Every year, from December to April, anthropogenic haze spreads over most of the North Indian Ocean, and South and Southeast Asia. The Indian Ocean Experiment (INDOEX) documented this Indo‐Asian haze at scales ranging from individual particles to its contribution to the regional climate forcing. This study integrates the multiplatform observations (satellites, aircraft, ships, surface stations, and balloons) with one‐ and four‐dimensional models to derive the regional aerosol forcing resulting from the direct, the semidirect and the two indirect effects. The haze particles consisted of several inorganic and carbonaceous species, including absorbing black carbon clusters, fly ash, and mineral dust. The most striking result was the large loading of aerosols over most of the South Asian region and the North Indian Ocean. The January to March 1999 visible optical depths were about 0.5 over most of the continent and reached values as large as 0.2 over the equatorial Indian ocean due to long‐range transport. The aerosol layer extended as high as 3 km. Black carbon contributed about 14% to the fine particle mass and 11% to the visible optical depth. The single‐scattering albedo estimated by several independent methods was consistently around 0.9 both inland and over the open ocean. Anthropogenic sources contributed as much as 80% (±10%) to the aerosol loading and the optical depth. The in situ data, which clearly support the existence of the first indirect effect (increased aerosol concentration producing more cloud drops with smaller effective radii), are used to develop a composite indirect effect scheme. The Indo‐Asian aerosols impact the radiative forcing through a complex set of heating (positive forcing) and cooling (negative forcing) processes. Clouds and black carbon emerge as the major players. The dominant factor, however, is the large negative forcing (‐20±4 W m⁻²) at the surface and the comparably large atmospheric heating. Regionally, the absorbing haze decreased the surface solar radiation by an amount comparable to 50% of the total ocean heat flux and nearly doubled the lower tropospheric solar heating. We demonstrate with a general circulation model how this additional heating significantly perturbs the tropical rainfall patterns and the hydrological cycle with implications to global climate.

Ice in the troposphere affects a variety of processes, including the formation of precipitation, and cloud lifetime, albedo, dynamics, and electrification. A lack of understanding of the ways in which ice is created and multiplied hampers progress in understanding all of these processes. We survey the state of knowledge, starting with homogeneous nucleation, where current formulations for freezing from both pure water and solutions have considerable predictive power. However, debate still exists on the underlying mechanisms of nucleation. Using the concepts and framework that homogeneous nucleation provides, heterogeneous nucleation, where neither a commonly agreed upon theory nor even standard measurement technique exists, is considered. Investigators have established the ice-nucleating characteristics of broad classes of substances, such as mineral dust and soot, which are important ice nuclei in the atmosphere, but a coherent theory of why these substances act as they do has yet to emerge. All... Abstract Ice in the troposphere affects a variety of processes, including the formation of precipitation, and cloud lifetime, albedo, dynamics, and electrification. A lack of understanding of the ways in which ice is created and multiplied hampers progress in understanding all of these processes. We survey the state of knowledge, starting with homogeneous nucleation, where current formulations for freezing from both pure water and solutions have considerable predictive power. However, debate still exists on the underlying mechanisms of nucleation. Using the concepts and framework that homogeneous nucleation provides, heterogeneous nucleation, where neither a commonly agreed upon theory nor even standard measurement technique exists, is considered. Investigators have established the ice-nucleating characteristics of broad classes of substances, such as mineral dust and soot, which are important ice nuclei in the atmosphere, but a coherent theory of why these substances act as they do has yet to emerge. All...

The influence of aerosol concentration on the cloud-droplet size distribution is investigated in a laboratory chamber that enables turbulent cloud formation through moist convection. The experiments allow steady-state microphysics to be achieved, with aerosol input balanced by cloud-droplet growth and fallout. As aerosol concentration is increased, the cloud-droplet mean diameter decreases, as expected, but the width of the size distribution also decreases sharply. The aerosol input allows for cloud generation in the limiting regimes of fast microphysics ( <mml:math><mml:mrow><mml:msub><mml:mi>τ</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mo><</mml:mo><mml:msub><mml:mi>τ</mml:mi><mml:mi>t</mml:mi></mml:msub></mml:mrow></mml:math>τc<τt ) for high aerosol concentration, and slow microphysics ( <mml:math><mml:mrow><mml:msub><mml:mi>τ</mml:mi><mml:mi>c</mml:mi></mml:msub><mml:mo>></mml:mo><mml:msub><mml:mi>τ</mml:mi><mml:mi>t</mml:mi></mml:msub></mml:mrow></mml:math>τc>τt ) for low aerosol concentration; here, <mml:math><mml:msub><mml:mi>τ</mml:mi><mml:mi>c</mml:mi></mml:msub></mml:math>τc is the phase-relaxation time and <mml:math><mml:msub><mml:mi>τ</mml:mi><mml:mi>t</mml:mi></mml:msub></mml:math>τt is the turbulence-correlation time. The increase in the width of the droplet size distribution for the low aerosol limit is consistent with larger variability of supersaturation due to the slow microphysical response. A stochastic differential equation for supersaturation predicts that the standard deviation of the squared droplet radius should increase linearly with a system time scale defined as <mml:math><mml:mrow><mml:msubsup><mml:mi>τ</mml:mi><mml:mi>s</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mrow><mml:msubsup><mml:mi>τ</mml:mi><mml:mi>c</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msubsup><mml:mo>+</mml:mo><mml:msubsup><mml:mi>τ</mml:mi><mml:mi>t</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msubsup></mml:mrow></mml:mrow></mml:math>τs−1=τc−1+τt−1 , and the measurements are in excellent agreement with this finding. The result underscores the importance of droplet size dispersion for aerosol indirect effects: increasing aerosol concentration changes the albedo and suppresses precipitation formation not only through reduction of the mean droplet diameter but also by narrowing of the droplet size distribution due to reduced supersaturation fluctuations. Supersaturation fluctuations in the low aerosol/slow microphysics limit are likely of leading importance for precipitation formation.

A detailed understanding of interactions of aerosols, cloud droplets/ice crystals, and trace gases within the atmosphere is of prime importance for an accurate understanding of Earth’s weather and climate. One aspect that remains especially vexing is that clouds are ubiquitously turbulent, and therefore thermodynamic and compositional variables, such as water vapor supersaturation, fluctuate in space and time. With these problems in mind, a multiphase, turbulent reaction chamber—called the Π chamber because of the internal volume of 3.14 m ³ with the cylindrical insert installed—has been developed. It is capable of pressures ranging from 1,000 to –60 hPa and can sustain temperatures of –55° to 55°C, thereby spanning much of the range of tropospheric clouds. To control the relative humidity in the chamber, it can be operated with a stable, unstable, or neutral temperature difference between the top and bottom surfaces, with or without expansion. A negative temperature difference induces turbulent Rayleigh–Bénard convection and associated supersaturation generation through isobaric mixing. Supporting instrumentation includes a suite of aerosol generation and characterization techniques; temperature, pressure, and humidity sensors; and a phase Doppler interferometer. Initial characterization experiments demonstrate the ability to sustain steady-state turbulent cloud conditions for times greater than 1 day, with droplet diameters typically in the range of 5–40 µ m. Typical turbulence has root-mean-square velocity fluctuations on the order of 10 cm s ^–1 and kinetic energy dissipation rates of 1 × 10 ^–3 W kg ^–1 .

Particle detection efficiency curves for 26 condensation particle counters were determined during a calibration workshop in preparation for the Aerosol Characterization Experiment 1 (ACE1). Three different types of commercially available particle counters, the ultrafine condensation particle counter (TSI-3025) and the condensation particle counters (TSI-3010 and TSI-3760 or TS1-7610) were investigated at default temperature and flow settings as well as for other flow rates and temperature differences between the saturator and the condenser. Furthermore, the pulse-height-analysis ultrafine condensation particle counter and a TSI-3010 modified to achieve a higher temperature difference were calibrated. In this study, the large number of particle counters investigated provided the opportunity to obtain a more statistically significant picture of the performance of different particle counters for different operating conditions.

Significance: Formation of cloud droplets is a threshold phenomenon; droplets form only when the local relative humidity (RH) exceeds a critical value which depends on the size and chemical composition of preexisting aerosol particles which serve as the seeds for droplets. In the traditional view of this process, only the average value of RH is considered. However, clouds are ubiquitously turbulent, meaning they are characterized not by a single value of relative humidity, but by a distribution. We show, with laboratory experiments and theory, that cloud formation occurs in three regimes, characterized by the relationship between the distribution of RH in the environment and the critical value. Our results show that fluctuations in RH must be considered, as well the average.