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At least 37 records · Page 2

Fingerprints of external forcings on Sahel rainfall: aerosols, greenhouse gases, and model-observation discrepancies

Over the 20th and 21st centuries, both anthropogenic greenhouse gas increases and changes in anthropogenic aerosols have affected rainfall in the Sahel. Using multiple characteristics of Sahel precipitation, we construct a multivariate fingerprint that allows us to distinguish between the model-predicted responses to greenhouse gases and anthropogenic aerosols. Models project the emergence of a detectable signal of aerosol forcing in the middle of the 20th century and a detectable signal of greenhouse gas forcing at the beginning of the 21st. However, the signals of both aerosol and greenhouse gas forcing in observations emerge earlier and are stronger than in the models, far stronger in the case of aerosols. The similarity between the response to aerosol forcing and the leading mode of internal variability makes it difficult to attribute this model-observation discrepancy to errors in the forcing, errors in the forced response, model inability to capture the amplitude of internal variability, or some combination of these. For greenhouse gases, however, the forced response is distinct from internal variability as estimated by models, and the observations are largely commensurate with the model projections.

54 ENVIRONMENTAL SCIENCES↗

Fingerprints of External Forcing Agents on Sahel Rainfall: Aerosols, Greenhouse Gases, and Model-Observation Discrepancies

Over the 20th and 21st centuries, both anthropogenic greenhouse gas increases and changes in anthropogenic aerosols have affected rainfall in the Sahel. Using multiple characteristics of Sahel precipitation, we construct a multivariate fingerprint that allows us to distinguish between the model-predicted responses to greenhouse gases and anthropogenic aerosols. Models project the emergence of a detectable signal of aerosol forcing in the middle of the 20th century and a detectable signal of greenhouse gas forcing at the beginning of the 21st. However, the signals of both aerosol and greenhouse gas forcing in observations emerge earlier and are stronger than in the models, far stronger in the case of aerosols. The similarity between the response to aerosol forcing and the leading mode of internal variability makes it difficult to attribute this model-observation discrepancy to errors in the forcing, errors in the forced response, model inability to capture the amplitude of internal variability, or some combination of these. For greenhouse gases, however, the forced response is distinct from internal variability as estimated by models, and the observations are largely commensurate with the model projections.

Sahel↗

The ionization structure of the Orion Nebula - Infrared line observations and models

Observations of the forbidden O III 52 and 88 microns lines and the forbidden N III 57 microns line have been made at six positions and the forbidden Ne III 36 microns line at four positions in the Orion Nebula to probe its ionization structure. The wavelength of the forbidden Ne III line was measured to be 36.009-36.017 microns. Electron densities and abundance ratios of N(++)/O(++) have been calculated and compared to other radio and optical observations. Detailed one-component and two-component (bar plus halo) spherical models were calculated for exciting stars with effective temperatures of 37,000-40,000 K and log g = 4.0 and 4.5. Both the new IR observations and the visible line measurements of oxygen and nitrogen require Teff of no more than 37,000 K. However, the doubly ionized neon requires a model with Teff of at least 39,000 K, which is more consistent with that inferred from the radio flux or spectral type. These differences in Teff are not due to effects of dust on the stellar radiation field but are probably due to inaccuracies in the assumed stellar spectrum. Neon and nitrogen are approximately solar, but oxygen is half-solar in abundance. From the IR O(++) lines, it is concluded that the ionization bar results from an increase in column depth rather than from a local density enhancement.

Simpson, J. P.↗

Theory and observations: Model simulations of the period 1955-1985

The main objective of the theoretical studies presented here is to apply models of stratospheric chemistry and transport in order to understand the processes that control stratospheric ozone and that are responsible for the observed variations. The model calculations are intended to simulate the observed behavior of atmospheric ozone over the past three decades (1955-1985), for which there exists a substantial record of both ground-based and, more recently, satellite measurements. Ozone concentrations in the atmosphere vary on different time scales and for several different causes. The models described here were designed to simulate the effect on ozone of changes in the concentration of such trace gases as CFC, CH4, N2O, and CO2. Changes from year to year in ultraviolet radiation associated with the solar cycle are also included in the models. A third source of variability explicitly considered is the sporadic introduction of large amounts of NO sub x into the stratosphere during atmospheric nuclear tests.

Isaksen, Ivar S. A.↗

Linear system identification via backward-time observer models

Presented here is an algorithm to compute the Markov parameters of a backward-time observer for a backward-time model from experimental input and output data. The backward-time observer Markov parameters are decomposed to obtain the backward-time system Markov parameters (backward-time pulse response samples) for the backward-time system identification. The identified backward-time system Markov parameters are used in the Eigensystem Realization Algorithm to identify a backward-time state-space model, which can be easily converted to the usual forward-time representation. If one reverses time in the model to be identified, what were damped true system modes become modes with negative damping, growing as the reversed time increases. On the other hand, the noise modes in the identification still maintain the property that they are stable. The shift from positive damping to negative damping of the true system modes allows one to distinguish these modes from noise modes. Experimental results are given to illustrate when and to what extent this concept works.

Juang, Jer-Nan↗

Southeast Atmosphere Studies: Learning from Model-Observation Syntheses

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

atmospheric chemistry↗

Cumulus clouds - Numerical models, observations and entrainment

The first computer simulation of the organization phase of a buoyant atmospheric thermal is described. Although crude, it showed the spontaneous development of a rounded tight-gradient 'cap' and internal vortical circulation. The complexities involved in these 'field of motion' models in part motivated the development of entity models, based upon laboratory thermals. These one-dimensional models and their uses with observations are briefly described as well as their limitations. Finally, an application of Schlesinger's three-dimensional model to a GATE cumulus situation clarifies many apparently conflicting observations and postulates, thereby raising further challenging questions to be addressed jointly by the more sophisticated measuring and modeling tools available in the 1980's.

Simpson, J.↗

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗

Observation model and parameter partials for the JPL geodetic GPS modeling software GPSOMC

The physical models employed in GPSOMC and the modeling module of the GIPSY software system developed at JPL for analysis of geodetic Global Positioning Satellite (GPS) measurements are described. Details of the various contributions to range and phase observables are given, as well as the partial derivatives of the observed quantities with respect to model parameters. A glossary of parameters is provided to enable persons doing data analysis to identify quantities in the current report with their counterparts in the computer programs. There are no basic model revisions, with the exceptions of an improved ocean loading model and some new options for handling clock parametrization. Such misprints as were discovered were corrected. Further revisions include modeling improvements and assurances that the model description is in accord with the current software.

Sovers, O. J.↗

Observation model and parameter partials for the JPL geodetic (GPS) modeling software 'GPSOMC'

The physical models employed in GPSOMC, the modeling module of the GIPSY software system developed at JPL for analysis of geodetic Global Positioning Satellite (GPS) measurements are described. Details of the various contributions to range and phase observables are given, as well as the partial derivatives of the observed quantities with respect to model parameters. A glossary of parameters is provided to enable persons doing data analysis to identify quantities with their counterparts in the computer programs. The present version is the second revision of the original document which it supersedes. The modeling is expanded to provide the option of using Cartesian station coordinates; parameters for the time rates of change of universal time and polar motion are also introduced.

Sovers, O. J.↗

Machine Learning for a-posteriori model-observed data fusion to enhance predictive value of ESM output

The proposed research is consistent with focal areas 2 and 3: when successful, this effort will enhance the predictive value of Earth System Model (ESM) output by identifying and quantifying its systematic deviations from available observations and by correcting and recalibrating to existing data. The product is a hybrid process & data-driven modeling tool whose estimation can also bring insights through pattern discovery recognition on model deficiencies on the one hand and data gaps on the other.

54 ENVIRONMENTAL SCIENCES↗

Observational Model for Precision Astrometry with the Space Interferometry Mission

The Space Interferometry Mission (SIM) is a space-based 10-m baseline Michelson optical interferometer operating in the visible waveband that is designed to achieve astrometric accuracy in the single digits of the microarcsecond domain. Over a narrow field of view SIM is expected to achieve a mission accuracy of 1 microarcsecond. In this mode SIM will search for planetary companions to nearby stars by detecting the astrometric "wobble" relative to a nearby reference star. In its wide-angle mode, SIM will provide 4 microarcsecond precision absolute position measurements of stars, with parallaxes to comparable accuracy, at the end of its 5-year mission. The expected proper motion accuracy is around 3 microarcsecond/year, corresponding to a transverse velocity of 10 m/ s at a distance of 1 kpc. The basic astrometric observable of the SIM instrument is the pathlength delay. This measurement is made by a combination of internal metrology measurements that determine the distance the starlight travels through the two arms of the interferometer, and a measurement of the white light stellar fringe to find the point of equal pathlength. Because this operation requires a non-negligible integration time, the interferometer baseline vector is not stationary over this time period, as its absolute length and orientation are time varying. This paper addresses how the time varying baseline can be "regularized" so that it may act as a single baseline vector for multiple stars, as required for the solution of the astrometric equations.

TILE OBSERVATIONS↗

First Direct Measurement of Mg (α,p) 25 Al and Implications for X-Ray Burst Model-Observation Comparisons

Type-I x-ray bursts can reveal the properties of an accreting neutron star system when compared with astrophysics model calculations. However, model results are sensitive to a handful of uncertain nuclear reaction rates, such as 22 Mg(α , p). We report the first direct measurement of 22 Mg(α , p), performed with the Active Target Time Projection Chamber. The corresponding astrophysical reaction rate is orders of magnitude larger than determined from a previous indirect measurement in a broad temperature range. Overall, our new measurement suggests a less-compact neutron star in the source GS1826-24.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Observation model and parameter partials for the JPL VLBI parameter estimation software MASTERFIT-1987

This report is a revision of the document of the same title (1986), dated August 1, which it supersedes. Model changes during 1986 and 1987 included corrections for antenna feed rotation, refraction in modelling antenna axis offsets, and an option to employ improved values of the semiannual and annual nutation amplitudes. Partial derivatives of the observables with respect to an additional parameter (surface temperature) are now available. New versions of two figures representing the geometric delay are incorporated. The expressions for the partial derivatives with respect to the nutation parameters have been corrected to include contributions from the dependence of UTI on nutation. The authors hope to publish revisions of this document in the future, as modeling improvements warrant.

Sovers, O. J.↗

Linear system identification via backward-time observer models

This paper presents an algorithm to identify a state-space model of a linear system using a backward-time approach. The procedure consists of three basic steps. First, the Markov parameters of a backward-time observer are computed from experimental input-output data. Second, the backward-time observer Markov parameters are decomposed to obtain the backward-time system Markov parameters (backward-time pulse response samples) from which a backward-time state-space model is realized using the Eigensystem Realization Algorithm. Third, the obtained backward-time state space model is converted to the usual forward-time representation. Stochastic properties of this approach will be discussed. Experimental results are given to illustrate when and to what extent this concept works.

Juang, Jer-Nan↗

The longitude dependence of the dayside F region trough - A detailed model-observation comparison

The nighttime main F-region trough extends into the sunlit afternoon sector. This trough feature exhibits both a strong magnetic-activity dependence and a longitude (UT) dependence. Whalen (1987), using IGY ionosonde data, showed that both of these effects are readly extracted from f0F2 observations. This study shows that the longitude effect is the same as that contained in the Utah State University time-dependent ionospheric model. It arises from the offset of the geomagnetic axis from the geographic axis. The magnetic-activity dependency is associated with the westward convection in the afternoon sector. It is also contained in the ionospheric model via the empirical magnetospheric convection model.

Sojka, J. J.↗

Challenges in Observing, Modeling, and Forecasting the June 2023 Smoke Event Over the Northeast United States

In the first week of May 2023, boreal Canada began an early start to the biomass burning season when fires erupted across Alberta and western Saskatchewan. Smoke entered the troposphere and spread across the United States as biomass burning emissions in Canada quadrupled the prior maximum since the onset of the MODIS satellite record. Adding to the already existing smoke, wildfires ignited in Quebec on June 2, 2023, producing a heavy plume of aerosol over the northeastern part of the continent. Meteorological factors, including an area of low pressure situated, nearly stationary, over Maine, transported the smoke into a densely populated corridor containing the cities of Washington, DC, Baltimore, Philadelphia, and New York City. Air quality alerts became widespread as near-surface levels of fine particulate matter (PM2.5) exceeded harmful levels due the low altitude of the smoke plume. Forecasting the smoke transport and impacts of such events requires a complex combination of observed initial conditions for meteorology and aerosols, knowledge of the emissions from wildfires, and a state-of-the-art Earth System model that couples these components together. Using a case-study perspective with the Goddard Earth Observing System (GEOS), challenges associated with near real time forecasting of the smoke plume are presented. Analyzed and forecasted aerosol optical depth will be evaluated using available satellite and AERONET observations, while surface aerosol will be assessed relative to observations of PM2.5. Lacking real time estimates of biomass burning emissions for inputs to our forecast model, particular attention is given to the use of day-old biomass burning emissions throughout the forecast period covering the first ten days in June 2023, and the resulting reduction in forecast skill will be quantified.

Allison Collow↗