Dusty Origins: The formation of cirrus clouds begins with the production of ice nuclei, on which water vapor then condenses. Cziczo et al. (p. 1320 , published online 9 May) determined the kinds of particles on which cirrus ice crystals form by sublimating samples collected by research aircraft and analyzing the chemical and physical properties of the residual seeds. Most of the seed particles were either mineral dust or metallic.

The Total Carbon Column Observing Network (TCCON) produces precise measurements of the column average dry-air mole fractions of CO₂, CO, CH₄, N₂O and H₂O at a variety of sites worldwide. These observations rely on spectroscopic parameters that are not known with sufficient accuracy to compute total columns that can be used in combination with in situ measurements. The TCCON must therefore be calibrated to World Meteorological Organization (WMO) in situ trace gas measurement scales. We present a calibration of TCCON data using WMO-scale instrumentation aboard aircraft that measured profiles over four TCCON stations during 2008 and 2009. These calibrations are compared with similar observations made in 2004 and 2006. The results indicate that a single, global calibration factor for each gas accurately captures the TCCON total column data within error.

Fine particulate matter (PM_2.5) is a well-established risk factor for public health. To support both health risk assessment and epidemiological studies, data are needed on spatial and temporal patterns of PM_2.5 exposures. This review article surveys publicly available exposure datasets for surface PM_2.5 mass concentrations over the contiguous U.S., summarizes their applications and limitations, and provides suggestions on future research needs. The complex landscape of satellite instruments, model capabilities, monitor networks, and data synthesis methods offers opportunities for research development, but would benefit from guidance for new users. Guidance is provided to access publicly available PM_2.5 datasets, to explain and compare different approaches for dataset generation, and to identify sources of uncertainties associated with various types of datasets. Three main sources used to create PM_2.5 exposure data are ground-based measurements (especially regulatory monitoring), satellite retrievals (especially aerosol optical depth, AOD), and atmospheric chemistry models. We find inconsistencies among several publicly available PM_2.5 estimates, highlighting uncertainties in the exposure datasets that are often overlooked in health effects analyses. Major differences among PM_2.5 estimates emerge from the choice of data (ground-based, satellite, and/or model), the spatiotemporal resolutions, and the algorithms used to fuse data sources. Implications: Fine particulate matter (PM_2.5) has large impacts on human morbidity and mortality. Even though the methods for generating the PM_2.5 exposure estimates have been significantly improved in recent years, there is a lack of review articles that document PM_2.5 exposure datasets that are publicly available and easily accessible by the health and air quality communities. In this article, we discuss the main methods that generate PM_2.5 data, compare several publicly available datasets, and show the applications of various data fusion approaches. Guidance to access and critique these datasets are provided for stakeholders in public health sectors.

Cloud phase and relative humidity (RH) distributions at −67° to 0°C over the Southern Ocean during austral summer are compared between in situ airborne observations and global climate simulations. A scale-aware comparison is conducted using horizontally averaged observations from 0.1 to 50 km. Cloud phase frequencies, RH distributions, and liquid mass fraction are found to be less affected by horizontal resolutions than liquid and ice water content (LWC and IWC, respectively), liquid and ice number concentrations (Nc_liq and Nc_ice, respectively), and ice supersaturation (ISS) frequency. At −10° to 0°C, observations show 27%–34% and 17%–37% of liquid and mixed phases, while simulations show 60%–70% and 3%–4%, respectively. Simulations overestimate (underestimate) LWC and Nc_liq in liquid (mixed) phase, overestimate Nc_ice in mixed phase, underestimate IWC in ice and mixed phases, and underestimate (overestimate) liquid mass fraction below (above) −5°C, indicating that observational constraints are needed for different cloud phases. RH frequently occurs at liquid saturation in liquid and mixed phases for all datasets, yet the observed RH in ice phase can deviate from liquid saturation by up to 20%–40% at −20° to 0°C, indicating that the model assumption of liquid saturation for coexisting ice and liquid is inaccurate for low liquid mass fractions (<0.1). Simulations lack RH variability for partial cloud fractions (0.1–0.9) and underestimate (overestimate) ISS frequency for cloud fraction <0.1 (≥0.6), implying that improving RH subgrid-scale parameterizations may be a viable path to account for small-scale processes that affect RH and cloud phase heterogeneities. Two sets of simulations (nudged and free-running) show very similar results (except for ISS frequency) regardless of sample sizes, corroborating the statistical robustness of the model–observation comparisons.