Demonstration of the Temporal Evolution of Tropical Cyclone “Phailin” Using Gray-Zone Simulations and Decadal Variability of Cyclones over the Bay of Bengal in a Warming Climate

The intensity and frequency variability of cyclones in the North Indian Ocean (NIO) have been amplified over the last few decades. The number of very severe cyclonic storms (VSCSs) over the North Indian Ocean has increased over recent decades. “Phailin”, an extreme severe cyclonic storm (ESCS), occurred during 8–13 October 2013 over the Bay of Bengal and made landfall near the Gopalpur coast of Odisha at 12 UTC on 12 October. It caused severe damage here, as well as in the coastal Odisha, Andhra Pradesh, and adjoining regions due to strong wind gusts (~115 knot/h), heavy precipitation, and devastating storm surges. The fidelity of the WRF model in simulating the track and intensity of tropical cyclones depends on different cloud microphysical parameterization schemes. Thus, four sensitivity simulations were conducted for Phailin using double-moment and single-moment microphysical (MP) parameterization schemes. The experiments were conducted to quantify and characterize the performance of such MP schemes for Phailin. The simulations were performed by the advanced weather research and forecasting (WRF-ARW) model. The model has two interactive domains covering the entire Bay of Bengal and adjoining coastal Odisha on 25 km and 8.333 km resolutions. Milbrandt–Yau (MY) double-moment and WRF single-moment microphysical schemes, with 6, 5, and 3 classes of hydrometeors, i.e., WSM6, WSM5, and WSM3, were used for the simulation. Experiments for Phailin were conducted for 126 h, starting from 00 UTC 08 October to 06 UTC 13 October 2013. It was found that the track, intensity, and structure of Phailin are highly sensitive to the different microphysical parameterization schemes. Further, the precipitation and cloud distribution were studied during the ESCS stage of Phailin. The microphysics schemes (MY, WSM3, WSM5, WSM6), along with Grell–Devenyi ensemble convection scheme predicted landfall of Phailin over the Odisha coast with significant track errors. Supply of moisture remains a more crucial component than SST and wind shear for rapid intensification of the Phailin 12 h before landfall over the Bay of Bengal. Finally, the comparison of cyclone formation between two decades 2001–2010 and 2011–2020 over the Bay of Bengal inferred that the increased numbers of VSCS are attributed to the supply of abundant moisture at low levels in the recent decade 2011–2020.

Interpretation of aerosol effects on precipitation susceptibility in warm clouds inferred from satellite measurements and model evaluation over Northeast Asia

Precipitation susceptibility (So), a parameter of aerosol-cloud-precipitation interaction over Northeast Asia during the Korea-United States Air Quality (KORUS-AQ) campaign, was analyzed using the CLAVR-x satellite data and WRF-Chem model. As Northeast Asia is one of the areas with the highest aerosol emissions, this study is expected to explore more elaborate aerosol-cloud linkages.Our results obtained from satellite data showed that So increased as the atmospheric condition became stable and humid, and the shift of the water conversion process to precipitation occurred in the LWP range of 300–500 g m-2. The So exhibited a maximum value of 0.61 at an LWP of 350 g m-2 where the dominance of the cloud-water conversion process changed from autoconversion to accretion. In the aerosol–cloud relation, the susceptibility of the cloud-drop effective radius showed a positive response to the cloud droplet number concentration (Nd) regardless of the environmental conditions, whereas the LWP vs. Nd relationship was highly dependent on the meteorological conditions.The WRF-Chem produced higher So values than those of the satellite data by factors of 2.4–3.3; the simulated results exhibited differences in shape, range, and amplitude. The overestimation of So was mainly due to the high precipitation rate under low LWP conditions as compared to the satellite observations. This result is associated with the initiation and intensity of precipitation, considering both autoconversion and accretion. Our modeling results were verified during KORUS-AQ, which implied that the aerosol–cloud relationship might be elucidated by improved microphysical parameterization schemes based on more detailed measurements such as aircraft-based observations.

Aerosol impacts for convective parameterizations: Recent changes to the Grell-Freitas Convective Parameterization

<p>The Grell-Freitas (GF) cumulus parameterization is an aerosol-aware, scale-aware convective parameterization. This presentation will focus one of the several developmental activities ongoing in GF: the continued development of its aerosol-aware capabilities and the impact in global forecast models.</p><p>Previous versions of GF initialized aerosols based on an assumed value of aerosol-optical depth (AOD) that was applied uniformly across the entire globe. Observations of AOD indicate that AOD varies substantially across the globe. Recently, the constant AOD value assumed in GF has been replaced by global AOD data from NASA’s MERRA2 reanalysis. Thus, the distribution of aerosols at initialization more physically reasonable and geographically appropriate. This is important since the treatment of aerosols in GF should be most sensitive in regions with either very high or very low AOD. This method is extremely efficient, but can be adapted so that other aerosol and AOD products can be used in GF. Other products that could be used for initialization include the aerosol climatology used by the Thompson Aerosol-Aware Microphysical Parameterization or predicted aerosols using NOAA’s aerosol prediction model, which is currently one ensemble in the Global Ensemble Forecast System – Aerosols (GEFS-Aerosols).   </p><p>GF includes three aerosol related cloud processes: aerosol-influenced evaporation, aerosol-influenced auto-conversion of cloud water to rain water, and aerosol wet scavenging based on memory. As in Wang (2013) the treatment of wet scavenging has been modified so that the aerosol wet scavenging efficiency is proportional to precipitation efficiency. Additionally, aerosols in GF are now allowed to slowly return to their original concentrations during precipitation-free periods. These changes are important since they allow the aerosols in GF to evolve over time in a physically realistic manner.</p><p>The impact of these changes to GF will be shown in a version of NOAA’s operational global prediction model.   </p>

The Microphysical Properties of a Sea-Fog Event along the West Coast of the Yellow Sea in Spring

The microphysics and visibility of a sea-fog event were measured at the Qingdao Meteorological Station (QDMS) (120°19′ E, 36°04′ N) from 5 April to 8 April 2017. The two foggy periods with low visibility (<200 m) lasted 31 h together. The mean value of the average liquid water content (LWC) was 0.057 g m−3, and the mean value of the number concentration (NUM) was 64.4 cm−3. We found that although large droplets only constituted a small portion of the total number of the concentration; they contributed the majority of the LWC and therefore determined ~76% of total extinction of the visibility. The observed droplet-size distribution (DSD) exhibited a new bimodal Gaussian (G-exponential) distribution function, rather than the well-accepted Gamma distribution. This work suggests a new distribution function to describe fog DSD, which may help to improve the microphysical parameterization for the Yellow Sea fog numerical forecasting.

Influences of Horizontal Grid Spacing and Microphysics on WRF Forecasts of Convective Morphology Evolution for Nocturnal MCSs in Weakly Forced Environments

Nocturnal mesoscale convective systems (MCSs) are important phenomena because of their contributions to warm-season precipitation and association with severe hazards. Past studies have shown that their morphology remains poorly forecast in current convection-allowing models operating at 3–4-km horizontal grid spacing. A total of 10 MCS cases occurring in weakly forced environments were simulated using the Weather Research and Forecasting (WRF) Model at 3- and 1-km horizontal grid spacings to investigate the impact of increased resolution on forecasts of convective morphology and its evolution. These simulations were conducted using four microphysics schemes to account for additional sensitivities to the microphysical parameterization. The observed and corresponding simulated systems were manually classified into detailed cellular and linear modes, and the overall morphology depiction and the forecast accuracy of each model configuration were evaluated. In agreement with past studies, WRF was found to underpredict the occurrence of linear modes and overpredict cellular modes at 3-km horizontal grid spacing with all microphysics schemes tested. When grid spacing was reduced to 1 km, the proportion of linear systems increased. However, the increase was insufficient to match observations throughout the evolution of the systems, and the accuracy scores showed no statistically significant improvement. This suggests that the additional linear modes may have occurred in the wrong subtypes, wrong systems, and/or at the wrong times. Accuracy scores were also shown to decrease with forecast length, with the primary decrease in score generally occurring during upscale growth in the early nocturnal period.

The Ice Particle and Aggregate Simulator (IPAS). Part I: Extracting Dimensional Properties of Ice–Ice Aggregates for Microphysical Parameterization

Aggregation, the process by which two or more ice particles attach to each other, is typically observed in clouds that span a range of temperatures and is influenced by the crystal shape (habit). In this study, the resulting characteristics of ice–ice two-monomer aggregation is investigated, which is expected to improve microphysical parameterizations through more precise aggregate characteristics and in turn better predict the rate of aggregation and snow development. A systematic way to determine the aspect ratio of the aggregate was developed, which takes into account the expected falling orientations, overlap of each monomer, and any contact angle that may form through so-called constrained randomization. Distributions were used to obtain the most frequent aspect ratio, major axis, and minor axis of aggregated particles with respect to the monomer aspect ratio. Simulations were completed using the Ice Particle and Aggregate Simulator (IPAS), a model that uses predefined three-dimensional geometries, (e.g., hexagonal prisms) to simulate ice crystal aggregation and allows for variation in crystal size, shape, number, and falling orientation. In this study, after collection in a theoretical grid space, detailed information is extracted from the particles to determine the properties of aggregates. It was found that almost all monomer aspect ratios aggregate to less extreme aggregate aspect ratios at nearly the same rate. Newly formed aggregate properties are amenable to implementation into more sophisticated bulk microphysical models designed to predict and evolve particle properties, which is crucial in realistically evolving cloud ice mass distribution and for representing the collection process.