T. A. Jones

University of Alabama in Huntsville, Huntsville, AL, United States

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Publications (17)59.93 Total impact

  • T.A. Jones, S.A. Christopher
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    ABSTRACT: A historic dust storm affected the eastern portions of Australia between September 22 and 24, 2009, causing significant reductions in air quality and visibility. Using multiple satellite remote sensing data sets and meteorological information, we assess the distribution of dust aerosols and their potential effects on the Earth-atmosphere system. Spaceborne active lidar data showed that dust aerosols were located up to 2 km above the surface. The thickness of the dust plume (0.55-μm aerosol optical thickness >; 1.0) reduced surface visibility to below 2 km. Dew-point depressions of 20 <;sup>;°<;/sup>;C or more occurred after passage of the dust plume, with decreases in surface temperature observed at some locations. Between the surface and 2-km level, temperature data show a cooling of ~10°C in the hours after passage of the cold front along which dust aerosols had converged. However, much of the temperature change that occurred is a result of cold air advection behind the northward traveling plume. Radiative transfer modeling suggests that only up to 1°C per day of this cooling is due to the decrease in solar radiation reaching the surface layer. Radiative transfer modeling also indicates a net warming of up to 2°C per day within and above the dust layer, possibly offsetting some cooling aloft due to the cold front passage. Modeling results indicate that expected aerosol radiative effects to temperature are small compared to synoptic influences and are unlikely to be sampled in observations under this scenario since the magnitudes of these effects are quite small.
    IEEE Geoscience and Remote Sensing Letters 04/2011; · 1.82 Impact Factor
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    T. A. Jones, S. A. Christopher
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    ABSTRACT: Using daily Goddard Chemistry Aerosol Radiation and Transport (GOCART) model simulations and columnar retrievals of 0.55 μm aerosol optical thickness (AOT) and fine mode fraction (FMF) from the Moderate Resolution Imaging Spectroradiometer (MODIS), we estimate the aerosol concentration and particle size over the global oceans between June 2006 and May 2007 due to black carbon (BC), organic carbon (OC), dust (DU), sea-salt (SS), and sulfate (SU) components. Using Aqua-MODIS aerosol properties embedded in the CERES-SSF product, we find that the mean MODIS FMF values are SS: 0.31±0.09, DU: 0.49±0.13, SU: 0.77±0.16, and (BC+OC):0.80±0.16. We further combine information from the ultraviolet spectrum using the Ozone Monitoring Instrument (OMI) onboard the Aura satellite to improve the classification process, since dust and carbonaceous aerosols have positive Aerosol Index (AI) values >0.5 while other aerosol types have near zero values. By combining MODIS and OMI datasets, we were able to identify and remove data in the SU and CC regions that were not associated with those aerosol types. The same methods used to estimate aerosol size characteristics from MODIS data within the CERES-SSF product were also applied to Level 2 (L2) MODIS aerosol data from both Terra and Aqua satellites for the same time period. As expected, FMF estimates from L2 Aqua data agreed well with the CERES-SSF dataset, also from Aqua. However, the FMF estimate for DU from Terra data was significantly lower (0.37 vs. 0.49) indicating that sensor calibration, sampling differences and/or diurnal changes in DU aerosol size characteristics were occurring. Differences for other aerosol types were generally smaller. Sensitivity studies show that a difference of 0.1 in the estimate of the anthropogenic component of FMF produces a corresponding change of 0.2 in the anthropogenic component of AOT (assuming a unit value of AOT). This uncertainty would then be passed along to any satellite-derived estimates of anthropogenic aerosol radiative effects.
    Atmospheric Chemistry and Physics 01/2010; · 4.88 Impact Factor
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    ABSTRACT: Using six years of top of the atmosphere (TOA) shortwave flux, cloud cover, and aerosol data sets, the direct TOA shortwave aerosol radiative effects over global land regions has been estimated. The TOA shortwave flux data were obtained from CERES broadband instruments, cloud masking information is from the MODIS high resolution data sets within the CERES footprint and Aerosol Optical Depth (AOD) is obtained from state-of-art MISR retrievals. All three instruments are onboard the EOS Terra satellite and have an equatorial overpass of 10:30 am local time. The estimated clear sky global mean shortwave direct radiative effect (DRE) of aerosols is -5.6 ± 1.5 Wm-2 although substantial regional variability in DRE over land exists due to differences in aerosol properties and land cover types. The seasonal and regional variability in DRE and associated uncertainties will be discussed in this paper.
    AGU Fall Meeting Abstracts. 12/2009;
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    ABSTRACT: During April and May 2007, several hundred fires burned uncontrollably in Georgia and Florida. The smoke from these fire events were visible throughout the Southeastern United States and had a major impact on particulate matter (PM) air quality near the surface. In this study, we show the strength of polar orbiting and geostationary satellite data in capturing the spatial distribution and diurnal variability of columnar smoke aerosol optical depth from these fires. We quantitatively evaluate PM air quality from satellites and ground-based monitors, near and far away (> 300 km) from fire source regions. We also show the changes in organic carbon concentrations (a tracer for smoke aerosols) before, during and after these fire events. Finally, we use fire locations and emissions retrieved and estimated from satellite observations as input to a regional mesoscale transport model to forecast the spatial distribution of aerosols and their impact on PM air quality. During the fire events, near the source regions, total column 550 nm aerosol optical thickness (AOT) exceeded 1.0 on several days and ground-based PM2.5 mass (particles less than 2.5 mum in aerodynamic diameter) reached unhealthy levels ( > 65.5 mug m<sup>-3</sup>). Since the aerosols were reasonably well mixed in the first 1-2 km (as estimated from meteorology), the column AOT values derived from both geostationary and polar orbiting satellites and the surface PM2.5 were well correlated (linear correlation coefficient, r > 0.7). Several hundred miles away from the fire sources, in Birmingham, AL, the impact of the fires were also seen through the high AOT's and PM2.5 values. Correspondingly, PM2.5 mass due to organic carbon obtained from ground-based monitors showed a three fold increase during fire events when compared to background values. Satellite data were especially useful in capturing PM2.5 air quality in areas where there were no ground-based monitors. Although the mesoscale transport model- captured the timing and location of aerosols, when compared to observations, the simulated mass concentrations are underestimated by nearly 70% due to various reasons including uncertainties in fire emission estimates, lack of chemistry in the model, and assumptions on vertical distribution of aerosols. Satellite products such as AOT, fire locations, and emissions from space-borne sensors are becoming a vital tool for assessing extreme events such as fires, smoke, and particulate matter air quality.
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10/2009; · 2.87 Impact Factor
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    T.A. Jones, S.A. Christopher
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    ABSTRACT: Understanding the vertical distribution of aerosols is critical to accurately determining their effects on air quality. Since current tools for obtaining this information have limited spatial and temporal coverage, we explore the use of Doppler radar data for obtaining the injection heights of biomass burning debris (BBD) produced from large fires in southern Georgia during Spring 2007. Due to their submicrometer sizes, the smoke aerosols are not detected by the radar. Therefore, we use BBD as a possible surrogate for aerosol height since smoke aerosols are often collocated with the debris. Using 32 h of Weather Surveillance Radar-1988 Doppler (WSR-88D) radar data from Jacksonville, FL, between May 23 and 25, 2007, the injection heights of BBD (D ~ 1mm) are calculated. Our analysis indicates that the maximum injection height is ~5 km for the strongest fire, with a mean injection height of 3 plusmn 1.0 km. Maximum injection heights are present between 1800 and 0000 UTC, during the late afternoon periods when both the intensity of the fire (based on radar information) and the convective mixing are greatest. The injection heights estimated from this approach represent the first step at providing inputs for future air-quality forecasting applications within numerical simulations, particularly ones that require diurnal information.
    IEEE Transactions on Geoscience and Remote Sensing 09/2009; · 3.47 Impact Factor
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    T. A. Jones, S. A. Christopher, Quaas J
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    ABSTRACT: Aerosols act as cloud condensation nuclei (CCN) for cloud water droplets, and changes in aerosol concentrations have significant microphysical impacts on the corresponding cloud properties. Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol and cloud properties are combined with NCEP Reanalysis data for six different regions around the globe between March 2000 and December 2005 to study the effects of different aerosol, cloud, and atmospheric conditions on the aerosol indirect effect (AIE). Emphasis is placed in examining the relative importance of aerosol concentration, type, and atmospheric conditions (mainly vertical motion) to AIE from region to region. Results show that in most regions, AIE has a distinct seasonal cycle, though the cycle varies in significance and period from region to region. In the Arabian Sea (AS), the six-year mean anthropogenic + dust AIE is −0.27 Wm−2 and is greatest during the summer months (−2) during which aerosol concentrations (from both dust and anthropogenic sources) are greatest. Comparing AIE as a function of thin (LWP−2) vs. thick (LWP≥20 gm−2) clouds under conditions of large scale ascent or decent at 850 hPa showed that AIE is greatest for thick clouds during periods of upward vertical motion. In the Bay of Bengal, AIE is negligible owing to less favorable atmospheric conditions, a lower concentration of aerosols, and a non-alignment of aerosol and cloud layers. In the eastern North Atlantic, AIE is weakly positive (+0.1 Wm−2) with dust aerosol concentration being much greater than the anthropogenic or sea salt components. However, elevated dust in this region exists above the maritime cloud layers and does not have a hygroscopic coating, which occurs in AS, preventing the dust from acting as CCN and limiting AIE. The Western Atlantic has a large anthropogenic aerosol concentration transported from the eastern United States producing a modest anthropogenic AIE (−0.46 Wm−2). Anthropogenic AIE is also present off the West African coast corresponding to aerosols produced from seasonal biomass burning (both natural and man-made). Interestingly, atmospheric conditions are not particularly favorable for cloud formation compared to the other regions during the times where AIE is observed; however, clouds are generally thin (LWP−2) and concentrated very near the surface. Overall, we conclude that vertical motion, aerosol type, and aerosol layer heights do make a significant contribution to AIE and that these factors are often more important than total aerosol concentration alone and that the relative importance of each differs significantly from region to region.
    Atmospheric Chemistry and Physics 01/2009; · 4.88 Impact Factor
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    ABSTRACT: A high-resolution global aerosol model (Oslo CTM2) driven by meteorological data and allowing a comparison with a variety of aerosol observations is used to simulate radiative forcing (RF) of the direct aerosol effect. The model simulates all main aerosol components, including several secondary components such as nitrate and secondary organic carbon. The model reproduces the main chemical composition and size features observed during large aerosol campaigns. Although the chemical composition compares best with ground-based measurement over land for modelled sulphate, no systematic differences are found for other compounds. The modelled aerosol optical depth (AOD) is compared to remote sensed data from AERONET ground and MODIS and MISR satellite retrievals. To gain confidence in the aerosol modelling, we have tested its ability to reproduce daily variability in the aerosol content, and this is performing well in many regions; however, we also identified some locations where model improvements are needed. The annual mean regional pattern of AOD from the aerosol model is broadly similar to the AERONET and the satellite retrievals (mostly within 10–20%). We notice a significant improvement from MODIS Collection 4 to Collection 5 compared to AERONET data. Satellite derived estimates of aerosol radiative effect over ocean for clear sky conditions differs significantly on regional scales (almost up to a factor two), but also in the global mean. The Oslo CTM2 has an aerosol radiative effect close to the mean of the satellite derived estimates. We derive a radiative forcing (RF) of the direct aerosol effect of −0.35 Wm−2 in our base case. Implementation of a simple approach to consider internal black carbon (BC) mixture results in a total RF of −0.28 Wm−2. Our results highlight the importance of carbonaceous particles, producing stronger individual RF than considered in the recent IPCC estimate; however, net RF is less different. A significant RF from secondary organic aerosols (SOA) is estimated (close to −0.1 Wm−2). The SOA also contributes to a strong domination of secondary aerosol species for the aerosol composition over land. A combination of sensitivity simulations and model evaluation show that the RF is rather robust and unlikely to be much stronger than in our best estimate.
    Atmospheric Chemistry and Physics 01/2009; 9:1365-1392. · 4.88 Impact Factor
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    T. A. Jones, S. A. Christopher
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    ABSTRACT: Given the complex interaction between aerosol, cloud, atmospheric properties, it is difficult to extract their individual effects to observed rainfall amount. This research uses principle component analysis (PCA) that combines Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol and cloud products, NCEP Reanalysis atmospheric products, and rainrate estimates from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) to assess the specific combinations of these inputs that most affect warm rain processes. Data collected during September 2006 over the South America, which includes the Amazon basin, are used as aerosols, clouds, and precipitation are all present in this region at this time. The goal of this research is to combine these observations into a smaller number of variables through PCA with each having a unique physical interpretation. In particular, we are concerned with PC variables whose weightings include aerosol optical thickness (AOT), as these may be an indicator of aerosol indirect effects. If they are indeed occurring, then PC values that include AOT should change as a function of rainrate. To emphasize the advantage of PCA, changes in aerosol, cloud, and atmospheric observations are compared to rainrate. Comparing no-rain, rain, and heavy rain (>5 mm h−1) samples, cloud thicknesses, humidity, and upward motion are all larger for the rain and heavy rain samples. However, no statistically significant difference in AOT exists, indicating that atmospheric conditions are more important to rainfall than aerosol concentrations as expected. If aerosols are affecting warm process clouds, it would be expected that stratiform precipitation would decrease as a function increasing aerosol concentration through either Twomey and/or semi-direct effects. PCA extracts the latter signal in a variable labeled PC2, which explains 15% of the total variance and is second in importance the variable (PC1) containing the broad atmospheric conditions. PC2 contains weightings showing that AOT is inversely proportional to low-level humidity and cloud optical thickness. Increasing AOT is also positively correlated with increasing low-level instability due to aerosol absorption. The nature of these weightings is strongly suggestive that PC2 is an indicator of the semi-direct effect with larger values associated with lower rainfall rates. PC weightings consistent with the Twomey effect (an anti-correlation between AOT and cloud droplet effective radius) are only present in PC13, which explains less than 1% of the total variance. Also, it does not vary significantly with rainrate. Thus, if the Twomey effect is occurring, it is highly non-linear and/or being overshadowed by other processes. Using the raw variables alone, these determinations could not be made; thus, we are able to show the advantage of using advanced statistical techniques such as PCA for analysis of aerosols impacts on precipitation in South America.
    Atmospheric Chemistry and Physics 01/2009; · 4.88 Impact Factor
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    T. A. Jones, S. A. Christopher, J. Quaas
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    ABSTRACT: Aerosols act as cloud condensation nuclei (CCN) for cloud water droplets, and changes in aerosol concentrations have significant microphysical impacts on the corresponding cloud properties. Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol and cloud properties are combined with NCEP Reanalysis data for six different regions around the globe between March 2000 and December 2005 to study the effects of different aerosol, cloud, and atmospheric conditions on the aerosol indirect effect (AIE). Emphasis is placed in examining the relative importance of aerosol concentration, type, and atmospheric conditions (mainly vertical motion) to AIE from region to region. Results show that in most regions, AIE has a distinct seasonal cycle, though the cycle varies in significance and period from region to region. In the Arabian Sea (AS), the six-year mean anthropogenic + dust AIE is -0.27 Wm-2 and is greatest during the summer months (
    Atmospheric Chemistry and Physics 01/2009; · 4.88 Impact Factor
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    ABSTRACT: A global aerosol model with relatively high resolution is used to simulate the distribution and radiative effect of aerosols during the Aerosol Direct Radiative Impact Experiment (ADRIEX) campaign in August and September 2004. The global chemical transport model Oslo CTM2 includes detailed chemistry, which is coupled to aerosol partitioning of sulphate, nitrate and secondary organic aerosols. In accordance with aircraft observations the aerosol model simulates a dominance of secondary aerosols compared to primary aerosols in the ADRIEX study region. The model underestimates the aerosol optical depth (AOD) at 550 nm in the main region of the campaign around Venice. This underestimation mainly occurs during a 3–4 day period of highest AODs. At two AERONET (Aerosol Robotic Network) stations related to the ADRIEX campaign outside the Po valley area, the model compares very well with the observed AOD. Comparisons with observed chemical composition show that the model mainly underestimates organic carbon, with better agreement for other aerosol species. The model simulations indicate that the emission of aerosols and their precursors may be underestimated in the Po valley. Recent results show a large spread in radiative forcing due to the direct aerosol effect in global aerosol models, which is likely linked to large differences in the vertical profile of aerosols and aerosol absorption. The modelled vertical profile of aerosol compares reasonably well to the aircraft measurements as was the case in two earlier campaigns involving biomass burning and dust aerosols. The radiative effect of aerosols over the northern part of the Adriatic Sea agrees well with the mean of three satellite-derived estimates despite large differences between the satellite-derived data. The difference between the model and the mean of the satellite data is within 10% for the radiative effect. The radiative forcing due to anthropogenic aerosols is simulated to be negative in the ADRIEX region with values between − 5 and − 2 W m−2. Copyright © 2008 Royal Meteorological Society
    Quarterly Journal of the Royal Meteorological Society 12/2008; 135(638):53 - 66. · 3.33 Impact Factor
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    T.A. Jones, S.A. Christopher
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    ABSTRACT: Applying principal component analysis (PCA) to one month of Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band short-wave radiance data and comparing with the Goddard Global Ozone Chemistry Aerosol Radiation Transport (GOCART) model simulations, we show that aerosol size and speciation information can be inferred from multispectral radiance information without having to use other parameters, such as a fine mode fraction (FMF), that are difficult to validate. PCA was applied to seven highly correlated MODIS solar channels (0.47, 0.55, 0.66, 0.86, 1.24, 1.64, and 2.12 mum) to extract noncorrelated pseudochannels, each with a unique interpretation. The first pseudochannel (PCI) can be interpreted as the mean radiance across the seven channels, which is directly proportional to the aerosol concentration. The second pseudochannel (PC2) is sensitive to the aerosol size since different aerosol types scatter and absorb differently across the seven MODIS short-wave channels. PC3 is inversely related to the aerosol optical thickness (AOT) and the FMF and appears most sensitive to changes in sulfate and maritime sea-salt concentrations. Results indicate that high values of PCI are indicative of high dust aerosol concentrations comprising more than 40% of the total AOT, whereas high values of PC2 indicate anthropogenic aerosol concentrations (deduced from GOCART) in excess of 60%. Compared to simple 0.55-mum FMF thresholds, the PC channels are much more sensitive to dust aerosol concentrations and certain aspects of anthropogenic aerosols, with very low FMF values alone (< 0.2) being the best indicator of predominately sea-salt aerosol concentrations. Our results indicate that PCA could be used as an alternate method for inferring aerosol speciation information in future research over ocean and more complex land surfaces.
    IEEE Transactions on Geoscience and Remote Sensing 10/2008; · 3.47 Impact Factor
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    S.A. Christopher, T.A. Jones
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    ABSTRACT: Satellite-based methods for estimating the top-of-atmosphere shortwave direct radiative effect (SWRE) either use the spatial distribution of aerosol optical thickness (AOT) coupled with radiative transfer calculations or combine the AOT with broadband radiative energy data sets such as the Clouds and the Earth's Radiant Energy System (CERES). The first approach typically utilizes the AOT at a spatial resolution of from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the second method relies on the same AOT, but it is convolved within the CERES footprint and has spatial resolutions that are greater than . Therefore, the SWRE may vary as a result of this difference in spatial resolution that we call sample bias. We correct for this sample bias using the AOT reported at the MODIS and the CERES product levels coupled with the radiative efficiency (SWRE per-unit optical depth) for 13 regions over the ocean as a function of season between December 2003 and November 2004 and demonstrate that the sample biases are seasonally and spatially dependent. Overall, nearly 75% of the pixels over the global oceans require a sample bias adjustment of some form. However, the adjustment is large , which is less than 7% of the time, primarily during the spring and summer months, in association with large dust aerosol concentrations with large optical depth gradients. If sample biases are not accounted for, they will globally reduce the SWRE by an average of 30% (4.1 versus ), although regionally, the adjustment could be larger (). We argue that these bias corrections are robust and simpler to use when compared with methods that employ narrow- to broadband relationships.
    IEEE Transactions on Geoscience and Remote Sensing 07/2008; · 3.47 Impact Factor
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    S.A. Christopher, T.A. Jones
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    ABSTRACT: Using one year of moderate resolution imaging spectroradiometer (MODIS) and clouds and the Earth's radiant energy system (CERES) data, we provide a satellite-based assessment of top-of-atmosphere (TOA) cloud-free shortwave and longwave dust radiative effects over global oceans from the Terra satellite. Over global cloud-free oceans, the dust net radiative effect is -0.7 plusmn0.2 W middotm<sup>-2</sup>, and the TOA dust shortwave radiative effect (SWRE) dominates the longwave radiative effect (LWRE). Globally, the annual mean dust contribution to the total MODIS level 2 aerosol optical thickness (AOT, at 550 nm) is about 30% with a dust SWRE of -0.7 plusmn0.2 W middotm<sup>-2</sup> and LWRE of 0.03 plusmn0.02 W middotm<sup>-2</sup>. Averaged over all seasons, the cloud-free diurnal mean dust radiative efficiency is -33 plusmn5 W middotm<sup>-2</sup> middottau<sup>-1</sup>, and there is a remarkable linear relationship between the CERES SWRE and the MODIS AOT. This is the first satellite-based assessment of dust net radiative effect over the global oceans and will serve as a useful constraint for numerical modeling analysis.
    IEEE Geoscience and Remote Sensing Letters 02/2008; · 1.82 Impact Factor
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    ABSTRACT: A high-resolution global aerosol model (Oslo CTM2) driven by meteorological data and allowing a comparison with a variety of aerosol observations is used to simulate radiative forcing (RF) of the direct aerosol effect. The model simulates all main aerosol components, including several secondary components such as nitrate and secondary organic carbon. The model reproduces the main chemical composition and size features observed during large aerosol campaigns. Although the chemical composition compares best with ground-based measurement over land for modelled sulphate, no systematic differences are found for other compounds. The modelled aerosol optical depth (AOD) is compared to remote sensed data from AERONET ground and MODIS and MISR satellite retrievals. To gain confidence in the aerosol modelling, we have tested its ability to reproduce daily variability in the aerosol content, and this is performing well in many regions; however, we also identified some locations where model improvements are needed. The annual mean regional pattern of AOD from the aerosol model is broadly similar to the AERONET and the satellite retrievals (mostly within 10–20%). We notice a significant improvement from MODIS Collection 4 to Collection 5 compared to AERONET data. Satellite derived estimates of aerosol radiative effect over ocean for clear sky conditions differs significantly on regional scales (almost up to a factor two), but also in the global mean. The Oslo CTM2 has an aerosol radiative effect close to the mean of the satellite derived estimates. We derive a radiative forcing (RF) of the direct aerosol effect of −0.35 Wm−2 in our base case. Implementation of a simple approach to consider internal black carbon (BC) mixture results in a total RF of −0.28 Wm−2. Our results highlight the importance of carbonaceous particles, producing stronger individual RF than considered in the recent IPCC estimate; however, net RF is less different. A significant RF from secondary organic aerosols (SOA) is estimated (close to −0.1 Wm−2). The SOA also contributes to a strong domination of secondary aerosol species for the aerosol composition over land. A combination of sensitivity simulations and model evaluation show that the RF is rather robust and unlikely to be much stronger than in our best estimate.
    Atmospheric Chemistry and Physics 01/2008; · 4.88 Impact Factor
  • T. A. Jones, S. A. Christopher
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    ABSTRACT: Using 6 years of combined Terra CERES radiance and MODIS aerosol data, we compute the global, ocean-only, shortwave (SW) and longwave (LW) radiative effect (SWRE, LWRE) for dust and anthropogenic aerosols. We will first use MODIS derived aerosol size properties to broadly classify aerosols into either sea salt, dust, or anthropogenic categories. We then use the quasi-linear relationship between SW flux and aerosol optical thickness (AOT) to derive a clear sky, aerosol free SW background. Since this relationship does not exist for LW, only pixels with low AOT are used to derive an aerosol-free LW background. Total aerosol SWRE and LWRE are calculated by subtracting the observed flux values from the clear sky background. SWRE and LWRE from individual aerosol components are then calculated using applying the ratio of the AOT from an individual aerosol species to the total AOT on a pixel-by-pixel basis. The uncertainties in the aerosol classifications will be applied to the individual SWRE and LWRE statistics to determine the overall uncertainty of individual aerosol radiative effect and the significance of differences in this effect from one aerosol species to another. Preliminary results indicate that globally averaged values for individual aerosol SWRE may not be representative of their true importance. Averaged over the entire ocean-only global, SWRE from anthropogenic sources exceeds dust SWRE by a factor of nearly 2. However, dust and anthropogenic SWRE are often maximized in certain regions during certain times of the year, are negligible elsewhere. As a result, we quantify SWRE on smaller regional and temporal scales to better examine the relationship between each. Similarly, LWRE does not appear to be significant on a globally averaged basis, but can offset SWRE up to 20 percent in high AOT, dust regions.
    AGU Fall Meeting Abstracts. 12/2007;
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    T. A. Jones, S. A. Christopher
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    ABSTRACT: The statistical variability of globally averaged MODIS aerosol optical thickness at 0.55 μm (AOT) and top of atmosphere CERES cloud-free shortwave radiative effect (SWRE) is presented. Statistical variability is defined as the robustness of globally averaged statistics relative to data distribution. At the CERES footprint level, which we label "raw data", both the AOT and SWRE data derived from clear-sky CERES-SSF products show significant deviations from a normal distribution as evidenced by high skewness values. The spatial and temporal distribution of the data is also not uniform, with a greater concentration of data occurring in aerosol heavy-regions. As a result, globally averaged AOT and SWRE are overestimated when derived from raw data alone. To compensate, raw data are gridded into 2×2 degree grid-cells (called "gridded" data) to reduce the effect of spatial non-uniformity. However, the underlying non-normal distribution remains and manifests itself by increasing the uncertainty of grid-cell values. Globally averaged AOT and SWRE derived from a gridded dataset are substantially lower than those derived from raw data alone. The range of globally averaged AOT and SWRE values suggests that up to a 50% statistical variability exists, much of which is directly tied to how the data are manipulated prior to averaging. This variability increases when analyzing aerosol components (e.g. anthropogenic) since component AOT (and SWRE) may not exist at all locations were AOT is present. As a result, regions where a particular component AOT does not exist must either not be included in the global average or have data within these regions set to null values. However, each method produces significantly different results. The results of this work indicate simple mean and standard deviation statistics do not adequately describe global aerosol climate forcing data sets like the one used here. We demonstrate that placing raw observations on to a uniform grid is a necessary step before calculating global statistics. However, this by no means eliminates uncertainty in globally averaged AOT and SWRE values, while adding its own set of assumptions. When reporting any globally averaged statistic, it is important to report corresponding distribution and coverage information, in the form of skewness values, probability density functions, and spatial distribution plots, to help quantify its usefulness and robustness.
    ATMOSPHERIC CHEMISTRY AND PHYSICS 01/2007; · 5.51 Impact Factor
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    T. A. Jones, S. A. Christopher
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    ABSTRACT: The statistical uncertainty of globally averaged MODIS aerosol optical thickness at 0.55 μm (AOT) and top of atmosphere CERES cloud-free shortwave radiative effect (SWRE) is presented. All analysis is presented at the CERES footprint level which we call "raw data". Statistical uncertainty may result from the raw data not being normally distributed. Both the AOT and SWRE data derived from clear-sky CERES-SSF products show significant deviations from a normal distribution as evidenced by high skewness values. The spatial and temporal distribution of the data is also not uniform, with a greater concentration of data being in aerosol heavy regions. As a result, globally averaged AOT and SWRE are overestimated when derived from raw data. Raw data are gridded into 2×2 degree grid-cells (called "gridded" data) to reduce the effect of spatial non-uniformity. However, the underlying non-normal distribution remains and manifests itself by increasing the uncertainty of grid-cell values. Globally averaged AOT and SWRE derived from a gridded dataset are substantially lower than those derived from raw data alone. The range of globally averaged AOT and SWRE values suggests that up to a 50% statistical uncertainty exists, much of which is directly tied to how the data are manipulated prior to averaging. This uncertainty increases when analyzing aerosol components (e.g. anthropogenic) since component AOT (and SWRE) may not exist at all locations were AOT is present. As a result, regions where a particular component AOT does not exist must either not be included in the global average or have data within these regions set to null values. However, each method produces significantly different results. The results of this work indicate that placing raw observations on to a uniform grid is a necessary step before calculating global statistics. However, this by no means eliminates statistical uncertainty, while adding its own set of assumptions. When reporting any globally averaged statistic, it is important to report corresponding distribution and coverage information, in the form of skewness values, probability density functions, and spatial distribution plots, to help quantify its usefulness and robustness.
    Atmospheric Chemistry and Physics 01/2007; · 4.88 Impact Factor