Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cloud parameterization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime

Abstract. The Earth's land surface features spatial and temporal heterogeneity over a wide range of scales below those resolved by current Earth system models (ESMs). State-of-the-art land and atmosphere models employ parameterizations to represent their subgrid heterogeneity, but the land–atmosphere coupling in ESMs typically operates on the grid scale. Communicating the information on the land surface heterogeneity with the overlying atmospheric boundary layer (ABL) remains a challenge in modeling land–atmosphere interactions. In order to account for the subgrid-scale heterogeneity in land–atmosphere coupling, we implement a new coupling scheme in the Energy Exascale Earth system model version 1 (E3SMv1) that uses adjusted surface variances and covariance of potential temperature and specific water content as the lower boundary condition for the atmosphere model. The new lower boundary condition accounts for both the variability of individual subgrid land surface patches and the inter-patch variability. The E3SMv1 single-column model (SCM) simulations over the Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) site were performed to assess the impacts. We find that the new coupling parameterization increases the magnitude and diurnal cycle of the temperature variance and humidity variance in the lower ABL on non-precipitating days. The impacts are primarily attributed to subgrid inter-patch variability rather than the variability of individual patches. These effects extend vertically from the surface to several levels in the lower ABL on clear days. We also find that accounting for surface heterogeneity increases low cloud cover and liquid water path (LWP). These cloud changes are associated with the change in cloud regime indicated by the skewness of the probability density function (PDF) of the subgrid vertical velocity. In precipitating days, the inter-patch variability reduces significantly so that the impact of accounting for surface heterogeneity vanishes. These results highlight the importance of accounting for subgrid heterogeneity in land–atmosphere coupling in next-generation ESMs.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Genesis of Pre-Hurricane Felix (2007): Warm Core Formation, Precipitation Evolution, and Predictability - Part 2

This is the second of a two-part study examining the simulated formation of Atlantic Hurricane Felix (2007) in a cloud-representing framework. Here several open issues are addressed concerning the formation of the storm's warm core, the evolution and respective contribution of stratiform versus convective precipitation within the parent wave's pouch, and the sensitivity of the development pathway reported in Part I to different model physics options and initial conditions. All but one of the experiments include ice microphysics as represented by one of several parameterizations, and the partition of convective versus stratiform precipitation is accomplished using a standard numerical technique based on the high-resolution control experiment. The transition to a warm-core tropical cyclone from an initially cold-core, lower tropospheric wave disturbance is analyzed first. As part of this transformation process, it is shown that deep moist convection is sustained near the pouch center. Both convective and stratiform precipitation rates increase with time. While stratiform precipitation occupies a larger area even at the tropical storm stage, deep moist convection makes a comparable contribution to the total rain rate at the pregenesis stage, and a larger contribution than stratiform processes at the storm stage. The convergence profile averaged near the pouch center is found to become dominantly convective with increasing deep moist convective activity there. Low-level convergence forced by interior diabatic heating plays a key role in forming and intensifying the near-surface closed circulation, while the midlevel convergence associated with stratiform precipitation helps to increase the midlevel circulation and thereby contributes to the formation and upward extension of a tropospheric-deep cyclonic vortex. Sensitivity tests with different model physics options and initial conditions demonstrate a similar pregenesis evolution. These tests suggest that the genesis location of a tropical storm is largely controlled by the parent wave's critical layer, whereas the genesis time and intensity of the protovortex depend on the details of the mesoscale organization, which is less predictable. Some implications of the findings are discussed.

Wang, zhuo↗
DOE OSTI2024

Perspectives on AI Architectures and Codesign for Earth System Predictability

Abstract Recently, the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research (BER), and Advanced Scientific Computing Research (ASCR) programs organized and held the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop series. From this workshop, a critical conclusion that the DOE BER and ASCR community came to is the requirement to develop a new paradigm for Earth system predictability focused on enabling artificial intelligence (AI) across the field, laboratory, modeling, and analysis activities, called model experimentation (ModEx). BER’s ModEx is an iterative approach that enables process models to generate hypotheses. The developed hypotheses inform field and laboratory efforts to collect measurement and observation data, which are subsequently used to parameterize, drive, and test model (e.g., process based) predictions. A total of 17 technical sessions were held in this AI4ESP workshop series. This paper discusses the topic of the AI Architectures and Codesign session and associated outcomes. The AI Architectures and Codesign session included two invited talks, two plenary discussion panels, and three breakout rooms that covered specific topics, including 1) DOE high-performance computing (HPC) systems, 2) cloud HPC systems, and 3) edge computing and Internet of Things (IoT). We also provide forward-looking ideas and perspectives on potential research in this codesign area that can be achieved by synergies with the other 16 session topics. These ideas include topics such as 1) reimagining codesign, 2) data acquisition to distribution, 3) heterogeneous HPC solutions for integration of AI/ML and other data analytics like uncertainty quantification with Earth system modeling and simulation, and 4) AI-enabled sensor integration into Earth system measurements and observations. Such perspectives are a distinguishing aspect of this paper. Significance Statement This study aims to provide perspectives on AI architectures and codesign approaches for Earth system predictability. Such visionary perspectives are essential because AI-enabled model-data integration has shown promise in improving predictions associated with climate change, perturbations, and extreme events. Our forward-looking ideas guide what is next in codesign to enhance Earth system models, observations, and theory using state-of-the-art and futuristic computational infrastructure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Perspectives on AI Architectures and Co-design for Earth System Predictability

Recently, the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research (BER), and Advanced Scientific Computing Research (ASCR) programs organized and held the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop series. From this workshop, a critical conclusion that the DOE BER and ASCR community came to is the requirement to develop a new paradigm for Earth system predictability focused on enabling artificial intelligence (AI) across the field, laboratory, modeling, and analysis activities, called model experimentation (ModEx). BER’s ModEx is an iterative approach that enables process models to generate hypotheses. The developed hypotheses inform field and laboratory efforts to collect measurement and observation data, which are subsequently used to parameterize, drive, and test model (e.g., process based) predictions. A total of 17 technical sessions were held in this AI4ESP workshop series. This paper discusses the topic of the AI Architectures and Codesign session and associated outcomes. The AI Architectures and Codesign session included two invited talks, two plenary discussion panels, and three breakout rooms that covered specific topics, including 1) DOE high-performance computing (HPC) systems, 2) cloud HPC systems, and 3) edge computing and Internet of Things (IoT). We also provide forward-looking ideas and perspectives on potential research in this codesign area that can be achieved by synergies with the other 16 session topics. These ideas include topics such as 1) reimagining codesign, 2) data acquisition to distribution, 3) heterogeneous HPC solutions for integration of AI/ML and other data analytics like uncertainty quantification with Earth system modeling and simulation, and 4) AI-enabled sensor integration into Earth system measurements and observations. Such perspectives are a distinguishing aspect of this paper.

58 GEOSCIENCES↗
NASA NTRS1999

Wind Field Measurements With Airborne Doppler Lidar

In collaboration with lidar atmospheric remote sensing groups at NASA Marshall Space Flight Center and National Oceanic and Atmospheric Administration (NOAA) Environmental Technology Laboratory, we have developed and flown the Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) lidar on the NASA DC-8 research aircraft. The scientific motivations for this effort are: to obtain measurements of subgrid scale (i.e. 2-200 km) processes and features which may be used to improve parameterizations in global/regional-scale models; to improve understanding and predictive capabilities on the mesoscale; and to assess the performance of Earth-orbiting Doppler lidar for global tropospheric wind measurements. MACAWS is a scanning Doppler lidar using a pulsed transmitter and coherent detection; the use of the scanner allows 3-D wind fields to be produced from the data. The instrument can also be radiometrically calibrated and used to study aerosol, cloud, and surface scattering characteristics at the lidar wavelength in the thermal infrared. MACAWS was used to study surface winds off the California coast near Point Arena, with an example depicted in the figure below. The northerly flow here is due to the Pacific subtropical high. The coastal topography interacts with the northerly flow in the marine inversion layer, and when the flow passes a cape or point that juts into the winds, structures called "hydraulic expansion fans" are observed. These are marked by strong variation along the vertical and cross-shore directions. The plots below show three horizontal slices at different heights above sea level (ASL). Bottom plots are enlargements of the area marked by dotted boxes above. The terrain contours are in 200-m increments, with the white spots being above 600-m elevation. Additional information is contained in the original.

Menzies, Robert T.↗
DOE OSTI2020

Thermal chains and entrainment in cumulus updrafts, Part 2: Analysis of idealized simulations

Research has suggested that the structure of deep convection often consists of a series of rising thermals, or “thermal chain”, which contrasts with existing conceptual models that are used to construct cumulus parameterizations. In this work, simplified theoretical expressions for updraft properties obtained in Part 1 of this study are used to develop a hypothesis explaining why this structure occurs. In this hypothesis, cumulus updraft structure is strongly influenced by organized entrainment below the updraft’s vertical velocity maximum. In a dry environment, this enhanced entrainment can locally reduce condensation rates and increase evaporation, thus eroding buoyancy. For moderate-to-large initial cloud radius R, this breaks up the updraft into a succession of discrete pulses of rising motion (i.e., a thermal chain). For small R, this leads to the structure of a single, isolated rising thermal. In contrast, moist environments are hypothesized to favor plume-like updrafts for moderate-to-large R. In a series of axisymmetric numerical cloud simulations, R and environmental relative humidity (RH) are systematically varied to test this hypothesis. Vertical profiles of fractional entrainment rate, passive tracer concentration, buoyancy, and vertical velocity from these runs agree well with vertical profiles calculated from the theoretical expressions in Part 1. Analysis of the simulations supports the hypothesized dependency of updraft structure on R and RH, that is, whether it consists of an isolated thermal, a thermal chain, or a plume, and the role of organized entrainment in driving this dependency. Additional 3-dimensional (3-D) turbulent cloud simulations are analyzed, and the behavior of these 3-D runs is qualitatively consistent with the theoretical expressions and axisymmetric simulations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Results from Global Land-Surface Data Assimilation Methods

Realistic representation of the land surface is crucial in global climate modeling (GCM). Recently, the Mosaic land-surface Model (LSM) has been driven off-line using GEOS DAS (Goddard Earth Observing System Data Assimilation System) atmospheric forcing, forming the Off-line Land-surface Global Assimilation (OLGA) system. This system provides a computationally efficient test bed for land surface data assimilation. Here, we validate the OLGA simulation of surface processes and the assimilation of ISCCP surface temperatures. Another component of this study as the incorporation of the Physical-space Statistical Analysis System (PSAS) into OLGA, in order to assimilate surface temperature observations from the International Satellite Cloud Climatology Project (ISCCP). To counteract the subsequent forcing of the analyzed skin temperature back to the initial state following the analysis. incremental bias correction (IBC) was included in the assimilation. The IBC scheme effectively removed the time mean bias, but did not remove him in the mean diurnal cycle. Therefore, a diurnal him correction (DBC) scheme was developed, where the time-dependent bias was modeled with a sine wave parameterization. In addition, quality control of the ISCCP data and anisotropic temperature correction were implemented in PSAS. Preliminary results showed a substantial impact from the inclusion of PSAS and DBC that was visible in the surface meteorology fields and energy budget. Also, the monthly mean diurnal cycle from the experiment closely matched the diurnal cycle from the observations.

Radakovich, Jon D.↗
NASA NTRS1998

Mechanisms Regulating Deep Moist Convection and Sea-Surface Temperatures of the Tropics

Despite numerous previous studies, two relationships between deep convection and the sea-surface temperature (SST) of the tropics remain unclear. The first is the cause for the sudden emergence of deep convection at about 28 deg SST, and the second is its proximity to the highest observed SST of about 30 C. Our analysis provides a rational explanation for both by utilizing the Improved Meteorological (IMET) buoy data together with radar rainfall retrievals and atmospheric soundings provided by the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE). The explanation relies on the basic principles of moist convection as enunciated in the Arakawa-Schubert cumulus parameterization. Our analysis shows that an SST range of 28-29 C is necessary for "charging" the atmospheric boundary layer with sufficient moist static energy that can enable the towering convection to reach up to the 200 hPa level. In the IMET buoy data, the changes in surface energy fluxes associated with different rainfall amounts show that the deep convection not only reduces the solar flux into the ocean with a thick cloud cover, but it also generates downdrafts which bring significantly cooler and drier air into the boundary-layer thereby augmenting oceanic cooling by increased sensible and latent heat fluxes. In this way, the ocean seasaws between a net energy absorber for non-raining and a net energy supplier for deep-convective raining conditions. These processes produce a thermostat-like control of the SST. The data also shows that convection over the warm pool is modulated by dynamical influences of large-scale circulation embodying tropical easterly waves (with a 5-day period) and MJOs (with 40-day period); however, the quasi-permanent feature of the vertical profile of moist static energy, which is primarily maintained by the large-scale circulation and thermodynamical forcings, is vital for both the 28 C SST for deep convection and its upper limit at about 30 C.

Sud, Y. C.↗
NASA NTRS2015

A WRF-Chem Analysis of Flash Rates, Lightning-NOx Production and Subsequent Trace Gas Chemistry of the 29-30 May 2012 Convective Event in Oklahoma During DC3

The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). This is a continuation of previous work, which compared lightning observations (Oklahoma Lightning Mapping Array and National Lightning Detection Network) with flashes generated by various flash rate parameterization schemes (FRPSs) from the literature in a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the 29-30 May 2012 Oklahoma thunderstorm. Based on the Oklahoma radar observations and Lightning Mapping Array data, new FRPSs are being generated and incorporated into the model. The focus of this analysis is on estimating the amount of lightning-generated nitrogen oxides (LNOx) produced per flash in this storm through a series of model simulations using different production per flash assumptions and comparisons with DC3 aircraft anvil observations. The result of this analysis will be compared with previously studied mid-latitude storms. Additional model simulations are conducted to investigate the upper troposphere transport, distribution, and chemistry of the LNOx plume during the 24 hours following the convective event to investigate ozone production. These model-simulated mixing ratios are compared against the aircraft observations made on 30 May over the southern Appalachians.

Cummings, Kristin A.↗
NASA NTRSDate not supplied

Synergy of Satellite Radiation, Precipitation, and Other Meteorological Variable Observations for Global Mean Sea Surface Turbulent Heat Flux Estimation

Sea surface turbulent heat flux is one of the key components in global freshwater and energy balances and plays an important role in atmospheric dynamics, thermodynamics and general circulation. This turbulent heat flux is dominantly decided by sea surface latent heat release with some contribution from sensible heat exchange. The flux and its anomaly could significantly affect ocean heat storage and ocean circulation. They are part of and have great impacts on climate variability. Though the turbulent heat flux is extremely important for the climate and weather systems, only very limited ship and buoy observations of the flux are available over open oceans. There are no global, operational, direct measurements of this crucial meteorological variable. Global estimates are, basically, indirectly calculated from bulk turbulent flux parameterization with a combination of satellite column water vapor, sea surface water temperature, and wind speed observations. Critical parameters such as sea surface air temperature and humidity are estimated from empirical relations of theses variables with the water vapor and sea surface water temperature, respectively. Lacking accurate knowledge on surface air temperature and humidity, uncertainties in the parameterization and potential changes in the non-linear turbulent processes with long-term climate variations could cause large errors in estimated long-term turbulent fluxes from the indirect method as shown in current global sea surface turbulent flux datasets. This study uses synergized data of satellite global radiation, precipitation, and other meteorological variable observations to estimate sea surface turbulent heat fluxes. The radiation observations are made by the satellite Clouds and the Earth’s Radiant Energy System (CERES) sensors, while the global precipitation data is from NASA’s satellite Global Precipitation Climatology Project (GPCP). Other data includes satellite sea surface water temperature and wind speed observations. These datasets are obtained from a wide range of space sensors from passive to active instruments and from visible and near infrared to thermal infrared and microwave spectral sounders. One significant feature of these datasets is that they have multi-decades long climate records. Top-of-atmosphere (TOA) radiation and its anomaly represents the net heat energy input to the climate system, and the oceanic precipitation and ocean-land moisture transport can be used to quantify sea surface latent heat release. Based on the synergized datasets and the principle of global water and energy balances, global mean turbulent heat fluxes are estimated. The turbulent heat anomalies for the first two decades of the 21st century are, then, obtained mainly from global CERES radiation and GPCP precipitation anomalies, along with CERES derived ocean-land heat transports. Analysis indicates that the uncertainties in the estimated turbulent flux anomalies may be reduced considerably. The results suggest a strong needs in synchronized and synergized observations of atmospheric radiation, precipitation, and oceanic meteorological variables for long-term climate studies.

Bing Lin↗
NASA NTRS2001

Airborne spectral Measurements of Surface-Atmosphere Anisotropy for Several Surfaces and Ecosystem over Southern Africa

The Cloud Absorption Radiometer (CAR) was flown aboard the University of Washington Convair CV-580 research aircraft and took measurements on 23 flights between August 15 and September 16. On 12 of those flights, BRF measurements were obtained over different natural surfaces and ecosystem in southern Africa. The BRF measurements were done to characterize surface anisotropy in support of SAFARI 2000 science objectives principally to validate products from NASA's EOS satellites, and to parameterize and validate BRF models. In this paper we present results of BRFs taken over two EOS validation sites: Skukuza tower, South Africa (25.0 deg S, 31.5 deg E) and Mongu tower, Zambia (15.4 deg S, 23.3 deg E). Additional sites are also considered and include, Maun tower, Botswana (20.0 deg S, 23.5 deg E), Sowa Pan, Botswana (20.6 deg S, 26.2 deg E) and Etosha Pan, Namibia (19.0 deg S, 16.0 deg E). The CAR is capable of measuring scattered light in fourteen spectral bands. The scan mirror, rotating at 100 rpm, directs the light into a Dall-Kirkham telescope where the beam is split into nine paths. Eight light beams pass through beam splitters, dichroics, and lenses to individual detectors (0.34-1.27 micrometers), and finally are registered by eight data channels. They are sampled simultaneously and continuously. The ninth beam passes through a spinning filter wheel to an InSb detector cooled by a Stirling cycle cooler. Signals registered by the ninth data channel are selected from among six spectral channels (1.55-2.30 micrometers). The filter wheel can either cycle through all six spectral bands at a prescribed interval (usually changing filter every fifth scan line), or lock onto any one of the six spectral bands and sample it continuously. To measure the BRF of the surface-atmosphere system, the University of Washington CV-580 had to bank at a comfortable roll angle of approximately 20 degrees and fly in a circle about 3 km in diameter above the surface for roughly two minutes. Replicated observations (multiple circular orbits) were acquired over selected surfaces so that average BRF smooth out small-scale surface and atmospheric inhomogeneities. At an altitude of 600 m above the targeted surface area and with a 1 deg IFOV, the pixel resolution is about 10 m at nadir and about 270 m at an 80 deg viewing angle from the CAR.

Gatebe, Charles K.↗
NASA NTRS2010

Mechanisms of Diurnal Precipitation over the United States Great Plains: A Cloud-Resolving Model Simulation

The mechanisms of summertime diurnal precipitation in the US Great Plains were examined with the two-dimensional (2D) Goddard Cumulus Ensemble (GCE) cloud-resolving model (CRM). The model was constrained by the observed large-scale background state and surface flux derived from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program s Intensive Observing Period (IOP) data at the Southern Great Plains (SGP). The model, when continuously-forced by realistic surface flux and large-scale advection, simulates reasonably well the temporal evolution of the observed rainfall episodes, particularly for the strongly forced precipitation events. However, the model exhibits a deficiency for the weakly forced events driven by diurnal convection. Additional tests were run with the GCE model in order to discriminate between the mechanisms that determine daytime and nighttime convection. In these tests, the model was constrained with the same repeating diurnal variation in the large-scale advection and/or surface flux. The results indicate that it is primarily the surface heat and moisture flux that is responsible for the development of deep convection in the afternoon, whereas the large-scale upward motion and associated moisture advection play an important role in preconditioning nocturnal convection. In the nighttime, high clouds are continuously built up through their interaction and feedback with long-wave radiation, eventually initiating deep convection from the boundary layer. Without these upper-level destabilization processes, the model tends to produce only daytime convection in response to boundary layer heating. This study suggests that the correct simulation of the diurnal variation in precipitation requires that the free-atmospheric destabilization mechanisms resolved in the CRM simulation must be adequately parameterized in current general circulation models (GCMs) many of which are overly sensitive to the parameterized boundary layer heating.

Lee, M.-I.↗
DOE OSTI2026

An Optimized Parameterization of Sub‐Grid Scale Advection for Convection Permitting Models

Convection‐permitting models (CPMs) explicitly resolve deep convection yet under‐resolve the organized lateral exchanges among drafts and their environment that control entrainment/detrainment, precipitation efficiency, and mesoscale structure. In this work, we introduce the Optimized Advection Scheme (OAS), which introduces a small rotation of the Cartesian frame of reference for the horizontal winds relative to other variables used in advection that induces cross‐gradient transport to mimic under‐resolved convective mixing. The rotation angle is selected to minimize the Kullback–Leibler divergence between the simulated and satellite observed precipitation intensity distributions, yielding a physically consistent perturbation that is computationally inexpensive and portable. Optimized Advection Scheme is implemented in WRF and evaluated over Amazon (April 2014). It shifts precipitation–precipitable‐water joint distributions toward lighter rain, reduces overly intense rates, and improves mesoscale convective system (MCS) lifetime and propagation. Mechanistically, the added cross‐gradient transport promotes convective detrainment and environmental mixing, which cools and moistens the mid‐troposphere, weakens downward momentum transport, alleviates excessive downwelling shortwave biases, and warms the surface temperature. The optimized rotation angle yields comparable improvements at 4‐km and 1‐km grid spacing, demonstrating resolution‐independent benefits across the CPM gray zone. By targeting the dynamical root of under‐mixed convective circulations, rather than tuning model microphysics or closures, OAS delivers robust, scale‐aware improvements in precipitation statistics, cloud vertical structure, and characteristics of MCS (MCSs), offering a practical pathway to more reliable CPM simulations for weather and climate applications.

CPM↗
DOE OSTI2021

The Energy Exascale Earth System Model Simulations With High Vertical Resolution in the Lower Troposphere

Abstract General circulation models (GCMs) are typically run with coarse vertical resolution. For example, the Energy Exascale Earth System Model (E3SM) has a vertical resolution of about 200 m in the boundary layer, which is far too coarse to resolve sharp gradients often found in the thermodynamic fields capping subtropical marine stratocumulus. In this article, we present a series of multiyear atmosphere only simulations of E3SM version 1 where we progressively increase the vertical resolution in the lower troposphere to scales approaching those often used in large eddy simulation (LES). We report marginal impacts in regards to the simulation of boundary layer clouds when vertical resolution is moderately increased, yet find significant positive impacts when the vertical resolution approaches that typically used in LES (∼10 m). In these experiments, there is a marked change in the simulated turbulence and thermodynamics which leads to more abundant marine stratocumulus. However, these simulations are burdened with excessive computational cost. They are also subject to degradations in overall climate metrics due to time step sensitivities and because some processes and parameterizations are sensitive to changes in the vertical resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A physics-based ensemble machine-learning approach to identifying a relationship between lightning indices and binary lightning hazard

To convert lightning indices generated by numerical weather prediction experiments into binary lightning hazard, a machine-learning tool was developed. This tool, consisting of parallel multilayer perceptron classifiers, was trained on an ensemble of planetary boundary layer schemes and microphysics parameterizations that generated four different lightning indices over 1 week. In a subsequent week, the multi-physics ensemble was applied and the machine-learning tool was used to evaluate the accuracy. Unintuitively, the machine-learning tool performed better on the testing dataset than the training dataset. Much of the error may be attributed to mischaracterizing the convection. The combination of the machine learning model and simulations could not differentiate between cloud-to-cloud lightning and cloud-to-ground lightning, despite being trained on cloud-to-ground lightning. It was found that the simulation most representative of the local operational model was the most accurate simulation tested.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Lightning NOx Statistics Derived by NASA Lightning Nitrogen Oxides Model (LNOM) Data Analyses

What is the LNOM? The NASA Marshall Space Flight Center (MSFC) Lightning Nitrogen Oxides Model (LNOM) [Koshak et al., 2009, 2010, 2011; Koshak and Peterson 2011, 2013] analyzes VHF Lightning Mapping Array (LMA) and National Lightning Detection Network(TradeMark) (NLDN) data to estimate the lightning nitrogen oxides (LNOx) produced by individual flashes. Figure 1 provides an overview of LNOM functionality. Benefits of LNOM: (1) Does away with unrealistic "vertical stick" lightning channel models for estimating LNOx; (2) Uses ground-based VHF data that maps out the true channel in space and time to < 100 m accuracy; (3) Therefore, true channel segment height (ambient air density) is used to compute LNOx; (4) True channel length is used! (typically tens of kilometers since channel has many branches and "wiggles"); (5) Distinction between ground and cloud flashes are made; (6) For ground flashes, actual peak current from NLDN used to compute NOx from lightning return stroke; (7) NOx computed for several other lightning discharge processes (based on Cooray et al., 2009 theory): (a) Hot core of stepped leaders and dart leaders, (b) Corona sheath of stepped leader, (c) K-change, (d) Continuing Currents, and (e) M-components; and (8) LNOM statistics (see later) can be used to parameterize LNOx production for regional air quality models (like CMAQ), and for global chemical transport models (like GEOS-Chem).

Koshak, William↗
NASA NTRS1985

The utilization of satellite data and dynamics in understanding and predicting global weather phenomena

A two layer spectral quasi-geostrophic model is used to simulate the effects of topography on the equilibria, the stability, and the long term evaluation of incipient unstable waves. The flow is forced by latitudinally dependent radiational heating. The nature of the form drag instability of high index equilibria is investigated. The proximity of the equilibrium shear to a resonant value is essential for the instability, provided the equilibrium occurs at a slightly stronger shear than resonance. The properties of the steady Hadley and Rossby required for a thermally forced rotating fluid on a sphere are further explained. An objective parameterization technique is developed for general nonlinear hydrodynamical systems. The typical structure is one in which the rates of change of the dependent variables depend on homogeneous quadratic and linear forms, as well as on inhomogeneous forcing terms. Also documented is a steady, axisymmetric model of the general circulation developed as a basis for climate stability studies. The model includes the effects of heating, rotation, and internal friction, but neglects topography. Included is further research on cloud street phenomena. Orientation angles and horizontal wavelengths of boundary layer rolls and cloud streets are determined from an analysis of a truncated spectral model of three dimensional shallow moist Boussinesq convection in a shearing environment is further explained. Relatively broadly spaced roll clouds have orientations for which the Fourier component of the roll perpendicular shear is nearly zero, but the second corresponds to narrowly spaced rolls having orientations for which the Fourier coefficients of both the perpendicular and the parallel components of the shear are nearly equal.

Shirer, H. N.↗
NASA NTRS1995

Assessment of climate variability of the Greenland ice sheet: Integration of in situ and satellite data

The proposed research involves the application of multispectral satellite data in combination with ground truth measurements to monitor surface properties of the Greenland ice sheet which are essential for describing the energy and mass of the ice sheet. Several key components of the energy balance are parameterized using satellite data and in situ measurements. The analysis will be done for a ten year time period in order to get statistics on the seasonal and interannual variations of the surface processes and the climatology. Our goal is to investigate to what accuracy and over what geographic areas large scale snow properties and radiative fluxes can be derived based upon a combination of available remote sensing and meterological data sets. Data analysis showed the following results: (1)cloud classification based on longwave sky radiation revealed that overcast sky occurred for 25% of the time in winter, and for 15% in spring and summer respectively (winter and summer both show the same occurrence of clear sky of approximately 26%); (2) comparison of aerodynamic profile method with eddy correlation method to derive sensible and latent heat flux showed good agreement in the diurnal cycle and the turbulent fluxes were underestimated with the aerodynamic method by 10 - 30% as compared to the in situ eddy flux method; (3) the katabatic wind shows a distinct diurnal cycle with a maximum in the morning (7-9 h solar time) and a minimum in the later afternoon (18 h solar time); (4) snow grain size was modeled with a surface energy balance model (SNTHERM) and compared with in situ measurements. Sharp decreases in the modeled snow grain size, caused by accumulation events such as precipitation and deposition, could be verified with observational data; (4) radiative transfer modeling of firn supports our beliefs that the observed trends in 18 and 19 GHz passive microwave brightness temperatures are attributable to accumulation rate changes (modeling also indicates the above relationship is detectable because of the presence of depth hoar; (5) snow melt can be detected by a distinct signal in the passive microwave cross-polarized gradient ratio (19h-37v)/(19h+37v) and has been used for wet/dry snow classification; (6) top of the atmosphere (TOA) broadband albedos were derived from AVHRR visible and near infrared reflectances for the entire ice sheet from May 1990 - June 1991, and the highest albedo values are found along the southeast coast of the ice sheet which is consistent with the summer peak of precipitation due to onshore flow loaded with high water vapor content (TOA albedo values dropped to around 40% along the south-western coast during July and August due to bare ice surfaces); and (7) the net all-wave radiation balance at the top of the atmosphere is negative over the entire ice sheet except for the summer months - June-July-August (in June, the net radiation balance is slightly positive over the dry snow areas--15 W/m2).

Steffen, K.↗