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India, home to a fifth of the world's population, employs a far-ranging spectrum of polluting technologies and fuels with societal consequences. Important gaps remain, however, in understanding human activities influencing [...]

ABSTRACTS The Gradient in Longitude of Atmospheric Constituents above the Mediterranean Basin (GLAM) airborne campaign was set up to investigate the summertime variability of gaseous pollutants, greenhouse gases, and aerosols [...]

Aerosols are known to cool the atmosphere, but much less is established about the magnitude of their forcing and climate effects. Understanding how aerosols oxidize in the atmosphere is an [...]

Mixed-phase stratus clouds are ubiquitous in the Arctic and play an important role in climate in this region. However, climate and regional models have generally proven unsuccessful at simulating Arctic cloudiness, particularly during the colder months. Specifically, models tend to underpredict the amount of liquid water in mixed-phase clouds. The Mixed-Phase Arctic Cloud Experiments (M-PACE), conducted from late September through October 2004 in the vicinity of the Department of Energy's Atmospheric Radiation Measurement (ARM) North Slope of Alaska field site, focused on characterizing low-level Arctic stratus clouds. Ice nuclei (IN) measurements were made using a continuous-flow ice thermal diffusion chamber aboard the University of North Dakota's Citation II aircraft. These measurements indicated IN concentrations that were significantly lower than those used in many models. Using the Regional Atmospheric Modeling System (RAMS), we show that these low IN concentrations, as well as inadequate parameterizations of the depletion of IN through nucleation scavenging, may be partially responsible for the poor model predictions. Moreover, we show that this can lead to errors in the modeled surface radiative energy budget of 10-100 W [m.sup.-2]. Finally, using the measured IN concentrations as input to RAMS and comparing to a mixed-phase cloud observed during M-PACE, we show excellent agreement between modeled and observed liquid water content and net infrared surface flux. (Page 541)

Assessments of the influence of aerosol emissions from human activities on the radiation budget, in particular via the modification of cloud properties, have been a challenge. In light of the variability to both aerosol properties and environmental properties affected by aerosols, observational evidence alone cannot provide accurate and global answers, because detailed observations are locally limited and/or lack statistical significance. Thus, current understanding is predominantly derived from simulations with global models. General discrepancies to envelope (backward) modeling, however, suggest that many aerosol processes in global (forward) modeling are not properly considered. Using analytically derived parameterizations is recommended wherever possible. If an analytical method does not exist or is too demanding computationally, laboratory results augmented by field data are the second-best approach. For the constraint of so-derived parameterizations at the GCM scale, evaluating individual parameterizations using statistical relationships of satellite-retrieved quantities relevant to the process is recommended. The set of parameterizations may also be evaluated and improved using the data assimilation technique. To improve the quality of data references to modeling, there is a need to link available atmospheric data from all scales, and establish and support validation networks and experiments, and a commitment to fine-tune and improve satellite retrievals in an iterative process even beyond the anticipated period of the mission. Only then can more reliable estimates of the indirect aerosol effect be expected.

This document outlines a practical strategy for achieving an observationally based quantification of direct climate forcing by anthropogenic aerosols. The strategy involves a four-step program for shifting the current assumption-laden estimates to an increasingly empirical basis using satellite observations coordinated with suborbital remote and in situ measurements and with chemical transport models. Conceptually, the problem is framed as a need for complete global mapping of four parameters: clear-sky aerosol optical depth [delta], radiative efficiency per unit optical depth E, fine-mode fraction of optical depth [f.sub.f], and the anthropogenic fraction of the fine mode [f.sub.af] The first three parameters can be retrieved from satellites, but correlative, suborbital measurements are required for quantifying the aerosol properties that control E, for validating the retrieval of [f.sub.f], and for partitioning fine-mode [delta] between natural and anthropogenic components. The satellite focus is on the 'A-Train,' a constellation of six spacecraft that will fly in formation from about 2005 to 2008. Key satellite instruments for this report are the Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) radiometers on Aqua, the Ozone Monitoring Instrument (OMI) radiometer oil Aura, the Polarization and Directionality of Earth's Reflectances (POLDER) polarimeter on the Polarization and Anistropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL), and the Cloud and Aerosol Lider with Orthogonal Polarization (CALIOP) lidar on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). This strategy is offered as an initial framework--subject to improvement over time--for scientists around the world to participate in the A-Train opportunity. It is a specific implementation of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) program, presented earlier in this journal, which identified the integration of diverse data as the central challenge to progress in quantifying global-scale aerosol effects. By designing a strategy around this need for integration, we develop recommendations for both satellite data interpretation and correlative suborbital activities that represent, in many respects, departures from current practice.

The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol retrieval algorithm was developed to derive aerosol properties at a global scale, suitable for climate studies. Under favorable conditions (clear sky and over dark surfaces), the standard 10 x 10 km MODIS aerosol products are also useful on regional scales to monitor aerosol distributions and transports. However, the 10-km resolution is insufficient to depict aerosol variation on local or urban scales, due to inherent aerosol variability as well as complex surface terrain. In this study, we have modified the MODIS algorithm to retrieve aerosol optical depth (AOD) at 1-km resolution over Hong Kong, a city of just over 1000 [km.sup.2] with very complex surface features. Accompanied by the increased spatial resolution are new aerosol models derived with single-scattering albedo (SSA) around 0.91-0.94 to accommodate higher aerosol absorption encountered in Hong Kong than that was presumed for MODIS standard products (SSA ~ 0.97) over the region. The derived AOD data are compared to handheld Microtops II sunphotometer observations at the Hong Kong University of Science and Technology and other locations across Hong Kong. Retrieval errors within 15% to 20% of sunphotometer measurements are found. Moreover, when compared with the standard 10-km AOD products, the 1-km AOD data are much better correlated with P[M.sub.10] measurements across Hong Kong, suggesting that the new 1-km AOD data can be used to better characterize the particulate matter distribution for cities like Hong Kong than the MODIS standard products. Index Terms--Aerosols, air pollution, remote sensing.

We use data from the Muitispectral Thermal Imager (MTI) to evaluate the effects of spatial resolution on the accuracy of aerosol optical depth (AOD) retrieval. Our results show that increasing the pixel size by itself has little effect on AOD retrieval accuracy at our chosen study site. However, increased pixel size does increase the error in AOD retrieval as a result of clouds. High-resolution sensors like MTI are able to avoid most clouds, but as the pixel size increases, subpixel clouds avoid the cloud mask, creep into selected pixels, and add a positive bias to the retrieved value of AOD. In accompanying work, we show that increasing pixel size has a small but noticeable impact on the normalized difference vegetation index (NDVI) and the 2.2-[micro]m reflectance, both used in the retrieval algorithm. We also examine the uniformity of the aerosol layer and show that the AOD varies by less than 0.02 in optical depth units over a 2.3 x 3.8 [km.sup.2] area. An analysis of the temporal variability of Aerosol Robotic Network-retrieved AOD shows a standard deviation of 0.02 on partly cloudy days and 0.004 on clear days. Index Terms--Aerosols, multispectral, Multispectral Thermal Imager (MT1), resolution, satellite.

The accuracy of the spaceborne Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask was evaluated for possible contamination by areas of heavy aerosol that may be misclassified as clouds. Analysis for several aerosol types shows that the cloud mask and products can be safely used in the presence of aerosol up to optical thickness of 0.6. Here we define as cloudy all MODIS 1-km (at nadir) pixels that were used to derive the cloud effective radius and optical thickness of water and ice clouds. The findings make it possible to study aerosol-cloud interaction from the MODIS aerosol and cloud products. Index Terms--Aerosols, clouds, Moderate Resolution Imaging Spectroradiometer (MODIS), remote sensing.

QUESTION: Where is the cleanest air on Earth? ANSWER: With a boundary layer untainted by man-made aerosols, the Southern Ocean directly off Australia is 'one of the very few places [...]

A new numerical modeling of inhaled charge aerosol has been developed based on a modified Weibel's model. Both the velocity profiles (slug and parabolic flows) and the particle distributions (uniform and parabolic distributions) have been considered. Inhaled particles are modeled as a dilute dispersed phase flow in which the particle motion is controlled by fluid force and external forces acting on particles. This numerical study extends the previous numerical studies by considering both space-and image-charge forces. Because of the complex computation of interacting forces due In space-charge effect, the Particle-Mesh (PM) method is selected In calculate these forces. In the PM technique, the charges of all particles are assigned to the space-charge field mesh, for calculating charge density. The Poisson's equation of the electrostatic potential is then solved, and the electrostatic force acting on individual particle is interpolated. It is assumed that there is no effect of humidity on charged particles. The results show that many significant factors also affect the deposition, such as the volume of particle cloud, the velocity profile and the particle distribution. This study allows a better understanding of electrostatic mechanism of aerosol transport and deposition in human airways. Index Terms--Charged aerosol, particle deposition, Particle-Mesh (PM) method.

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) spaceborne lidar, expected to be launched in 2004, will collect profiles of the lidar attenuated backscattering coefficients of aerosol and clouds at 0.53 and 1.06 [micro]m. The measurements are sensitive to the vertical distribution of aerosols. However, the information is insufficient to be mapped into unique aerosol physical properties and vertical distribution. Spectral radiances measured by the Moderate Resolution Imaging Spectrometer (MODIS) on the Aqua spacecraft, acquired simultaneously with the CALIPSO observations, can constrain the solutions. The combination of the MODIS and CALIPSO data can be used to derive extinction profiles of the fine and coarse modes of the aerosol size distribution for aerosol optical thickness of 0.1 and larger. Here we describe a new inversion method developed to invert simultaneously MODIS and CALIPSO data over glint-free ocean. The method is applied to aircraft lidar and MODIS data collected over a dust storm off the coast of West Africa during the Saharan Dust Experiment (SHADE). The backscattering-to-extinction ratio (BER) (BER = [[omega].sub.o]P(180)/4[pi]) can be retrieved from the synergism between measurements avoiding a priori hypotheses required for inverting lidar measurements alone. For dust, the resultant value of BER = 0.016 [sr.sup.-1] is over 50% smaller than what is expected using Mie theory, but in good agreement with recent results obtained from Raman lidar observations of dust episodes. The inversion is robust in the presence of 10% and 20% noise in the lidar signal at 0.53 and 1.06 [micro]m, respectively. Calibration errors of the lidar of 5% to 10% can cause an error in optical thickness of 20% to 40%, respectively, in the tested cases. Index Terms--Aerosol, lidar, remote sensing.

Scientists have long known that vapors emitted from coniferous trees can create tiny particles that form seemingly out of nowhere and grow rapidly into sizeable aerosols. But as is the [...]

Aerosol sampling instruments, their operating principles, availability, applicability with respect to head-disk interface (HDI) research and manufacturing, and price are presented. Experiments were conducted using a laser particle counter to address sampling issues of background elimination, sampling frequency and sampling location for HDI tests. Results show that continuous sampling was acceptable and sampling at either leading or trailing edge of the interface did not affect sampling performance appreciably. Index Terms - Aerosol sampling, Clean room monitoring, Particulate contamination, Rigid disk

This paper presents the data of a series of multiangle experiments performed from the orbital station MIR in 1993-1994 over the semiarid regions of Kazakstan and the forest test sites of Zabaikal'e and Khabarovsky Krai (Russia). Collected data were processed to obtain the optical thickness and scattering function of atmospheric aerosol and surface albedo in ten spectral bands of spectrometer MKS-M2. To this end, the following approach was adopted. In the visible part of the spectrum, where the reflectance of observed surfaces is relatively low, they were assumed to be Lambertian. On this basis, spectral dependencies of the above parameters were obtained using the multiangle method reported earlier. In the near-infrared (NIR) part of the spectrum, where the surface reflectance is considerable and its anisotropy gives a substantial contribution to the angular dependence of radiance, the optical thickness was obtained via the extrapolation from the visible spectral interval and then the effective surface albedo was estimated from measurements. To test the validity of the Lambertian assumption, a qualitative criterion is suggested. Obtained results were also verified by the ground albedo measurements: spectral albedo retrieved for the semiarid terrain and the measurements in subsatellite point coincided with the average accuracy 0.01.

One of the most confident predictions regarding tropical cyclones (TCs) and climate is that TC intensities should increase, on average, with global warming. So have they increased yet, given that [...]

This paper presents the principles and performances of the stratospheric aerosol correction schemes for the Polarization and Directionality of the Earth's Reflectances (POLDER) spatial polarimeter measurements and the method used to derive, from the Stratospheric Aerosol and Gas Experiment II (SAGE II) data, the information about the aerosols that is needed for the correction. On the Advanced Earth Observing Satellite (ADEOS) platform since August 1996, POLDER performs multidirectional measurements, both of reflectance and of polarization in visible and near-infrared spectral bands. These new observational capabilities are used to observe clouds, lands, ocean surfaces, and tropospheric aerosols. These observations are weakly perturbed by the stratospheric aerosols, whose amount is currently low, but in the case of a major volcanic eruption, would increase strongly for few years. The possibility of such a situation has to be considered. Moreover, even near background conditions, the stratospheric aerosols perturb accurate retrieval of the ocean color and products deduced from the polarized light. That is why a systematic correction of their influence on the measured signal has been developed. Index Terms - Atmospheric correction, Polarization and Directionality of the Earth's Reflectances (POLDER), polarization, stratospheric aerosols.

A new technique for remote sensing of aerosol over the land and for atmospheric correction of Earth imagery is developed. It is based on detection of dark surface targets in the blue and red channels, as in previous methods, but uses the 2.1[[micro]meter] channel, instead of the 3.75 [[micro]meter] for their detection. A 2.1[[micro]meter] channel is present on ADEOS OCTS and GLI, and planned on EOS-MODIS and EOSP, and a similar 2.2-[[micro]meter] channel is present on Landsat TM. The advantage of the 2.1-[[micro]meter] channel over the 3.75-[[micro]meter] channel is that it is not affected by emitted radiation. The 2.1-[[micro]meter] channel is transparent to most aerosol types (except dust) and therefore can be used to detect dark surface targets. Correlation between the surface reflection in the blue (0.49 [[micro]meter]), red (0.66 [[micro]meter]), and 2.1 [[micro]meter] is established using atmospherically corrected Landsat TM and AVIRIS aircraft images collected over the Eastern United States, Maine, and California and spectral data obtained from the ground and light aircraft near San Diego, CA. Results from a variety of surface covers show that the surface reflectance at 0.49 [[micro]meter] ([[Rho].sub.0.49]) and 0.66 [[micro]meter] ([[Rho].sub.0.66]) can be predicted from that at 2.2 [[micro]meter] ([[Rho].sub.2.2]) within [Delta][Rho] = [+ or -]0.006 for [[Rho].sub.2.2] [less than or equal to] 0.10, using [[Rho].sub.0.49] = [[Rho].sub.2.2/4] and [[Rho].sub.0.66] = [[Rho].sub.2.2]/2. Error in surface reflectance of 0.006 corresponds to an error in remote sensing of aerosol optical thickness, [Tau], of [Delta][Tau] [similar to] [+ or -]-0.06. These relationships were validated using spectral data taken close to the surface over vegetated areas in a different biome. This method expands application of dark targets for remote sensing of aerosol to brighter, nonforested vegetation. The higher reflection of the surface at 2.2 [[micro]meter] than that of 3.75 [[micro]meter] may even enable remote sensing of dust above surfaces with reflectivity [[Rho].sub.2.2] = 0.15 [+ or -] 0.05. For this reflectivity range the dust radiative effect at 2.2 [[micro]meter] is small, and the surface reflectance in the blue and red channels can be retrieved. Index Terms - Aerosols, atmosphere correction, remote sensing.

This paper describes the life cycle of the background (nonvolcanic) stratospheric sulfate aerosol. The authors assume the particles are formed by homogeneous nucleation near the tropical tropopause and are carried aloft into the stratosphere. The particles remain in the Tropics for most of their life, and during this period of time a size distribution is developed by a combination of coagulation, growth by heteromolecular condensation, and mixing with air parcels containing preexisting sulfate particles. The aerosol eventually migrates to higher latitudes and descends across isentropic surfaces to the lower stratosphere. The aerosol is removed from the stratosphere primarily at mid- and high latitudes through various processes, mainly by isentropic transport across the tropopause from the stratosphere into the troposphere.

The most abundant class of aerosol in the atmosphere, sea spray aerosols (SSAs) originate from breaking waves and float into the atmosphere, where they can have significant climatic effects by [...]

Scientists who study cloud formation have generally believed that the most important influence on the creation of cloud droplets is the water solubility of the aerosol particle that seeds the [...]

Global map of aerosol parameters (optical thickness, Angstrom exponent, and refractive index) are derived from the POLDER instrument on board the ADEOS-1 platform. This paper focuses on aerosol optical thickness and Angstrom exponent retrievals that are based on visible and near infrared back scattering measurements. Assessment of the retrieval quality is achieved by means of comparison with AERONET sunphotometer data. The results show that the POLDER measurements can be used to distinguish several aerosol types from their Angstrom coefficients, in addition to a precise estimate of the aerosol optical thickness.

An analysis of ocean color temperature scanner [(OCTS) on board the advanced earth observation satellite (ADEOS)] spectral radiance data was performed for retrieving global distributions of Angstrom factor and exponent, which represent the aerosol optical thickness at a reference wavelength (500 nm in our study) and a spectral dependence of the optical thicknesses, respectively, over ocean. Determination of calibration constants for OCTS-received radiances and development of an efficient look.up table method for synthesizing the radiances are key issues for development of the present two-channel algorithm with use of channel 6 and 8 radiances of OCTS. This algorithm has been applied to Level-1B OCTS GAC data sets for producing three month (April, May, and June 1997) global distributions of Angstrom parameters. Geographical and seasonal distribution patterns of Angstrom parameters suggest that anthropogenic sulfate aerosols in mid-latitudes and biomass burning aerosols in the subtropical region are characterized by small particles having large Angstrom exponents, whereas mineral dust particles from subtropical arid regions are characterized by large particles having small Angstrom exponents. There was a fairly good agreement between satellite-retrieved values of Angstrom parameters and values obtained by sky radiometers located on coasts.