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A SmallSat mission concept is formulated here to carry out Time-varying Optical Measurements of Clouds and Aerosol Transport (TOMCAT) from space while embracing low-cost opportunities enabled by the revolution in Earth science observation technologies. TOMCAT’s “around-the-clock” measurements will provide needed insights and strong synergy with existing Earth observation satellites to 1) statistically resolve diurnal and vertical variation of cirrus cloud properties (key to Earth’s radiation budget), 2) determine the impacts of regional and seasonal planetary boundary layer (PBL) diurnal variation on surface air quality and low-level cloud distributions, and 3) characterize smoke and dust emission processes impacting their long-range transport on the subseasonal to seasonal time scales. Clouds, aerosol particles, and the PBL play critical roles in Earth’s climate system at multiple spatiotemporal scales. Yet their vertical variations as a function of local time are poorly measured from space. Active sensors for profiling the atmosphere typically utilize sun-synchronous low-Earth orbits (LEO) with rather limited temporal and spatial coverage, inhibiting the characterization of spatiotemporal variability. Pairing compact active lidar and passive multiangle remote sensing technologies from an inclined LEO platform enables measurements of the diurnal and vertical variability of aerosols, clouds, and aerosol-mixing-layer (or PBL) height in tropical-to-midlatitude regions where most of the world’s population resides. TOMCAT is conceived to bring potential societal benefits by delivering its data products in near–real time and offering on-demand hazard-monitoring capabilities to profile fire injection of smoke particles, the frontal lofting of dust particles, and the eruptive rise of volcanic plumes.

Tropical cyclones (TCs) are among the most destructive natural phenomena with huge societal and economic impact. They form and evolve as the result of complex multiscale processes and nonlinear interactions. Even today the understanding and modeling of these processes is still lacking. A major goal of NASA is to bring the wealth of satellite and airborne observations to bear on addressing the unresolved scientific questions and improving our forecast models. Despite their significant amount, these observations are still underutilized in hurricane research and operations due to the complexity associated with finding and bringing together semicoincident and semicontemporaneous multiparameter data that are needed to describe the multiscale TC processes. Such data are traditionally archived in different formats, with different spatiotemporal resolution, across multiple databases, and hosted by various agencies. To address this shortcoming, NASA supported the development of the Jet Propulsion Laboratory (JPL) Tropical Cyclone Information System (TCIS)—a data analytic framework that integrates model forecasts with multiparameter satellite and airborne observations, providing interactive visualization and online analysis tools. TCIS supports interrogation of a large number of atmospheric and ocean variables, allowing for quick investigation of the structure of the tropical storms and their environments. This paper provides an overview of the TCIS’s components and features. It also summarizes recent pilot studies, providing examples of how the TCIS has inspired new research, helping to increase our understanding of TCs. The goal is to encourage more users to take full advantage of the novel capabilities. TCIS allows atmospheric scientists to focus on new ideas and concepts rather than painstakingly gathering data scattered over several agencies.

Monte Carlo and Morris screening techniques are used to examine the relative sensitivity of deep convective simulations to changes in initial conditions (IC) versus changes to microphysical parameters (MP). IC are perturbed using a set of empirical orthogonal function–principal component pairs obtained from a database of tropical soundings, while MP are perturbed consistent with their range of realistic values. Monte Carlo experiments provide a broad overview of parameter–output response, while Morris screening techniques identify the most significant influences on specific model output variables. Changes to MP produce a similar order-of-magnitude response in convective hydrologic cycle, dynamics, and latent heating as changes to IC. Changes in IC appear to have a larger effect on radiative fluxes than perturbations to MP. The distribution of low-level latent heating reveals that changes in MP have a larger influence on cold pool properties than changes to the environment. The dominant effects are produced by a subset of cloud MP and thermodynamic structure functions, indicating perturbation of a subset of the control factors may be used to produce most of the variability in a short-term convective-scale ensemble forecast. The most influential MP are the autoconversion threshold, the rain particle size distribution intercept, and the ice particle fall speed parameters. The most influential EOFs are those that correspond to variability in lower- to midtropospheric temperature and water vapor, as well as zonal low-level shear. The results have implications for both the understanding of what influences convective development and the design of ensemble-based prediction and data assimilation systems.

When unaccounted for in numerical weather prediction (NWP) models, heavy aerosol events can cause significant unrealized biases in forecasted meteorological parameters such as surface temperature. To improve near-surface forecasting accuracies during heavy aerosol loadings, we demonstrate the feasibility of incorporating aerosol fields from a global chemical transport model as initial and boundary conditions into a higher resolution NWP model with aerosol-meteorological coupling. This concept is tested for a major biomass burning smoke event over the Northern Great Plains region of the United States that occurred during summer of 2015. Aerosol analyses from the global Navy Aerosol Analysis and Prediction System (NAAPS) are used as initial and boundary conditions for Weather Research and Forecasting with Chemistry (WRF-Chem) simulations. Through incorporating more realistic aerosol direct effects into the WRF-Chem simulations, errors in WRF-Chem simulated surface downward shortwave radiative fluxes and near-surface temperature are reduced compared with surface-based observations. This study confirms the ability to decrease biases induced by the aerosol direct effect for regional NWP forecasts during high-impact aerosol episodes through the incorporation of analyses and forecasts from a global aerosol transport model.

The purpose of this workshop was to reinforce the working partnership between centers who are actively involved in global aerosol forecasting, and to discuss issues related to forecast verification. Participants included representatives from operational centers with global aerosol forecasting requirements, a panel of experts on Numerical Weather Prediction and Air Quality forecast verification, data providers, and several observers from the research community. The presentations centered on a review of current NWP and AQ practices with subsequent discussion focused on the challenges in defining appropriate verification measures for the next generation of aerosol forecast systems.

WHAt: approximately 15 developers for many of the world’s operational numerical weather prediction centers with aerosol forecasting mandates met with an equal number of representatives for the satellite data providers to discuss the aerosol observability issues facing the next generation of aerosol forecast systems. WHen: 27–29 april 2010 WHere: Monterey, California W hile the last three years have seen rapid operational implementation of aerosol and pollution models around the world, the key to further development of aerosol forecasting systems is aerosol observational data from satellites for model evaluation and data assimilation. However, although the dynamical meteorology community has a well-developed, near-real-time observing system to support forecasting, the aerosol community is only beginning to address its needs. This meeting was the first ever to combine the lead aerosol model developers and remote sensing data providers from around the globe in discussing state-of-the-art technologies and operational requirements for aerosol forecasting. Participants included representatives from the operational centers of ECMWF, FNMOC, JMA, NCEP, and the Met Office; remote sensing data providers from EUMETSAT, ESA, JAXA, NASA, and NOAA NESDIS; and additional developers from NASA GMAO, NGST, NOAA, NRL, and several universities.1 Overviews were given by operational participants as to their centers’ current forecasting status and projected data needs. Remote sensing agencies described current and planned relevant space missions. Last, developers provided an overview of future directions in aerosol data assimilation. Much of the development of operational aerosol systems has relied on climate satellite datasets, predominantly from the MODIS instrument on the NASA Terra and Aqua spacecraft. With near-real time data available from the joint NASA–NOAA NRTPE (aka “bent pipe”) beginning in 2002 and the recent implementation of the NASA LANCE data server, operational centers have developed a neartotal reliance on MODIS aerosol, fire, and albedo products for model initialization and assimilation.

Handheld sun photometers are typically used to make aerosol optical depth measurements while on the ground. Various investigators, in unrelated efforts, have used handheld sun photometers to make aerosol optical depth measurements from light aircraft, but the strengths and weakness of this approach have not been characterized until now. While the ease and relatively low cost of an aircraft manual sun photometer are attractive, determining if the sun photometer was correctly pointed at the sun for each measurement is the biggest challenge. This problem can be partially addressed by collecting a large number of measurements at each altitude, then manually removing the largest optical depths (misalignment always results in erroneous larger values). Examples of past aircraft manual sun photometer measurements are demonstrating that it is possible to obtain quantitative measurements if sufficient sun photometer measurements are made at each elevation. In order to improve on manual sun photometer measurements, a small webcam was attached to the side of a Microtops sun photometer, and the Microtops sun photometer was triggered by computer control. By detecting the position of the sun in the webcam image, it is possible to determine whether the sun photometer was pointed at the sun correctly when the aerosol optical depth measurement was made. Unfortunately, it was found that the Microtops sun photometer takes ∼1.1 s to scan over the five wavelength channels. This 1.1-s delay proved to be too long, preventing the proposed approach from working as the aircraft was bouncing around.

Although the importance of the aerosol contribution to the global radiative budget has been recognized, the forcings of aerosols in general, and specifically the role of the organic component in these forcings, still contain large uncertainties. In an attempt to better understand the relationship between the background forcings of aerosols and their chemical speciation, marine air samples were collected off the windward coast of Oahu, Hawaii, during the Rough Evaporation Duct project (RED) using filters mounted on both the Twin Otter aircraft and the Floating Instrument Platform (FLIP) research platform. Laboratory analysis revealed a total of 17 species, including 4 carboxylic acids and 2 carbohydrates that accounted for 74% ± 20% of the mass gain observed on the shipboard filters, suggesting a possible significant unresolved organic component. The results were correlated with in situ measurements of particle light scattering (σsp) at 550 nm and with aerosol hygroscopicities. Principal component analysis revealed a small but ubiquitous pollution component affecting the σsp and aerosol hygroscopicity of the remote marine air. The Princeton Organic-Electrolyte Model (POEM) was used to predict the growth factor of the aerosols based upon the chemical composition. This output, coupled with measured aerosol size distributions, was used to attempt to reproduce the observed σsp. It was found that while the POEM model was able to reproduce the expected trends when the organic component of the aerosol was varied, due to large uncertainties especially in the aerosol sizing measurements, the σsp predicted by the POEM model was consistently higher than observed.

Using in situ measurements of aerosol optical properties and ground-based measurements of aerosol optical thickness (τs) during the Smoke, Clouds and Radiation—Brazil (SCAR-B) experiment, a four-stream broadband radiative transfer model is used to estimate the downward shortwave irradiance (DSWI) and top-of-atmosphere (TOA) shortwave aerosol radiative forcing (SWARF) in cloud-free regions dominated by smoke from biomass burning in Brazil. The calculated DSWI values are compared with broadband pyranometer measurements made at the surface. The results show that, for two days when near-coincident measurements of single-scattering albedo ω0 and τs are available, the root-mean-square errors between the measured and calculated DSWI for daytime data are within 30 W m−2. For five days during SCAR-B, however, when assumptions about ω0 have to be made and also when τs was significantly higher, the differences can be as large as 100 W m−2. At TOA, the SWARF per unit optical thickness ranges from −20 to −60 W m−2 over four major ecosystems in South America. The results show that τs and ω0 are the two most important parameters that affect DSWI calculations. For SWARF values, surface albedos also play an important role. It is shown that ω0 must be known within 0.05 and τs at 0.55 μm must be known to within 0.1 to estimate DSWI to within 20 W m−2. The methodology described in this paper could serve as a potential strategy for determining DSWI values in the presence of aerosols. The wavelength dependence of τs and ω0 over the entire shortwave spectrum is needed to improve radiative transfer calculations. If global retrievals of DSWI and SWARF from satellite measurements are to be performed in the presence of biomass-burning aerosols on a routine basis, a concerted effort should be made to develop methodologies for estimating ω0 and τs from satellite and ground-based measurements.