Results for “cloud type” — Page 35

NASA NTRS1990

Fourier transform infrared studies of model polar stratospheric cloud surfaces - Growth and evaporation of ice and nitric acid/ice

Fourier-transform infrared surface studies are used to probe the microphysical properties of nitric acid trihydrate (NAT) and ice films representative of type I and II polar stratospheric clouds (PSC). Experiments indicate that, on initial exposure to 1.8 microtorr of HNO3, a layer of ice is quantitatively converted to NAT. However, conversion of ice to NAT does not proceed indefinitely, but rather the system reaches saturation. For longer exposures or higher HNO3 pressures, NAM becomes the dominant nitric acid containing species on the surface. Evaporation studies were performed to test the feasibility of a recent denitrification mechanism. The results indicate that ice coated with 0.20 micron of NAT evaporates at a temperature of about 4 C higher than uncoated ice.

Tolbert, Margaret A.↗

DOE OSTI2021

Quality control and crop characterization framework for multi-temporal UAV LiDAR data over mechanized agricultural fields

Recent developments in remote sensing are enabling automatic, high resolution, and non-destructive survey of agriculture fields, providing the key basis for advancing plant breeding. Among the used remote sensing modalities, LiDAR has attracted wide attention for its ability to directly provide accurate 3D information. Despite the increasing utilization of LiDAR technology in phenotyping, there is still a lack of effective quality control strategies, in particular, quality control of LiDAR data collected on a multi-temporal basis. This study proposes a targetless framework for multi-temporal LiDAR data quality control and crop characterization in mechanized agricultural fields. Features extracted from the fields – terrain patches and row/alley locations – are utilized for evaluating the vertical and planimetric relative accuracy of the point clouds. Row/alley locations in the field are automatically identified from the point clouds based on the assumption that higher point density and/or higher elevation correspond to plant locations. The performance of the proposed quality control strategies is evaluated using multi-temporal datasets collected in agricultural fields of different sizes, orientation, crops, and growth stages. The result shows that the net vertical and planimetric discrepancies between multi-temporal point clouds are ±3 cm and ±8 cm, respectively. While the former reflects the actual accuracy of the point clouds, the latter is a combined effect of the LiDAR point cloud accuracy, rasterization artifacts, crop type, growth pattern, and wind condition during data acquisition. In terms of row and alley detection, the result shows that the proposed strategy achieves high performance and can deal with different planting orientation, crop types, growth stages, canopy cover, and planting density. In conclusion, this study presents a quality control framework for multi-temporal LiDAR data. Finally, the row and alley detection leads to automated extraction of plots, and hence facilitates the use of remotely sensed data for automated phenotyping.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2012

Use NU-WRF and GCE Model to Simulate the Precipitation Processes During MC3E Campaign

One of major CRM approaches to studying precipitation processes is sometimes referred to as "cloud ensemble modeling". This approach allows many clouds of various sizes and stages of their lifecycles to be present at any given simulation time. Large-scale effects derived from observations are imposed into CRMs as forcing, and cyclic lateral boundaries are used. The advantage of this approach is that model results in terms of rainfall and QI and Q2 usually are in good agreement with observations. In addition, the model results provide cloud statistics that represent different types of clouds/cloud systems during their lifetime (life cycle). The large-scale forcing derived from MC3EI will be used to drive GCE model simulations. The model-simulated results will be compared with observations from MC3E. These GCE model-simulated datasets are especially valuable for LH algorithm developers. In addition, the regional scale model with very high-resolution, NASA Unified WRF is also used to real time forecast during the MC3E campaign to ensure that the precipitation and other meteorological forecasts are available to the flight planning team and to interpret the forecast results in terms of proposed flight scenarios. Post Mission simulations are conducted to examine the sensitivity of initial and lateral boundary conditions to cloud and precipitation processes and rainfall. We will compare model results in terms of precipitation and surface rainfall using GCE model and NU-WRF

Tao, Wei-Kuo↗

DOE OSTI2018

Combined impacts of convection and microphysics parameterizations on the simulations of precipitation and cloud properties over Asia

Not Available

Liu, Dongqing (ORCID:0000000312584499)↗

NASA NTRS2015

Improving High-Resolution Weather Forecasts using the Weather Research and Forecasting (WRF) Model with an Updated Kain-Fritsch Scheme

Efforts to improve the prediction accuracy of high resolution (1-10 km) surface precipitation distribution and variability are of vital importance to local aspects of air pollution, wet deposition, and regional climate. However, precipitation biases and errors can occur at these spatial scales due to uncertainties in initial meteorological conditions and/or grid-scale cloud microphysics schemes. In particular, it is still unclear to what extent a subgrid-scale convection scheme could be modified to bring in scale-awareness for improving high-resolution short-term precipitation forecasts in the WRF model. To address these issues, we introduced scale-aware parameterized cloud dynamics for high-resolution forecasts by making several changes to the Kain-Fritsch (KF) convective parameterization scheme in the WRF model. These changes include subgrid-scale cloud-radiation interactions, a dynamic adjustment timescale, impacts of cloud updraft mass fluxes on grid-scale vertical velocity, and lifting condensation level-based entrainment methodology that includes scale dependency. A series of 48-hour retrospective forecasts using a combination of three treatments of convection (KF, updated KF, and the use of no cumulus parameterization), two cloud microphysics schemes and two types of initial condition datasets were performed over the U.S. southern Great Plains on 9- and 3-km grid spacings during the summers of 2002 and 2010. Results indicate that (1) the source of initial conditions play a key role in high-resolution precipitation forecasting, and (2) our updated KF scheme greatly alleviates the excessive precipitation at 9-km grid spacing and improves results at 3-km grid spacing as well. Overall, we found that the updated KF scheme incorporated into a high-resolution model does provide better forecasts for precipitation location and intensity.

convective parameterization↗

NASA NTRS1987

The nonlinear thermodynamics of meteors, noctilucent clouds, enhanced airglow and global atmospheric circulation

Two types of fundamental topological junctions of elements are deduced from a nonlinear thermodynamical model. Using this scheme, the possibility of a causal relation between fireballs and faint meteors as nonlinear sources on the one hand, and noctilucent clouds (NC) and Hoffmeister's enhanced airglow (EA) as complementary formative processes in the middle atmosphere and ionosphere, on the other hand, is examined. The principal role of the global atmospheric circulation in this relation is demonstrated. Such circulation in the mesosphere appears to prevent the neutral dust dissipated by fireballs from becoming an efficient agent in NLC generation. In this case, the behavior of ionized material deposited by both the bright and faint meteors is more probably controlled, as shown from the annual variation of the E sub s layer by the darkness of lunar eclipses and the global circulation of the lower thermosphere. The role of fireballs and neutral dust might be more significant as a source of EA phenomenon.

Rajchl, J.↗

NASA NTRSDate not supplied

CERES Clouds and Radiative Swath (CRS) data in HDF. (CER_CRS_Terra-FM2-MODIS_Edition2A

The Clouds and Radiative Swath (CRS) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The CRS contains all of the CERES SSF product data. For each CERES footprint on the SSF the CRS also contains vertical flux profiles evaluated at four levels in the atmosphere: the surface, 500-, 70-, and 1-hPa. The CRS fluxes and cloud parameters are adjusted for consistency with a radiative transfer model and adjusted fluxes are evaluated at the four atmospheric levels for both clear-sky and total-sky. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2001-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CLOUD LAYER AREA↗

NASA NTRS1986

Distributions of (C-13)O emission in the disks of late-type spiral galaxies

In studies of molecular clouds in external galaxies, the distribution of (C-12)O emissivity as a function of radius in a galaxy has been employed to infer the surface density of molecular hydrogen with galactocentric radius. In principle, observations of more optically thin molecular species, such as (C-13)O, can be used as an alternative tracer of the mass of molecular hydrogen in a galaxy. Since the (C-13)O lines have a much lower opacity than the saturated, nearly thermalized (C-12)O lines, their intensity variations as a function of galactocentric radius are more readily interpreted in terms of gas density variations. The first strip maps of the (C-13)O distributions in six spiral galaxies are presented, and the (C-13)O and (C-12)O radial distributions are compared. Attention is given to the reliability of H2 masses and H2 distributions derived from (C-12)O data.

Young, J. S.↗

NASA NTRS1994

Spatial distribution of plasma wave activity in the nightside ionosphere of Venus

In this study we use 14 years of Pioneer Venus Orbiter Electric Field Detector (OEFD) data to define the characteristics of (VLF) burst activity in the nightside ionosphere of Venus. Our statistical results show that there are essentially four types of VLF signals. The first type of signal is only observed in the 100 Hz channel and not in any of the higher frequency channels (730 Hz, 5.4 kHz or 30 kHz). Occurrence of these waves is controlled by the magnetic field with a weaker dependence on electron density. The occurrence of these waves is controlled by the magnetic field with a weaker dependence on electron density. The occurrence rate decreases with increasing altitude to a height of 600 km. For higher altitudes beyond 600 km the occurrence rate remains roughly constant. The statistics of these signals are what one would expect for whistler mode waves from a subionospheric source. The second type of signal is broadline wave activity appearing below 300 km in the low altitude ionosphere. These signals often occur in all four channels of the OEFD. These signals are also thought to come from a subionospheric source. The third type of signal appearing near the edge of the planetary optical shadow. They are probably ion acoustic waves generated by a current driven instability associated with plasma clouds in the wake. The fourth type of signal is a narrow band wave. It occurs in either of the two high frequency channels in the high altitude tail region, and is attributed to locally generated Langmuir waves. In addition, we also observe spacecraft interference noise in both the 100 and 730 Hz channels. These signals mainly occur near the edge of the planetary optical shadow and have an inbound and outbound asymmetry in activity.

Ho, C.-M.↗

NASA NTRS2002

Overlap Properties of Clouds Generated by a Cloud Resolving Model

In order for General Circulation Models (GCMs), one of our most important tools to predict future climate, to correctly describe the propagation of solar and thermal radiation through the cloudy atmosphere a realistic description of the vertical distribution of cloud amount is needed. Actually, one needs not only the cloud amounts at different levels of the atmosphere, but also how these cloud amounts are related, in other words, how they overlap. Currently GCMs make some idealized assumptions about cloud overlap, for example that contiguous cloud layers overlap maximally and non-contiguous cloud layers overlap in a random fashion. Since there are difficulties in obtaining the vertical profile of cloud amount from observations, the realism of the overlap assumptions made in GCMs has not been yet rigorously investigated. Recently however, cloud observations from a relatively new type of ground radar have been used to examine the vertical distribution of cloudiness. These observations suggest that the GCM overlap assumptions are dubious. Our study uses cloud fields from sophisticated models dedicated to simulate cloud formation, maintenance, and dissipation called Cloud Resolving Models . These models are generally considered capable of producing realistic three-dimensional representation of cloudiness. Using numerous cloud fields produced by such a CRM we show that the degree of overlap between cloud layers is a function of their separation distance, and is in general described by a combination of the maximum and random overlap assumption, with random overlap dominating as separation distances increase. We show that it is possible to parameterize this behavior in a way that can eventually be incorporated in GCMs. Our results seem to have a significant resemblance to the results from the radar observations despite the completely different nature of the datasets. This consistency is encouraging and will promote development of new radiative transfer codes that will estimate the radiation effects of multi-layer cloud fields more accurately.

Oreopoulos, L.↗

NASA NTRS1984

A dynamical basis for the parameterization of organized deep convection in large-scale numerical models

A hierarchy of steady, nonlinear, semianalytic models of different types of convection were produced. These provide a theoretical framework for determining cloud outflow fluxes of both dynamic and thermodynamic quantities, which can be used to formulate dynamical transports in parameterization schemes. This was achieved by exploiting certain Lagrangian conservation properties of steady flow, from which an equation for the vertical displacement of particles can be obtained and the outflow entropy, energy and momentum fluxes and the infow/outflow mass fluxes can be determined from solution to the equation. These fluxes are determined in terms of grid scale parameters such as convective available potential energy (CAPE), cloud layer shear, and horizontal pressure gradients. Five main types of system models are identified, respectively representing archtypes of convection in zero shear, large shear, midlatitude squall lines, tropical squall lines and cellular convection. The downdraught is an important aspect in the first four of these and the cloud scale transport of momentum is very distinctive.

Moncrieff, M. W.↗

DOE OSTI2018

A Topological Approach to Representational Data Models

As data accumulate faster and bigger, building representa- tional models has turned into an art form. Despite sharing common data types, each scientific discipline often takes a different approach. In this work, we propose representational models grounded in the mathematics of algebraic topology to understand foundational data types. We present hypergraphs for multi-relational data, point clouds for vector data, and sheaf models when both data types are present and interrelated. These three models use similar principles from algebraic topology and provide a domain-agnostic framework. We will discuss each method, provide ref- erences to their foundational mathematical papers, and give examples of their use.

relational data, relational data, vector data, vec↗

DOE OSTI2019

csapr2cfrmrhi (a1)

The C-Band Scanning ARM Precipitation Radar is a dual-polarization Doppler weather radar that operates in a simultaneous transmit and receive (STAR) mode, splitting the transmit signal so that power is transmitted on both horizontal and vertical polarizations at the same time. The CSAPR can also transmit on a single polarization (horizontal or vertical) and measure linear depolarization ratio (LDR). In addition to the first three Doppler moments (reflectivity, radial velocity, and spectra width), the CSAPR also provides differential reflectivity, correlation coefficient, and specific differential phase. The dual-polarization variables enable the provision of rainfall rate estimates and identification of precipitation types. For the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina, ARM deployed a second-generation CSAPR, known as CSAPR2. CACTI data from the CSAPR2 are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

csapr2cfrrhi (a1)

The C-Band Scanning ARM Precipitation Radar is a dual-polarization Doppler weather radar that operates in a simultaneous transmit and receive (STAR) mode, splitting the transmit signal so that power is transmitted on both horizontal and vertical polarizations at the same time. The CSAPR can also transmit on a single polarization (horizontal or vertical) and measure linear depolarization ratio (LDR). In addition to the first three Doppler moments (reflectivity, radial velocity, and spectra width), the CSAPR also provides differential reflectivity, correlation coefficient, and specific differential phase. The dual-polarization variables enable the provision of rainfall rate estimates and identification of precipitation types. For the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina, ARM deployed a second-generation CSAPR, known as CSAPR2. CACTI data from the CSAPR2 are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

csapr2cfrcrc (a1)

The C-Band Scanning ARM Precipitation Radar is a dual-polarization Doppler weather radar that operates in a simultaneous transmit and receive (STAR) mode, splitting the transmit signal so that power is transmitted on both horizontal and vertical polarizations at the same time. The CSAPR can also transmit on a single polarization (horizontal or vertical) and measure linear depolarization ratio (LDR). In addition to the first three Doppler moments (reflectivity, radial velocity, and spectra width), the CSAPR also provides differential reflectivity, correlation coefficient, and specific differential phase. The dual-polarization variables enable the provision of rainfall rate estimates and identification of precipitation types. For the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina, ARM deployed a second-generation CSAPR, known as CSAPR2. CACTI data from the CSAPR2 are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

csapr2cfrppi (a1)

The C-Band Scanning ARM Precipitation Radar is a dual-polarization Doppler weather radar that operates in a simultaneous transmit and receive (STAR) mode, splitting the transmit signal so that power is transmitted on both horizontal and vertical polarizations at the same time. The CSAPR can also transmit on a single polarization (horizontal or vertical) and measure linear depolarization ratio (LDR). In addition to the first three Doppler moments (reflectivity, radial velocity, and spectra width), the CSAPR also provides differential reflectivity, correlation coefficient, and specific differential phase. The dual-polarization variables enable the provision of rainfall rate estimates and identification of precipitation types. For the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina, ARM deployed a second-generation CSAPR, known as CSAPR2. CACTI data from the CSAPR2 are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

csapr2cfrzppi (a1)

The C-Band Scanning ARM Precipitation Radar is a dual-polarization Doppler weather radar that operates in a simultaneous transmit and receive (STAR) mode, splitting the transmit signal so that power is transmitted on both horizontal and vertical polarizations at the same time. The CSAPR can also transmit on a single polarization (horizontal or vertical) and measure linear depolarization ratio (LDR). In addition to the first three Doppler moments (reflectivity, radial velocity, and spectra width), the CSAPR also provides differential reflectivity, correlation coefficient, and specific differential phase. The dual-polarization variables enable the provision of rainfall rate estimates and identification of precipitation types. For the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina, ARM deployed a second-generation CSAPR, known as CSAPR2. CACTI data from the CSAPR2 are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

csapr2cfrmmisc (a1)

The C-Band Scanning ARM Precipitation Radar is a dual-polarization Doppler weather radar that operates in a simultaneous transmit and receive (STAR) mode, splitting the transmit signal so that power is transmitted on both horizontal and vertical polarizations at the same time. The CSAPR can also transmit on a single polarization (horizontal or vertical) and measure linear depolarization ratio (LDR). In addition to the first three Doppler moments (reflectivity, radial velocity, and spectra width), the CSAPR also provides differential reflectivity, correlation coefficient, and specific differential phase. The dual-polarization variables enable the provision of rainfall rate estimates and identification of precipitation types. For the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina, ARM deployed a second-generation CSAPR, known as CSAPR2. CACTI data from the CSAPR2 are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗