Papers by Sarika Kulkarni
The largest uncertainty in the radiative forcing of climate change over the industrial era is tha... more The largest uncertainty in the radiative forcing of climate change over the industrial era is that due to aerosols, a substantial fraction of which is the uncertainty associated with scattering and absorption of shortwave (solar) radiation by anthropogenic aerosols in cloud-free conditions [IPCC, 2001]. Quantifying and reducing the uncertainty in aerosol influences on climate is critical to understanding climate change over the industrial period and to improving predictions of future climate change for assumed emission scenarios. Measurements of aerosol properties during major field campaigns in several regions of the globe during the past decade are contributing to an enhanced understanding of atmospheric aerosols and their effects on light scattering and climate. The present study, which focuses on three regions downwind of major urban/population centers (North Indian Ocean (NIO) during INDOEX, the Northwest Pacific Ocean (NWP) during ACE-Asia, and the Northwest Atlantic Ocean (NWA) during ICARTT), incorporates understanding gained from field observations of aerosol distributions and properties into calculations of perturbations in radiative fluxes due to these aerosols. This study evaluates the current state of observations and of two chemical transport models (STEM and MOZART). Measurements of burdens, extinction optical depth (AOD), and direct radiative effect of aerosols (DRE-change in radiative flux due to total aerosols) are used as measurement-model check points to assess uncertainties. In-situ measured and remotely sensed aerosol properties for each region (mixing state, mass scattering efficiency, single scattering albedo, and angular scattering properties and their dependences on relative humidity) are used as input parameters to two radiative transfer models (GFDL and University of Michigan) to constrain estimates of aerosol radiative effects, with uncertainties in each step propagated through the analysis. Constraining the radiative transfer calculations by observational inputs increases the AOD (34±8%), top of atmosphere (TOA) DRE (32±12%), and TOA direct climate forcing of aerosols (DCFchange in radiative flux due to anthropogenic aerosols) (37±7%) relative to values obtained with "a priori" parameterizations of aerosol loadings and properties (GFDL RTM). The resulting constrained TOA DCF is-3.3±0.47,-14±2.6,-6.4±2.1 W m-2 for the NIO, NWP, and NWA, respectively. Constraining the radiative transfer calculations by observational inputs reduces the uncertainty range in the DCF in these regions relative to global IPCC [2001] estimates by a factor of approximately 3. Such comparisons with observations and resultant reductions in uncertainties are essential for improving and developing confidence in climate model calculations incorporating aerosol forcing. ΔF = ε A τ A + ε B τ B (2) is expected to hold. This relation is the basis of use of forcing efficiency as a measurable aerosol property that can be compared with observations and used to constrain estimates of DRE and DCF. We note, however, that non-linearities can be important in global-mean calculations. Aerosol properties have been intensely measured over several regions of the globe in major international field campaigns conducted during the past decade [Yu et al., 2005]. These measurements provide in-situ and remotely sensed aerosol data that can be used in calculations of aerosol distributions and their radiative effects. The present study examines DRE and DCF over the North Indian, northwestern Pacific, and northwestern Atlantic Oceans (Figure 2 and Table 1). These regions are selected because of the large anthropogenic aerosol sources upwind of these ocean basins and the availability of suitable measurement data sets: North Indian Ocean (1999-INDOEX); northwestern Pacific Ocean (2001-ACE-Asia and TRACE-P]); and northwestern Atlantic Ocean (2002-NEAQS; 2004-ICARTT). Aerosol concentrations and their radiative impacts are particularly large in these regions, with diurnally averaged clear-sky surface DRE as great as-30 Wm-2 [Russell et al., 1999; Ramanathan et al., 2001; Conant et al., 2003]; here the negative sign denotes a decrease in the net incoming radiative flux to Earth. Restriction of the examination to ocean areas, which are characterized by low surface reflectance, minimizes the influence of uncertainty in this reflectance. This study summarizes in-situ data from these regions from the above named campaigns (Sections 3), compares the data from these campaigns with available longer term monitoring data (Sections 3), compares the chemical data from the intensive campaigns with results of CTM calculations (Section 4), and uses the CTM distributions and in-situ measured aerosol optical properties in RTMs to calculate regional aerosol optical depth, DRE, DCF, and aerosol radiative efficiency (forcing per unit optical depth) (section 5). This analysis is one of three aerosol-related studies being prepared for the Climate Change
The largest uncertainty in the radiative forcing of climate change over the industrial era is tha... more The largest uncertainty in the radiative forcing of climate change over the industrial era is that due to aerosols, a substantial fraction of which is the uncertainty associated with scattering and absorption of shortwave (solar) radiation by anthropogenic aerosols in cloud-free conditions [IPCC, 2001]. Quantifying and reducing the uncertainty in aerosol influences on climate is critical to understanding climate change over the industrial period and to improving predictions of future climate change for assumed emission scenarios. Measurements of aerosol properties during major field campaigns in several regions of the globe during the past decade are contributing to an enhanced understanding of atmospheric aerosols and their effects on light scattering and climate. The present study, which focuses on three regions downwind of major urban/population centers (North Indian Ocean (NIO) during INDOEX, the Northwest Pacific Ocean (NWP) during ACE-Asia, and the Northwest Atlantic Ocean (NWA) during ICARTT), incorporates understanding gained from field observations of aerosol distributions and properties into calculations of perturbations in radiative fluxes due to these aerosols. This study evaluates the current state of observations and of two chemical transport models (STEM and MOZART). Measurements of burdens, extinction optical depth (AOD), and direct radiative effect of aerosols (DRE-change in radiative flux due to total aerosols) are used as measurement-model check points to assess uncertainties. In-situ measured and remotely sensed aerosol properties for each region (mixing state, mass scattering efficiency, single scattering albedo, and angular scattering properties and their dependences on relative humidity) are used as input parameters to two radiative transfer models (GFDL and University of Michigan) to constrain estimates of aerosol radiative effects, with uncertainties in each step propagated through the analysis. Constraining the radiative transfer calculations by observational inputs increases the AOD (34±8%), top of atmosphere (TOA) DRE (32±12%), and TOA direct climate forcing of aerosols (DCFchange in radiative flux due to anthropogenic aerosols) (37±7%) relative to values obtained with "a priori" parameterizations of aerosol loadings and properties (GFDL RTM). The resulting constrained TOA DCF is-3.3±0.47,-14±2.6,-6.4±2.1 W m-2 for the NIO, NWP, and NWA, respectively. Constraining the radiative transfer calculations by observational inputs reduces the uncertainty range in the DCF in these regions relative to global IPCC [2001] estimates by a factor of approximately 3. Such comparisons with observations and resultant reductions in uncertainties are essential for improving and developing confidence in climate model calculations incorporating aerosol forcing. ΔF = ε A τ A + ε B τ B (2) is expected to hold. This relation is the basis of use of forcing efficiency as a measurable aerosol property that can be compared with observations and used to constrain estimates of DRE and DCF. We note, however, that non-linearities can be important in global-mean calculations. Aerosol properties have been intensely measured over several regions of the globe in major international field campaigns conducted during the past decade [Yu et al., 2005]. These measurements provide in-situ and remotely sensed aerosol data that can be used in calculations of aerosol distributions and their radiative effects. The present study examines DRE and DCF over the North Indian, northwestern Pacific, and northwestern Atlantic Oceans (Figure 2 and Table 1). These regions are selected because of the large anthropogenic aerosol sources upwind of these ocean basins and the availability of suitable measurement data sets: North Indian Ocean (1999-INDOEX); northwestern Pacific Ocean (2001-ACE-Asia and TRACE-P]); and northwestern Atlantic Ocean (2002-NEAQS; 2004-ICARTT). Aerosol concentrations and their radiative impacts are particularly large in these regions, with diurnally averaged clear-sky surface DRE as great as-30 Wm-2 [Russell et al., 1999; Ramanathan et al., 2001; Conant et al., 2003]; here the negative sign denotes a decrease in the net incoming radiative flux to Earth. Restriction of the examination to ocean areas, which are characterized by low surface reflectance, minimizes the influence of uncertainty in this reflectance. This study summarizes in-situ data from these regions from the above named campaigns (Sections 3), compares the data from these campaigns with available longer term monitoring data (Sections 3), compares the chemical data from the intensive campaigns with results of CTM calculations (Section 4), and uses the CTM distributions and in-situ measured aerosol optical properties in RTMs to calculate regional aerosol optical depth, DRE, DCF, and aerosol radiative efficiency (forcing per unit optical depth) (section 5). This analysis is one of three aerosol-related studies being prepared for the Climate Change
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Papers by Sarika Kulkarni