Inverse Methods: a Powerful Tool for Evaluating Aerosol Data, Exemplified on Cases With Relevance for the Atmosphere and the Aerosol Climate Effect

For a complete description of a given aerosol, more than one parameter is necessary, e.g. parameters concerning size distribution, chemical composition, and particle morphology. On the other hand, most instruments measuring aerosol properties are sensitive mostly to one parameter, but cross-sensitive to others. These cross-sensitivities are often eliminated by assumptions during data evaluation, inducing systematic uncertainties in the results. The use of assumptions can be reduced by combining the information of several instruments on the same aerosol and using inverse methods for interpretation of the data. The presentation focuses on two application examples of these methods. The first example concerns a size distribution inversion algorithm that combines data from several instruments into one size distribution. The second example deals with an algorithm that retrieves the aerosol asymmetry parameter (with respect to particle scattering) from measurements of the aerosol absorption and spectral scattering and hemispheric backscattering coefficients, thereby providing a set of parameters that completely describes an aerosol with respect to its direct climate effect

Scientific Objectives, Measurement Needs, and Challenges Motivating the PARAGON Aerosol Initiative

Aerosols are involved in a complex set of processes that operate across many spatial and temporal scales. Understanding these processes, and ensuring their accurate representation in models of transport, radiation transfer, and climate, requires knowledge of aerosol physical, chemical, and optical properties and the distributions of these properties in space and time. To derive aerosol climate forcing, aerosol optical and microphysical properties and their spatial and temporal distributions, and aerosol interactions with clouds, need to be understood. Such data are also required in conjunction with size-resolved chemical composition in order to evaluate chemical transport models and to distinguish natural and anthropogenic forcing. Other basic parameters needed for modeling the radiative influences of aerosols are surface reflectivity and three-dimensional cloud fields. This large suite of parameters mandates an integrated observing and modeling system of commensurate scope. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) concept, designed to meet this requirement, is motivated by the need to understand climate system sensitivity to changes in atmospheric constituents, to reduce climate model uncertainties, and to analyze diverse collections of data pertaining to aerosols. This paper highlights several challenges resulting from the complexity of the problem. Approaches for dealing with them are offered in the set of companion papers

Aerosol Data Sources and Their Roles within PARAGON

We briefly but systematically review major sources of aerosol data, emphasizing suites of measurements that seem most likely to contribute to assessments of global aerosol climate forcing. The strengths and limitations of existing satellite, surface, and aircraft remote sensing systems are described, along with those of direct sampling networks and ship-based stations. It is evident that an enormous number of aerosol-related observations have been made, on a wide range of spatial and temporal sampling scales, and that many of the key gaps in this collection of data could be filled by technologies that either exist or are expected to be available in the near future. Emphasis must be given to combining remote sensing and in situ active and passive observations and integrating them with aerosol chemical transport models, in order to create a more complete environmental picture, having sufficient detail to address current climate forcing questions. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) initiative would provide an organizational framework to meet this goal

Reply to ''Comments on 'Why Hasn't Earth Warmed as much as Expected?'''

In response to our article, Why Hasnt Earth Warmed as Much as Expected? (2010), Knutti and Plattner (2012) wrote a rebuttal. The term climate sensitivity is usually defined as the change in global mean surface temperature that is produced by a specified change in forcing, such as a change in solar heating or greenhouse gas concentrations. We had argued in the 2010 paper that although climate models can reproduce the global mean surface temperature history over the past century, the uncertainties in these models, due primarily to the uncertainty in climate forcing by airborne particles, mean that the models lack the confidence to actually constrain the climate sensitivity within useful limits for climate prediction. Knutti and Plattner are climate modelers, and they argued essentially that because the models could reproduce the surface temperature history, the issue we raised was moot. Our response amounts to straightening out this confusion; for the models to be constraining, they must be able to reproduce the surface temperature history with sufficient confidence, not just to match the measurements, but to exclude alternative histories. As before, we concluded that if we can actually make the aerosol measurements using currently available, state-of-the-art techniques, we can determine the aerosol climate forcing to the degree required to constrain that aspect of model climate sensitivity. A technical issue relating to the timescale over which a change in CO2 emissions would be equilibrated in the environmental energy balance was also discussed, again, a matter of differences in terminology

Cloud-Driven Changes in Aerosol Optical Properties - Final Technical Report

The optical properties of aerosol particles are the controlling factors in determining direct aerosol radiative forcing. These optical properties depend on the chemical composition and size distribution of the aerosol particles, which can change due to various processes during the particles’ lifetime in the atmosphere. Over the course of this project we have studied how cloud processing of atmospheric aerosol changes the aerosol optical properties. A counterflow virtual impactor was used to separate cloud drops from interstitial aerosol and parallel aerosol systems were used to measure the optical properties of the interstitial and cloud-scavenged aerosol. Specifically, aerosol light scattering, back-scattering and absorption were measured and used to derive radiatively significant parameters such as aerosol single scattering albedo and backscatter fraction for cloud-scavenged and interstitial aerosol. This data allows us to demonstrate that the radiative properties of cloud-processed aerosol can be quite different than pre-cloud aerosol. These differences can be used to improve the parameterization of aerosol forcing in climate models

Cloud Scavenging Effects on Aerosol Radiative and Cloud-nucleating Properties - Final Technical Report

The optical properties of aerosol particles are the controlling factors in determining direct aerosol radiative forcing. These optical properties depend on the chemical composition and size distribution of the aerosol particles, which can change due to various processes during the particles’ lifetime in the atmosphere. Over the course of this project we have studied how cloud processing of atmospheric aerosol changes the aerosol optical properties. A counterflow virtual impactor was used to separate cloud drops from interstitial aerosol and parallel aerosol systems were used to measure the optical properties of the interstitial and cloud-scavenged aerosol. Specifically, aerosol light scattering, back-scattering and absorption were measured and used to derive radiatively significant parameters such as aerosol single scattering albedo and backscatter fraction for cloud-scavenged and interstitial aerosol. This data allows us to demonstrate that the radiative properties of cloud-processed aerosol can be quite different than pre-cloud aerosol. These differences can be used to improve the parameterization of aerosol forcing in climate models

Development of Aerosol Models for Radiative Flux Calculations at ARM Sites

The direct radiative forcing (DRF) of aerosols, the change in net radiative flux due to aerosols in non-cloudy conditions, is an essential quantity for understanding the human impact on climate change. Our work has addressed several key issues that determine the accuracy, and identify the uncertainty, with which aerosol DRF can be modeled. These issues include the accuracy of several radiative transfer models when compared to measurements and to each other in a highly controlled closure study using data from the ARM 2003 Aerosol IOP. The primary focus of our work has been to determine an accurate approach to assigning aerosol properties appropriate for modeling over averaged periods of time and space that represent the observed regional variability of these properties. We have also undertaken a comprehensive analysis of the aerosol properties that contribute most to uncertainty in modeling aerosol DRF, and under what conditions they contribute the most uncertainty. Quantification of these issues enables the community to better state accuracies of radiative forcing calculations and to concentrate efforts in areas that will decrease uncertainties in these calculations in the future

An Integrated Approach for Characterizing Aerosol Climate Impacts and Environmental Interactions

Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the long-term benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, inter-agency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality

Temporal Variation of Aerosol Properties at a Rural Continental Site and Study of Aerosol Evolution through Growth Law Analysis

Aerosol size distributions were measured by a Scanning Mobility Particle Sizer (SMPS) onboard the CIRPAS Twin Otter aircraft during 16 flights at the Southern Great Plains (SGP) site in northern central Oklahoma as part of the Aerosol Intensive Operation period in May, 2003. During the same period a second SMPS was deployed at a surface station and provided continuous measurements. Combined with trace gas measurements at the SGP site and back-trajectory analysis, the aerosol size distributions provided insights into the sources of aerosols observed at the SGP site. High particle concentrations, observed mostly during daytime, were well correlated with the sulfur dioxide (SO2) mixing ratios, suggesting nucleation involving sulfuric acid is likely the main source of newly formed particles at the SGP. Aerosols within plumes originating from wildfires in Central America were measured at the surface site. Vertically compact aerosol layers, which can be traced back to forest fires in East Asia, were intercepted at altitudes over 3000 meters. Analyses of size dependent particle growth rates for four periods during which high cloud coverage was observed indicate growth dominated by volume controlled reactions. Sulfate accounts for 50% to 72% of the increase in aerosol volume concentration; the rest of the volume concentration increase was likely due to secondary organic species. The growth law analyses and meteorological conditions indicate that the sulfate was produced mainly through aqueous oxidation of SO2 in clouds droplets and hydrated aerosol particles

On Aethalometer measurement uncertainties and an instrument correction factor for the Arctic

Several types of filter-based instruments are used to estimate aerosol light absorption coefficients. Two significant results are presented based on Aethalometer measurements at six Arctic stations from 2012 to 2014. First, an alternative method of post-processing the Aethalometer data is presented, which reduces measurement noise and lowers the detection limit of the instrument more effectively than box-car averaging. The biggest benefit of this approach can be achieved if instrument drift is minimised. Moreover, by using an attenuation threshold criterion for data post-processing, the relative uncertainty from the electronic noise of the instrument is kept constant. This approach results in a time series with a variable collection time (Delta t) but with a constant relative uncertainty with regard to electronic noise in the instrument. An additional advantage of this method is that the detection limit of the instrument will be lowered at small aerosol concentrations at the expense of temporal resolution, whereas there is little to no loss in temporal resolution at high aerosol concentrations (>2.1-6.7Mm(-1) as measured by the Aethalometers). At high aerosol concentrations, minimising the detection limit of the instrument is less critical. Additionally, utilising co-located filter-based absorption photometers, a correction factor is presented for the Arctic that can be used in Aethalometer corrections available in literature. The correction factor of 3.45 was calculated for low-elevation Arctic stations. This correction factor harmonises Aethalometer attenuation coefficients with light absorption coefficients as measured by the co-located light absorption photometers. Using one correction factor for Arctic Aethalometers has the advantage that measurements between stations become more inter-comparable.Peer reviewe