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NASA NTRS1983

Mesoscale meteorology - Theories, observations and models; Proceedings of the Advanced Study Institute, Bonas, Gers, France, July 13-31, 1982

Among the topics discussed are mesoscale processes and variability, regional and cyclonic scale motions and their prediction modeling, fronts, mesoscale instabilities, buoyancy (gravity) waves and topographic forcing, buoyant convection, boundary layers, and observational technology. The specific issues investigated include methods for initializing mesoscale forecast models, an energy theory for the propagation of gravity currents, a theory for rain bands within extratropical cyclones, the morning glory as a nonlinear wave phenomenon, cumulus clouds, the prediction of severe convection, planetary boundary layer parameterization, and three-dimensional wind field analysis from Doppler radar data.

Lilly, D. K.↗
NASA NTRS2007

Using Multi-scale Modeling Systems to Study the Precipitation Processes

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (CRM), (2) a regional scale model, (3) a coupled CRM and global model, and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer processes and the explicit cloud-radiation, and cloudland surface interactive processes are applied in this multi-scale modeling system. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented.

Tao, Wei-Kuo↗
NASA NTRS1983

NASA/MSFC FY-83 Atmospheric Processes Research Review

The atmospheric processes research program was reviewed. Research tasks sponsored by the NASA Office of Space Science and Applications, Earth Sciences and Applications Division in the areas of upper atmosphere, global weather, and mesoscale processes are discussed. The are: the research project summaries, together with the agenda and other information about the meeting.

Turner, R. E.↗
NASA NTRS2008

Cloud-System Resolving Models: Status and Prospects

Cloud-system resolving models (CRM), which are based on the nonhydrostatic equations of motion and typically have a grid-spacing of about a kilometer, originated as cloud-process models in the 1970s. This paper reviews the status and prospects of CRMs across a wide range of issues, such as microphysics and precipitation; interaction between clouds and radiation; and the effects of boundary-layer and surface-processes on cloud systems. Since CRMs resolve organized convection, tropical waves and the large-scale circulation, there is the prospect for several advances in both basic knowledge of scale-interaction requisite to parameterizing mesoscale processes in climate models. In superparameterization, CRMs represent convection, explicitly replacing many of the assumptions necessary in contemporary parameterization. Global CRMs have been run on an experimental basis, giving prospect to a new generation of climate weather prediction in a decade, and climate models due course. CRMs play a major role in the retrieval of surface-rain and latent heating from satellite measurements. Finally, enormous wide dynamic ranges of CRM simulations present new challenges for model validation against observations.

Tao, Wei-Kuo↗
NASA NTRS2023

The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project: A Review

The Southern Ocean serves as the primary gateway through which the intermediate, deep, and bottom waters of the ocean interact with the surface ocean (and thus the atmosphere), and it has a profound influence on the oceanic uptake of anthropogenic carbon and heat as well as nutrient resupply from the abyss to the surface. Yet it has been the least observed and understood region of the world ocean. The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) project was implemented in 2014 with a goal to help remedy this deficit in observations and understanding. The SOCCOM project is based on two major advances that have the potential to transform understanding of the Southern Ocean. The first is the development of new biogeochemical sensors mounted on autonomous profiling floats that allow sampling of ocean biogeochemistry in 3-dimensional space. Floats may detect processes with a temporal resolution that ranges from hours to years. The second is that the climate modeling community finally has the computational resources and physical understanding to develop fully coupled climate models that can represent crucial, mesoscale processes in the Southern Ocean, as well as corresponding models that assimilate observations to produce a state estimate. The observational component, based on deployment of profiling floats with oxygen, nitrate, pH and bio-optical sensors, is generating vast amounts of new biogeochemical data that provide a year-round view of the Southern Ocean from the surface to 2000 m. The modeling effort is applying these observations and enhancing our understanding of the current ocean, and reducing uncertainty in projections of future carbon and nutrient cycles and climate. After nine years of operation, including a project renewal in the sixth year, the SOCCOM project has deployed more than 260 profiling floats. These floats have collected over 27,000 vertical profiles throughout the Southern Ocean. A data-assimilating biogeochemical state estimate model has been implemented. Here, the design of the SOCCOM project is reviewed and the scientific results that have been obtained are described. The project’s capability to help meet the observing system priorities outlined for a notional UN Decade for Ocean Sciences Southern Ocean observing system is assessed.

Jorge L. Sarmiento↗
NASA NTRS1990

Preliminary simulations of the large-scale environment during the FIRE cirrus IFO

Large scale forcing (scales greater than 500 km) is the dominant factor in the generation, maintenance, and dissipation of cirrus cloud systems. However, the analyses of data acquired during the first Cirrus IFO have highlighted the importance of mesoscale processes (scales of 20 to 500 km) to the development of cirrus cloud systems. Unfortunately, Starr and Wylie found that the temporal and spatial resolution of the standard and supplemental rawinsonde data were insufficient to allow an explanation of all of the mesoscale cloud features that were present on the 27 to 28 Oct. 1986. It is described how dynamic initialization, or 4-D data assimilation (FDDA) can provide a method to address this problem. The first steps towards application of FDDA to FIRE are also described.

Westphal, Douglas L.↗
NASA NTRSDate not supplied

A Study of the Kinematic and Dynamic Processes associated with Mesoscale Snowbands in a Midwest United States Snowstorm on 5 February 2020

Mesoscale snowbands are frequently responsible for dumping large amounts of snow over a relatively small region and pose a considerable forecasting challenge. The present study focuses on the mesoscale snowbands observed on 5 February 2020 over the Midwest United States. In order to improve the forecasting of mesoscale snowbands, it is important to understand the processes that organize these features. To this end, we are investigating the kinematic and dynamic processes that shape the mesoscale snowbands using a combination of high-altitude airborne radar, in-situ aircraft measurements, surface observations, and model simulations. This presentation will primarily focus on the three-dimensional structure of the mesoscale snowbands in terms of EXRAD reflectivity and horizontal winds. The horizontal winds are retrieved from the EXRAD scanning-beam Doppler velocities using a VAD technique. These winds, in combination with virtual potential temperature taken from the HRRR operational analysis, are used to compute the bulk Richardson number in order to investigate any contributions to banding features that might be tied to Kelvin-Helmholtz instability. Our analysis does not support the presence of Kelvin-Helmholtz instability. That said, low, but not subcritical, Richardson numbers were found near the top of some banding features in this event and it is possible that the model analysis is smoothing out the virtual potential temperature fields. Finally, we present arguments for using a flight module designed to sample the along-band structures with particular emphasis on observing generating cells and low-level microphysics.

Charles N. Helms↗
NASA NTRS1984

Data analysis and model simulation of the initiation of convection on April 24, 1982

A combined modelling and data analysis is used to examine the initiation and development of a hail-producing mesoscale convective system which developed over the Texas panhandle near Amarillo, Texas, on April 24, 1982, and propagated east into Oklahoma. This event occurred during the NASA AVE-VAS IV experiment, as a dense upper air mesoscale network was collecting data at three-hour intervals. The results show that both synoptic and mesoscale processes separately and in concert help to force the convection. The destabilization of the atmosphere due to cold advection is important in removing any cap to deep convective development. The upper level moistening due to flow from the northwest also helps to increase the convective instability of the atmosphere. The mesoscale convergence due to cloud shading appears dominant over that of topography, but the latter cannot be ignored, especially in its sustained effect. The developing mesoscale circulation also appears to tap a surface supply of moisture feeding the convection.

Mcnider, R. T.↗
NASA NTRS1991

High resolution atmospheric and surface variability from combined MAMS and VAS radiances

Measuring of the variation of atmospheric and surface quantities such as moisture and stability at small scales is an important step to monitoring, understanding and forecasting mesoscale processes. For instance, moisture and stability products from the geostationary platform VISSR Atmospheric Sounder (VAS) exhibit interesting detail at the meso B (20-200 km) level (Chesters et al., 1986; Smith et al., 1985). However, variations at the meso C scale (2-20 km) and at the lower end of the meso B scale (20-100 km) suffer from the effects of noise. Noise can be greatly reduced by using a high resolution data collection system. The Multispectral Atmospheric Mapping Sensor (MAMS), with its 100-m resolution over a 36km swath, is well suited to provide high resolution mesoscale information about the atmosphere and surface of the earth. A more complete depiction of the atmospheric state at the smaller scales is possible through the combination of the high horizontal resolution MAMS data with the vertical sounding data of the VAS. This paper demonstrates a procedure for combining MAMS and VAS data in a physical retrieval to produce high resolution derived products of precipitable water (PW), lifted index (LI), and skin temperature (TS). The variability of these products is evaluated in a structure function analysis similar to that of Hillger and Vonder Haar (1979). Results for 19 June 1986 from the Cooperative Hunstville Meteorological Experiment (COHMEX) are presented.

Moeller, Christopher C.↗
NASA NTRS2006

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard will be presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗
NASA NTRS2006

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial-lkm scales are resolved in horizontal domains as large as 10,000 kilometers in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard wlll be is presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗
NASA NTRS2006

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard will be presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗
NASA NTRS2008

A Multi-Scale Modeling System with Unified Physics

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. In recent years, exponentially increasing computer power has extended cloud-resolving-mode1 integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique.

Tao, Wei-Kuo↗
NASA NTRS1986

Coupled ice-ocean dynamics in the marginal ice zones Upwelling/downwelling and eddy generation

This study is aimed at modeling mesoscale processes such as upwelling/downwelling and ice edge eddies in the marginal ice zones. A two-dimensional coupled ice-ocean model is used for the study. The ice model is coupled to the reduced gravity ocean model through interfacial stresses. The parameters of the ocean model were chosen so that the dynamics would be nonlinear. The model was tested by studying the dynamics of upwelling. Wings parallel to the ice edge with the ice on the right produce upwelling because the air-ice momentum flux is much greater than air-ocean momentum flux; thus the Ekman transport is greater than the ice than in the open water. The stability of the upwelling and downwelling jets is discussed. The downwelling jet is found to be far more unstable than the upwelling jet because the upwelling jet is stabilized by the divergence. The constant wind field exerted on a varying ice cover will generate vorticity leading to enhanced upwelling/downwelling regions, i.e., wind-forced vortices. Steepening and strengthening of vortices are provided by the nonlinear terms. When forcing is time-varying, the advection terms will also redistribute the vorticity. The wind reversals will separate the vortices from the ice edge, so that the upwelling enhancements are pushed to the open ocean and the downwelling enhancements are pushed underneath the ice.

Hakkinen, S.↗
NASA NTRS1986

Observing the polar oceans with spaceborne radar

The application of spaceborne imaging radar data to polar oceanography and sea ice is explored. Several problems come to mind which are presently ripe with ideas and models, but are in need of new data, SAR data, for any progress to be made. These are the study of the ice mass balance, the ice momentum balance, and the circulation of the Arctic Ocean. These problems are described along with the data which is applicable to them and can be extracted from SAR imagery. Some uses are discussed of these data to explore mesoscale processes which affect the oceans and ice cover.

Rothrock, Drew↗
NASA NTRS1991

Mesoscale characteristics of a monsoon rainband

A Doppler-radar-based case study of a monsoonal rainband (MRB) observed on the evening of January 12, 1990 near Darwin, Austrialia, is presented. Convective and mesoscale circulation features of this system are elucidated. The structure of the MRB is similar to the conceptual model of Houze (1989). The convergence profiles observed in the stratiform region differed considerably from the classical Houze model. Divergence and not convergence existed at heights of 3-6 km. It is suggested that in the MRB stratiform region, consistent with the observed rearward advection of decaying convective cells, the observed mesoscale updraft/downdraft configuration is a result of decaying convection and not a separately evolving mesoscale process.

Keenan, T. D.↗
NASA NTRS1994

A statistical analysis of the dependency of closure assumptions in cumulus parameterization on the horizontal resolution

Simulated data from the UCLA cumulus ensemble model are used to investigate the quasi-universal validity of closure assumptions used in existing cumulus parameterizations. A closure assumption is quasi-universally valid if it is sensitive neither to convective cloud regimes nor to horizontal resolutions of large-scale/mesoscale models. The dependency of three types of closure assumptions, as classified by Arakawa and Chen, on the horizontal resolution is addressed in this study. Type I is the constraint on the coupling of the time tendencies of large-scale temperature and water vapor mixing ratio. Type II is the constraint on the coupling of cumulus heating and cumulus drying. Type III is a direct constraint on the intensity of a cumulus ensemble. The macroscopic behavior of simulated cumulus convection is first compared with the observed behavior in view of Type I and Type II closure assumptions using 'quick-look' and canonical correlation analyses. It is found that they are statistically similar to each other. The three types of closure assumptions are further examined with simulated data averaged over selected subdomain sizes ranging from 64 to 512 km. It is found that the dependency of Type I and Type II closure assumptions on the horizontal resolution is very weak and that Type III closure assumption is somewhat dependent upon the horizontal resolution. The influences of convective and mesoscale processes on the closure assumptions are also addressed by comparing the structures of canonical components with the corresponding vertical profiles in the convective and stratiform regions of cumulus ensembles analyzed directly from simulated data. The implication of these results for cumulus parameterization is discussed.

Xu, Kuan-Man↗
NASA NTRS1995

The importance of mesoscale circulations generated by subgrid-scale landscape heterogeneities in general circulation models

A mesoscale atmospheric model was used to evaluate the impact of subgrid-scale landscape discontinuities on the vertical profiles of resolved temperature, moisture, and moist static energy in the planetary boundary layer (PBL) of general circulation models (GCMs). These profiles were produced with a 3D version of the model (using a horizontal grid resolution of 7.5 km and 13 vertical layers in the PBL) by averaging horizontally the various atmospheric variables over a 180 x 180 sq km domain-about the size of the horizontal domain represented by a single grid element in a GCM. They were compared to corresponding vertical profiles produced with a 1D version of the model, which simulates the PBL, as in a GCM, over a single horizontal grid element. Differences obtained between the horizontally averaged atmospheric variables produced with the 3D simulations and the 1D simulations emphasize the impact of subgrid-scale landscape discontinuities on GCM-resolved variables. Various types of landscape discontinuities, characterized by horizontal contrasts of surface wetness and size of land patches, were simulated under various background-wind conditions. Differences of temperature, specific humidity, and moist static energy as large as 4 K, 6 g/kg, and 10 kJ/kg were obtained in some cases. These differences were not affected significantly by moderate winds but were sensitive to the spatial distribution of surface wetness. These results emphasize the need to parameterize mesoscale processes induced by landscape discontinuities in GCMss.

Lynn, Barry H.↗