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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Improving a Spectral Bin Microphysical Scheme Using TRMM Satellite Observations

Comparisons between cloud model simulations and observations are crucial in validating model performance and improving physical processes represented in the mod Tel.hese modeled physical processes are idealized representations and almost always have large rooms for improvements. In this study, we use data from two different sensors onboard TRMM (Tropical Rainfall Measurement Mission) satellite to improve the microphysical scheme in the Goddard Cumulus Ensemble (GCE) model. TRMM observed mature-stage squall lines during late spring, early summer in central US over a 9-year period are compiled and compared with a case simulation by GCE model. A unique aspect of the GCE model is that it has a state-of-the-art spectral bin microphysical scheme, which uses 33 different bins to represent particle size distribution of each of the seven hydrometeor species. A forward radiative transfer model calculates TRMM Precipitation Radar (PR) reflectivity and TRMM Microwave Imager (TMI) 85 GHz brightness temperatures from simulated particle size distributions. Comparisons between model outputs and observations reveal that the model overestimates sizes of snow/aggregates in the stratiform region of the squall line. After adjusting temperature-dependent collection coefficients among ice-phase particles, PR comparisons become good while TMI comparisons worsen. Further investigations show that the partitioning between graupel (a high-density form of aggregate), and snow (a low-density form of aggregate) needs to be adjusted in order to have good comparisons in both PR reflectivity and TMI brightness temperature. This study shows that long-term satellite observations, especially those with multiple sensors, can be very useful in constraining model microphysics. It is also the first study in validating and improving a sophisticated spectral bin microphysical scheme according to long-term satellite observations.

Li, Xiaowen↗
NASA NTRS2015

Distributed Space Mission Design for Earth Observation Using Model-Based Performance Evaluation

Distributed Space Missions (DSMs) are gaining momentum in their application to earth observation missions owing to their unique ability to increase observation sampling in multiple dimensions. DSM design is a complex problem with many design variables, multiple objectives determining performance and cost and emergent, often unexpected, behaviors. There are very few open-access tools available to explore the tradespace of variables, minimize cost and maximize performance for pre-defined science goals, and therefore select the most optimal design. This paper presents a software tool that can multiple DSM architectures based on pre-defined design variable ranges and size those architectures in terms of predefined science and cost metrics. The tool will help a user select Pareto optimal DSM designs based on design of experiments techniques. The tool will be applied to some earth observation examples to demonstrate its applicability in making some key decisions between different performance metrics and cost metrics early in the design lifecycle.

Constellation↗
DOE OSTI2023

Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations

Abstract. Ice-nucleating particles (INPs) in the Southern Ocean (SO) atmosphere have significant impacts on cloud radiative and microphysical properties. Yet, INP prediction skill in climate models remains poorly understood, in part because of the lack of long-term measurements. Here we show, for the first time, how model-simulated INP concentrations compare with year-round INP measurements during the Macquarie Island Cloud Radiation Experiment (MICRE) campaign from 2017–2018. We simulate immersion-mode INP concentrations using the Energy Exascale Earth System Model version 1 (E3SMv1) by combining simulated aerosols with recently developed deterministic INP parameterizations and the native classical nucleation theory (CNT) for mineral dust in E3SMv1. Because MICRE did not collect aerosol measurements of super-micron particles, which are more effective ice nucleators, we evaluate the model's aerosol fields at other high-latitude sites using long-term in situ observations of dust and sea spray aerosol. We find that the model underestimates dust and overestimates sea spray aerosol concentrations by 1 to 2 orders of magnitude for most of the high-latitude sites in the Southern Hemisphere. We next compare predicted INP concentrations with concentrations of INPs collected on filter samples (typically for 2 or 3 d) and processed offline using the Colorado State University ice spectrometer (IS) in immersion freezing mode. We find that when deterministic parameterizations for both dust and sea spray INPs are used, simulated INPs are within a factor of 10 of observed INPs more than 60 % of the time during summer. Our results also indicate that the E3SM's current treatment of mineral dust immersion freezing in the SO is impacted by compensating biases – an underprediction of dust amount was compensated by an overprediction of its effectiveness as INPs. We also perform idealized droplet freezing experiments to quantify the implications of the time-dependent behavior assumed by the E3SM's CNT-parameterization and compare with the ice spectrometer observations. We find that the E3SM CNT 10 s diagnostic used in this study is a reasonable approximation of the exact formulation of CNT, when applied to ice spectrometer measurements in low-INP conditions similar to Macquarie Island. However, the linearized 10 s diagnostic underestimates the exact formula by an order of magnitude or more in places with high-INP conditions like the Sahara. Overall, our findings suggest that it is important to correct the biases in E3SM's simulated dust life cycle and update E3SM's INP parameterizations. INP prediction errors of 2 to 3 orders of magnitude can have considerable impacts on the simulated cloud and radiative properties in global climate models. On comparing INP concentrations during MICRE against ship-based campaigns, Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) and Antarctic Circumnavigation Expedition (ACE), we find that INPs from the latter are significantly higher only in regions closer to Macquarie Island. This alludes to the fact that physical, chemical and biological processes affecting INP concentrations as stimulated by the island could be partly responsible for the high INP concentrations observed at Macquarie Island during the MICRE campaign. Therefore, improvements to both aerosol simulation and INP parameterizations are required to adequately simulate INPs and their cloud impacts in E3SM. It will be helpful to include a parallel measurement of the size-resolved aerosol composition and explore opportunities for long-term measurement platforms in future field campaigns studying INP sources in remote marine regions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Observations of three BL Lacertae objects - Constraints on inhomogeneous relativistically beamed jet models

Multifrequency observations are presented of three BL Lac objects, including the first UV measurements of 0912 + 297 and 1219 + 285. An eight day optical flare was measured from 0422 = 004 in which a doubling in visual flux density was noted; other sources displayed smaller daily fluctuations. The 5-15 GHz radio flux from these three objects remained constant for two months, although the 15-20 GHz emission from 0912 + 297 varied slightly over a period of a month. Constraints which are provided by these and other Bl Lac data are discussed for inhomogeneous relativistically beamed jet models. It is concluded that a tapered jet model is in good agreement with the data for each source and that additional emission regions are not required.

Worrall, D. M.↗
NASA NTRS1981

Observational, reference and model data on solar EUV, from measurements on AE-E

Information on solar irradiance at wavelengths below 185 nm, observed by the EUVS experiment on the AE-E satellite over the entire development of the present sunspot cycle 21, is important to a variety of investigations of planetary thermospheres and ionospheres. Since strictly observational information is generally lacking in both the completeness and the spectral detail required by the more advanced programs, it has been necessary to develop computer models in connection with fully detailed compilations of an appropriate reference spectrum. The period of July 13-18, 1976, is selected as an observationally reliable AE-E data reference period reflecting solar conditions of minimum activity for solar cycle 21. It is pointed out that the assignments of absolute irradiance-reference values have been drawn for all available sources of information other than that provided by AE-E.

Hinteregger, H. E.↗
NASA NTRS2010

Eight Year Climatologies from Observational (AIRS) and Model (MERRA) Data

We examine climatologies derived from eight years of temperature, water vapor, cloud, and trace gas observations made by the Atmospheric Infrared Sounder (AIRS) instrument flying on the Aqua satellite and compare them to similar climatologies constructed with data from a global assimilation model, the Modern Era Retrospective-Analysis for Research and Applications (MERRA). We use the AIRS climatologies to examine anomalies and trends in the AIRS data record. Since sampling can be an issue for infrared satellites in low earth orbit, we also use the MERRA data to examine the AIRS sampling biases. By sampling the MERRA data at the AIRS space-time locations both with and without the AIRS quality control we estimate the sampling bias of the AIRS climatology and the atmospheric conditions where AIRS has a lower sampling rate. While the AIRS temperature and water vapor sampling biases are small at low latitudes, they can be more than a few degrees in temperature or 10 percent in water vapor at higher latitudes. The largest sampling biases are over desert. The AIRS and MERRA data are available from the Goddard Earth Sciences Data and Information Services Center (GES DISC). The AIRS climatologies we used are available for analysis with the GIOVANNI data exploration tool. (see, http://disc.gsfc.nasa.gov).

Hearty, Thomas↗
NASA NTRS1988

Mesoscale spiral vortex embedded within a Lake Michigan snow squall band - High resolution satellite observations and numerical model simulations

It is known that Great Lakes snow squall convection occurs in a variety of different modes depending on various factors such as air-water temperature contrast, boundary-layer wind shear, and geostrophic wind direction. An exceptional and often neglected source of data for mesoscale cloud studies is the ultrahigh resolution multispectral data produced by Landsat satellites. On October 19, 1972, a clearly defined spiral vortex was noted in a Landsat-1 image near the southern end of Lake Michigan during an exceptionally early cold air outbreak over a still very warm lake. In a numerical simulation using a three-dimensional Eulerian hydrostatic primitive equation mesoscale model with an initially uniform wind field, a definite analog to the observed vortex was generated. This suggests that intense surface heating can be a principal cause in the development of a low-level mesoscale vortex.

Lyons, Walter A.↗
NASA NTRS2018

Performance and Evaluation of the Global Modeling and Assimilation Office Observing System Simulation Experiment

The National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) has spent more than a decade developing and implementing a global Observing System Simulation Experiment framework for use in evaluting both new observation types as well as the behavior of data assimilation systems. The NASA/GMAO OSSE has constantly evolved to relect changes in the Gridpoint Statistical Interpolation data assimiation system, the Global Earth Observing System model, version 5 (GEOS-5), and the real world observational network. Software and observational datasets for the GMAO OSSE are publicly available, along with a technical report. Substantial modifications have recently been made to the NASA/GMAO OSSE framework, including the character of synthetic observation errors, new instrument types, and more sophisticated atmospheric wind vectors. These improvements will be described, along with the overall performance of the current OSSE. Lessons learned from investigations into correlated errors and model error will be discussed.

OSS↗
NASA NTRS2011

Earth as an Extrasolar Planet: Earth Model Validation Using EPOXI Earth Observations

The EPOXI Discovery Mission of Opportunity reused the Deep Impact flyby spacecraft to obtain spatially and temporally resolved visible photometric and moderate resolution near-infrared (NIR) spectroscopic observations of Earth. These remote observations provide a rigorous validation of whole disk Earth model simulations used to better under- stand remotely detectable extrasolar planet characteristics. We have used these data to upgrade, correct, and validate the NASA Astrobiology Institute s Virtual Planetary Laboratory three-dimensional line-by-line, multiple-scattering spectral Earth model (Tinetti et al., 2006a,b). This comprehensive model now includes specular reflectance from the ocean and explicitly includes atmospheric effects such as Rayleigh scattering, gas absorption, and temperature structure. We have used this model to generate spatially and temporally resolved synthetic spectra and images of Earth for the dates of EPOXI observation. Model parameters were varied to yield an optimum fit to the data. We found that a minimum spatial resolution of approx.100 pixels on the visible disk, and four categories of water clouds, which were defined using observed cloud positions and optical thicknesses, were needed to yield acceptable fits. The validated model provides a simultaneous fit to the Earth s lightcurve, absolute brightness, and spectral data, with a root-mean-square error of typically less than 3% for the multiwavelength lightcurves, and residuals of approx.10% for the absolute brightness throughout the visible and NIR spectral range. We extend our validation into the mid-infrared by comparing the model to high spectral resolution observations of Earth from the Atmospheric Infrared Sounder, obtaining a fit with residuals of approx.7%, and temperature errors of less than 1K in the atmospheric window. For the purpose of understanding the observable characteristics of the distant Earth at arbitrary viewing geometry and observing cadence, our validated forward model can be used to simulate Earth s time dependent brightness and spectral properties for wavelengths from the far ultraviolet to the far infrared.brightness

Robinson, Tyler D.↗
NASA NTRS1983

Cumulus clouds - Interactions between laboratory experiments and observations as foundations for models

Early Woods Hole cumulus observations conducted with the aid of an aircraft suggested that buoyancy dilution by entrainment was a major brake upon tropical cumulus growth. The mechanism by which entrainment occurred, however, was not well understood. Ludlam and Scorer (1953) postulated that buoyant bubbles were the building blocks of cumulus clouds and that it was aerodynamic drag which caused the tops to cease rising. The present investigation is concerned with laboratory experiments and analyses which have been conducted to clarify remaining questions. Attention is given to bubbles in water of uniform density, bubbles released into stably stratified fluids, bubbles released into a two-layer fluid, some observational questions, and buoyant plumes and thermals. The considered experiments provide some insight concerning the mechanism involved in the conversion of buoyancy into motion, taking into account a simpler fluid situation.

Simpson, J.↗
NASA NTRS2006

Constraining Numerical Geodynamo Modeling with Surface Observations

Numerical dynamo solutions have traditionally been generated entirely by a set of self-consistent differential equations that govern the spatial-temporal variation of the magnetic field, velocity field and other fields related to dynamo processes. In particular, those solutions are obtained with parameters very different from those appropriate for the Earth s core. Geophysical application of the numerical results therefore depends on correct understanding of the differences (errors) between the model outputs and the true states (truth) in the outer core. Part of the truth can be observed at the surface in the form of poloidal magnetic field. To understand these differences, or errors, we generate new initial model state (analysis) by assimilating sequentially the model outputs with the surface geomagnetic observations using an optimal interpolation scheme. The time evolution of the core state is then controlled by our MoSST core dynamics model. The final outputs (forecasts) are then compared with the surface observations as a means to test the success of the assimilation. We use the surface geomagnetic data back to year 1900 for our studies, with 5-year forecast and 20-year analysis periods. We intend to use the result; to understand time variation of the errors with the assimilation sequences, and the impact of the assimilation on other unobservable quantities, such as the toroidal field and the fluid velocity in the core.

Kuang, Weijia↗
NASA NTRS2004

Status of NASA Satellite, Field Observations, and Numerical Modeling Addressing the Impact of Urbanization on Short and Long Term Precipitation Variability

Howard (1833a) made the first documented observation of a temperature difference between an urban area and its rural environment. Manley (1958) termed this contrast the "urban heat island (UHI)". The UHI has now become a widely acknowledged, observed, and researched phenomenon because of its broad implications. It is estimated that by the year 2025, 60% of the world's population will live in cities (UNFP, 1999). In the United States, the current urban growth rate is approximately 12.5%, with 80% currently living in urban areas. As cities continue to grow, urban sprawl creates unique problems related to land use, transportation, agriculture, housing, pollution, and development for policymakers. Urban expansion and its associated urban heat islands also have measurable impacts on weather and climate processes.

Shepherd, J. Marshall↗
NASA NTRS2015

A-Train Based Observational Metrics for Model Evaluation in Extratropical Cyclones

Extratropical cyclones contribute most of the precipitation in the midlatitudes, i.e. up to 70 during winter in the northern hemisphere, and can generate flooding, extreme winds, blizzards and have large socio-economic impacts. As such, it is important that general circulation models (GCMs) accurately represent these systems so their evolution in a warming climate can be understood. However, there are still uncertainties on whether warming will increase their frequency of occurrence, their intensity and how much rain or snow they bring. Part of the issue is that models have trouble representing their strength, but models also have biases in the amount of clouds and precipitation they produce. This is caused by potential issues in various aspects of the models: convection, boundary layer, and cloud scheme to only mention a few. In order to pinpoint which aspects of the models need improvement for a better representation of extratropical cyclone precipitation and cloudiness, we will present A-train based observational metrics: cyclone-centered, warm and cold frontal composites of cloud amount and type, precipitation rate and frequency of occurrence. Using the same method to extract similar fields from the model, we will present an evaluation of the GISS-ModelE2 and the IPSL-LMDZ-5B models, based on their AR5 and more recent versions. The AR5 version of the GISS model underestimates cloud cover in extratropical cyclones while the IPSL AR5 version overestimates it. In addition, we will show how the observed CloudSat-CALIPSO cloud vertical distribution across cold fronts changes with moisture amount and cyclone strength, and test if the two models successfully represent these changes. We will also show how CloudSat-CALIPSO derived cloud type (i.e. convective vs. stratiform) evolves across warm fronts as cyclones age, and again how this is represented in the models. Our third process-based analysis concerns cumulus clouds in the post-cold frontal region and how their amount relates to the stability of the boundary layer. This test uses Aqua cloud and vertical atmospheric profiles and when applied to the model output can help assess the accuracy of the convection, boundary layer and cloud scheme.

Convection clouds↗
DOE OSTI2021

A Modified Vegetation Photosynthesis and Respiration Model (VPRM) for the Eastern USA and Canada, Evaluated With Comparison to Atmospheric Observations and Other Biospheric Models

Atmospheric CO 2 measurements from a dense surface network can help to evaluate terrestrial biosphere model (TBM) simulations of Net Ecosystem Exchange (NEE) with two key benefits. First, gridded CO 2 flux estimates can be evaluated over regional scales, not possible using flux tower observations at discrete locations for model evaluation. Second, TBM ability to explain atmospheric CO 2 fluctuations due to the biosphere can be directly tested, an important objective for anthropogenic emissions monitoring using atmospheric observations. Here, we customize the Vegetation Photosynthesis and Respiration Model (VPRM) for an eastern North American domain with strong biological activity upwind of urban areas. Parameters are optimized using flux tower observations from a historical database with sites in (and near) the domain. In addition, the respiration model (originally a linear function of temperature) is modified to account for impacts of changing foliage, non-linear temperature, and water stress. Flux estimates from VPRM, the Carnegie-Ames-Stanford Approach (CASA) model and the Simple Biosphere Model v4 (SiB4), are convolved with footprints from atmospheric transport models for evaluation with CO 2 observations at 21 towers in the domain, with roughly half of the towers used here for the first time. Results show that the new respiration model in VPRM helps to correct a growing season sink bias in the atmosphere associated with underestimated summertime respiration using the original model with annual parameters. The new VPRM also better explains fine-scale atmospheric CO 2 variability compared to other TBMs, due to higher resolution diagnostic phenology, the new respiration model, domain-specific parameters, and high-quality input data sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Clouds and Radiation Processes in Regional Climate Models Evaluated Using Observations Over the Ice‐free Arctic Ocean

Abstract The presence of clouds in the Arctic regulates the surface energy budget (SEB) over the sea‐ice surface and the ice‐free ocean. Following several previous field campaigns, the cloud‐radiation relationship, including cloud vertical structure and phase, has been elucidated; however, modeling of this relationship has matured slowly. In recognition of the recent decline in the Arctic sea‐ice extent, representation of the cloud system in numerical models should consider the effects of areas covered by sea ice and ice‐free areas. Using an in situ stationary meteorological observation data set obtained over the ice‐free Arctic Ocean by the Japanese Research Vessel Mirai (September 2014), coordinated evaluation of six regional climate models (RCMs) with nine model runs was performed by focusing on clouds and the SEB. The most remarkable findings were as follows: (1) reduced occurrence of unstable stratification with low‐level cloud water in all models in comparison to the observations, (2) significant differences in cloud water representations between single‐ and double‐moment cloud schemes, (3) extensive differences in partitioning of hydrometeors including solid/liquid precipitation, and (4) pronounced lower‐tropospheric air temperature biases. These issues are considered as the main sources of SEB uncertainty over ice‐free areas of the Arctic Ocean. The results from a coupled RCM imply that the SEB is constrained by both the atmosphere and the ocean (and sea ice) with considerable feedback. Coordinated improvement of both stand‐alone atmospheric and coupled RCMs would promote a more comprehensive and improved understanding of the Arctic air‐ice‐sea coupled system.

Inoue, Jun↗
NASA NTRSDate not supplied

Enhancing Radiative Transfer Models for Optimized Assimilation of Microwave and Radar Observations

Radiative transfer models are extensively used for the assimilation of satellite observations into NWP models as well as retrieving geophysical products from satellite measurements. The Community Radiative Transfer Model (CRTM) is a community model developed by NOAA JCSDA and widely used for different purposes requiring RT calculations. CRTM requires bulk optical properties of hydrometeors in the form of lookup tables in order to perform all-sky RT calculations. However, the current cloud scattering lookup tables in CRTM assume spherical shapes for all frozen hydrometeors, whereas actual clouds contain frozen particles with diverse shapes. The first part of this talk presents the implementation and validation of a comprehensive Discrete Dipole Approximation (DDA) cloud scattering database into CRTM, specifically targeting microwave frequencies. The DDA technique proves effective in simulating the optical properties of non-spherical hydrometeors in the microwave region. The original DDA database assumes total random orientation in calculating single scattering properties. To generate the required mass scattering parameters for CRTM, the single scattering properties and water content dependent particle size distributions are used. The evaluation of results involved a collocated dataset comprising short-term forecasts from the Integrated Forecast System of the European Center for Medium-Range Weather Forecasts and satellite microwave data. The findings demonstrate that the DDA lookup tables significantly reduce discrepancies between simulated and observed values when compared to the Mie tables. Passive instruments lack the ability to provide vertically resolved measurements of clouds and precipitation, which can be obtained by active radar instruments. However, incorporating these active measurements into data assimilation systems presents challenges due to the absence of fast forward radiative transfer models and difficulties in error modeling. The second part of the talk focuses on the development, evaluation, and sensitivity analysis of a forward radar model integrated into CRTM. The forward radar model utilizes scattering properties obtained from hydrometeor lookup tables generated using the discrete dipole approximation. By utilizing CRTM instrument-specific coefficients, the model can calculate both reflectivity and attenuated reflectivity for any given radar instrument and zenith angles. Evaluation using CloudSat measurements demonstrates a strong agreement between simulations and observations when the input profiles of hydrometeors align with the measured reflectivity profiles.

Isaac Moradi↗
DOE OSTI2020

Reconstruction and uncertainty quantification of lattice Hamiltonian model parameters from observations of microscopic degrees of freedom

The emergence of scanning probe and electron beam imaging techniques has allowed quantitative studies of atomic structure and minute details of electronic and vibrational structure on the level of individual atomic units. These microscopic descriptors, in turn, can be associated with local symmetry breaking phenomena, representing the stochastic manifestation of the underpinning generative physical model. In this work, we explore the reconstruction of exchange integrals in the Hamiltonian for a lattice model with two competing interactions from observations of microscopic degrees of freedom and establish the uncertainties and reliability of such analysis in a broad parameter-temperature space. In contrast to other approaches, we specifically specify a loss function inherent to thermodynamic systems and utilize it to estimate uncertainty in simulated realizations of different models. As an ancillary task, we develop a machine learning approach based on histogram clustering to predict phase diagrams efficiently using a reduced descriptor space. We further demonstrate that reconstruction is possible well above the phase transition and in the regions of parameter space when the macroscopic ground state of the system is poorly defined due to frustrated interactions. This suggests that this approach can be applied to the traditionally complex problems of condensed matter physics such as ferroelectric relaxors and morphotropic phase boundary systems, spin and cluster glasses, and quantum systems once the local descriptors linked to the relevant physical behaviors are known.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2014

Land Surface Microwave Emissivity Dynamics: Observations, Analysis and Modeling

Land surface microwave emissivity affects remote sensing of both the atmosphere and the land surface. The dynamical behavior of microwave emissivity over a very diverse sample of land surface types is studied. With seven years of satellite measurements from AMSR-E, we identified various dynamical regimes of the land surface emission. In addition, we used two radiative transfer models (RTMs), the Community Radiative Transfer Model (CRTM) and the Community Microwave Emission Modeling Platform (CMEM), to simulate land surface emissivity dynamics. With both CRTM and CMEM coupled to NASA's Land Information System, global-scale land surface microwave emissivities were simulated for five years, and evaluated against AMSR-E observations. It is found that both models have successes and failures over various types of land surfaces. Among them, the desert shows the most consistent underestimates (by approx. 70-80%), due to limitations of the physical models used, and requires a revision in both systems. Other snow-free surface types exhibit various degrees of success and it is expected that parameter tuning can improve their performances.

Modeling↗