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NASA NTRS1982

Ship and satellite bio-optical research in the California Bight

Mesoscale biological patterns and processes in productive coastal waters were studied. The physical and biological processes leading to chlorophyll variability were investigated. The ecological and evolutionary significance of this variability, and its relation to the prediction of fish recruitment and marine mammal distributions was studied. Seasonal primary productivity (using chlorophyll as an indication of phytoplankton biomass) for the entire Southern California Bight region was assessed. Complementary and contemporaneous ship and satellite (Nimbus 7-CZCS) bio-optical data from the Southern California Bight and surrounding waters were obtained and analyzed. These data were also utilized for the development of multi-platform sampling strategies and the optimization of algorithms for the estimation of phytoplankton biomass and primary production from satellite imagery.

Smith, R. C.↗

NASA NTRS2011

Analysis of Summertime Convective Initiation in Central Alabama Using the Land Information System

During the summer months in the southeastern United States, convective initiation presents a frequent challenge to operational forecasters. Thunderstorm development has traditionally been referred to as random due to their disorganized, sporadic appearance and lack of atmospheric forcing. Horizontal variations in land surface characteristics such as soil moisture, soil type, land and vegetation cover could possibly be a focus mechanism for afternoon convection during the summer months. The NASA Land Information System (LIS) provides a stand-alone land surface modeling framework that incorporates these varying soil and vegetation properties, antecedent precipitation, and atmospheric forcing to represent the soil state at high resolution. The use of LIS as a diagnostic tool may help forecasters to identify boundaries in land surface characteristics that could correlate to favored regions of convection initiation. The NASA Shortterm Prediction Research and Transition (SPoRT) team has been collaborating with the National Weather Service Office in Birmingham, AL to help incorporate LIS products into their operational forecasting methods. This paper highlights selected convective case dates from summer 2009 when synoptic forcing was weak, and identifies any boundaries in land surface characteristics that may have contributed to convective initiation. The LIS output depicts the effects of increased sensible heat flux from urban areas on the development of convection, as well as convection along gradients in land surface characteristics and surface sensible and latent heat fluxes. These features may promote mesoscale circulations and/or feedback processes that can either enhance or inhibit convection. With this output previously unavailable to operational forecasters, LIS provides a new tool to forecasters in order to help eliminate the randomness of summertime convective initiation.

James, Robert S.↗

NASA NTRS2022

Interplanetary Mesoscale Observatory (InterMeso): A Mission to Untangle Dynamic Mesoscale Structures Throughout the Heliosphere

Mesoscale dynamics are a fundamental process in space physics, but fall within an observational gap of current and planned missions. Particularly in the solar wind, measurements at the mesoscales (100s RE to a few degrees heliographic longitude at 1 au) are crucial for understanding the connection between the corona and an observer anywhere within the heliosphere. Mesoscale dynamics may also be key to revealing the currently unresolved physics regulating particle acceleration and transport, magnetic field topology, and the causes of variability in the composition and acceleration of solar wind plasma. Studies using single-point observations do not allow for investigations into mesoscale solar wind dynamics and plasma variability, nor do they allow for the exploration of the sub-structuring of large-scale solar wind structures like coronal mass ejections (CMEs), co-rotating/stream interaction regions (CIR/SIRs), and the heliospheric plasma sheet. To address this fundamental gap in our knowledge of the heliosphere at these scales, the Interplanetary Mesoscale Observatory (InterMeso) concept employs a multi-point approach using four identical spacecraft in Earth-trailing orbits near 1 au. Varying drift speeds of the InterMeso spacecraft enable the mission to span a range of mesoscale separations in the solar wind, achieving significant and innovative science return. Simultaneous, longitudinally-separated measurements of structures co-rotating over the spacecraft also allow for disambiguation of spatiotemporal variability, tracking of the evolution of solar wind structures, and determination of how the transport of energetic particles is impacted by these variabilities.

solar wind↗

NASA NTRS2022

Interplanetary Mesoscale Observatory (InterMeso): A mission to untangle dynamic mesoscale structures throughout the heliosphere

solar wind↗

NASA NTRS1990

Moist wind relationships

The equations describing the temporal and spatial behavior of the kinematic moisture and heat flux are described. In these nonlinear equations, the contribution by diabatic processes to the large-scale flux is composed of two parts. One part is associated with a Rayleigh damping term while the other arises from temporal and spatial changes in the pressure gradient term. It was found that the influence of diabatic processes on large-scale moisture fluxes depends greatly on the degree of balance between forcing and damping terms in the governing kinematic flux equations. The existence of a near balance requires a reduction in the large-scale horizontal geostrophic wind speed. Based on an examination of the moisture flux equations, it is argued that reductions in the large-scale horizontal wind speed observed within major cumulus cloud systems help conserve large-scale moisture fluxes. The deviation of the wind from geostrophic conditions is easily estimated for a near balanced state. This wind modification induces secondary vertical circulations that contribute to convergence, creating or supporting long-lived mesoscale flows. We believe this process to be a major supporter of the mesoscale circulations observed in severe storms and squall lines. In the tropics the wind modification has an antitriptic relationship. These diagnostic findings suggest possible modifications to the wind field in the application of a cumulus parameterization, and may be important in diabatic initialization of numerical weather prediction models.

Raymond, William H.↗

NASA NTRS1993

Waves and mesoscale features in the marginal ice zone

Ocean-ice interaction processes in the Marginal Ice Zone (MIZ) by waves and mesoscale features, such as upwelling and eddies, are studied using ERS-1 Synthetic Aperture Radar (SAR) imagery and wave-ice interaction models. Satellite observations of mesoscale features can play a crucial role in ocean-ice interaction study.

Liu, Antony K.↗

NASA NTRS1985

Use of observational and model-derived fields and regime model output statistics in mesoscale forecasting

Various empirical and statistical weather-forecasting studies which utilize stratification by weather regime are described. Objective classification was used to determine weather regime in some studies. In other cases the weather pattern was determined on the basis of a parameter representing the physical and dynamical processes relevant to the anticipated mesoscale phenomena, such as low level moisture convergence and convective precipitation, or the Froude number and the occurrence of cold-air damming. For mesoscale phenomena already in existence, new forecasting techniques were developed. The use of cloud models in operational forecasting is discussed. Models to calculate the spatial scales of forcings and resultant response for mesoscale systems are presented. The use of these models to represent the climatologically most prevalent systems, and to perform case-by-case simulations is reviewed. Operational implementation of mesoscale data into weather forecasts, using both actual simulation output and method-output statistics is discussed.

Forbes, G. S.↗

NASA NTRS1987

Automated mesoscale winds determined from satellite imagery

A new automated technique for extracting mesoscale fields from GOES visible/infrared satellite imagery was developed. Quality control parameters were defined to allow objective editing of the wind fields. The system can produce equivalent or superior cloud wind estimates compared to the time consuming manual methods used on various interactive meteorological processing systems. Analysis of automated mesoscale cloud wind for a test case yields an estimated random error value one meter per second and produces both regional and mesoscale vector wind field structure and divergence patterns that are consistent in time and highly correlated with subsequent severe thunderstorm development.

Source record↗

NASA NTRS1990

Diabatic forcing and initialization with assimilation of cloud and rain water in a forecast model: Methodology

The focus of this part of the investigation is to find one or more general modeling techniques that will help reduce the time taken by numerical forecast models to initiate or spin-up precipitation processes and enhance storm intensity. If the conventional data base could explain the atmospheric mesoscale flow in detail, then much of our problem would be eliminated. But the data base is primarily synoptic scale, requiring that a solution must be sought either in nonconventional data, in methods to initialize mesoscale circulations, or in ways of retaining between forecasts the model generated mesoscale dynamics and precipitation fields. All three methods are investigated. The initialization and assimilation of explicit cloud and rainwater quantities computed from conservation equations in a mesoscale regional model are examined. The physical processes include condensation, evaporation, autoconversion, accretion, and the removal of rainwater by fallout. The question of how to initialize the explicit liquid water calculations in numerical models and how to retain information about precipitation processes during the 4-D assimilation cycle are important issues that are addressed. The explicit cloud calculations were purposely kept simple so that different initialization techniques can be easily and economically tested. Precipitation spin-up processes associated with three different types of weather phenomena are examined. Our findings show that diabatic initialization, or diabatic initialization in combination with a new diabatic forcing procedure, work effectively to enhance the spin-up of precipitation in a mesoscale numerical weather prediction forecast. Also, the retention of cloud and rain water during the analysis phase of the 4-D data assimilation procedure is shown to be valuable. Without detailed observations, the vertical placement of the diabatic heating remains a critical problem.

Raymond, William H.↗

NASA NTRS1993

Scientific goals of the Cooperative Multiscale Experiment (CME)

Mesoscale Convective Systems (MCS) form the focus of CME. Recent developments in global climate models, the urgent need to improve the representation of the physics of convection, radiation, the boundary layer, and orography, and the surge of interest in coupling hydrologic, chemistry, and atmospheric models of various scales, have emphasized the need for a broad interdisciplinary and multi-scale approach to understanding and predicting MCS's and their interactions with processes at other scales. The role of mesoscale systems in the large-scale atmospheric circulation, the representation of organized convection and other mesoscale flux sources in terms of bulk properties, and the mutually consistent treatment of water vapor, clouds, radiation, and precipitation, are all key scientific issues concerning which CME will seek to increase understanding. The manner in which convective, mesoscale, and larger scale processes interact to produce and organize MCS's, the moisture cycling properties of MCS's, and the use of coupled cloud/mesoscale models to better understand these processes, are also major objectives of CME. Particular emphasis will be placed on the multi-scale role of MCS's in the hydrological cycle and in the production and transport of chemical trace constituents. The scientific goals of the CME consist of the following: understand how the large and small scales of motion influence the location, structure, intensity, and life cycles of MCS's; understand processes and conditions that determine the relative roles of balanced (slow manifold) and unbalanced (fast manifold) circulations in the dynamics of MCS's throughout their life cycles; assess the predictability of MCS's and improve the quantitative forecasting of precipitation and severe weather events; quantify the upscale feedback of MCS's to the large-scale environment and determine interrelationships between MCS occurrence and variations in the large-scale flow and surface forcing; provide a data base for initialization and verification of coupled regional, mesoscale/hydrologic, mesoscale/chemistry, and prototype mesoscale/cloud-resolving models for prediction of severe weather, ceilings, and visibility; provide a data base for initialization and validation of cloud-resolving models, and for assisting in the fabrication, calibration, and testing of cloud and MCS parameterization schemes; and provide a data base for validation of four dimensional data assimilation schemes and algorithms for retrieving cloud and state parameters from remote sensing instrumentation.

Cotton, William↗

NASA NTRS2001

An Investigation of the Influence of Urban Areas on Rainfall Using a Cloud-Mesoscale Model and the TRMM Satellite

A recent paper by Shepherd and Pierce (conditionally accepted to Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. A convective-mesoscale model with extensive land-surface processes is employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. Early analysis suggests that urban surface roughness (through turbulence and low-level convergence) may control timing and initial location of UHI-induced convection. The magnitude of the heat island appears to be closely linked to the total rainfall amount with minor impact on timing and location. The physical size of the city may predominantly impact on the location of UHI-induced rainfall anomaly. The UHI factor parameter space will be thoroughly investigated with respect to their effects on rainfall amount, location, and timing. This study extends prior numerical investigations of the impact of urban surfaces on meteorological processes, particularly rainfall development. The work also contains several novel aspects, including the application of a high-resolution (less than I km) cloud-mesoscale model to investigate urban-induce rainfall process; investigation of thermal magnitude of the UHI on rainfall process; and investigation of UHI physical size on rainfall processes.

Shepherd, J. Marshall↗

NASA NTRS1988

Budget study of a mesoscale convective system - Model simulation

A tropical squall-type cloud cluster is examined as an example of a mesoscale convective complex. The precipitation growth processes and air circulations that develop in the convective and stratiform regions are studied using a data set generated from a time-dependent numerical cloud model. The relationship of the stratiform region of the mesoscale convective complex is discussed. The vertical profiles of heating and drying are calculated. Comparisons are made between simulations with and without ice-phase microphysical processes and a simulation with forcing by weaker lifting at middle and upper levels.

Tao, Wei-Kuo↗

NASA NTRS1989

Wind and waves in the middle atmosphere observed with the MU radar

The VHF band MU radar at Shigaraki, Japan, has been in full operation successfully since April 1985. Dynamical features found primarily in the data obtained by the radar during a one year period from December 1985 to November 1986 are examined. These include: basic wind observations, quasi-monochromatic gravity waves generated by the jet stream or through a geostrophic adjustment process, seasonal variation of the mesoscale wind variability, the momentum flux due to gravity wave motions, and saturated gravity wave spectrum. A short discussion is added to the relationship between turbulent layers and ambient wind field in the mesosphere.

Fukao, S.↗

NASA NTRS2001

Cloud Macro- and Microphysical Properties Derived from GOES over the ARM SGP Domain

Cloud macrophysical properties like fractional coverage and height Z(sub c) and microphysical parameters such as cloud liquid water path (LWP), effective droplet radius r(sub e), and cloud phase, are key factors affecting both the radiation budget and the hydrological cycle. Satellite data have been used to complement surface observations from Atmospheric Radiation Measurements (ARM) by providing additional spatial coverage and top-of-atmosphere boundary conditions of these key parameters. Since 1994, the Geostationary Operational Environmental Satellite (GOES) has been used for deriving at each half-hour over the ARM Southern Great Plains (SGP) domain: cloud amounts, altitudes, temperatures, and optical depths as well as broadband shortwave (SW) albedo and outgoing longwave radiation at the top of the atmosphere. A new operational algorithm has been implemented to increase the number of value-added products to include cloud particle phase and effective size (r(sub e) or effective ice diameter D(sub e)) as well as LWP and ice water path. Similar analyses have been performed on the data from the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission satellite as part of the Clouds and Earth's Radiant Energy System project. This larger suite of cloud properties will enhance our knowledge of cloud processes and further constrain the mesoscale and single column models using ARM data as a validation/initialization resource. This paper presents the results of applying this new algorithm to GOES-8 data taken during 1998 and 2000. The global VIRS results are compared to the GOES SGP results to provide appropriate context and to test consistency.

Minnis, P.↗

NASA NTRS1983

AVE/VAS experiment: Synoptic summary and preliminary results

The AVE/VAS ground truth field experiment was conducted during the Spring of 1982 severe storms and weather research program. The experiment consisted of acquiring correlative ground truth measurements of rawinsonde data, corresponding to the time and space resolutions of VAS sounding data. The objectives of the AVE/VAS experiment are: (1) to acquire four dimensional data sets of the actual atmospheric structure down to the mesoscale; (2) to provide measurements for quantitative comparisons between ground based and VAS-derived atmospheric parameters; (3) to evaluate the impact of VAS data on diagnostic analysis of structural features and dynamical processes important to the development of mesoscale phenomena; (4) to evaluate the impact of VAS data on numerical model simulations, nowcasting, and other mesoscale forecasting systems.

Jedlovec, G. J.↗

NASA NTRSDate not supplied

Boundary-Layer Cloud Modeling Challenges on the North Slope of Alaska

The accurate modeling and prediction of cloud base heights is critical for energy balance calculations and aviation operations, alike. Low-level (i.e., boundary-layer) Arctic clouds can be difficult to model, making prediction of formation and dissipation challenging. Primarily mixed-phase, these clouds typically contain low quantities of supercooled liquid water and often slowly precipitate relatively small amounts of moderately and heavily rimed snow particles. While this appears to be the predominant cloudy state on the North Slope of Alaska (NSA), the delicate balance of microphysical, dynamical, radiative, surface coupling, and advective processes can rapidly shift to heavy snow (with various degrees of riming) or to a complete dissipation of the cloud layer without any precipitation, depending on the dominant processes. Here we strive to disentangle these various processes. First, we compare the predictive performances of four different numerical weather models in forecasting the presence and base-heights of low-level clouds: the High-Resolution Rapid Refresh - Alaska (HRRR-AK) model, the Polar Weather Research and Forecasting (Polar WRF) model, the Unified Model (UM), and the European Centre for Medium-range Weather Forecasting (ECMWF) model. Initial results comparing model output at two U.S. Department of Energy Atmospheric Radiation Measurement (AMT) NSA sites, during the fall season in 2019 and 2022, show that the UM slightly outperforms the HRRR-AK in terms of accurately forecasting the presence of a low-level cloud layer (89% of the time). All models have a significant bias of 300 to 800 meters in forecasting cloud base height (lower than is observed); however, the UM and ECMWF models have the lowest biases. Finally, a case study for a particularly challenging April 2017 thin-cloud event is presented, wherein we compare the performance of four different bulk microphysical parameterization schemes using a higher-resolution large eddy simulation (LES) model, the WRF-LES. Initial results show that the Thompson scheme was the only one able to reproduce and sustain a substantial supercooled liquid layer, but it was unable to reproduce the transition from a deep, liquid-rich cloud to a thin layer with moderately and heavily rimed precipitation. This is the first step in linking simulated LES-scale riming processes with those parameterized at a coarser mesoscale model scale. This has important implications for forecasting low-level clouds in an operational environment, given the efficiency of the riming process.

cloud base heights↗

NASA NTRS1992

Observation of mesoscale ocean features in the northeast Pacific using Geosat radar altimetry data

Mesoscale circulation in the Gulf of Alaska is studied by means of processed Geosat radar altimetry results with comparisons to observations of mesoscale eddies and surface circulation. The first set of Geosat data is treated by sea-surface height (SSH) binning in 1-deg latitude x 2-deg longitude boxes and analyzed by complex empirical orthogonal functions and 2D spectral analysis. The second set is taken from ascending Geosat tracks and analyzed as a time series. The Geosat data are compared to observational data including mesoscale eddies and fluctuations in mean surface circulation as well as sea-surface signals generated by numerical models. The data demonstrate the feasibility of a westward propagation of sea-level anomalies, and the Geosat SSH data are found to agree well with model solutions of seasonal variations in sea level in the northeast Pacific.

Matthews, Paul E.↗

NASA NTRS2014

The Goddard Cumulus Ensemble Model (GCE): Improvements and Applications for Studying Precipitation Processes

Convection is the primary transport process in the Earth's atmosphere. About two-thirds of the Earth's rainfall and severe floods derive from convection. In addition, two-thirds of the global rain falls in the tropics, while the associated latent heat release accounts for three-fourths of the total heat energy for the Earth's atmosphere. Cloud-resolving models (CRMs) have been used to improve our understanding of cloud and precipitation processes and phenomena from micro-scale to cloud-scale and mesoscale as well as their interactions with radiation and surface processes. CRMs use sophisticated and realistic representations of cloud microphysical processes and can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems. CRMs also allow for explicit interaction between clouds, outgoing longwave (cooling) and incoming solar (heating) radiation, and ocean and land surface processes. Observations are required to initialize CRMs and to validate their results. The Goddard Cumulus Ensemble model (GCE) has been developed and improved at NASA/Goddard Space Flight Center over the past three decades. It is amulti-dimensional non-hydrostatic CRM that can simulate clouds and cloud systems in different environments. Early improvements and testing were presented in Tao and Simpson (1993) and Tao et al. (2003a). A review on the application of the GCE to the understanding of precipitation processes can be found in Simpson and Tao (1993) and Tao (2003). In this paper, recent model improvements (microphysics, radiation and land surface processes) are described along with their impact and performance on cloud and precipitation events in different geographic locations via comparisons with observations. In addition, recent advanced applications of the GCE are presented that include understanding the physical processes responsible for diurnal variation, examining the impact of aerosols (cloud condensation nuclei or CCN and ice nuclei or IN) on precipitation processes, utilizing a satellite simulator to improve the microphysics, providing better simulations for satellite-derived latent heating retrieval, and coupling with a general circulation model to improve the representation of precipitation processes.

GCE↗