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

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Using Kalman Filter Chemical Data Assimilation to Study Ozone Catalytic Loss Cycles in January 1992

This paper presents for the first time a global study of the ozone catalytic destruction cycles operating in the stratosphere using a stratospheric analyses for January 1992. The chemical analyses were produced using a Kalman filter data assimilation system. Because a major component of the variability of trace gases is due to the atmospheric motions the analyses have been cast in a flow-tracking coordinate system that moves with the large scale flow pattern. Particular attention is paid to the kinetic aspects of these cycles such as the rate limiting step and chain length. Although it is an important kinetic parameter, the chain length of the various cycles is seldom considered when the various catalytic cycles are discussed. This survey highlights that in the low stratosphere the cycles involving HO2 and halogens (notably bromine) are particularly important. In approximate order of effectiveness the most important ozone loss cycles in the polar lower stratosphere are the BrO/ClO, HO2/BrO, and OH/HO2 cycles. The ClO/ClO cycle clearly delineates the regions of chlorine activation. The chain length of the HO2/ClO, OH/HO2, Br/BrO, and ClO/NO2, clearly delineate the vortex edge region. The chain length of the BrO/NO2 and Cl/NO2 cycles highlight the regions of chemical processing outside the vortex where streamers of chemically processed air are stripped-off and transported away from the vortex. This is also true in the very low stratosphere for the Cl/ClO and BrO/ClO cycles.

Lary, David J.↗
NASA NTRS2003

Retrospective Data Assimilation for GEOS-4

The NASA/Goddard Earth Observing System 3 (GEOS-3) has recently been replaced operationally by GEOS-4. One of the major components of the new system is the finite-volume general circulation model (GCM) of Lin and Rood. Updating the GEOS-3 retrospective data assimilation system of Zhu et al. to GEOS-4 requires two main steps: (i) developing the adjoint of the finite-volume GCM; and (ii) developing the adjoint of the procedures interfacing the GCM with the Physical-space Statistical Analysis System. These required adjoints are being developed automatically through the use of the Transformation of Algorithms in Fortran compiler of Giering and Kaminski. In this presentation we discuss the current status of development and plans for the near future as well as show preliminary results.

Todling, Ricardo↗
NASA NTRS1999

Stratospheric Tides and Data Assimilation

In the upper stratosphere, the atmosphere exhibits significant diurnal and semi-diurnal tidal variations, with typical amplitude of about 2K in mid-latitudes. In this paper we examine how well the tidal variations in temperature are represented by the Goddard Geodesic Earth Orbiting Satellite (GEOS-2) data assimilation system. We show that the GEOS-2 atmospheric model is quite successful at simulating the tidal temperature variations. However, the assimilation of satellite temperature soundings significantly damps the simulated tides. The reason is because the tides are not well represented by the satellite retrievals used by the assimilation system (which have a typical tidal amplitude of around 1K). As a result of this study, we suggest improvements that should be made to the treatment of satellite soundings by the assimilation system.

Swinbank, R.↗
NASA NTRS1999

Satellite Altimetry, Ocean Circulation, and Data Assimilation

Ocean circulation is a critical factor in determining the Earth's climate. Satellite altimetry has been proven a powerful technique for measuring the height of the sea surface for the study of global ocean circulation dynamics. A major objective of my research is to investigate the utility of altimeter data for ocean circulation studies. The 6 years' data record of TOPEX/POSEIDON have been analyzed to study the spatial and temporal characteristics of large-scale ocean variability. A major result obtained in 1998 is the discovery of large-scale oscillations in sea level with a period of 25 days in the Argentine Basin of the South Atlantic Ocean (see diagram). They exhibit a dipole pattern with counterclockwise rotational propagation around the Zapiola Rise (centered at 45S and 317E), a small seamount in the abyssal plain of the basin. The peak-to-trough amplitude is about 10 cm over a distance of 500-1000 km. The amplitude of these oscillations has large seasonal-to-interannual variations. The period and rotational characteristics of these oscillations are remarkably similar to the observations made by two current meters deployed near the ocean bottom in the region. What TOPEX/POSEIDON has detected apparently are manifestations of the movement of the entire water column (barotropic motion). The resultant transport variation is estimated to be about 50 x 10(exp 6) cubic M/S, which is about 50% of the total water transport in the region. Preliminary calculations suggest that these oscillations are topographically trapped waves. A numerical model of the South Atlantic is used to investigate the nature of and causes for these waves. A very important property of sea surface height is that it is directly related to the surface geostrophic velocity, which is related to deep ocean circulation through the density field. Therefore altimetry observations are not only useful for determining the surface circulation but also for revealing information about the deep ocean. Another objective of my research is to investigate the extent of information one can infer about the deep ocean from altimetric observations. The approach is data assimilation by ocean models. The objective is to develop a modeling/data assimilation system that will produce estimates of the 3-dimensional state of the ocean for the entire duration of the TOPEX/POSEIDON Mission.

Fu, Lee-Lueng↗
NASA NTRS2017

Estimating the Distribution of Colored Dissolved Organic Matter During the Southern Ocean Gas Exchange Experiment Using Four-Dimensional Variational Data Assimilation

We diagnosed the effect of various physical processes on the distribution of mixed-layer colored dissolved organic matter (CDOM) and a sulfur hexauoride (SF6) tracer during the Southern Ocean Gas Exchange Experiment (SO GasEx). The biochemical upper ocean state estimate uses in situ and satellite biochemical and physical data in the study region, including CDOM (absorption coefcient and spectral slope), SF6, hydrography, and sea level anomaly. Modules for photobleaching of CDOM and surface transport of SF6 were coupled with an ocean circulation model for this purpose. The observed spatial and temporal variations in CDOM were captured by the state estimate without including any new biological source term for CDOM, assuming it to be negligible over the 26 days of the state estimate. Thermocline entrainment and photobleaching acted to diminish the mixed-layer CDOM with time scales of 18 and 16 days, respectively. Lateral advection of CDOM played a dominant role and increased the mixed-layer CDOM with a time scale of 12 days, whereas lateral diffusion of CDOM was negligible. A Lagrangian view on the CDOM variability was demonstrated by using the SF6 as a weighting function to integrate the CDOM elds. This and similar data assimilation methods can be used to provide reasonable estimates of optical properties, and other physical parameters over the short-term duration of a research cruise, and help in the tracking of tracer releases in large-scale oceanographic experiments, and in oceanographic process studies.

Del Castillo, C. E.↗
NASA NTRS2009

Atlantic Tropical Cyclogenetic Processes during SOP-3 NAMMA in the GEOS-5 Global Data Assimilation and Forecast System

This article investigates the role of the Saharan Air Layer (SAL) in tropical cyclogenetic processes associated with a non-developing and a developing African easterly wave observed during the Special Observation Period (SOP-3) phase of the 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA). The two waves are chosen because both interact heavily with Saharan air. A global data assimilation and forecast system, the NASA GEOS-5, is being run to produce a set of high-quality global analyses, inclusive of all observations used operationally but with denser satellite information. In particular, following previous works by the same Authors, the quality-controlled data from the Atmospheric Infrared Sounder (AIRS) used to produce these analyses have a better coverage than the one adopted by operational centers. From these improved analyses, two sets of 31 5-day high resolution forecasts, at horizontal resolutions of both half and quarter degrees, are produced. Results show that very steep moisture gradients are associated with the SAL in forecasts and analyses even at great distance from the Sahara. In addition, a thermal dipole (warm above, cool below) is present in the non-developing case. Moderate Resolution Imaging Spectroradiometer (MODIS) show that aerosol optical thickness is higher in the non-developing case. Altogether, results suggest that radiative effect of dust may play some role in producing a thermal structure less favorable to cyclogenesis. Results also indicate that only global horizontal resolutions on the order of 20-30 kilometers can capture the large-scale transport and the fine thermal structure of the SAL, inclusive of the sharp moisture gradients, reproducing the effect of tropical cyclone suppression which has been hypothesized by previous authors from observational and regional modeling perspectives. These effects cannot be fully represented at lower resolutions. Global resolution of a quarter of a degree is a minimum critical threshold to investigate Atlantic tropical cyclogenesis from a global modeling perspective.

Reale, Oreste↗
DOE OSTI2021

Probabilistic Machine Learning and Data Assimilation

This white paper responds to Focal Area 1. The associated portfolio of research activities is well-suited to DOE’s asset mix of HPC platforms, climate expertise, climate simulation codes, and AI expertise, which creates an opportunity to use manifold-finding probabilistic AI methods to create more powerful data assimilation techniques that increase the fidelity and forecasting skill of Earth System Prediction.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2009

Atlantic Tropical Cyclogenetic Processes During SOP-3 NAMMA in the GEOS-5 Global Data Assimilation and Forecast System

This article investigates the role of the Saharan air layer (SAL) in tropical cyclogenetic processes associated with a nondeveloping and a developing African easterly wave observed during the Special Observation Period (SOP-3) phase of the 2006 NASA African. Monsoon Multidisciplinary Analyses (NAMMA). The two waves are chosen because they both interact heavily with Saharan air. A glottal data assimilation and forecast system, the NASA Goddard Earth Observing System. version 5 (GEOS-5), is being run to produce a set of high-9 uality global analyses, inclusive of all observations used operationally but with additional satellite information. In particular, following previous works by the same authors, the duality-controlled data from the Atmospheric Infrared Sounder (AIRS) used to produce these analyses have a better coverage than the one adopted by operational centers. From these improved analyses, two sets of 31 five-day high-resolution forecasts, at horizontal resolutions of both half and quarter degrees, are produced. Results indicate that very steep moisture gradients are associated with the SAL in forecasts and analyses, even at great distances from their source over the Sahara. In addition, a thermal dipole in the vertiieat (warm above, cool below) is present in the nondeveloping case. The Moderate Resolution Imaging Spoctroradiometer (MODIS) aboard NASA's Terra and Aqua satellites shows that aerosol optical thickness, indicative of more dust as opposed to other factors, is higher in the nondeveloping case. Altogether, results suggest that the radiative effect of dust may play some role in producing a thermal structure less favorable to cyclogenesis. Results also indicate that only global horizontal resolutions on the order of 20-30 km can capture the large-scale transport and the tine thermal structure of the SAL, inclusive of the sharp moisture gradients, reproducing the effect of tropical cyclone suppression that has been hypothesized by previous authors from observational and regional modeling perspectives. Thcse effects cannot be fully represented at lower resolutions, therefore global resolution of a quarter of a degree is a minimum critical threshold necessary to investigate Atlantic tropical cyclogenesis from a global modeling perspective

Reale, Oreste↗
NASA NTRS1997

Data Assimilation in the Ocean and in the Atmosphere: What Should be Next?

As part of the International Symposium on Assimilation of Observation in Meteorology and Oceanography, a panel discussion was held on the evening of 15 March 1995. The purpose of this panel discussion was focus on what the next major areas of research in data assimilation should be. The panelists had five minutes each for short presentations (Kalman filters, representers, etc.) and this was followed by an open discussion. This preprocessing will require a good understanding of the fine-scale phenomena. Least square methods such as Kalman filters and variational schemes are inefficient estimators of non-Gaussian field such as chemical traces. Regardless of the modeling technique employed (Lagrangian methods seem best), a least squares assimilation scheme will smear fine structure. The estimator of maximum likelihood must be sought, by examination of tracer probability distributions.

Kalnay, Eugenia↗
NASA NTRS2017

Data Assimilation to Extract Soil Moisture Information From SMAP Observations

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, they can be used to reduce the need for localized bias correction techniques typically implemented in data assimilation (DA) systems that tend to remove some of the independent information provided by satellite observations. Here, we use a statistical neural network (NN) algorithm to retrieve SMAP (Soil Moisture Active Passive) surface soil moisture estimates in the climatology of the NASA Catchment land surface model. Assimilating these estimates without additional bias correction is found to significantly reduce the model error and increase the temporal correlation against SMAP CalVal in situ observations over the contiguous United States. A comparison with assimilation experiments using traditional bias correction techniques shows that the NN approach better retains the independent information provided by the SMAP observations and thus leads to larger model skill improvements during the assimilation. A comparison with the SMAP Level 4 product shows that the NN approach is able to provide comparable skill improvements and thus represents a viable assimilation approach.

D↗
NASA NTRS2009

AIRS Impact on the Analysis and Forecast Track of Tropical Cyclone Nargis in a Global Data Assimilation and Forecasting System

Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. Moreover, the automated analyses of cyclones over the northern Indian Ocean, produced by operational global data assimilation systems (DASs), are generally of inferior quality than in other basins. In this work it is shown that the assimilation of Atmospheric Infrared Sounder (AIRS) temperature retrievals under partial cloudy conditions can significantly impact the representation of the cyclone Nargis (which caused devastating loss of life in Myanmar in May 2008) in a global DAS. Forecasts produced from these improved analyses by a global model produce substantially smaller track errors. The impact of the assimilation of clear-sky radiances on the same DAS and forecasting system is positive, but smaller than the one obtained by ingestion of AIRS retrievals, possibly due to poorer coverage.

Reale, O.↗
NASA NTRS1990

Optimizing the use of remotely sensed atmospheric data through four-dimensional data assimilation

Results with the GLA interactive forecast-retrieval-assimilation system, which directly uses satellite radiance data in the assimilation cycle, are presented. Forecasts made from initial conditions derived with this system are shown to be more skillful than those whose initial conditions came from a comparable assimilation using statistically based temperature soundings, or ones using no sounding data at all. Examples are also given of additional parameters which are produced through the physical inversion of the satellite radiance data during the interactive assimilation cycle. These are potentially useful for analysis purposes.

Pfaendtner, J.↗
NASA NTRS2017

Data Descriptor: A Land Data Assimilation System for Sub-Saharan Africa Food and Water Security Applications

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWSNETs operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

albedo↗
NASA NTRS2017

Quantifying Chemical Ozone Loss in the Arctic Stratosphere with GEOS-STRATCHEM Data Assimilation System

A faithful representation of polar stratospheric chemistry in models and its connection with dynamical variability is essential for our understanding of the evolution of the ozone layer in a changing climate and during the projected continuing decline of ozone depleting substances in the atmosphere. We use a new configuration of the Goddard Earth Observing System Data Assimilation System with a stratospheric chemistry model to study ozone depletion in the Arctic polar stratosphere during the exceptionally cold (in the stratosphere) winters 2015/2016 and 2010/2011.

Arctic↗
NASA NTRS1997

High Performance Input/Output Systems for High Performance Computing and Four-Dimensional Data Assimilation

The approach of this task was to apply leading parallel computing research to a number of existing techniques for assimilation, and extract parameters indicating where and how input/output limits computational performance. The following was used for detailed knowledge of the application problems: 1. Developing a parallel input/output system specifically for this application 2. Extracting the important input/output characteristics of data assimilation problems; and 3. Building these characteristics s parameters into our runtime library (Fortran D/High Performance Fortran) for parallel input/output support.

Fox, Geoffrey C.↗
NASA NTRS1999

Data Assimilation in the Presence of Forecast Bias: The GEOS Moisture Analysis

We describe the application of the unbiased sequential analysis algorithm developed by Dee and da Silva (1998) to the GEOS DAS moisture analysis. The algorithm estimates the persistent component of model error using rawinsonde observations and adjusts the first-guess moisture field accordingly. Results of two seasonal data assimilation cycles show that moisture analysis bias is almost completely eliminated in all observed regions. The improved analyses cause a sizable reduction in the 6h-forecast bias and a marginal improvement in the error standard deviations.

Dee, Dick P.↗
NASA NTRSDate not supplied

Improving Drought Monitoring for the Middle East and North Africa Region via Data Assimilation Using the NASA Land Information System (LIS)

Food and water security become an increasingly pressing concern for countries within the Middle East and North Africa (MENA) region under climate change. Droughts are among the most important issues facing this region in both economic and social terms, which have become much more severe in recent decades. An effective drought monitoring and early warning system is, therefore, critical to support drought impact assessment and risk management. This presentation describes the effort to improve the simulation of hydrological conditions for such semi-arid environment by Noah Multi-parameterization Land Surface Model within the NASA Land Information System (LIS) via assimilating remotely sensed leaf area index and soil moisture in the presence of irrigation. Multi-source satellite evapotranspiration products are used to evaluate the model performance under the impact of the choice of met-forcings, the presence of irrigation and data assimilation. The improved model configuration is aimed to deliver a better soil moisture estimation for the composite drought indicator (CDI) for drought monitoring and to provide a better initial condition in support for hydrological drought forecasting.

Wanshu Nie↗