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NASA NTRSDate not supplied

Inertia of Ionospheric Conductance During Electron Precipitation Events in Pulsating Aurora and Polar Arcs

Using coupled SuperThermal Electron Transport (STET) and Super-thermal Proton Electron Atomic Hydrogen – tRansport in the Ionosphere and Thermosphere (SPEAH-RIT) codes, we demonstrate that temporal variability of ionospheric conductance is defined by several time scales: magnetospheric source time variations, starting time of electron precipitation, and termination of the corresponding source of magnetospheric origin. In this case, the time scales are defined by dissipation of energetic electrons and effective recombination processes. The results presented in this paper were applied in the regions of pulsating aurora and polar arcs, demonstrating the fact that ionospheric conductance requires some time to form and decay. These time delays constitute an effective “inertia” in the conductance calculation which is not accounted for in many global models which assume an instantaneous connection between precipitation and conductance. Ionospheric conductance inertia influences the temporal variation in ionospheric and magnetospheric electric fields, and as a result, impacts magnetospheric dynamics and ultimately reconfigures the electron precipitation.

Khazanov, George V↗
NASA NTRSDate not supplied

Impact Assessment of All-Sky TROPICS Microwave Observations on the NASA GEOS Analyses and Forecasts and Progress to Use the Data in the JEDI-GEOS Analysis System

The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a constellation of small satellites carrying state-of-art microwave temperature and humidity sounders with 12 channels between 91 GHz and 205 GHz frequency. Including TROPICS-pathfinder, launched on 30 June 2021, five TROPICS CubeSats operate and provide temperature and humidity data to NWP and atmospheric retrieval communities. This study is dedicated to evaluating the impact of the TROPICS satellite constellation microwave observations in numerical weather prediction (NWP) using the NASA Goddard Earth Observing System (GEOS). The TROPICS-01 (TROPICS-Pathfinder), TROPICS-03, TROPICS-05, and TROPICS-06 data in all-sky conditions over the ocean during the period of 25 July 2023 and 6 September 2023 are used for assessing forecast impacts on global NWP analysis and five-day forecasts. A series of experiments are carried out to measure the benefits of assimilating observations from only temperature sounders, water vapor sounders, and both sounders. Statistical analysis of the Observing System Experiments (OSEs) results has shown incremental improvements in global model forecast skills for critical geophysical parameters, including temperature, winds, and geopotential heights. The results demonstrate the potential of the TROPICS-like data to positively impact NWP by adding new information to the current observation and forecast system. In another set of experiments, the TROPICS-03, TROPICS-05, and TROPICS-06 data sets are added to the TROPICS-01 one by one to evaluate the impacts of increasing the revisit rate of TROPICS satellite measurements on NWP analysis for a tropical cyclone’s dynamical and microphysical structures. This study offers important insights into the capabilities of a new generation of small satellite microwave radiometers based on emerging technologies, including their unique measurements at 118 GHz and 205 GHz that are not available in traditional operational microwave sounders. Finally, the efforts to implement these new developments for TROPICS in the JEDI-GEOS atmospheric data assimilation system are in progress, and preliminary results from cycled JEDI-GEOS data assimilation experiments are presented.

Min-Jeong Kim↗
DOE OSTI2024

Commercial EV Charging Infrastructure: Modeling Concepts & Techniques

This presentation offers an overview of key concepts and techniques for modeling global commercial EV charging infrastructure. We begin by comparing the unique needs of commercial vehicles with those of personal vehicles. Next, we delve into network design topics, including phased deployment of public infrastructure, port sharing across and within fleets, power requirements for en-route charging, and strategies for estimating depot charging availability. Finally, we outline the primary steps NREL follows in conducting an EV charging infrastructure needs assessment.

ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗
NASA NTRS2000

A Coupled Ocean General Circulation, Biogeochemical, and Radiative Model of the Global Oceans: Seasonal Distributions of Ocean Chlorophyll and Nutrients

A coupled ocean general circulation, biogeochemical, and radiative model was constructed to evaluate and understand the nature of seasonal variability of chlorophyll and nutrients in the global oceans. Biogeochemical processes in the model are determined from the influences of circulation and turbulence dynamics, irradiance availability. and the interactions among three functional phytoplankton groups (diatoms. chlorophytes, and picoplankton) and three nutrients (nitrate, ammonium, and silicate). Basin scale (greater than 1000 km) model chlorophyll results are in overall agreement with CZCS pigments in many global regions. Seasonal variability observed in the CZCS is also represented in the model. Synoptic scale (100-1000 km) comparisons of imagery are generally in conformance although occasional departures are apparent. Model nitrate distributions agree with in situ data, including seasonal dynamics, except for the equatorial Atlantic. The overall agreement of the model with satellite and in situ data sources indicates that the model dynamics offer a reasonably realistic simulation of phytoplankton and nutrient dynamics on synoptic scales. This is especially true given that initial conditions are homogenous chlorophyll fields. The success of the model in producing a reasonable representation of chlorophyll and nutrient distributions and seasonal variability in the global oceans is attributed to the application of a generalized, processes-driven approach as opposed to regional parameterization and the existence of multiple phytoplankton groups with different physiological and physical properties. These factors enable the model to simultaneously represent many aspects of the great diversity of physical, biological, chemical, and radiative environments encountered in the global oceans.

Gregg, Watson W.↗
DOE OSTI2024

How Well Does the DOE Global Storm Resolving Model Simulate Clouds and Precipitation Over the Amazon?

This study assesses a 40-day 3.25-km global simulation of the Simple Cloud-Resolving E3SM Model (SCREAMv0) using high-resolution ground-based observations from the Atmospheric Radiation Measurement (ARM) Green Ocean Amazon (GoAmazon) field campaign. SCREAMv0 reasonably captures the diurnal timing of boundary layer clouds yet underestimates the boundary layer cloud fraction and mid-level congestus. SCREAMv0 well replicates the precipitation diurnal cycle, however it exhibits biases in the precipitation cluster size distribution compared to scanning radar observations. Specifically, SCREAMv0 overproduces clusters smaller than 128 km, and does not form enough large clusters. Such biases suggest an inhibition of convective upscale growth, preventing isolated deep convective clusters from evolving into larger mesoscale systems. This model bias is partially attributed to the misrepresentation of land-atmosphere coupling. This study highlights the potential use of high-resolution ground-based observations to diagnose convective processes in global storm resolving model simulations, identify key model deficiencies, and guide future process-oriented model sensitivity tests and detailed analyses.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Tropical Cyclones in Global Storm-Resolving Models

Recent progress in computing and model development has initiated the era of global storm-resolving modeling, and with it the potential to transform weather and climate prediction. Within the general theme of vetting this new class of models, the present study evaluates nine global-storm resolving models in their ability to simulate tropical cyclones (TCs). Results indicate that, broadly speaking, the models produce realistic TCs and remove longstanding issues known from global models such as the deficiency in accurately simulating TC intensity. However, TCs are strongly affected by model formulation, and all models suffer from unique biases regarding the number of TCs, intensity, size, and structure. Some models simulated TCs better than others, but no single model was superior in every way. The overall results indicate that global storm-resolving models can open a new chapter in TC prediction, but they need to be improved to unleash their full potential.

Falko Judt↗
NASA NTRS1987

Utilization of Global Reference Atmosphere Model (GRAM) for shuttle entry

At high latitudes, dispersions in values of density for the middle atmosphere from the Global Reference Atmosphere Model (GRAM) are observed to be large, particularly in the winter. Trajectories have been run from 28.5 deg to 98 deg. The critical part of the atmosphere for reentry is 250,000 to 270,000 ft. 250,000 ft is the altitude where the shuttle trajectory levels out. For ascending passes the critical region occurs near the equator. For descending entries the critical region is in northern latitudes. The computed trajectory is input to the GRAM, which computes means and deviations of atmospheric parameters at each point along the trajectory. There is little latitude dispersion for the ascending passes; the strongest source of deviations is seasonal; however, very wide seasonal and latitudinal deviations are exhibited for the descending passes at all orbital inclinations. For shuttle operations the problem is control to maintain the correct entry corridor and avoid either aerodynamic skipping or excessive heat loads.

Joosten, Kent↗
NASA NTRS2008

The NASA MSFC Earth Global Reference Atmospheric Model-2007 Version

Reference or standard atmospheric models have long been used for design and mission planning of various aerospace systems. The NASA/Marshall Space Flight Center (MSFC) Global Reference Atmospheric Model (GRAM) was developed in response to the need for a design reference atmosphere that provides complete global geographical variability, and complete altitude coverage (surface to orbital altitudes) as well as complete seasonal and monthly variability of the thermodynamic variables and wind components. A unique feature of GRAM is that, addition to providing the geographical, height, and monthly variation of the mean atmospheric state, it includes the ability to simulate spatial and temporal perturbations in these atmospheric parameters (e.g. fluctuations due to turbulence and other atmospheric perturbation phenomena). A summary comparing GRAM features to characteristics and features of other reference or standard atmospheric models, can be found Guide to Reference and Standard Atmosphere Models. The original GRAM has undergone a series of improvements over the years with recent additions and changes. The software program is called Earth-GRAM2007 to distinguish it from similar programs for other bodies (e.g. Mars, Venus, Neptune, and Titan). However, in order to make this Technical Memorandum (TM) more readable, the software will be referred to simply as GRAM07 or GRAM unless additional clarity is needed. Section 1 provides an overview of the basic features of GRAM07 including the newly added features. Section 2 provides a more detailed description of GRAM07 and how the model output generated. Section 3 presents sample results. Appendices A and B describe the Global Upper Air Climatic Atlas (GUACA) data and the Global Gridded Air Statistics (GGUAS) database. Appendix C provides instructions for compiling and running GRAM07. Appendix D gives a description of the required NAMELIST format input. Appendix E gives sample output. Appendix F provides a list of available parameters to enable the user to generate special output. Appendix G gives an example and guidance on incorporating GRAM07 as a subroutine in other programs such as trajectory codes or orbital propagation routines.

Leslie, F.W.↗
DOE OSTI2026

Convective Biases in the US DOE Global Storm‐Resolving Model: Insights From Regionally Refined Simulations During the CACTI Campaign

Accurately simulating convective processes in complex terrain remains a critical challenge for global storm-resolving models (GSRMs). This study systematically evaluates moist convective biases in the Regionally Refined Mesh configuration of the U.S. Department of Energy Simple Cloud-Resolving E3SM Atmosphere Model (RRM-SCREAM) using comprehensive observations and large-eddy simulations from the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign in the mountainous area of central Argentina. Comparisons of simulations with high-resolution observations and reanalysis data indicate that RRM-SCREAM effectively captures large-scale meteorological patterns, including regional atmospheric gradients and diurnal variability. However, RRM-SCREAM disproportionately produces smaller precipitation clusters referred to as “popcorn convection,” and exaggerated rainfall intensities compared to observations and reference models. Detailed examination of a representative orographic shallow-to-deep convective transition case shows that RRM-SCREAM delays initial shallow convection growth due to lower-tropospheric dryness and sustained convective inhibition, but once triggered, deep convection becomes overly vigorous with excessively strong vertical velocities and elevated cloud ice content, linked to a thermodynamic structure characterized by suppressed low-level moistening and excessive upper-level moisture retention. Our results highlight specific deficiencies in the model representation of convective vertical velocity, cloud microphysical processes, and convective precipitation organization within RRM-SCREAM. Addressing these biases is essential for improving the predictions of convective clouds and precipitation in the global high-resolution atmospheric models.

Su, Tianning [Lawrence Livermore National Laborato↗
NASA NTRS2008

Utilizing Mars Global Reference Atmospheric Model (Mars-GRAM 2005) to Evaluate Entry Probe Mission Sites

Engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM s perturbation modeling capability is commonly used, in a Monte-Carlo mode, to perform high fidelity engineering end-to-end simulations for entry, descent, and landing (EDL)1. Traditional Mars-GRAM options for representing the mean atmosphere along entry corridors include: a) TES Mapping Years 1 and 2, with Mars-GRAM data coming from MGCM model results driven by observed TES dust optical depth; and b) TES Mapping Year 0, with user-controlled dust optical depth and Mars-GRAM data interpolated from MGCM model results driven by selected values of globally-uniform dust optical depth. From the surface to 80 km altitude, Mars-GRAM is based on NASA Ames Mars General Circulation Model (MGCM). Mars-GRAM and MGCM use surface topography from Mars Global Surveyor Mars Orbiter Laser Altimeter (MOLA), with altitudes referenced to the MOLA areoid, or constant potential surface. Mars-GRAM 2005 has been validated2 against Radio Science data, and both nadir and limb data from the Thermal Emission Spectrometer (TES)

Justh, Hilary L.↗
NASA NTRS2019

Long-Term, Non-Anthropogenic Groundwater Storage Changes Simulated by Three Global-Scale Hydrological Models

This study examined long-term, natural (i.e., excluding anthropogenic impacts) variability of groundwater storage worldwide. Groundwater storage changes were estimated by forcing three global-scale hydrological models with three 50+ year meteorological datasets. Evaluation using in situ groundwater observations from the U.S. and terrestrial water storage derived from the Gravity Recovery and Climate Experiment (GRACE) satellites showed that these models reasonably represented inter-annual variability of water storage, as indicated by correlations greater than 0.5 in most regions. Empirical orthogonal function analysis revealed influences of the El Niño Southern Oscillation (ENSO) on global groundwater storage. Simulated groundwater storage, including its global average, exhibited trends generally consistent with that of precipitation. Global total (natural) groundwater storage decreased over the past 5-7 decades with modeled rates ranging from 0.01 to 2.18 mm year-1. This large range can be attributed in part to groundwater’s low frequency (inter-decadal) variability, which complicates identification of real long-term trends even within a 50+ year time series. Results indicate that non-anthropogenic variability in groundwater storage is substantial, making knowledge of it fundamental to quantifying direct human impacts on groundwater storage.

Groundwater storage↗
NASA NTRS2019

Long-Term, Non-Anthropogenic Groundwater Storage Changes Simulated by Three Global-Scale Hydrological Models

This study examined long-term, natural (i.e., excluding anthropogenic impacts) variability of groundwater storage worldwide. Groundwater storage changes were estimated by forcing three global-scale hydrological models with three 50+ year meteorological datasets. evaluation using in situ groundwater observations from the U.S. and terrestrial water storage derived from the Gravity Recovery and Climate experiment (GRACe) satellites showed that these models reasonably represented inter-annual variability of water storage, as indicated by correlations greater than 0.5 in most regions. Empirical orthogonal function analysis revealed influences of the El Niño Southern Oscillation (ENSO) on global groundwater storage. simulated groundwater storage, including its global average, exhibited trends generally consistent with that of precipitation. Global total (natural) groundwater storage decreased over the past 5–7 decades with modeled rates ranging from 0.01 to 2.18 mm year−1. this large range can be attributed in part to groundwater’s low frequency (inter-decadal) variability, which complicates identification of real long-term trends even within a 50+ year time series. Results indicate that non-anthropogenic variability in groundwater storage is substantial, making knowledge of it fundamental to quantifying direct human impacts on groundwater storage.

Bailing Li↗
NASA NTRSDate not supplied

Impacts of Improved Process Representation of Particle Dry Deposition on PM Pollution in a Global Chemistry-Climate Model: Differences Across Regions, Seasons, and PM Sizes

Dry deposition (DD) is a primary removal pathway of particulate matter (PM). The aerosol DD schemes in most global models do not reflect current mechanistic understanding gleaned from observations. The NASA GISS global chemistry-climate model has a new and more dynamic DD scheme that largely captures observed changes in deposition velocities with particle size. We quantify the response of simulated PM to changes in the DD scheme for the Northeast US, Central Europe, North China Plain, and Punjab. Relative to the widely used old scheme, the new scheme shows higher annual PM2.5 for all regions (up to +14%) except C. Europe where there are very small decreases. For PM1, annual increases occur over all regions (up to +20%). For PM10, there are decreases in C. Europe (-8%) and very small decreases in the NE US yet increases (up to +12%) in Punjab and N. China Plain. While there are always increases across seasons for Punjab and N. China Plain, there are both seasonal increases and decreases for the NE US and C. Europe. Given incomplete understanding of observed variations in deposition velocities for a given particle size, we perform sensitivity simulations that perturb the magnitude of the deposition velocities simulated by the new scheme. The annual PM response to increasing DD is similar in magnitude to decreasing DD, implying linearity in the PM sensitivity to DD. The relative annual response to perturbing the DD magnitude is weaker over Punjab and sometimes N. China Plain than the NE US and C. Europe. Higher PM over Punjab and N. China Plain implies a stronger sensitivity to DD when aerosol abundances are low. More mechanistic representation of aerosol DD can sometimes improve or worsen existing model PM biases, which suggests that PM biases due to other processes can be confounded or compounded by biases in DD. Further improvements to DD parameterizations require not only more observational constraints on aerosol deposition velocities but also an advanced understanding of the processes controlling observed variability.

Environmental pollution↗
NASA NTRS1993

A global multilevel atmospheric model using a vector semi-Lagrangian finite-difference scheme. I - Adiabatic formulation

An adiabatic global multilevel primitive equation model using a two time-level, semi-Lagrangian semi-implicit finite-difference integration scheme is presented. A Lorenz grid is used for vertical discretization and a C grid for the horizontal discretization. The momentum equation is discretized in vector form, thus avoiding problems near the poles. The 3D model equations are reduced by a linear transformation to a set of 2D elliptic equations, whose solution is found by means of an efficient direct solver. The model (with minimal physics) is integrated for 10 days starting from an initialized state derived from real data. A resolution of 16 levels in the vertical is used, with various horizontal resolutions. The model is found to be stable and efficient, and to give realistic output fields. Integrations with time steps of 10 min, 30 min, and 1 h are compared, and the differences are found to be acceptable.

Bates, J. R.↗
NASA NTRS1995

Decadal variability of the Tropical Atlantic Ocean Surface Temperature in shipboard measurements and in a Global Ocean-Atmosphere model

Sea surface temperature (SST) variability was investigated in a 200-yr integration of a global model of the coupled oceanic and atmospheric general circulations developed at the Geophysical Fluid Dynamics Laboratory (GFDL). The second 100 yr of SST in the coupled model's tropical Atlantic region were analyzed with a variety of techniques. Analyses of SST time series, averaged over approximately the same subregions as the Global Ocean Surface Temperature Atlas (GOSTA) time series, showed that the GFDL SST anomalies also undergo pronounced quasi-oscillatory decadal and multidecadal variability but at somewhat shorter timescales than the GOSTA SST anomalies. Further analyses of the horizontal structures of the decadal timescale variability in the GFDL coupled model showed the existence of two types of variability in general agreement with results of the GOSTA SST time series analyses. One type, characterized by timescales between 8 and 11 yr, has high spatial coherence within each hemisphere but not between the two hemispheres of the tropical Atlantic. A second type, characterized by timescales between 12 and 20 yr, has high spatial coherence between the two hemispheres. The second type of variability is considerably weaker than the first. As in the GOSTA time series, the multidecadal variability in the GFDL SST time series has approximately opposite phases between the tropical North and South Atlantic Oceans. Empirical orthogonal function analyses of the tropical Atlantic SST anomalies revealed a north-south bipolar pattern as the dominant pattern of decadal variability. It is suggested that the bipolar pattern can be interpreted as decadal variability of the interhemispheric gradient of SST anomalies. The decadal and multidecadal timescale variability of the tropical Atlantic SST, both in the actual and in the GFDL model, stands out significantly above the background 'red noise' and is coherent within each of the time series, suggesting that specific sets of processes may be responsible for the choice of the decadal and multidecadal timescales. Finally, it must be emphasized that the GFDL coupled ocean-atmosphere model generates the decadal and multidecadal timescale variability without any externally applied force, solar or lunar, at those timescales.

Mehta, Vikram M.↗
NASA NTRS2011

The NASA Marshall Space Flight Center Earth Global Reference Atmospheric Model-2010 Version

Reference or standard atmospheric models have long been used for design and mission planning of various aerospace systems. The NASA Marshall Space Flight Center Global Reference Atmospheric Model was developed in response to the need for a design reference atmosphere that provides complete global geographical variability and complete altitude coverage (surface to orbital altitudes), as well as complete seasonal and monthly variability of the thermodynamic variables and wind components. In addition to providing the geographical, height, and monthly variation of the mean atmospheric state, it includes the ability to simulate spatial and temporal perturbations.

Leslie, F. W.↗