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NASA NTRS1984

Bone loss in tail-suspended rats in restricted to the unweighted limbs

Space flight which results in certain characteristic changes in the skeleton and it was hypothesized that these abnormalities are a direct result of the weightless state. To determine the role of PTH and 1,25(OH)2D in the bone changes associated with weightlessness, we studied bone metabolism under various dietary conditions using an Earth based rat model system which simulates weightlessness. In this model, rats are suspended by their tails such that their rear limbs are completely unloaded while their fore limbs are normally loaded. It is suggested that skeletal unloading induces a localized defect in the unloaded bone which results in abnormal growth and mineralization. It is concluded that skeletal unloading may make the unloaded bone more or less sensitive to a systemic factor which in turn could account for a change in bone metabolism.

Bikle, D. D.↗

NASA NTRS1993

AVIRIS calibration and application in coastal oceanic environments - Tracers of soluble and particulate constituents of the Tampa Bay coastal plume

AVIRIS is a testbed for future spacecraft sensors (such as HIRIS and MODIS) planned for the Earth Observing System. Model-derived absorption coefficients at 415 nm, a(415), and back-scattering coefficients at 671 nm, b sub b (671) for Tampa Bay waters were used to create images from AVIRIS data of the dissolved component of a(415) due to gelbstoff, a sub g (415), and salinity. Images of a sub g (415), salinity, and b sub b (671) were used to depict the distribution of dissolved and particulate constituents, respectively, for Tampa Bay plume during late, ebb-tidal conditions. Salinity covaried with a sub g (415), which provided a means of mapping salinity from the a sub g (415) imagery. The concentration of suspended particles, as inferred from b sub g (671), was extremely variable in the shallow regions where waves and currents interacted. Pollutants covarying with fresh water or suspended sediments can be mapped from a sub g (415) and b sub b (671) images, respectively.

Carder, K. L.↗

NASA NTRS1992

Towards coupled physical-biogeochemical models of the ocean carbon cycle

The purpose of this review is to discuss the critical gaps in our knowledge of ocean dynamics and biogeochemical cycles. It is assumed that the ultimate goal is the design of a model of the earth system that can predict the response to changes in the external forces driving climate.

Rintoul, Stephen R.↗

NASA NTRS2007

Use of Combined A-Train Observations to Validate GEOS Model Simulated Dust Distributions During NAMMA

During August 2006, the NASA African Multidisciplinary Analyses Mission (NAMMA) field experiment was conducted to characterize the structure of African Easterly Waves and their evolution into tropical storms. Mineral dust aerosols affect tropical storm development, although their exact role remains to be understood. To better understand the role of dust on tropical cyclogenesis, we have implemented a dust source, transport, and optical model in the NASA Goddard Earth Observing System (GEOS) atmospheric general circulation model and data assimilation system. Our dust source scheme is more physically based scheme than previous incarnations of the model, and we introduce improved dust optical and microphysical processes through inclusion of a detailed microphysical scheme. Here we use A-Train observations from MODIS, OMI, and CALIPSO with NAMMA DC-8 flight data to evaluate the simulated dust distributions and microphysical properties. Our goal is to synthesize the multi-spectral observations from the A-Train sensors to arrive at a consistent set of optical properties for the dust aerosols suitable for direct forcing calculations.

Nowottnick, E.↗

NASA NTRS2008

Interannual Variability and Trends of Extratropical Ozone: Northern Hemisphere - Part 1

The authors apply principal component analysis (PCA) to the extratropical total column ozone from the combined merged ozone data product and the European Centre for Medium-Range Weather Forecasts assimilated ozone from January 1979 to August 2002. The interannual variability (IAV) of extratropical O-3 in the Northern Hemisphere (NH) is characterized by four main modes. Attributable to dominant dynamical effects, these four modes account for nearly 60% of the total ozone variance in the NH. The patterns of variability are distinctly different from those derived for total O-3 in the tropics. To relate the derived patterns of O-3 to atmospheric dynamics, similar decompositions are performed for the 30 100-Wa geopotential thickness. The results reveal intimate connections between the IAV of total ozone and the atmospheric circulation. The first two leading modes are nearly zonally symmetric and represent the connections to the annular modes and the quasi-biennial oscillation. The other two modes exhibit in-quadrature, wavenumber-1 structures that, when combined, describe the displacement of the polar vortices in response to planetary waves. In the NH, the extrema of these combined modes have preferred locations that suggest fixed topographical and land-sea thermal forcing of the involved planetary waves. Similar spatial patterns and trends in extratropical column ozone are simulated by the Goddard Earth Observation System chemistryclimate model (GEOS-CCM). The decreasing O-3 trend is captured in the first mode. The largest trend occurs at the North Pole, with values similar to-1 Dobson Unit (DU) yr(-1). There is almost no trend in tropical O-3. The trends derived from PCA are confirmed using a completely independent method, empirical mode decomposition, for zonally averaged O-3 data. The O-3 trend is also captured by mode 1 in the GEOS-CCM, but the decrease is substantially larger than that in the real atmosphere.

Yung, Yuk L.↗

NASA NTRS2014

Mars Science Laboratory (MSL) Entry, Descent, and Landing Instrumentation (MEDLI): Complete Flight Data Set

The Mars Science Laboratory (MSL) entry vehicle (EV) successfully entered the Mars atmosphere and landed the Curiosity rover safely on the surface of the planet in Gale crater on August 6, 2012. MSL carried the MSL Entry, Descent, and Landing (EDL) Instrumentation (MEDLI). MEDLI delivered the first in-depth understanding of the Mars entry environments and the response of the entry vehicle to those environments. MEDLI was comprised of three major subsystems: the Mars Entry Atmospheric Data System (MEADS), the MEDLI Integrated Sensor Plugs (MISP), and the Sensor Support Electronics (SSE). Ultimately, the entire MEDLI sensor suite consisting of both MEADS and MISP provided measurements that were used for trajectory reconstruction and engineering validation of aerodynamic, atmospheric, and thermal protection system (TPS) models in addition to Earth-based systems testing procedures. This report contains in-depth hardware descriptions, performance evaluation, and data information of the three MEDLI subsystems.

Cheatwood, F. McNeil↗

NASA NTRS2015

ISMIP6: Ice Sheet Model Intercomparison Project for CMIP6

ISMIP6 (Ice Sheet Model Intercomparison Project for CMIP6) targets the Cryosphere in a Changing Climate and the Future Sea Level Grand Challenges of the WCRP (World Climate Research Program). Primary goal is to provide future sea level contribution from the Greenland and Antarctic ice sheets, along with associated uncertainty. Secondary goal is to investigate feedback due to dynamic ice sheet models. Experiment design uses and augment the existing CMIP6 (Coupled Model Intercomparison Project Phase 6) DECK (Diagnosis, Evaluation, and Characterization of Klima) experiments. Additonal MIP (Model Intercomparison Project)- specific experiments will be designed for ISM (Ice Sheet Model). Effort builds on the Ice2sea, SeaRISE (Sea-level Response to Ice Sheet Evolution) and COMBINE (Comprehensive Modelling of the Earth System for Better Climate Prediction and Projection) efforts.

CMIP6↗

NASA NTRS2018

Preliminary Evaluation of the Simplified Higher Order Closure (SHOC) in the NASA Goddard Earth Observing System (GEOS)

Here we evaluate alternative planetary boundary layer (PBL) schemes in the NASA Goddard Earth Observing System (GEOS) model. The model currently calculates turbulent diffusivities with a local Richardson number-based scheme for stable layers, and a K-profile scheme with surface- and cloud-driven plumes based on Lock et al. (2000) for unstable layers. In this study, these are replaced with the TKE-based Simplified Higher Order Closure (SHOC). SHOC combines a 1.5-order turbulence closure with a double-Gaussian PDF serving as a subgrid condensation scheme. The new diffusivity calculations are paired with two new shallow mass flux schemes. First, the University of Washington shallow cumulus scheme of Park and Bretherton (2009), a buoyancy-sorting entraining-detraining bulk plume with overshooting entrainment and a TKE/CIN-based closure. Second, an Eddy Diffusivity Mass Flux (EDMF) scheme based on the multiple plume model of Suselj et al. (2013) with stochastic lateral entrainment. Global climatologies of low level temperature, humidity, and wind are evaluated against MERRA-2 and ERA-Interim reanalyses, and significant reductions in bias are seen with both mass flux schemes. The diurnal cycle over the continental United States is evaluated using MERRA-2 and an in situ network of surface Lidar profilers.

Arnold, Nathan↗

NASA NTRS2018

Sensitivity of Different Types of Observations to NASA GEOS Hurricane Analyses and Forecasts

The 2017 Atlantic hurricane season was the 5th most active, featuring 17 named storms, the highest number of major hurricanes since 2005, and by far the costliest season on record. African easterly waves often serve as the seeding circulation for a large portion of hurricanes (i.e. tropical storms with wind over 74mph in the Atlantic and Northeast Pacific). Warm SST, moist air, and low wind shear are the main requirements for tropical cyclones to develop and maintain hurricane strength. In terms of hurricane propagation (so called hurricane tracks), Atlantic hurricanes typically propagate around the periphery of the subtropical ridge called the Bermuda High (Azores High), riding along its strongest winds. If the high is positioned to the east, then hurricanes generally propagate northeastward around the high's western edge into the open Atlantic Ocean without making land fall. If the high is positioned to the west and extends far enough to the south, storms are blocked from curving north and forced to continue west towards Florida, Cuba, and the Gulf of Mexico. If we have accurate atmospheric temperature distribution, which is directly related to atmospheric wave patterns, wind distributions, moisture distribution, and SST distribution in the analyses, we will have better NWP skills in hurricane analyses including hurricane intensity and tracks. Assimilating various observation data are supposed to play these roles in the analyses. To examine impacts of different types of observation data on NASA Goddard Earth Observing System (GEOS) model hurricane analyses and forecasts during the period of 2017 summer, this study performs data denial experiments using GEOS Atmospheric Data Assimilation System (ADAS), which is based on the hybrid 4D-EnVar GSI algorithm. Various types of observations such as microwave sounders, infrared sounders, TCvitals, and conventional data are removed in the experiments. In addition, the interaction between the different observation groups as certain instruments are removed from the analysis is investigated in detail using adjoint based forecast sensitivity observation impact (FSOI).

Hurricane↗

NASA NTRS2018

Impact Study of the Assimilation of Surface Sensitive Microwave Radiances in the GEOS

The aim of this study is to investigate the feasibility of assimilating low frequency microwave observations from different satellite Microwave radiometers such as the Advanced Microwave Sounding Unit-A (AMSU-A). These observations are relevant to the description of air temperature, humidity, and surface parameters such as ocean surface temperature. Their assimilation into Goddard Earth Observing System (GEOS) modeling and assimilation system helps better constrain models in regions where very few observations are assimilated. In recent years, Channels 1â€“4 and 15 have not been assimilated in GEOS because of their large sensitivities to uncertain surface parameters such as emissivity and skin temperature. Here, the impact of using different channels will be discussed. Also we investigate the validity of the emissivity model in these channels over ocean and sea ice.Radiative transfer calculations necessary for the assimilation of satellite radiances are performed using the Community Radiative Transfer Model (CRTM). The CRTM performs forward radiative transfer calculations of brightness temperature from atmospheric profiles (temperature, moisture, and ozone) and surface characteristics. Additionally, the CRTM calculates the Jacobians of brightness temperature with respect to the input . The Jacobians are for the inversion of these radiances within the Gridpoint Statistical Interpolation (GSI) analysis system. Here, For direct assimilation of the radiance observations, the interface between GSI and CRTM, is slightly modified. Finally, we validate the assimilation results, and discuss the impact of each channels in detail.

Ebrahimi, Hamideh↗

NASA NTRS2019

Impact Study of the Assimilation of Surface Sensitive Microwave Radiances in the GEOS

The aim of this study is to investigate the feasibility of assimilating low-frequency microwave observations from different satellite Microwave radiometers such as the Advanced Microwave Sounding Unit-A (AMSU-A), Global Precipitation Measurement (GPM) Microwave Imager (GMI), and Advanced Microwave Scanning Radiometer 2 (AMSR2). These observations are relevant to the description of air temperature, humidity, and surface parameters such as ocean surface temperature. Their assimilation into Goddard Earth Observing System (GEOS) modeling and assimilation system helps better constrain models in regions where very few observations are assimilated. In recent years, surface sensitive channels have not been assimilated in GEOS because of their large sensitivities to uncertain surface parameters such as emissivity and skin temperature.

Ebrahimi, Hamideh↗

NASA NTRS2019

File Specification for GEOS-CF Products

The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (about 25 km). This GEOS Composition Forecast (GEOS-CF) system combines the GEOS weather analysis and forecasting system with the state-of-the-science GEOS-Chem chemistry module (Bey et al., 2001; Keller et al., 2014; Long et al., 2015) to provide detailed chemical analysis of a wide range of air pollutants including ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5).

Knowland, Katherine E.↗

NASA NTRS2019

Evaluation of GEOS Total Cloud Fraction with GLOBE Citizen Science Observations and Co-Located Satellite Data

Here we evaluate the total cloud fraction in cycled forecast experiments with the NASA Global Earth Observing System (GEOS) model. Forecasts were run for summer and winter periods of 2017/2018 and compared with ground-based and satellite observations. Citizen science observations from the Global Learning and Observations to Benefit the Environment (GLOBE) Program were matched with MODIS satellite overpasses and geostationary cloud fraction, yielding a dataset of coincident observations for comparison with hourly model output. The observations indicate a model bias toward overcast and clear conditions, with underestimation of intermediate cloud fractions. We investigate underestimation of variance in the sub-grid total water probability density function (PDF) as a possible cause. The PDF determines large-scale cloud fraction as the sub-grid fraction with total water exceeding the saturation specific humidity. We conduct model experiments in which the shape, width, and spatial dependence of the PDF are varied, and consider the impacts on cloud fraction relative to the combined observations.

Starke, Matthew↗

NASA NTRS2020

Cascading toward a Kilometer‐scale GCM: Impacts of a Scale‐aware Convection Parameterization in the Goddard Earth Observing System GCM.

The NASA Goddard Earth Observing System global model is evaluated through a cascade of simulations with increasing horizontal resolution. This model employs a non-hydrostatic dynamical core and includes a scale-aware, deep convection parameterization (DPCP). 40-daysimulations at six resolutions (100km to 3km) with unvarying model formulation were produced. At the highest resolution, extreme experiments were carried out; one with no DPCP, and one with its scale-awareness eliminated. Simulated precipitation, radiative balance, and atmospheric thermodynamic and dynamical variables are well reproduced with respect to both observational and reanalysis data. As model resolution increases, the convective precipitation smoothly transitions from being mostly produced by the convection parameterization to the cloud microphysics parameterization. However, contrary to current thought, these extreme cases argue for maintaining, to some extent, the scale-aware deep convection parameterization even at 3kmscale, as the run relying solely on explicit grid-scale production of rainfall performs more poorly at this resolution.

Saulo Freitas↗

NASA NTRSDate not supplied

Calculating the Height of Volcanic Cloud SO2 With a Lagrangian Trajectory Tool: Raikoke (2019) and Pinatubo (1991) Cases

We have developed a new data analysis tool to reconstruct the altitude of SO2 clouds ejected by avolcanic eruption. Starting with 2D fields of satellite observed SO2 column density, known volcanolocation, and reanalysis wind fields, the Goddard Lagrangian trajectory tool allows us to estimatethe altitude and local concentration of SO2 at the time of observation. We demonstrate this tool forthe June 21, 2019 Mt. Raikoke eruption (8h, 30h and 78 hours after eruption). We use SO2 data fromthe Ozone Mapping and Profiler Suite/Nadir Mapper (OMPS/NM) onboard the NASA-NOAASuomi National Polar Partnership satellite and the Tropospheric Monitoring Instrument(TROPOMI) onboard the European Copernicus Sentinel 5 precursor satellite and wind fields fromthe NASA Goddard Earth Observing System (GEOS) model. We obtained a wide distribution ofSO2 altitudes between 1 and 19 kilometers in different parts of the Raikoke SO2 clouds, with thehighest SO2 concentration between 11 and 16 km, in good agreement with data from independentSO2 layer height retrievals from TROPOMI and Infrared Atmospheric Sounding Interferometer(IASI). We then applied this method to the June 15, 1991 Mt. Pinatubo eruption using SO2 columnmeasurements from the NASA Total Ozone Mapping Spectrometer (TOMS) on June 16, 17, 18 andusing wind fields from the National Centers for Environmental Prediction Reanalysis version 2. Weobtained a wide distribution of SO2 heights from 6 km up to 30 km in the northern part of the cloud.We use our new trajectory tool to reconstruct volcanic SO2/aerosol emission sources as functions oftime and altitude, providing inputs to the GEOS model aerosol and chemistry schemes in order tosimulate the dispersion of volcanic SO2 and aerosol clouds from these events.

SO2↗

NASA NTRSDate not supplied

NASA's High-Resolution GEOS Forecasting and Reanalysis Products: A Unified Tool from Local to Global Scales

NASA's GMAO produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric chemical composition at unprecedented horizontal resolution of 0.25 degrees (~25 km), freely available to the public. This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). GEOS-CF also assimilated satellite observations into the system for improved representation of weather and smoke. The assimilation system is currently being expanded to include chemically reactive trace gases. While the main focus of this new product is on tropospheric air quality information, the GEOS-Chem chemistry model used in this system includes the unified tropospheric stratospheric chemistry mechanism for improved forecasts of total column ozone during anomalous dynamical and chemical events. I will discuss current capabilities of the GEOS Constituent Data Assimilation System (CoDAS) to improve atmospheric composition modeling and possible future directions for GEOS-CF and reanalysis products. In addition, I will show how machine learning techniques can be used to correct for sub-grid-scale variability, which further improves model estimates at a given observation site.

Co-DAS↗

NASA NTRS2022

Investigation of the Potential Saturation of Information from Global Navigation Satellite System Radio Occultation Observations with an Observing System Simulation Experiment

The potential impact of large numbers of Global Navigation Satellite System radio occultation (GNSS-RO) observations on numerical weather prediction is investigated using a global observing system simulation experiment (OSSE). The hybrid four-dimensional ensemble variational Gridpoint Statistical Interpolation (GSI) data assimilation system and Global Earth Observing System (GEOS) model are used to ingest up to 100,000 GNSS-RO soundings per day in addition to the current suite of conventional and radiance data. Analysis quality, forecast skill, and forecast sensitivity to observation impact are examined with differing quantities of additional GNSS-RO profiles. It is found that saturation of information from additional RO soundings has not been reached with 100,000 soundings per day. There are some indications of suboptimal performance of the GSI in handling GNSS-RO observations particularly in the middle and lower tropospheric extratropics.

GNSS-RO↗

NASA NTRS2022

GMAO Office Note No. 17 (Version 1.3) File Specification for GEOS-CF Products

GEOS-CF↗