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At least 541 records · Page 30

Machine Learning Global Simulation of Nonlocal Gravity Wave Propagation

Global climate models typically operate at a grid resolution of hundreds of kilometers and fail to resolve atmospheric mesoscale processes, e.g., clouds, precipitation, and gravity waves (GWs).Model representation of these processes and their sources is essential to the global circulation and planetary energy budget, but subgrid scale contributions from these processes are often only approximately represented in models using parameterizations. These parameterizations are subject to approximations and idealizations, which limit their capability and accuracy. The most drastic of these approximations is the “single-column approximation” which completely neglects the horizontal evolution of these processes, resulting in key biases in current climate models. With a focus on atmospheric GWs, we present the first-ever global simulation of atmospheric GW fluxes using machine learning (ML) models trained on the WINDSET dataset to emulate global GW emulation in the atmosphere, as an alternative to traditional single-column parameterizations. Using an Attention U-Net-based architecture trained on globally resolved GW momentum fluxes, we illustrate the importance and effectiveness of global nonlocality, when simulating GWs using data-driven schemes.

Aman Gupta↗

Sensitivity of Precipitation Processes to Microphysics and Resolution in a Cloud Resolving Model

The Goddard Cumulus Ensemble (GCE) model examines the impact of various microphysical schemes, and vertical and horizontal resolution in the development, intensity and rainfall associated with mesoscale convective systems, idealized hurricanes and an ensemble of clouds. The model variables include horizontal and vertical velocities, potential temperature, perturbation pressure, turbulent kinetic energy, and mixing rations of all water phases (vapor, liquid and ice). The major characteristics of the GCE model are the explicit representation of warm rain and ice microphysical processes, and their complex interactions with solar and infrared radiative transfer processes and with surface processes. For idealized hurricanes, an axisymmetric version of the GCE model was developed and used to simulate the tropical cyclogenesis process using both a Rankin vortex and saturated air within a specified radius as initial conditions. For mesoscale convective systems, the 3-D version of the GCE model was use to simulate squall lines that developed in the western Pacific, South China Sea, eastern Atlantic, South America and central U.S. FOr the cloud ensemble, the GCE model was integrated for several days in order to have a good sampling of cloud statistics. In this paper, the sensitivities of hurricane intensity to various microphysical processes and model grid resolutio will be examined. This will be mainly achieved by performing sensitivity tests using various horizontal (from 1-to 5-km) and vertical resolutions (from 20- to 200-m in the lower troposphere to 200- to 500m in the middle and upper troposphere). Sensitivity test using various microphysical schemes (warm rain only, and three ice with either graupel or hail) will also be performed. The thermodynamic and water budget associated with various types of precipitation systems will also be evaluated. The budgets will be calculated for different regions (i.e., convective and stratiform regions).

Tao, Wei-Kuo↗

Mesoscale disturbances in the tropical stratosphere excited by convection - Observations and effects on the stratospheric momentum budget

Aircraft temperature and pressure measurements as well as satellite imagery are used to establish the amplitudes and the space and time scale of potential temperature disturbances over convective systems. A conceptual model is proposed for the generation of mesoscale gravity waves by convection. The momentum forcing that a reasonable distribution of convection might exert on the tropical stratosphere through convectively excited mesoscale gravity waves of the observed amplitudes is estimated. Aircraft measurements show that presence of mesoscale disturbances in the lower stratospheric temperature, disturbances that appear to be associated with underlying convection. If the disturbances are convectively excited mesoscale gravity waves, their amplitude is sufficient that their breakdown in the upper stratosphere will exert a zonal force comparable to but probably smaller than the planetary-scale Kelvin waves.

Pfister, Leonhard↗

A nested-grid limited-area model for short term weather forecasting

The present investigation is concerned with a mesoscale atmospheric simulation system (MASS), incorporating the sigma-coordinate primitive equations. The present version of this model (MASS 3.0) has 14 vertical layers, with the upper boundary at 100 mb. There are 128 x 96 grid points in each layer. The earlier version of this model (MASS 2.0) has been described by Kaplan et al. (1982). The current investigation provides a summary of major revisions to that version and a description of the parameterization schemes which are presently included in the model. The planetary boundary layer (PBL) is considered, taking into account aspects of generalized similarity theory and free convection, the surface energy budget, the surface moisture budget, and prognostic equations for the depth h of the PBL. A cloud model is discussed, giving attention to stable precipitation, and cumulus convection.

Wong, V. C.↗

Mesoscale density variability in the mesosphere and thermosphere: Effects of vertical flow accelerations

A mechanistic one dimensional numerical (iteration) model was developed which can be used to simulate specific types of mesoscale atmospheric density (and pressure) variability in the mesosphere and the thermosphere, namely those due to waves and those due to vertical flow accelerations. The model was developed with the idea that it could be used as a supplement to the TGCMs (thermospheric general circulation models) since such models have a very limited ability to model phenomena on small spatial scales. The simplest case to consider was the integration upward through a time averaged, height independent, horizontally divergent flow field. Vertical winds were initialized at the lower boundary using the Ekman pumping theory over flat terrain. The results of the computations are summarized.

Revelle, D. O.↗

On the sensitivity of a residual circulation model to differences in input temperature data

The residual mean circulation (RMC) formulation of zonally averaged transport in the middle atmosphere produces a circulation which depends on the distributions of net diabatic heating and temperature. Such circulations are from two temperature data sets, using the same radiative transfer code (Rosenfield et al. 1987). These circulations are then used to transport N2O in a photochemical model. The circulations and the resulting N2O distributions are notably different during the Northern Hemisphere winter, with that based on the NMC temperatures producing too much upward transport in the tropical stratosphere, as judged by comparison with the stratospheric and mesoscale sounder data. The experiment demonstrates that model calculations, in general, and perturbation assessments, in particular, are likely to be quite sensitive to the choice of input temperature data (where this is not computed self-consistently). It also reveals what appears to be a seasonally dependent bias in NMC zonally averaged temperatures with respect to those obtained from the LIMS instrument during 1978/1979.

Guthrie, Paul D.↗

Statistically conditioned least squares retrievals planned for the VAS demonstration experiment

Problems in the retrieval of atmospheric profiles from passively observed satellite radiances are reviewed. Plans are described for statistically conditioned least squares retrievals of temperature and moisture profiles around mesoscale events, based upon the expected sensitivity of the VAS channels to the atmospheric variations. Simulated soundings for a global data set and for the 1976 National Storm Laboratory (NSSL) severe storm data set are also examined. This combination of radiance modeling and statistical conditioning should yield reliable mesoscale soundings and provide a test bed for sounding research and development with the VAS instrument.

Chester, D.↗

Climate and smoke - An appraisal of nuclear winter

A reevaluation is presented of the 'nuclear winter' scenario of Turco et al. (1983). New pertinent data have emerged from laboratory studies, field experiments, and numerical models on the smoke-plume, mesoscale, and global scales. A full-scale nuclear exchange's probable soot injections lead, in three-dimensional climate simulations, to midsummer land temperature decreases averaging 10-20 C in northern midlatitudes, with local cooling of as much as 35 C. Anomalous circulation patterns due to solar heating of the soot could stabilize the upper atmosphere against overturning, thereby prolonging the soot's residence time in the atmosphere. Monsoon disruptions and severe ozone layer depletion are also foreseen.

Turco, R. P.↗

Convective dynamics - Panel report

Aspects of highly organized forms of deep convection at midlatitudes are reviewed. Past emphasis in field work and cloud modeling has been directed toward severe weather as evidenced by research on tornadoes, hail, and strong surface winds. A number of specific issues concerning future thrusts, tactics, and techniques in convective dynamics are presented. These subjects include; convective modes and parameterization, global structure and scale interaction, convective energetics, transport studies, anvils and scale interaction, and scale selection. Also discussed are analysis workshops, four-dimensional data assimilation, matching models with observations, network Doppler analyses, mesoscale variability, and high-resolution/high-performance Doppler. It is also noted, that, classical surface measurements and soundings, flight-level research aircraft data, passive satellite data, and traditional photogrammetric studies are examples of datasets that require assimilation and integration.

Carbone, Richard↗

Asymmetry in the Diurnal Variation of Surface Albedo

Remote sensing of surface properties and estimation of clear-sky and surface albedo generally assumes that the albedo depends only on the solar zenith angle. The effects of dew, frost, and precipitation as well as evaporation and wind can lead to some systematic diurnal variability resulting in an asymmetric diurnal cycle of albedo. This paper examines the symmetry of both surface-observed albedos and top-of-the-atmosphere (TOA) albedos derived from satellite data. Broadband and visible surface albedos were measured at the Department of Energy Atmospheric Radiation Measurement (ARM) Program Southern Great Plains Central Facility, at some fields near the ARM site, and over a coniferous forest in eastern Virginia. Surface and wind conditions are available for most cases. GOES-8 satellite radiance data are converted to broadband albedo using bidirectional reflectance functions and an empirical narrowband-to-broadband relationship. The initial results indicate that surface moisture has a significant effect and can change the albedo in the afternoon by 20% relative to its morning counterpart. Such effects may need to be incorporated in mesoscale and even large-scale models of atmospheric processes.

Mayor, S.↗

Satellite Proving Ground for the GOES-R Geostationary Lightning Mapper (GLM)

The key mission of the Satellite Proving Ground is to demonstrate new satellite observing data, products and capabilities in the operational environment to be ready on Day 1 to use the GOES-R suite of measurements. Algorithms, tools, and techniques must be tested, validated, and assessed by end users for their utility before they are finalized and incorporated into forecast operations. The GOES-R Proving Ground for the Geostationary Lightning Mapper (GLM) focuses on evaluating how the infusion of the new technology, algorithms, decision aids, or tailored products integrate with other available tools (weather radar and ground strike networks; nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing forecasts and warning products. Additionally, the testing concept fosters operation and development staff interactions which will improve training materials and support documentation development. Real-time proxy total lightning data from regional VHF lightning mapping arrays (LMA) in Northern Alabama, Central Oklahoma, Cape Canaveral Florida, and the Washington, DC Greater Metropolitan Area are the cornerstone for the GLM Proving Ground. The proxy data will simulate the 8 km Event, Group and Flash data that will be generated by GLM. Tailored products such as total flash density at 1-2 minute intervals will be provided for display in AWIPS-2 to select NWS forecast offices and national centers such as the Storm Prediction Center. Additional temporal / spatial combinations are being investigated in coordination with operational needs and case-study proxy data and prototype visualizations may also be generated from the NASA heritage Lightning Imaging Sensor and Optical Transient Detector data. End users will provide feedback on the utility of products in their operational environment, identify use cases and spatial/temporal scales of interest, and provide feedback to the developers for adjusted or new products.

Goodman, Steven J.↗

The GOES-R Geostationary Lightning Mapper (GLM) and the Global Observing System for Total Lightning

for the existing GOES system currently operating over the Western Hemisphere. New and improved instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved temporal, spatial, and spectral resolution for the next generation Advanced Baseline Imager (ABI). The GLM will map total lightning continuously day and night with near-uniform spatial resolution of 8 km with a product latency of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency among a number of potential applications. The GLM will help address the National Weather Service requirement for total lightning observations globally to support warning decision-making and forecast services. Science and application development along with pre-operational product demonstrations and evaluations at NWS national centers, forecast offices, and NOAA testbeds will prepare the forecasters to use GLM as soon as possible after the planned launch and check-out of GOES-R in 2016. New applications will use GLM alone, in combination with the ABI, or integrated (fused) with other available tools (weather radar and ground strike networks, nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing more timely and accurate forecasts and warnings.

Goodman, Steven J.↗

TPSAS-NF1676L-31539-DND

TROPICS (Time-Resolved Observations of Precipitation Structure and Storm Intensity with a Constellation of Smallsats) Science Objectives - Relate precipitation structure evolution, including diurnal cycle, to the evolution of the upper-level warm core and associated intensity changes - Relate the occurrence of intense precipitation cores (convective bursts) to storm intensity evolution - Relate retrieved environmental moisture measurements to coincident measures of storm structure (including size) and intensity - Assimilate microwave observations in mesoscale and global numerical weather prediction models to assess impacts on storm track and intensity

William Blackwell↗

Sensitivity of Precipitation Processes to Microphysics and Resolution in a Cloud-Resolving Model

The Goddard Cumulus Ensemble (GCE) model is used to examine the impact of various microphysical schemes, and vertical and horizontal resolution on the development, intensity and rainfall associated with mesoscale convective systems, idealized hurricanes and an ensemble of clouds. The model variables include horizontal and vertical velocities, potential temperature, perturbation pressure, turbulent kinetic energy, and mixing ratios of all water phases (vapor, liquid, and ice). The major characteristics of the GCE model are the explicit representation of warm rain and ice microphysical processes, and their complex interactions with solar and infrared radiative transfer processes, and with surface processes. For idealized hurricane, an axisymmetric version of the GCE model was developed and used successfully to simulate the tropical cyclogenesis process using both a Rankin vortex and saturated air within a specified radius as initial conditions. For mesoscale convective systems, the 3-D version of the GCE model was used to simulate squall lines that developed in the western Pacific, South China Sea, eastern Atlantic, South America and central U.S. For the cloud ensemble, the GCE model was integrated for several days in order to have good sampling of cloud statistics. In this paper, the sensitivities of hurricane intensity to various microphysical processes and model grid resolution will be examined. This will be mainly achieved by performing sensitivity tests using various horizontal (from 1- to 5-kilometers) and vertical resolutions (from 20- to 200-meters in the lower troposphere to 200- to 500-m in the middle and upper troposphere). Sensitivity tests using various microphysical schemes (warm rain only, and three ice with either graupel or hail) will also be performed. The PBL and diurnal variation of precipitation processes will also be evaluated. The budgets will be calculated for different regions (i.e., convective and stratiform regions).

Tao, Wei-Kao↗

Sensitivity of Precipitation Processes to Microphysics and Resolution in a Cloud-resolving Model

The Goddard Cumulus Ensemble (GCE) model is used to examine the impact of various microphysical schemes, and vertical and horizontal resolution on the development, intensity and rainfall associated with mesoscale convective systems, idealized hurricanes and an ensemble of clouds. The model variables include horizontal and vertical velocities, potential temperature, perturbation pressure, turbulent kinetic energy, and mixing ratios of all water phases (vapor, liquid, and ice). The major characteristics of the GCE model are the explicit representation of warm rain and ice microphysical processes, and their complex interactions with solar and infrared radiative transfer processes. For idealized hurricane, an axisymmetric version of the GCE model was developed and used successfully to simulate the tropical cyclogenesis process using both a Rankin vortex and saturated air within a specified radius as initial conditions. For mesoscale convective systems, the 3-D version of the GCE model was used to simulate squall lines that developed in the western Pacific, South China Sea, eastern Atlantic, South America and central US. For the cloud ensemble, the GCE model was integrated for several days in order to have a good sampling of cloud statistics.

Tao, Wei-Kuo↗

Sensitivity of Precipitation Processes to Microphysics and Resolution in a Cloud-Resolving Model

The Goddard Cumulus Ensemble (GCE) model is used to examine the impact of various microphysical schemes, and vertical and horizontal resolution on the development, intensity and rainfall associated with mesoscale convective systems, idealized hurricanes and an ensemble of clouds. The model variables include horizontal and vertical velocities, potential temperature, perturbation pressure, turbulent kinetic energy, and mixing ratios of all water phases (vapor, liquid, and ice). The major characteristics of the GCE model are the explicit representation of warm rain and ice microphysical processes, and their complex interactions with solar and infrared radiative transfer processes, and with surface processes. For idealized hurricane, an axisymmetric version of the GCE model was developed and used successfully to simulate the tropical cyclogenesis process using both a Rankin vortex and saturated air within a specified radius as initial conditions. For mesoscale convective systems, the 3-D version of the GCE model was used to simulate squall lines that developed in the western Pacific, eastern Atlantic and central US. For the cloud ensemble, the GCE model was integrated for several days in order to have good sampling of cloud statistics. In this paper, the sensitivities of hurricane intensity to various microphysical processes and model grid resolution will be examined.

Tao, Wei-Kuo↗

Sensitivity of Precipitation Processes of Microphysics and Resolution in a Cloud-Resolving Model

The Goddard Cumulus Ensemble (GCE) model is used to examine the impact of various microphysical schemes, and vertical and horizontal resolution ion the development, intensity and rainfall associated with mesoscale convective systems, idealized hurricanes and an ensemble f clouds. The model variables include horizontal and vertical velocities, potential temperatures, perturbation pressure, turbulent kinetic energy, and mixing ratios of all water phases (vapor, liquid, and ice). The major characteristics of the GCE model are the explicit representation of warm rain and ice microphysical processes, and their complex interactions with solar and infrared radiative transfer processes, and with surface processes. For idealized hurricane, an axisymmetric version of the GCE model was developed and used successfully to simulate the tropical cyclogenesis process using both a Rankin vortex and saturated air within a specified radius as initial conditions. For mesoscale convective systems, the 3-D version of the GCE model was used to simulated squall lines that developed in the western Pacific, eastern Atlantic and central US. For the cloud ensemble, the GCE model was integrated for several days in order to have good sampling of cloud statistics. In this paper, the sensitivities of hurricane intensity to various microphysical processes and model grid resolution will be examined. This will be mainly achieved by performing sensitivity tests using various horizontal (from 1- to 5-km) and vertical resolutions (from 20- to 200-m in the lower troposphere to 200- to 500-m in the middle and upper troposphere). Sensitivity tests using various microphysical schemes (warm rain only, and three ice with either graupel or hail) will also be performed. The thermodynamic and water budget associated with various types of precipitation systems will also be evaluated. The budgets will be calculated for different regions (i.e., convective and stratiform regions).

Tao, Wei-Kuo↗

Understanding and Utilizing PBL Height Data from Multiple Observing Systems in the GEOS System

The accuracy of PBL height simulation is a key issue in many applications including forecasting near surface meteorology and air quality, however, it is a very challenging problem due to the lack of not only comprehensive, global Planetary Boundary Layer (PBL) observations but also a strategy and infrastructure to utilize PBL height data from a variety of sensors. Following the designation of PBL as an incubation class observable in the 2017 Decadal Survey, the PBL Incubation Study Team Report [14] made clear that “a future global PBL observing system requires modeling and data assimilation as essential components.” There is an urgent need for global modeling development in order to utilize Program of Record (POR) observations, assess their impacts, and identify gaps to be filled by future PBL missions. Our overall objective is to develop PBL data assimilation capabilities in the NASA Global Earth Observing System (GEOS), focusing on PBL height from multiple observing systems, to support the assessment and use of future PBL observations. The NASA GEOS system is composed of the GEOS global atmospheric general circulation model (AGCM) and the atmospheric data assimilation system (ADAS). The PBL parameterizations include the “Lock” K-profile scheme driven by surface and cloud-top buoyancy fluxes ([4]), and the “Louis” local scheme for stable conditions based on the Richardson number ([5]). Above the mixed layer defined by the Lock surface plume, shallow cumulus convection is represented by the mass flux scheme of [9]. Additional parameterizations are summarized in [1]. The ADAS employs the hybrid 4D Ensemble- Variational (EnVar) configuration ([15]), with the ensemble providing flow-dependent background error covariance information. The resultant analysis increments are fed back to the forecast model through the 4D incremental analysis update (IAU) approach ([11]). In this study, PBL height data are being or have been generated from radiosondes, GNSS RO, satellite (CATS, CALIPSO and ICESat-2) and ground-based (MPLNET) lidars, and wind profiler. Investigations have been conducted to specify quality marks for PBL height retrievals for the data assimilation purpose. These PBL height data have different strengths and weaknesses ([2], [3], [6], [7], [8], [10]), and the satellite PBL height data provide better global coverage and complement in-situ PBL height data. Radiosondes offer high accuracy and in situ measurement of temperature and humidity profiles, but with poor spatio-temporal sampling. The in-situ observing systems like MPLNET and wind profiler provide long history of PBL height records at each station. The GNSS RO based PBL height is retrieved based on the sharp gradients in refractivity profile that represent the fine vertical structure of temperature and moisture changes above the PBL. However, not all RO refractivity profiles reach the surface depending on location and regime, and RO refractivity retrievals can be negatively biased below 2km. The PBL height data from satellite lidars provide high resolution along track PBL height retrievals, but over land they are affected by previous day convective PBL aerosol and strongly associated with mixing layer and retrievals cannot be made below thick, attenuating clouds. A successful assimilation of PBL height data requires a thorough understanding of the observing method and the retrieval algorithm for each observing system in order to use the PBL height data from multiple observing systems properly. Due to the sensitivity of PBL height data to the observing method and choice of algorithm, it is important to use a model definition appropriate for each observation type to compute differences between PBL height data and model PBL height (OmFs). The GEOS model currently includes two PBL height definitions suitable for direct comparison with observed PBL height, and additional definitions are being added in this study. Evaluation of different model PBL height definitions is underway. Meanwhile, efforts have been made in the GEOS data assimilation system to develop PBL height data assimilation capability. PBL height data can be assimilated using two different approaches. The traditional approach is to construct an observation operator and its tangent linear and adjoint, which link control variables to PBL height data from each observing system. This observation operator can be very complicated, e.g., the lidar-based PBL height observation operator includes the backscatter lidar forward observation operator, the algorithm to derive PBL height from attenuated total backscatter, interpolation, and calculations handling the mismatch between observed and model scales. The other approach is to augment PBL height to the control variable vector, and it is adopted in this study. The latter approach was also used in previous studies, e.g., the assimilation of PBL height data from radiosonde and aircraft in the Real Time Mesoscale Analysis (RTMA) system for a dispersion modelling study ([13]); the PBL height assimilation study using lidar PBL height data at Greensburg, Kansas for a field campaign ([12]). The PBL height assimilation from multiple observing systems in this study allows us to take advantage of the diverse PBL height data that provide much better global coverage collectively under different meteorological conditions and with different temporal and spatial scales. As all the PBL heights are tightly coupled with the PBL thermodynamic variables, the strong correlations, which are provided by the 4D ensemble forecast, enable PBL height data from various sources to interact and combine coherently and provide additional information for PBL temperature and moisture fields. The results of comparisons among PBL height data from different sources and the evaluation of the model PBL height definitions with the PBL height data will be presented, and the PBL height data synergy strategies and preliminary results will also be discussed at the conference.

Y. Zhu↗