summer seasons (Kumar
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and Devara, 2012). This layer was a result of transferring dust particles from Mesopotamian
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sources to Zanjan.
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For an accurate comparison, it is better to calculate ARF efficiency (∆FDEE .), ∆FDEE is the rate at
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which the atmosphere is forced per unit of AOD at 0.55 µm at either the TOA or the earth’s
331
surface as follows (Seinfeld and Pandis, 2006): ∆FDEE = ∆F/AOD
332
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(7)
The ARF efficiency at the TOA and earth’s surface is shown in Fig. 7. The annual averaged
334
values of ARF efficiency at the TOA and surface were -65.08 Wm-2 and -158.43 Wm-2,
335
respectively. At the TOA an opposing behaviour was recognized. More absorption of aerosols
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showed lower ARF efficiency averages. This is a result of the higher absorption of these aerosols
337
that decreased the backscattered energy towards the TOA and into the space (Garcia et al., 2012).
338
Many researchers have discussed the ARF, atmospheric heating rate and ARF efficiency. Table 3
339
shows comparison of ARF values at the TOA, earth's surface and within the atmosphere, and
340
also ARF efficiency and atmospheric heating rate for different locations worldwide.
341
Finally, the relationship between ARF directly retrieved from AERONET and simulated by
342
SBDART was shown in Fig. 8. The correlation coefficient was greater than 0.98, which indicates
343
the accuracy of the SBDART model in the present work. Alam et al. (2012) found the
344
AERONET-SBDART correlation coefficients to be 0.99 for Lahore, and 0.98 for Karachi.
345
Adesina et al. (2015) reported the correlation coefficient for AERONET vs. SBDART at the
346
surface and TOA and were 0.95 and 0.97 respectively over Gorongosa. Adesina et al. (2014)
347
obtained the correlation between SBDART and AERONET and found correlation coefficient of
348
0.84 at TOA, and 0.94 at the surface, while 0.88 within the atmosphere over Pretoria. In addition,
349
Kumar and Devara (2012), Ramachandran and Kedia (2012) and Li et al. (2010) obtained a good
350
correlation among the ARF retrieved from AERONET and simulated by SBDART.
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3. Conclusion
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Aerosols are important components in the climate studies, and a major source of uncertainty in
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climate models. Aerosols can directly affect climate through scattering or absorbing solar
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radiation, therefore, exert a negative or positive radiative forcing at TOA, earth's surface and
355
within the atmosphere. A comprehensive study of aerosol optical and radiative properties was
356
accomplished over Zanjan for the period from 2010 to 2013. The aerosol optical properties like
357
AOD, AE, ASY, SSA, and AVSD have been evaluated using AERONET data. The silent
358
conclusion can be summarized as follow:
359
1. Temporal variation of AOD and AE were investigated. The high AOD values and low AE
360
values during spring and summer seasons revealed that coarse mode particles such as dust are
361
dominant. Likewise, high AE values and low AOD values in the fall and winter represent the
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dominance of anthropogenic fine mode particles.
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2. Spectral variations of the ASY over Zanjan show that a decrease of ASY in the visible
364
spectrum is due to the dominance of anthropogenic absorbing aerosol. Also the slight
365
increase in the infrared region is as a result of the dominance of the coarse mode particles.
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3. During spring and summer, SSA increases with increasing wavelength, because of the
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dominance of coarse dust particles. However, during winter SSA values were found to be
368
lower due to the presence of absorbing aerosols.
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4. The ARF at the TOA and surface ranged between -28.45 and 5.7 Wm-2 and -7.92 and -91.67
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Wm-2 respectively, with corresponding annual averaged values of -13.47 Wm-2 and -36.1
371
Wm-2. The relationship between SBDART simulated ARF and AERONET retrieved ARF
372
revealed a strong positive correlation of 0.98, which indicates the accuracy of the SBDART
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model in the present study.
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5. The atmospheric ARF and heating rate were ranged from 0.91 to 72.47 Wm-2 and 0.01 to
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0.87 Kday-1 respectively, which showed the significant heating of the atmosphere over the
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studied region.
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Acknowledgments. The authors wish to thank NASA and Institute for Advanced Studies in
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Basic Sciences in Zanjan for providing AERONET data. To obtain the surface albedo values, the
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Giovanni online data system, developed by the NASA GES DISC was utilized. We appreciate
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the Iran Meteorological Organization for providing meteorological data. NCEP/NCAR would be
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thankful for providing reanalysis data.
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ACCEPTED MANUSCRIPT Table 1. Seasonally averaged values and their standard deviations of AOD at 500 nm, water vapour AE at 440–870 nm for the period 2010–2014 over Zanjan.
AOD 0.26± 0.08 0.29±0.05 0.16±0.02 0.14 ±0.04
AE 0.71±0.16 0.75±0.11 1.00±0.17 1.17± 0.10
Water vapour cm 0.660 1.206 0.818 0.399
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Season Spring Summer Fall Winter
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TOA (Wm-2) -11.57 -16.73 -14.01 -10.67
Surface (Wm-2) -44.02 -48.05 -26.37 -23
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Spring Summer Fall Winter
Atmosphere (Wm-2) 32.46 31.32 12.37 12.32
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Study period
TOA ARF efficiency Wm-2
Surface ARF efficiency Wm-2
TOA ARF Wm-2
Atmosphere ARF Wm-2
Srivastava et al., 2011
Ahmedabad
2008
-67 to -89
-
-
-
Karachi
August 2006 - July 2007
-
-
-7 to 35
+41 to +61
2010-2011
-
-
-50.1 to -74.7 -48.4 to -68.4
Alam et al.,2011
-16 to -31 -14 to -21
Alam et al.,2012
Lahore Karachi
Ramachandran and Kedi, 2012
Kanpur Gandhi College
2006–2008
-8.2 to -16.9 -12.7 to -15.7
Adesina et al., 2014
Pretoria
2012
-76.5
-210.7
Srivastava et al.,2015
Manora Peak
-
-
Panicker et al. 2010
Pune
Oct 2004– May 2005
-
-
−0.5 to +0.6
Present study
Zanjan
2010-2013
16.2 to -164.6
-85.7 to
-28.45 to 5.7
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Heating rate Kday-1
-56 to 96
+51 to +82 +33 to +51
-70 to 112 -52 to 73
+24.5 to+31.8 +24 to +34.1
-50.1 to 137.5 -65.6 to 152.9
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-14.6 to -45.7 -20.1 to -40.5
Surface ARF Wm-2 -15 to 45
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1.8 to 2.3 1.1 to 1.2 ≥0.4 >0.6
+8 to +29
-15.6 to -38.6
0.2 to 0.8
+3 to +65
-50 to 3
0.1 to 1.8
+33 to +48
−33 to −47
-
+0.91 to +72.47
-7.9 to -91.67
0.01 to 0.87
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Fig. 1. Variation in (a) daily mean temperature and precipitation, (b(i-iv)) Mean synoptic wind vector at a pressure level of 850 mb over west of Iran during 2010-2014. The location of Zanjan is marked by a black circle.
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Fig. 2. Monthly averaged variations of AOD at 500 nm, AE at 440–870 nm and water vapour over Zanjan during 2010-2014.
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Fig. 3. Spectral variation of seasonal averaged of ASY over Zanjan during 2010-2014.
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Fig. 4. Spectral variations of seasonal averaged of SSA over Zanjan during 2011-2014.
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Fig. 5. Seasonal averaged of AERONET retrieved AVSD for Zanjan during 2010-2014.
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Fig. 6. ARF at the TOA, earth’s surface, within the atmosphere from SBDART calculations, and atmospheric heating rate during 2011-2014, over Zanjan.
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Fig. 7. ARF efficiency at the TOA and earth’s surface during 2011-2014, over Zanjan.
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Fig. 8. Comparison of ARF obtained at the TOA, earth's surface and within the atmosphere, directly retrieved from AERONET and simulated by SBDART over Zanjan during 2011-2014.
ACCEPTED MANUSCRIPT Highlights Detailed analysis of aerosol optical properties have been analyzed in Zanjan, Iran.
•
Higher AOD & relatively lower AE values observed in spring & summer seasons.
•
Higher AE & lower AOD values observed in fall & winter seasons.
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The annual mean ARF & heating rate were 22.63 Wm-2 & 0.27 Kday-1, respectively.
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The correlation (R2) of the AERONET- SBDART ARF was greater than 0.97.
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S1364-6826(17)30425-X
DOI:
10.1016/j.jastp.2017.09.006
Reference:
ATP 4689
To appear in:
Journal of Atmospheric and Solar-Terrestrial Physics
Received Date: 26 July 2017 Revised Date:
6 September 2017
Accepted Date: 7 September 2017
Please cite this article as: Gharibzadeh, M., Alam, K., Abedini, Y., Bidokhti, A.A., Masoumi, A., Monthly and seasonal variations of aerosol optical properties and direct radiative forcing over Zanjan, Iran, Journal of Atmospheric and Solar-Terrestrial Physics (2017), doi: 10.1016/j.jastp.2017.09.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Monthly and seasonal variations of aerosol optical properties and direct radiative forcing over Zanjan, Iran
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Maryam Gharibzadeh1, Khan Alam2*, Yousefali Abedini1, 3, 4, Abbasali Aliakbari Bidokhti5, and Amir Masoumi1 1
Department of Physics, Faculty of Sciences, University of Zanjan, Zanjan, Iran Department of Physics, University of Peshawar, Peshawar, Khyber Pakhtunkhwa, Pakistan 3 Environmental Science Department, University of Zanjan, Zanjan, Iran 4 Center for Research in Climate and Global Warming, IASBS, Zanjan, Iran 5 Institute of Geophysics, University of Tehran, Tehran, Iran 2
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*Corresponding author:
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[email protected]
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Abstract Aerosol optical properties and radiative forcing over Zanjan in northwest of Iran has been
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analyzed during 2010-2013. The aerosol optical and radiative properties are less studied over
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Zanjan, and therefore, require a careful and in depth analysis. The optical properties like
47
Aerosol Optical Depth (AOD), Ångström Exponent (AE), ASYmmetry parameter (ASY),
48
Single Scattering Albedo (SSA), and Aerosol Volume Size Distribution (AVSD) have been
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evaluated using the ground-based AErosol RObotic NETwork (AERONET) data. Higher
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AOD while relatively lower AE were observed in the spring and summer, which showed the
51
presence of coarse mode particles in these seasons. An obvious increase of coarse mode
52
particles in AVSD distribution, as well as a higher value of SSA represented considerable
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addition of coarse mode particles like dust into the atmosphere of Zanjan in these two
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seasons. Increase in AE, while a decrease in AOD was detected in the winter and fall. The
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presence of fine particles indicates the dominance of particles like urban-industrial aerosols
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from local sources especially in the winter. The Santa Barbara DISORT Atmospheric
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Radiative Transfer (SBDART) model was utilized to calculate the Aerosol Radiative Forcing
58
(ARF) at the Top of the Atmosphere (TOA), earth's surface and within the atmosphere. The
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annual averaged ARF values were -13.47 Wm-2 and -36.1 Wm-2 at the TOA and earth's
60
surface, respectively, which indicate a significant cooling effect. Likewise, the ARF
61
efficiencies at the TOA and earth's surface were -65.08 Wm-2 and -158.43 Wm-2,
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respectively. The annual mean atmospheric ARF and heating rate within the atmosphere
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were 22.63 Wm-2 and 0.27 Kday-1 respectively, represented the warming effect within the
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atmosphere. Finally, a good agreement was found between AERONET retrieved ARF and
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SBDART simulated ARF.
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Keywords: AOD; Ǻngström Exponent; Single Scattering Albedo; SBDART; ARF
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1. Introduction
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Aerosols are one of the major components of the atmosphere which can affect the radiation
69
equilibrium and the energy balance of the earth's atmospheric system (Hansen et al., 1997).
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Aerosols can change the radiative processes and climate, directly by scattering and absorbing the
71
solar radiation (McCormick and Ludwig, 1967; Miller and Tegen, 1998). While, indirectly by
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changing the micro-physics of clouds and modifying the precipitation (Gunn and Phillips, 1957;
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Liou and Ou, 1989; Kumar et al., 2011). The influence of aerosols on structure of atmospheric
74
temperature, cloud droplets evaporation, liquid water path and cloud cover is a semi direct effect
75
(Hansen et al., 1997; Koren et al., 2004). Aerosols can cause many problems and much influence
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on global climate change. However, they are one of the major source of uncertainties in climate
77
models (Hansen et al., 1997; Liou, 2002). The lack of detailed studies in regional and global
78
scale, as well as the extended spatio-temporal distribution of aerosols leads to large uncertainties.
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Aerosols are generated from a variety of natural and anthropogenic sources. They can be
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classified according to their size, physical and chemical structures.
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The effect of aerosols by absorbing and scattering of radiations are considered as direct Aerosol
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Radiative Forcing (ARF). The analysis of the aerosol optical properties can significantly help in
83
understanding the radiative processes and energy budget calculations. Many factors determine
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the sign and magnitude of the ARF including the nature, size, source and distribution of the
85
aerosols as well as the surface albedo (Feng and Christopher, 2013; Bhaskar et al., 2015).
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During the last two decades the number and severity of dust storms has increased significantly in
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the West Asia. These storms deteriorated air quality and created climatic and health related
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issues in Iran. In order to carry out detailed analysis on climatic impacts of aerosol, it is crucial to
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analyze aerosol optical and radiative properties over the region. To inquire optical properties of
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aerosols over Iran, limited studies have been conducted by means of remote sensing techniques
91
(Bayat et al., 2013; Masoumi et al., 2013; Khoshsima et al., 2014). These studies focused only on
92
aerosol optical properties for a limited time period, however, to the best of authors knowledge,
93
no study has yet been conducted to focus on aerosol radiative impacts over long time period. The
94
analysis of aerosol optical properties and radiative impacts was merely reported during dust
95
events over Zanjan by Gharibzadeh et al. (2017). In order to better understand the climatic
96
impacts of aerosol over Zanjan, relatively long-term data (2010-2013) has been used. Zanjan is
97
the least study location in terms of aerosol readiative properties, therefore, this study has the
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potential to fill scientific and geographic gap of our present knowledge about aerosol optical and
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radiative properties over the region.
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In the present study, monthly ARF has been calculated for a period of four years (2010-2013)
101
over Zanjan, Iran. First, the optical properties such as Aerosol Optical Depth (AOD), Ångström
102
Exponent (AE), ASYmmetry parameter (ASY), Single Scattering Albedo (SSA) and Aerosol
103
Volume Size Distribution (AVSD) were analyzed using AErosol RObotic NETwork
104
(AERONET) data. The Santa Barbara Discrete-ordinate Atmospheric Radiative Transfer
105
(SBDART) model was utilized to simulate the solar irradiance values at the Top Of the
106
Atmosphere (TOA), at the earth’s surface, and within the atmosphere (Ricchiazzi et al., 1998).
107
AERONET retrieved parameters (AOD, SSA, ASY) and surface albedo data from Ozone
108
Monitoring Instrument (OMI) were used as inputs to SBDART model. The surface albedo values
109
were obtained from Aura OMI through the Giovanni online data system. Finally, SBDART
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simulated ARF values were compared with that of AERONET retrieved ARF obtained directly
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from inversion product. Furthermore, ARF efficiency and atmospheric heating rate were also
112
calculated.
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Data and methodology
114
1.1. Site description
115
Iran is located approximately in the middle of a dust belt, the semi-arid to arid area which is
116
spread from North Africa to China. Dust storms in the Middle East are active round all the year,
117
especially in the spring and summer. When dust storms occur, they cover many parts of Iran,
118
particularly the southwest, west and central regions. Zanjan is located in the northwest of Iran
119
(36.70° N, 48.50° E, and 1800 m above sea surface). Zagros Mountains separate the city from
120
Mesopotamian low-altitude area. Dust aerosols in this region often are derived from some
121
important sources like Tigris and Euphrates basins in Iraq, the Arabian Peninsula and west Syria
122
during dry months from May to July. Anthropogenic aerosols are also present in the atmosphere
123
(Bayat et al., 2013; Masoumi et al., 2013).
124
The meteorological situation over Zanjan was analyzed as shown in Fig 1. The daily mean
125
temperature and precipitation have been provided by Iran Meteorological Organization from the
126
earth’s surface (1805 m above sea level) during 2010-2014 (see Fig.1a). The mean temperature
127
ranges from -4 °C to 24 °C with maximum in the summer and minimum in the winter. The mean
128
precipitation during spring, winter, fall and summer were 50.7, 28.9, 20.8, and 10.2 mm,
129
respectively. To understand the role of the surface wind at 850 mb, wind flow patterns were
130
obtained from NCEP/NCAR reanalysis (http://www.cdc.noaa.gov) over west of Iran (see Fig.
131
1b) for each year in the study period. The arrows show wind directions and the colours represent
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the wind speeds. As it can be seen, strong winds are almost from the west and southwest. To
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understand what pathway the air mass have been transported from their sources to Zanjan, back-
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trajectory analyses based on the NOAA HYSPLIT model were performed for the selected dusty
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days in each of the four years. The results revealed that the air masses arriving from North
136
Africa, Saudi Arabia and Iraq significantly contribute in high aerosol loading over Zanjan
137
(Khoshsima et al., 2014).
138
1.2. AERONET
139
The AERONET is a ground-based remote sensing network of sun photometers which provides
140
an aerosol and radiative properties database. The only sunphotometer in Iran is the CIMEL
141
Sunphotometer of Zanjan, which takes measurements of the direct sun and diffuses sky
142
radiances. AOD data are available for three quality levels: Level 1.0 (unscreened), Level 1.5
143
(cloud-screened) and Level 2.0 (cloud screened and quality-assured). The present study utilized
144
the Level 2.0 data during the period (2010-2013) to analyze the climatic impacts of aerosol. The
145
AERONET automatic filtering algorithm described by Smirnov et al. (2000) filters out a lot of
146
AOD values due to very rapid change of aerosol load. Since the majority of the high AOD values
147
were considered as ''clouds'' by the Level 2.0 filtering algorithm, when in reality there were
148
irregular high dust concentrations. Therefore, it will be vital to use Level 1.0 parallel to Level 2.0
149
data for dust or high AOD values, because the dust events may have been screened out of the
150
cloud-screened data (Tripathi et al., 2005; Mahler et al., 2006).
151
The uncertainty in retrieval under cloud-free conditions for AOD is less than ±0.01 for the
152
wavelengths greater than 0.44 nm and for shorter wavelengths it is less than ±0.02. Moreover,
153
the uncertainty for the retrieval of sky radiance measurements is less than ±0.05 (Dubovik et al.,
154
2000). There are data gaps in this study because data are not available on AERONET site due to
155
process of calibration of sunphotometer.
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1.3. SBDART
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SBDART model is a FORTRAN computer code. This model calculates the plane-parallel
158
radiative transfer at earth's surface and top of the atmosphere. This software is used in a wide
159
variety of studies related to radiative transfer problems. To solve the plane-parallel radiative
160
transfer equations, a numerically stable algorithm was used. At most, five different aerosol layers
161
with particular radiative characteristics can be recognized. This code is a complex set of
162
DISORT (Discrete Ordinate Radiative Transfer), Mie scattering code and atmospheric
163
transmission models (Ricchiazzi et al., 1998).
164
The daily net fluxes at the earth's surface and TOA were calculated for short wavelengths (0.3–
165
4.0 µm) using the SBDART model. Then monthly average of ARF was determined from daily
166
averaged values during the study period. The mid-latitude winter atmospheric model was used.
167
To improve the accuracy of the estimated ARF, mean values for columnar water vapor were
168
utilized. To calculate the radiative forcing in the clear sky conditions, the AERONET data such
169
as AOD, SSA, and ASY were used as input in the SBDART model. The surface albedo values
170
were obtained from Aura OMI version 3 aerosols level 2 data through the Giovanni online data
171
system, developed and maintained by the NASA Goddard Earth Sciences (GES) Data and
172
Information Services Centre (DISC), retrieved from https://giovanni.sci.gsfc.nasa.gov/giovanni.
173
For other inputs like solar zenith angle, a code was used which is available in SBDART model
174
by specifying the values of latitude, longitude, time and date.
175
2. Results and discussion
176
2.1. Variation in aerosol optical properties
177
2.1.1. Aerosol optical depth and Ångström exponent
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AOD represents the amount of solar radiations absorbed or scattered by aerosols. It is a measure
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of the total column extinction of transmitted radiations due to atmospheric aerosols. The amount
180
of radiation that reaches the earth's surface, determines the measured voltage by sunphotometer.
181
The total optical depth can be calculated using Eq. (1): Vλ = V λd e
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(1)
where V is digital voltage at λ, V0 is extraterrestrial voltage, d is the ratio of the average to the
184
actual earth-sun distance, τTot is the total optical depth and m is the optical air mass (Holben et
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al., 1998).
186
Wavelength dependence of the AOD determines AE which is a good indicator of aerosol particle
187
size which is demonstrated by the Ångström relationship (Ångström, 1964) given as:
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τ λ = βλ
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(2)
where τ λ is AOD at wavelength λ, β is the turbidity coefficient indicating aerosol loading in
190
the atmosphere and α is AE.
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There are occasionally dust aerosols in the atmosphere of Zanjan during spring and summer, it is
192
due to dryness of soil and high activity of dust sources, therefore, dust particles are more
193
dominant in the atmosphere (Bayat et al., 2013; Masoumi et al., 2013; Gharibzadeh et al., 2017).
194
Monthly variation of AOD at 500 nm, AE at 440–870 nm and water vapour over Zanjan during
195
2010-2013 are shown in Fig. 2. The monthly averaged AOD ranged between 0.051 and 0.57 with
196
the lowest in December 2014 and the highest in June 2011 with a mean value of 0.21. The
197
monthly variations of AE were in the range from 0.3 to 1.74 with an average value of 0.9.
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Correspondingly, the monthly averaged values of water vapour varied between 0.30-1.37 cm
199
having maximum values in August 2011 and minimum in January 2012.
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The behaviour of AOD in response to changes in water vapour revealed that AOD and water
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vapour showed positive correlation of 0.15, 0.05 and 0.56 in the spring, summer and fall,
202
respectively, and a negative correlation of -0.21 in the winter. The seasonal averaged AOD, AE
203
and water vapour along with their standard deviations are listed in the Table 1. The higher AOD
204
in the spring months (March–May) and summer months (June–August) and relatively lower
205
AOD in the winter months (December–February) and fall months (September–November) were
206
observed. The high AOD values in the spring and summer were due to dust aerosols, which
207
originated from external sources like Tigris-Euphrates basin and Arabian Peninsula as well as
208
local dust sources such as dried seasonal lakes or rivers during dry months (Bayat et al., 2013;
209
Masoumi et al., 2013, Gharibzadeh et al., 2017). During summer high temperature plays an
210
important role in heating and lifting lose materials from the ground due to high wind speed, and
211
therefore, higher AOD values were observed (Alam et al., 2011). Moreover, the values of water
212
vapour were observed to be higher during summer months when the dust particles were
213
dominant. During spring and summer water soluble aerosols grow hygroscopically in the
214
presence of water vapour, consequently contribute to high AOD values (Alam et al., 2011; Alam
215
et al., 2012). The variation of AE was relatively different than that of AOD. The increase in AE
216
values were observed in the winter and fall while decreases were found in the summer and
217
spring. Low values of AE represent the dominance of coarse mode particles, which were
218
indicatives of dust storms in these seasons. AE was high in the fall and winter because of local
219
anthropogenic activities such as increase of fossil fuels consumption and the dominance of
220
urban/industrial aerosols that were fine mode particles (Singh et al., 2005; Alam et al., 2011).
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Recently, Patel and Kumar (2016) reported the abundance of fine and coarse mode particles,
222
which were associated with high AE and low AE, respectively over Dehradun.
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Similarly, Khoshsima et al., (2014) reported high AOD in late spring and early summer with a
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maximum in the month of June over Zanjan, representing the impact of dust storms and regional
225
climate. Che et al., (2013) found the same seasonal trend of AOD and AE over Taklimakan
226
Desert. They found that low AOD in the fall and winter and high AOD in the summer and
227
spring. These findings about the inverse relationship between AOD and AE for dust events are
228
similar to the results reported earlier (Kumar et al., 2013; Srivastava et al., 2014). However, the
229
high values of AE indicate the dominance of fine particles, when dust particle are not prominent
230
in the atmosphere (Alam et al., 2011; Srivastava et al., 2014). Recently, Bibi et al. (2016) found
231
the high AOD and low AE for coarse mode particles and high AOD and high AE for the fine
232
mode aerosol.
233
2.1.2. Asymmetry parameter and Single scattering albedo
234
ASY represents a preferred direction in scattering and is one of the important components in
235
determining the radiative forcing calculations. ASY is calculated by Eq. (3):
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ASYλ = cos θ Pλ, θ sin θ dθ
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where θ is the angle between the incident and scattered radiation and P (λ,θ) is the phase function
238
(angular distribution of scattered light) (Muneer, 2007). ASY is 1 if the scattering is completely
239
in the forward direction and is -1 for completely backward scattering.
240
Fig. 3 shows the spectral variation of ASY over Zanjan during the study period. In all seasons,
241
ASY depicted high values at a wavelength of 440 nm. The ASY values were decreasing with
242
increasing wavelengths from 440 to 870 nm (the visible range). The increase in infrared region
243
(from 870 to 1020 nm) in summer is due to the dominance of the coarse mode dust aerosols.
244
Similar to the results reported by Srivastava et al. (2011), Adesina et al. (2014), and Bibi et al.
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(2016). In the winter ASY decreased with increasing wavelengths. The lowest value of ASY
246
occurred at 1020 nm in winter is due to the dominance of anthropogenic aerosol. The decline
247
trend was not so prominent in the wavelength range from 870 to1020 nm during the spring and
248
fall. Similar results were reported by Bi et al. (2011), Alam et al. (2012) and Adesina et al.
249
(2015).
250
The ratio of scattering efficiency to total extinction efficiency is called SSA (Steinfeld, 1998).
251
SSA is a good indicator showing the type of aerosols, which is 1 and 0 for the totally scattering
252
and absorbing types of aerosol, respectively. Spectral variation of the seasonal averaged SSA is
253
shown in Fig. 4. The SSA was observed to be strongly wavelength dependent during all seasons
254
except during fall. Increase in SSA with increasing wavelength, represented the dominance of
255
dust particles with larger size during summer. Similar increasing trend in SSA with increasing
256
wavelength was observed to be common during dust episodes as documented by previous
257
researchers Eck et al. (2010), Alam et al. (2014) and Yu et al. (2016). But in the winter, the
258
decrease in SSA with increasing wavelength was noted due to major contribution of fine
259
particles. Zheng et al. (2008) and Bi et al. (2011) also reported the similar spectral dependency
260
(decrease in SSA with increasing wavelength) over China. Whereas slightly increase in SSA
261
with increasing wavelength between 440 and 675 nm and then smooth decrease till 1020 nm was
262
found during spring, which show the possibility of mixed aerosol (Dust and anthropogenic
263
aerosols) (Alam et al., 2011; Alam et al., 2012). Recently, Bibi et al. (2016) pointed out that
264
SSA sharply increases from 440 to 675 nm and decreases from 675 to 1020 nm. In the fall, the
265
SSA value was higher as compared to other seasons showing the presence of dust particles with
266
minor contribution of fine particles. Similarly, Bibi et al. (2016) noticed the less spectral
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dependency of SSA during fall season over IGP, but with lower SSA values than the results
268
reported in this study.
269
2.1.3. Aerosol volume size distribution
270
Aerosol distributions are classified in two categories: the fine particles smaller than 0.6 µm and
271
the coarse mode particles larger than 0.6 µm (Dubovik et al., 2002) AVSD can be shown as
272
follows:
$'(&
=
* ∑/0 +,, -#.
,
exp 3−
7
5'(& '(&+,, 6 .7,
8
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$%&
(4)
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where, σ/ is the standard deviation, r%,/ is the volume median radius and c%,/ is the volume
275
concentration for fine and coarse modes (Che et al., 2013). Fig. 5 shows the seasonal averaged
276
of AERONET retrieved AVSD for Zanjan during 2010-2013. Both fine and coarse modes are
277
seen in the Fig. 5, but significant variations can be found in the coarse mode. The peak values of
278
AVSD for fine and coarse mode were observed about radii of 0.11 and 2.24 µm, respectively,
279
during all the seasons. The higher amounts of AVSD in the coarse mode in the spring and
280
summer could be due to the presence of dust particles (Alam et al., 2012; Adesina et al., 2014;
281
Srivastava et al., 2014).
282
During winter and fall coarse mode aerosol are also dominant over fine mode due to re-
283
suspended road dust. The results are similar to other earlier results (Alam et al., 2012; Adesina et
284
al., 2014; Srivastava et al., 2014). The values for coarse mode volume concentrations were
285
0.108, 0.149, 0.077 and 0.037 in the spring, summer, fall and winter, respectively. The values of
286
0.016, 0.023, 0.015 and 0.011 were obtained for fine mode volume concentrations in spring,
287
summer, fall and winter, respectively. The ratio of coarse to fine mode volume concentrations
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increased in the summer and spring and decreased in the fall and winter. As a result of dust
289
particles transferred from Mesopotamian sources to Zanjan especially in late spring and summer.
290
2.2. Aerosol radiative forcing and atmospheric heating rate
291
Further knowledge and extensive research about radiations and their interaction with aerosol and
292
cloud are the most important requirements in climate studies. The difference between the net
293
solar flux (down minus up) with and without aerosols, either at the TOA or the earth’s surface
294
(Jacob, 1999):
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∆F = F↓ − F↑ − F↓ − F↑
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(5)
where ∆F denotes the irradiance (downwelling or upwelling, Wm-2), and (F↓-F↑) denotes the net
297
irradiance (downwelling minus upwelling) computed with aerosol (Fa) and without aerosol (Fo)
298
at either the TOA or at the earth’s surface (Alam et al., 2012). The ARF at the TOA, surface,
299
within the atmosphere from SBDART calculations and atmospheric heating rate during the study
300
period of 2010-2013 are shown in Fig. 6.
301
In addition to the optical parameters such as AOD, SSA and ASY, few other parameters like
302
surface albedo and meteorological conditions are also used as input in SBDART model for
303
calculation of ARF. The calculated values of ARF at the TOA were between -28.45 Wm-2 (in
304
April 2011) and 5.7 Wm-2 (in May 2010) having an average annual value of -13.47 Wm-2 for the
305
whole study period. The surface ARF varied between -7.92 Wm-2 in December 2013 and -91.67
306
Wm-2 in June 2011 with an average annual of -36.1 Wm-2. Table 2 shows the seasonal averaged
307
ARF values at the TOA, surface and within the atmosphere.
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The difference between ARF at the surface and at the TOA indicates the ARF within the
309
atmosphere. Positive atmospheric ARF demonstrates heating of the atmosphere which causes a
310
reduction in solar radiation flux reaching the earth’s surface. This effect can influence cloud
311
formation, precipitation, and hydrological cycle (Ramachandran and Kedia, 2012). The
312
atmospheric heating rate calculated by Liou (2002) is given in Eq. (7): ∆=
313
=−
? ∆B
@A ∆C
(6)
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where g denotes gravitational acceleration (ms-2), Cp denotes the specific heat of air (JK-1kg-1),
315
∆F is the atmospheric irradiance and P denotes the pressure (Pa). Fig. 6 also shows the monthly
316
atmospheric heating rate and ARF within the atmosphere during 2010-2013. The variation of
317
atmospheric heating rate over Zanjan ranged from 0.01 Kday-1 in December 2013 to 0.87 Kday-1
318
in June 2011 with the annual mean of 0.27 Kday-1. Atmospheric ARF values were between 0.91
319
Wm-2 in December 2013 and 72.47 Wm-2 in June 2011. The mean value was 22.63 Wm-2 , which
320
reveals a warming effect within the atmosphere. Some earlier studies reported higher values than
321
our results in different locations (Alam et al., 2012; Adesina et al., 2014; Srivastava et al., 2015),
322
while, other reported lower values (Ramachandran and Kedia, 2012).
323
The high values of atmospheric heating rate and atmospheric ARF in the spring and summer
324
seasons demonstrate net atmospheric absorption due to aerosols. This happened because of the
325
higher aerosol concentration and varying characteristics of aerosols (Kumar and Devara, 2012),
326
and also due to presence of an elevated aerosol layer during spring and summer seasons (Kumar
327
and Devara, 2012). This layer was a result of transferring dust particles from Mesopotamian
328
sources to Zanjan.
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For an accurate comparison, it is better to calculate ARF efficiency (∆FDEE .), ∆FDEE is the rate at
330
which the atmosphere is forced per unit of AOD at 0.55 µm at either the TOA or the earth’s
331
surface as follows (Seinfeld and Pandis, 2006): ∆FDEE = ∆F/AOD
332
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(7)
The ARF efficiency at the TOA and earth’s surface is shown in Fig. 7. The annual averaged
334
values of ARF efficiency at the TOA and surface were -65.08 Wm-2 and -158.43 Wm-2,
335
respectively. At the TOA an opposing behaviour was recognized. More absorption of aerosols
336
showed lower ARF efficiency averages. This is a result of the higher absorption of these aerosols
337
that decreased the backscattered energy towards the TOA and into the space (Garcia et al., 2012).
338
Many researchers have discussed the ARF, atmospheric heating rate and ARF efficiency. Table 3
339
shows comparison of ARF values at the TOA, earth's surface and within the atmosphere, and
340
also ARF efficiency and atmospheric heating rate for different locations worldwide.
341
Finally, the relationship between ARF directly retrieved from AERONET and simulated by
342
SBDART was shown in Fig. 8. The correlation coefficient was greater than 0.98, which indicates
343
the accuracy of the SBDART model in the present work. Alam et al. (2012) found the
344
AERONET-SBDART correlation coefficients to be 0.99 for Lahore, and 0.98 for Karachi.
345
Adesina et al. (2015) reported the correlation coefficient for AERONET vs. SBDART at the
346
surface and TOA and were 0.95 and 0.97 respectively over Gorongosa. Adesina et al. (2014)
347
obtained the correlation between SBDART and AERONET and found correlation coefficient of
348
0.84 at TOA, and 0.94 at the surface, while 0.88 within the atmosphere over Pretoria. In addition,
349
Kumar and Devara (2012), Ramachandran and Kedia (2012) and Li et al. (2010) obtained a good
350
correlation among the ARF retrieved from AERONET and simulated by SBDART.
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3. Conclusion
352
Aerosols are important components in the climate studies, and a major source of uncertainty in
353
climate models. Aerosols can directly affect climate through scattering or absorbing solar
354
radiation, therefore, exert a negative or positive radiative forcing at TOA, earth's surface and
355
within the atmosphere. A comprehensive study of aerosol optical and radiative properties was
356
accomplished over Zanjan for the period from 2010 to 2013. The aerosol optical properties like
357
AOD, AE, ASY, SSA, and AVSD have been evaluated using AERONET data. The silent
358
conclusion can be summarized as follow:
359
1. Temporal variation of AOD and AE were investigated. The high AOD values and low AE
360
values during spring and summer seasons revealed that coarse mode particles such as dust are
361
dominant. Likewise, high AE values and low AOD values in the fall and winter represent the
362
dominance of anthropogenic fine mode particles.
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2. Spectral variations of the ASY over Zanjan show that a decrease of ASY in the visible
364
spectrum is due to the dominance of anthropogenic absorbing aerosol. Also the slight
365
increase in the infrared region is as a result of the dominance of the coarse mode particles.
366
3. During spring and summer, SSA increases with increasing wavelength, because of the
367
dominance of coarse dust particles. However, during winter SSA values were found to be
368
lower due to the presence of absorbing aerosols.
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4. The ARF at the TOA and surface ranged between -28.45 and 5.7 Wm-2 and -7.92 and -91.67
370
Wm-2 respectively, with corresponding annual averaged values of -13.47 Wm-2 and -36.1
371
Wm-2. The relationship between SBDART simulated ARF and AERONET retrieved ARF
372
revealed a strong positive correlation of 0.98, which indicates the accuracy of the SBDART
373
model in the present study.
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5. The atmospheric ARF and heating rate were ranged from 0.91 to 72.47 Wm-2 and 0.01 to
375
0.87 Kday-1 respectively, which showed the significant heating of the atmosphere over the
376
studied region.
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Acknowledgments. The authors wish to thank NASA and Institute for Advanced Studies in
379
Basic Sciences in Zanjan for providing AERONET data. To obtain the surface albedo values, the
380
Giovanni online data system, developed by the NASA GES DISC was utilized. We appreciate
381
the Iran Meteorological Organization for providing meteorological data. NCEP/NCAR would be
382
thankful for providing reanalysis data.
383
References
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ACCEPTED MANUSCRIPT Table 1. Seasonally averaged values and their standard deviations of AOD at 500 nm, water vapour AE at 440–870 nm for the period 2010–2014 over Zanjan.
AOD 0.26± 0.08 0.29±0.05 0.16±0.02 0.14 ±0.04
AE 0.71±0.16 0.75±0.11 1.00±0.17 1.17± 0.10
Water vapour cm 0.660 1.206 0.818 0.399
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TOA (Wm-2) -11.57 -16.73 -14.01 -10.67
Surface (Wm-2) -44.02 -48.05 -26.37 -23
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Spring Summer Fall Winter
Atmosphere (Wm-2) 32.46 31.32 12.37 12.32
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Study period
TOA ARF efficiency Wm-2
Surface ARF efficiency Wm-2
TOA ARF Wm-2
Atmosphere ARF Wm-2
Srivastava et al., 2011
Ahmedabad
2008
-67 to -89
-
-
-
Karachi
August 2006 - July 2007
-
-
-7 to 35
+41 to +61
2010-2011
-
-
-50.1 to -74.7 -48.4 to -68.4
Alam et al.,2011
-16 to -31 -14 to -21
Alam et al.,2012
Lahore Karachi
Ramachandran and Kedi, 2012
Kanpur Gandhi College
2006–2008
-8.2 to -16.9 -12.7 to -15.7
Adesina et al., 2014
Pretoria
2012
-76.5
-210.7
Srivastava et al.,2015
Manora Peak
-
-
Panicker et al. 2010
Pune
Oct 2004– May 2005
-
-
−0.5 to +0.6
Present study
Zanjan
2010-2013
16.2 to -164.6
-85.7 to
-28.45 to 5.7
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Heating rate Kday-1
-56 to 96
+51 to +82 +33 to +51
-70 to 112 -52 to 73
+24.5 to+31.8 +24 to +34.1
-50.1 to 137.5 -65.6 to 152.9
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-14.6 to -45.7 -20.1 to -40.5
Surface ARF Wm-2 -15 to 45
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+8 to +29
-15.6 to -38.6
0.2 to 0.8
+3 to +65
-50 to 3
0.1 to 1.8
+33 to +48
−33 to −47
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+0.91 to +72.47
-7.9 to -91.67
0.01 to 0.87
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Fig. 1. Variation in (a) daily mean temperature and precipitation, (b(i-iv)) Mean synoptic wind vector at a pressure level of 850 mb over west of Iran during 2010-2014. The location of Zanjan is marked by a black circle.
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Fig. 2. Monthly averaged variations of AOD at 500 nm, AE at 440–870 nm and water vapour over Zanjan during 2010-2014.
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Fig. 3. Spectral variation of seasonal averaged of ASY over Zanjan during 2010-2014.
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Fig. 4. Spectral variations of seasonal averaged of SSA over Zanjan during 2011-2014.
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Fig. 5. Seasonal averaged of AERONET retrieved AVSD for Zanjan during 2010-2014.
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Fig. 6. ARF at the TOA, earth’s surface, within the atmosphere from SBDART calculations, and atmospheric heating rate during 2011-2014, over Zanjan.
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Fig. 7. ARF efficiency at the TOA and earth’s surface during 2011-2014, over Zanjan.
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Fig. 8. Comparison of ARF obtained at the TOA, earth's surface and within the atmosphere, directly retrieved from AERONET and simulated by SBDART over Zanjan during 2011-2014.
ACCEPTED MANUSCRIPT Highlights Detailed analysis of aerosol optical properties have been analyzed in Zanjan, Iran.
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Higher AOD & relatively lower AE values observed in spring & summer seasons.
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Higher AE & lower AOD values observed in fall & winter seasons.
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The annual mean ARF & heating rate were 22.63 Wm-2 & 0.27 Kday-1, respectively.
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