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At least 73 records · Page 4

International Conference on Mesoscale Precipitation: Hydrologic and Meteorological Aspects, 3rd, College Station, TX, Feb. 27-Mar. 1, 1991, Proceedings

Papers presented in this volume discuss a mechanism causing mesoscale organizations of precipitation in midlatitude cyclones, the spatial variability of summer Florida precipitation and its impact on microwave radiometer rainfall-measurement systems, the relation between the mean areal rainfall and the fractional area where it rains above a given threshold, and a possible explanation for low correlation dimension estimates for the atmosphere. Attention is also given to a physically based simulation of radar rainfall data using a space-time rainfall model, the predictability of mesoscale rainfall in the tropics, and an intercomparison of tree satellite infrared rainfall techniques over Japan and surrounding waters. Other papers are on an evaluation of sampling errors of precipitation from spaceborne and ground sensors, an approach to the estimation of the areal rain-rate distribution from spaceborne radar by the use of multiple thresholds, and a comparison of two satellite-based rainfall algorithms using Pacific atoll raingage data.

Valdes, Juan B.↗

Objectively Identifying Transverse Cirrus Bands in Tropical Cyclones using a Convolutional Neural Network

Transverse cirrus bands (TCBs) are bands of upper-level clouds that are regularly seen in mesoscale and synoptic-scale weather systems. In tropical cyclones, their appearance has been subjectively linked to intensification and the diurnal cycle, but these hypothesized relationships have not been rigorously tested due to the difficulty of objectively identifying TCBs in satellite images. This presentation describes a machine learning technique that successfully identifies TCBs in imagery from the GOES-16 Advanced Baseline Imager. The technique uses a convolutional neural network (CNN) that assigns a probability of each pixel in the image being associated with a TCB. Using the CNN, a database of TCBs from 2018 to 2022 was developed for the Atlantic basin. Statistics using this database will be presented, including the relationship between TCBs and deep-layer vertical wind shear, intensity change, and the TC diurnal cycle.

John Mark Mayhall↗

Climatology of the Vertical Profiles of Polarimetric Radar Variables and Retrieved Microphysical Parameters in Continental/Tropical MCSs and Landfalling Hurricanes

Most existing cloud models tend to overestimate the size of cloud ice particles and underestimate their concentration. This emphasizes the need to provide a reliable observational reference to optimize cloud model performance, particularly in areas of high concentration of ice at high altitudes. The dual-polarization radars give the community a unique opportunity to quantify cloud ice with a good accuracy using polarimetric radar retrievals. Here, in this study, we utilize the network of operational WSR-88D radars to build a climatology of the vertical profiles of radar variables, such as radar reflectivity Z, differential reflectivity Z DR , and specific differential phase K DP as well as the radar-retrieved vertical profiles of ice water content (IWC) above the melting layer and liquid water content below it, mean volume diameter D m , and total number concentration N t of ice and liquid particles. Such climatology was created for continental/marine mesoscale convective systems (MCSs) and tropical cyclones including hurricanes. The dataset includes 13 continental MCSs, 10 marine MCSs, and 11 tropical cyclones. Separate statistics of the “background” vertical profiles and the ones associated with high IWC aloft have been obtained in the course of this study. It is shown that continental MCSs exhibit larger size of ice in lower concentration aloft compared to the marine MCSs and especially tropical cyclones/hurricanes. A combination of high KDP and low Z aloft signifies lower D m , higher N t , and often substantial IWC.

54 ENVIRONMENTAL SCIENCES↗

Assessment of Storm-Associated Precipitation and Its Extremes Using Observational Data Sets and Climate Model Short-Range Hindcasts

Heavy precipitation, often associated with weather phenomena such as tropical cyclones, extratropical cyclones (ETCs), atmospheric rivers (ARs), and mesoscale convective systems (MCSs), can cause significant socio-economic loss. Here, in this study, we apply atmospheric feature trackers to quantify the contributions of these storm types in observational data sets and climate model short-range hindcasts. We generate a global hourly storm data set at 0.25° spatial resolution covering 2006–2020, based on the tracking results from TempestExtremes and Python FLEXible object TRacKeR. Our analyses show that these four storm types account for 67% of global annual mean precipitation and 82% of top 1% precipitation extremes, with MCSs mainly over the tropics, and ARs and ETCs over the midlatitudes. The percentage of precipitation contributions from these storms also show strong seasonality over many geographical locations. We further apply the tracking results to the Energy Exascale Earth System Model (E3SM) short-range hindcasts and evaluate how well these storms are simulated. The evaluation show that E3SM, with ∼1° resolution, significantly underestimates storm-associated precipitation totals and extremes, especially for MCSs in the tropics. Our analysis also suggests that model fails to capture the correct mean diurnal phases and amplitude of MCS precipitation. This phenomenon-based approach provides a better understanding of precipitation characteristics and can lead to enhanced model evaluation by revealing underlying problems in model physics related to precipitation processes associated with the heavy-precipitating storms.

54 ENVIRONMENTAL SCIENCES↗

Global Precipitation Experiment—A New World Climate Research Programme Lighthouse Activity

The future state of the global water cycle and the prediction of freshwater availability for humans around the world remain among the challenges of climate research and are relevant to several United Nations Sustainable Development Goals. The Global Precipitation Experiment (GPEX) takes on the challenge of improving the prediction of precipitation quantity, phase, timing, and intensity, characteristics that are products of a complex integrated system. It will achieve this by leveraging existing World Climate Research Programme (WCRP) activities and community capabilities in satellite, surface-based, and airborne observations, modeling, and experimental research and by conducting new and focused activities. It was launched in October 2023 as a WCRP Lighthouse Activity. Here, we present an overview of the GPEX Science Plan that articulates the primary science questions related to precipitation measurements, process understanding, model performance and improvements, and plans for capacity development. The central phase of GPEX is the WCRP Years of Precipitation for 2–3 years with coordinated global field campaigns focusing on different storm types (atmospheric rivers, mesoscale convective systems, monsoons, and tropical cyclones, among others) over different regions and seasons. Activities are planned over the three phases (before, during, and after the Years of Precipitation) spanning a decade. These include gridded data evaluation and development, advanced modeling, enhanced understanding of processes critical to precipitation, multiscale prediction of precipitation events across scales, and capacity development. These activities will be further developed as part of the GPEX Implementation Plan.

Climate change↗

Results of the US contribution to the joint US/USSR Bering Sea experiment

The atmospheric circulation which occurred during the Bering Sea Experiment, 15 February to 10 March 1973, in and around the experiment area is analyzed and related to the macroscale morphology and dynamics of the sea ice cover. The ice cover was very complex in structure, being made up of five ice types, and underwent strong dynamic activity. Synoptic analyses show that an optimum variety of weather situations occurred during the experiment: an initial strong anticyclonic period (6 days), followed by a period of strong cyclonic activity (6 days), followed by weak anticyclonic activity (3 days), and finally a period of weak cyclonic activity (4 days). The data of the mesoscale test areas observed on the four sea ice option flights, and ship weather, and drift data give a detailed description of mesoscale ice dynamics which correlates well with the macroscale view: anticyclonic activity advects the ice southward with strong ice divergence and a regular lead and polynya pattern; cyclonic activity advects the ice northward with ice convergence, or slight divergence, and a random lead and polynya pattern.

Campbell, W. J.↗

The impact of dynamic data assimilation on the numerical simulations of the QE II cyclone and an analysis of the jet streak influencing the precyclogenetic environment

A mesoscale numerical model is combined with a dynamic data assimilation via Newtonian relaxation, or 'nudging', to provide initial conditions for subsequent simulations of the QE II cyclone. Both the nudging technique and the inclusion of supplementary data are shown to have a large positive impact on the simulation of the QE II cyclone during the initial phase of rapid cyclone development. Within the initial development period (from 1200 to 1800 UTC 9 September 1978), the dynamic assimilation of operational and bogus data yields a coherent two-layer divergence pattern that is not well defined in the model run using only the operational data and static initialization. Diagnostic analysis based on the simulations show that the initial development of the QE II storm between 0000 UTC 9 September and 0000 UTC 10 September was embedded within an indirect circulation of an intense 300-hPa jet streak, was related to baroclinic processes extending throughout a deep portion of the troposphere, and was associated with a classic two-layer mass-divergence profile expected for an extratropical cyclone.

Manobianco, John↗

Session on validation of coupled models

The session on validation of coupled models is reviewed. The current use of a mesoscale model with a grid size of 20-km during STORM-FEST in 1992 has proven to be extremely valuable. The availability of forecast products at a much higher temporal and spatial resolution was very helpful for mesoscale forecasting, mission planning, and the guidance of research aircraft. Recent numerical simulation of ocean cyclones and mesoscsle convective systems using nonhydrostatic cloud/mesoscale models with a grid size as small as 2-km have demonstrated the potential of these models for predicting mesoscale convective systems, squall lines, hurricane rainbands, mesoscale gravity waves, and mesoscale frontal structures embedded within an extratropical cyclone. Although mesoscale/cloud scale models have demonstrated strong potential for use in operational forecasting, very limited quantitative evaluation (and verification) of these models were performed. As a result, the accuracy, the systematic biases, and the useful forecasts limits were not properly defined for these models. Also, no serious attempts were made to use these models for operational prediction of mesoscale convective systems.

Kuo, Bill↗

Characterizing the Severe Turbulence Environments Associated with Commercial Aviation Accidents: Hydrostatic Mesobeta Scale Numerical Simulations of Supergradient Wind Flow and Streamwise Ageostrophic Frontogenesis - Part 2

Simulation experiments reveal key processes that organize a hydrostatic environment conducive to severe turbulence. The paradigm requires juxtaposition of the entrance region of a curved jet stream, which is highly subgeostrophic, with the entrance region of a straight jet stream, which is highly supergeostrophic. The wind and mass fields become misphased as the entrance regions converge resulting in the significant spatial variation of inertial forcing, centripetal forcing, and along- and cross-stream pressure gradient forcing over a mesobeta scale region. This results in frontogenesis and the along-stream divergence of cyclonic and convergence of cyclonic ageostrophic vertical vorticity. The centripetally forced mesoscale front becomes the locus of large gradients of ageostrophic vertical vorticity along an overturning isentrope. This region becomes favorable for streamwise vorticity gradient formation enhancing the environment for organization of horizontal vortex tubes in the presence of buoyant forcing.

Kaplan, Michael L.↗

Summer mean and extreme precipitation over the Mid-Atlantic region: climatological characteristics and contributions from different precipitation types

Based on a long-term observational dataset from the tracking of mesoscale convective systems (MCSs), isolated deep convection (IDC), and tropical cyclones (TCs), we examine the climatological characteristics of summer mean and extreme precipitation during 2004 – 2017 and their respective contributions from MCS, IDC, TC, and non-convective (NC) systems and the local vs. remote influence of MCS and IDC over the MAR. On average, MCS, IDC, TC, and NC contribute 22%, 29%, 4%, and 45% to the total summer mean precipitation in the region. While MCS and TC precipitation primarily occurs in the coastal areas east of the Appalachian Mountains, IDC precipitation is more concentrated in the southern MAR and near the mountain windward slopes. Each summer, ~41 MCSs with an average lifetime of 19.6 hours influence the MAR, with 80% initiated outside and traveling on average 10 hours to the region. Around 13 MCSs initiated in the Great Plains and Midwest propagate across the Appalachian Mountains and contribute 20-40% to summer MCS precipitation in the central Mid-Atlantic coastal areas. In contrast, more than 2000 IDCs with an average lifetime of 2.0 hours influence the MAR each summer, and 77% are initiated locally. MCS, IDC, TC, and NC contribute 31% (30%), 26% (31%), 18% (7%), and 26% (32%) to the top 1% (5%) extreme daily precipitation, respectively. Considering extreme hourly precipitation, however, the IDC contributions increase to 41% (top 1%) and 38% (top 5%) due to the shorter duration of IDC events than the other precipitation types.

Li, Jianfeng↗

Regional models - Emerging research tools for synoptic meteorologists

A number of regional-scale numerical weather prediction models are discussed together with their application to the study of the structure and the dynamics of mesoscale phenomena. Consideration is given to investigations of natural phenomena (such as midlatitude cyclones and related baroclinic disturbances; upper-level jet-front systems; surface frontal zones, squall lines, and rain bands; mesoscale convective systems; and severe-storm environments) in which two operational models and four research models are used for regional-model studies. It is shown that these models provide investigators with four-dimensional dynamically consistent data sets to supplement and extend those available from observations.

Keyser, Daniel↗

Future Changes in Midwest Extreme Precipitation Depend on Storm Type

Midwestern U.S. extreme precipitation is associated with multiple storm types including mesoscale convective systems (MCSs) and/or training thunderstorms, tropical cyclone (TC) remnants, and winter storms. Anthropogenic warming is expected to increase climatological precipitation globally, however, there may be little correspondence with regional storm-based changes. Furthermore, uncertainty remains in precipitation-temperature scaling due to use of convective parameterization in most global models. In this study, we investigated historically impactful extreme precipitation events from multiple types of Midwest storms using the Weather Research and Forecasting model at convection-permitting resolution. We simulated five-member ensembles of historical hindcasts and experiments representing the storms in the future using the pseudo-global warming method. We found that future precipitation changes depend on storm type, with increases near Clausius-Clapeyron (CC) for winter storms, no consensus for MCSs and/or training thunderstorms, and sub-CC increases for TC remnants. This research highlights the importance of considering storm type in future extreme precipitation projections.

54 ENVIRONMENTAL SCIENCES↗

Combined Microwave and Sferics Measurements as a Continuous Proxy for Latent Heating in Mesoscale Model Predictions

Planar rainfall distributions were retrieved from data provided by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Special Sensor Microwave/Imager (SSM/I) radiometers. Lightning generates Very Low Frequency (VLF) radio noise pulses called sferics. Those pulses propagate over large distances so that they can be continuously monitored with a network of ground based radio receivers. An empirical relationship between the sferics rate and the convective rainfall permitted maps of convective latent heating profiles to be derived continuously from the sferics distributions. Those inferred latent heating rates were assimilated into the Penn State/NCAR Mesoscale Model (MM5) that depicted an intense winter cyclone that passed over Florida on 2 February 1998. When compared to a 14 hour MM5 rainfall forecast using conventional data, the use of lightning data improved the forecast.

Chang, D.-E.↗

Combined Microwave and Sferics Measurements as a Continuous Proxy for Latent Heating in Mesoscale Model Predictions

Planar rainfall distributions were retrieved from data provided by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Special Sensor Microwave Imager (SSM/I) radiometers. Lightning generates Very Low Frequency (VLF) radio noise pulses called sferics. Those pulses propagate over large distances so that they can be continuously monitored with a network of ground based radio receivers. An empirical relationship between the sferics rate and the convective rainfall permitted maps of convective latent heating profiles to be derived continuously from the sferics distributions. Those inferred latent heating rates were assimilated into the Penn State/NCAR Mesoscale Model (MM5) that depicted an intense winter cyclone that passed over Florida on 2 February 1998. When compared to a 14 hour MM5 rainfall forecast using conventional data, the use of lightning data improved the forecast.

Chang, D. -E.↗

Modeling and observations of North Atlantic cyclones: Implications for U.S. Offshore wind energy

To meet the Biden-Harris administration's goal of deploying 30 GW of offshore wind power by 2030 and 110 GW by 2050, expansion of wind energy into U.S. territorial waters prone to tropical cyclones (TCs) and extratropical cyclones (ETCs) is essential. This requires a deeper understanding of cyclone-related risks and the development of robust, resilient offshore wind energy systems. Here, this paper provides a comprehensive review of state-of-the-science measurement and modeling capabilities for studying TCs and ETCs, and their impacts across various spatial and temporal scales. We explore measurement capabilities for environments influenced by TCs and ETCs, including near-surface and vertical profiles of critical variables that characterize these cyclones. The capabilities and limitations of Earth system and mesoscale models are assessed for their effectiveness in capturing atmosphere–ocean–wave interactions that influence TC/ETC-induced risks under a changing climate. Additionally, we discuss microscale modeling capabilities designed to bridge scale gaps from the weather scale (a few kilometers) to the turbine scale (dozens to a few meters). We also review machine learning (ML)-based, data-driven models for simulating TC/ETC events at both weather and wind turbine scales. Special attention is given to extreme metocean conditions like extreme wind gusts, rapid wind direction changes, and high waves, which pose threats to offshore wind energy infrastructure. Finally, the paper outlines the research challenges and future directions needed to enhance the resilience and design of next-generation offshore wind turbines against extreme weather conditions.

17 WIND ENERGY↗

Effective Visualization of Radar Data for Users Impacted by Color Vision Deficiency

Color vision deficiency (CVD) is a decreased ability to discern between particular colors. Eight percent of genetic males and half a percent of genetic females have some form of CVD, with many in the radar community falling into this group. When presenting data on a two-dimensional plane, it is common to use colors to represent values via a colormap. Colormap choice in the radar community is influenced by the ability to highlight scientifically interesting features in data, institutional choices, and domain dominance of legacy colormaps. The problem with these current colormaps is that many do not project well for those with CVD (i.e., green next to red). In working with the CVD community to address this problem, multiple colormaps for moments such as equivalent reflectivity factor and Doppler velocity were created for users with forms of CVD such as deuteranomaly, protanomaly, protanopia, and deuteranopia using Python tools such as colorspacious and viscm. We show how these colormaps can improve interpretability for four cases: a mesoscale convective system, a pyrocumulonimbus storm, a wintertime midlatitude cyclone, and widespread storms with a large bird migration. These new radar equivalent reflectivity factor, Doppler velocity, and polarization colormaps are designed to highlight rain, frozen precipitation, nonmeteorological targets, and velocity-based items, are perceptually uniform, and are visually friendly for those with CVD.

54 ENVIRONMENTAL SCIENCES↗

The structure and dynamics of mesoscale systems influencing severe thunderstorm development during AVE/SESAME 1

Relationships between meso-beta scale systems and thunderstorm formation were examined as part of the NASA atmospheric variability experiment/severe environmental storms and mesoscale experiment 1979. The McIdas program was employed for meso-beta scale analyses of atmospheric structure and dynamics in kinematic computations of the Abilene Triangle on a grid mesh of 100 km for station spacing of 275 km. Mesoscale short wave systems were detected imbedded and propagating cyclonically around upper-level vortex circulation and creating environmental conditions conducive to thunderstorm development. TIROS-N and GOES satellite data served to connect the systems with two convective storms which developed. The necessity to use spaceborne instrumentation carried on the Shuttle or on free-flying satellites for enhancing the data-base on storm development is noted.

Wilson, G. S.↗