Soot Volume Fraction Measurements by Auto-Compensating Laser-Induced Incandescence in Diffusion Flames Generated by Ethylene Pool Fire

The main characteristics of pool fire flames are flame height, air entrainment, pulsation of the flame, formation and properties of soot particles, mass burning rate, radiation feedback to the pool surface, and the amount of pollutants including soot released to the environment. In this type of buoyancy controlled flames, the soot content produced and their subsequent thermal radiation feedback to the pool surface are key to determine the self-sustainability of the flame, their mass burning rate and the heat release rate. The accurate characterization of these flames is an involved task, specially for modelers due to the difficulty of imposing adequate boundary conditions. For this reason, efforts are being made to design experimental campaigns with well-controlled conditions for their reliable repeatability, reproducibility and replicability. In this work, we characterized the production of soot in a surrogate pool fire. This is emulated by a bench-scale porous burner fueled with pure ethylene burning in still air. The flame stability was characterized with high temporal and spatial resolution by using a CMOS camera and a fast photodiode. The results show that the flame exhibit a time-varying propagation behavior with a periodic separation of the reactive zone. Soot volume fraction distributions were measured at nine locations along the flame centerline from 20 to 100 mm above the burner exit using the auto-compensating laser-induced incandescence (AC-LII) technique. The mean, standard deviation and probability density function of soot volume fraction were determined. Soot volume fraction presents an increasing tendency with the height above the burner, in spite of a local decrease at 90 mm which is approximately the position separating the lower and attached portion of the flame from the higher more intermittent one. The results of this work provide a valuable data set for validating soot production models in pool fire configurations.

The Critical Role of Cloud–Infrared Radiation Feedback in Tropical Cyclone Development

<p>The deep convective clouds of developing tropical cyclones (TCs) are highly effective at trapping the infrared (or longwave) radiation welling up from the surface. This “cloud greenhouse effect” locally warms the lower–mid-troposphere relative to the TC’s surroundings – an effect that manifests in all stages of the TC lifecycle. While idealized studies suggest the importance of this feedback for TC formation, this issue has remained unexplored for TCs in nature, where non-zero background flow, wind shear, and synoptic-scale variability are known to greatly constrain TC development.</p><p>To address this gap, we examine the potential role of this cloud–infrared (or longwave) radiation feedback in the context of two archetypal storms: Super Typhoon Haiyan (2013) and Hurricane Maria (2017). We conduct a set of numerical model experiments for both storms with a convection-resolving model (WRF-ARW) from the very early stages of TC development. We examine sensitivity experiments wherein this cloud–radiation feedback is removed at various lead-times prior to TC genesis and the onset of rapid intensification (RI). In both storms, removing this cloud–radiation feedback at a lead-time of ~1 day or less leads to delayed and/or weaker intensification than in the control case. When this feedback is removed with a lead-time of two days or longer, however, the storms altogether fail to development and intensify. This local cloud greenhouse effect strengthens the thermally direct transverse circulation of the incipient storm, in turn both promoting saturation within its core and accelerating the spin-up of its surface tangential circulation via angular momentum convergence. These findings indicate that the cloud greenhouse effect plays a critical role in accelerating and promoting TC development in nature. Progress in the prediction of TC formation and intensification has been very limited in recent decades. Cloud–radiation feedback represents a large source of uncertainty in models, which hence manifests as uncertainty in the prediction of TC development. Our findings highlight the pressing need to better constrain this feedback in models. Doing so holds promise for advancing our ability to forecast TCs.</p>

Impacts of aerosol-photolysis interaction and aerosol-radiation feedback on surface-layer ozone in North China during a multi-pollutant air pollution episode

We examined the impacts of aerosol-radiation interactions, including the effects of aerosol-photolysis interaction (API) and aerosol-radiation feedback (ARF), on surface-layer ozone (O3) concentrations during one multi-pollutant air pollution episode characterized by high O3 and PM2.5 levels from 28 July to 3 August 2014 in North China, by using the Weather Research and Forecasting with Chemistry (WRF-Chem) model embedded with an integrated process analysis scheme. Our results show that aerosol-radiation interactions decrease the daytime downward shortwave radiation at surface, 2 m temperature, 10 m wind speed, planetary boundary layer height, photolysis rates J[NO2] and J[O1D] by 115.8 W m−2, 0.56 °C, 0.12 m s−1, 129 m, 1.8 × 10−3 s−1 and 6.1 × 10−6 s−1, and increase relative humidity at 2 m and downward shortwave radiation in the atmosphere by 2.4 % and 72.8 W m−2. The weakened photolysis rates and changed meteorological conditions reduce surface-layer O3 concentrations by up to 11.4 ppb (13.5 %), with API and ARF contributing 74.6 % and 25.4 % of the O3 decrease, respectively. The combined impacts of API and ARF on surface O3 are further quantitatively characterized by the ratio of changed O3 concentration to local PM2.5 level. The ratio is calculated to be −0.14 ppb (µg m−3)−1 averaged over the multi-pollutant air pollution area in North China. Process analysis indicates that the weakened O3 chemical production makes the greatest contribution to API effect while the reduced vertical mixing is the key process for ARF effect. This study implies that future PM2.5 reductions will lead to O3 increases due to weakened aerosol-radiation interactions. Therefore, tighter controls of O3 precursors are needed to offset O3 increases caused by weakened aerosol-radiation interactions in the future.

Intercomparison of MJO column moist static energy and water vapor budget among six modern reanalysis products

This study conducts an intercomparison of the column-integrated moist static energy (MSE) and water vapor budget of the Madden-Julian Oscillation (MJO) among six modern global reanalysis products (RAs). Inter-RA differences in the mean MSE, MJO MSE anomalies, individual MSE budget terms and their relative contributions to the propagation and maintenance of MJO MSE anomalies are examined. Also investigated is the relationship between the MJO column water vapor (CWV) budget residuals with the other CWV budget terms as well as the two parameters that characterize cloud-radiation feedback and moisture-convection coupling.Results show a noticeable inter-RA spread in the mean state MSE, especially its vertical structure. In all RAs, horizontal MSE advection dominates the propagation of the MJO MSE while column-integrated longwave radiative heating and vertical MSE advection are found to be the key processes for MJO maintenance. The MSE budget terms directly affected by the model parameterization schemes exhibit high uncertainty. The differences in anomalous vertical velocity mainly contribute to the large differences in vertical MSE advection among the RAs. The budget residuals show large inter-RA differences and have non-negligible contributions to MJO maintenance and propagation in most RAs.RAs that underestimate (overestimate) the strength of cloud-radiation feedback and the convective moisture adjustment timescale tend to have positive (negative) MJO CWV budget residual, indicating the critical role of these processes in the maintenance of MJO CWV anomalies. Our results emphasize that a correct representation of the interactions among moisture, convection, cloud, and radiation is the key for an accurate depiction of the MJO MSE and CWV budget in RAs.