Search NASA⌕ Search

SEARCH · Search NASA

Results for “Atmospheric data assimilation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Global Gridded Data from the Goddard Earth Observing System Data Assimilation System (GEOS-DAS)

The Goddard Earth Observing System Data Assimilation System (GEOS-DAS) timeseries is a globally gridded atmospheric data set for use in climate research. This near real-time data set is produced by the Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center in direct support of the operational EOS instrument product generation from the Terra (12/1999 launch), Aqua (05/2002 launch) and Aura (01/2004 launch) spacecrafts. The data is archived in the EOS Core System (ECS) at the Goddard Earth Sciences Data and Information Services Center/Distributed Active Archive Center (GES DISC DAAC). The data is only a selection of the products available from the GEOS-DAS. The data is organized chronologically in timeseries format to facilitate the computation of statistics. GEOS-DAS data will be available for the time period January 1, 2000, through present.

Source record↗
NASA NTRS2000

The Correlation Between Atmospheric Dust Deposition to the Surface Ocean and SeaWiFS Ocean Color: A Global Satellite-Based Analysis

Since the atmospheric deposition of iron has been linked to primary productivity in various oceanic regions, we have conducted an objective study of the correlation of dust deposition and satellite remotely sensed surface ocean chlorophyll concentrations. We present a global analysis of the correlation between atmospheric dust deposition derived from a satellite-based 3-D atmospheric transport model and SeaWiFs estimates of ocean color. We use the monthly mean dust deposition fields of Ginoux et al. which are based on a global model of dust generation and transport. This model is driven by atmospheric circulation from the Data Assimilation Office (DAO) for the period 1995-1998. This global dust model is constrained by several satellite estimates of standard circulation characteristics. We then perform an analysis of the correlation between the dust deposition and the 1998 SeaWIFS ocean color data for each 2.0 deg x 2.5 deg lat/long grid point, for each month of the year. The results are surprisingly robust. The region between 40 S and 60 S has correlation coefficients from 0.6 to 0.95, statistically significant at the 0.05 level. There are swaths of high correlation at the edges of some major ocean current systems. We interpret these correlations as reflecting areas that have shear related turbulence bringing nitrogen and phosphorus from depth into the surface ocean, and the atmospheric supply of iron provides the limiting nutrient and the correlation between iron deposition and surface ocean chlorophyll is high. There is a region in the western North Pacific with high correlation, reflecting the input of Asian dust to that region. The southern hemisphere has an average correlation coefficient of 0.72 compared that in the northern hemisphere of 0.42 consistent with present conceptual models of where atmospheric iron deposition may play a role in surface ocean biogeochemical cycles. The spatial structure of the correlation fields will be discussed within the context of guiding the design of field programs.

Erickson, D. J., III↗
NASA NTRS2009

Improving Regional Forecast by Assimilating Atmospheric InfraRed Sounder (AIRS) Profiles into WRF Model

In data sparse regions, remotely-sensed observations can be used to improve analyses and produce improved forecasts. One such source comes from the Atmospheric InfraRed Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced space-based atmospheric sounding systems. The purpose of this paper is to describe a procedure to optimally assimilate high resolution AIRS profile data into a regional configuration of the Advanced Research WRF (ARW) version 2.2 using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background type, and an optimal methodology for ingesting AIRS temperature and moisture profiles as separate overland and overwater retrievals with different error characteristics. The AIRS thermodynamic profiles are derived from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm and contain information about the quality of each temperature layer. The quality indicators were used to select the highest quality temperature and moisture data for each profile location and pressure level. The analyses were then used to conduct a month-long series of regional forecasts over the continental U.S. The long-term impacts of AIRS profiles on forecast were assessed against verifying NAM analyses and stage IV precipitation data.

Chou, Shih-Hung↗
NASA NTRS2007

The Evolution of the Stratopause During the 2006 Major Warming: Satellite Data and Assimilated Meteorological Analyses

Microwave Limb Sounder and Sounding of the Atmosphere with Broadband Emission Radiometry data show the polar stratopause, usually higher than and separated from that at midlatitudes, dropping from <55-60 to near 30 km, and cooling dramatically in January 2006 during a major stratospheric sudden warming (SSW). After a nearly isothermal period, a cool stratopause reforms near 75 km in early February, then drops to <55 km and warms. The stratopause is separated in longitude as well as latitude, with lowest temperatures in the transition regions between higher and lower stratopauses. Operational assimilated meteorological analyses, which are not constrained by data at stratopause altitude, do not capture a secondary temperature maximum that overlies the stratopause or the very high stratopause that reforms after the SSW; they underestimate the stratopause altitude variation during the SSW. High-quality daily satellite temperature measurements are invaluable in improving our understanding of stratopause evolution and its representation in models and assimilation systems.

Manney, Gloria L.↗
NASA NTRS2009

Sensitivity of Short-Term Weather Forecasts to Assimilated AIRS Data: Implications for NPOESS Applications

The Atmospheric Infrared Sounder (AIRS) is acting as a heritage and risk reduction instrument for the Cross-track lnfrared Sounder (CrIS) to be flown aboard the NPP and NPOESS satellites. The hyperspectral nature of AIRS and CrIS provides high-quality soundings that, along with their asynoptic observation time over North America, make them attractive sources to fill the spatial and temporal data voids in upper air temperature and moisture measurements for use in data assimilation and numerical weather prediction. Observations from AlRS can be assimilated either as direct radiances or retrieved thermodynamic profiles, and the Short-Term Prediction Research and Transition (SPORT) Center at NASA's Marshall Space Flight Center has used both data types to improve short-term (0-48h), regional forecasts. The purpose of this paper is to share SPORT'S experiences using AlRS radiances and retrieved profiles in regional data assimilation activities by showing that proper handling of issues-including cloud contamination and land emissivity characterization-are necessary to produce optimal analyses and forecasts.

Zavodsky, Bradley↗
NASA NTRS2007

Preliminary Evaluation of GEOS-5 Aerosol and CO Distributions Forecast During TC4

The NASA Tropical Composition, Cloud, and Climate Coupling (TC4) Mission was based out San Jose, Costa Rica during July and August 2007. During TC4 the NASA Global Modeling and Assimilation Office (GMAO) ran twice-daily 0.5 x 0.666 global 5-day forecasts of the Goddard Earth Observing System atmospheric general circulation model and data assimilation system (GEOS-5). This implementation of GEOS-5 contained an aerosol and carbon monoxide (CO) model to provide online forecast tropospheric distributions of dust, sea salt, sulfate, and carbonaceous aerosols and CO for both the planning of flights and for science. Here we provide a description of the aerosol and CO modeling system and give a preliminary evaluation of forecast tracer distributions. Our comparisons to satellite observations of aerosol and CO show qualitatively similar simulated distributions of tracers to those observed. During TC4 copious amounts of dust were observed in the Caribbean. The model generally reproduced the observations of the timing of dust events and the vertical structure in the lower atmosphere. However, the model simulations had too much aerosol at high altitudes relative to airborne Cloud Physics Lidar observations. The results were similar for biomass burning aerosol and CO tracers, where the model showed higher simulated concentrations of these tracers at aircraft flight altitude than observations.

Colarco, Peter R.↗
NASA NTRS1992

Diabatic dynamic initialization

A generalized dynamical adjustment procedure was applied to a diabatic model to produce balanced initial conditions. Namely, backward adiabatic model integration is followed by forward diabatic model integration, with a high frequency (low pass) filter in the form of the Euler-backward time differencing scheme being applied throughout the whole integration. As a result of the application of such a diabatic dynamic initialization procedure within the Goddard Laboratory for Atmospheres (GLA) 4-D data assimilation system, the following properties of forecasts from initialized fields are achieved right from the beginning of the usual forecast integration: (1) the forecast tendencies (and fields) are free of any noise due to imbalance in initial conditions; (2) the shocks related to an initial imbalance between model physics and dynamics, and especially the substantial initial imbalance of precipitation and evaporation fields, or the initial spin-up effect, are practically removed. Diabatic dynamic initialization has been compared with implicit nonlinear normal mode initialization, and found to be superior in removing the initial spin-up effect, and also in improving the tropical structure. The diabatic dynamic initialization procedure was successfully tested for the GLA system with the use of all conventional data and the GLA satellite data retrievals. It allows a smooth data insertion without any shocks or imbalances, which is highly desirable for efficient functioning of 4-D data assimilation systems. The developed initialization procedure is computationally efficient and in principle easily applicable to different forecast models.

Fox-Rabinovitz, Michael S.↗
NASA NTRS2002

New Concepts for Refinement of Cumulus Parameterization in GCM's the Arakawa-Schubert Framework

Several state-of-the-art models including the one employed in this study use the Arakawa-Schubert framework for moist convection, and Sundqvist formulation of stratiform. clouds, for moist physics, in-cloud condensation, and precipitation. Despite a variety of cloud parameterization methodologies developed by several modelers including the authors, most of the parameterized cloud-models have similar deficiencies. These consist of: (a) not enough shallow clouds, (b) too many deep clouds; (c) several layers of clouds in a vertically demoralized model as opposed to only a few levels of observed clouds, and (d) higher than normal incidence of double ITCZ (Inter-tropical Convergence Zone). Even after several upgrades consisting of a sophisticated cloud-microphysics and sub-grid scale orographic precipitation into the Data Assimilation Office (DAO)'s atmospheric model (called GEOS-2 GCM) at two different resolutions, we found that the above deficiencies remained persistent. The two empirical solutions often used to counter the aforestated deficiencies consist of a) diffusion of moisture and heat within the lower troposphere to artificially force the shallow clouds; and b) arbitrarily invoke evaporation of in-cloud water for low-level clouds. Even though helpful, these implementations lack a strong physical rationale. Our research shows that two missing physical conditions can ameliorate the aforestated cloud-parameterization deficiencies. First, requiring an ascending cloud airmass to be saturated at its starting point will not only make the cloud instantly buoyant all through its ascent, but also provide the essential work function (buoyancy energy) that would promote more shallow clouds. Second, we argue that training clouds that are unstable to a finite vertical displacement, even if neutrally buoyant in their ambient environment, must continue to rise and entrain causing evaporation of in-cloud water. These concepts have not been invoked in any of the cloud parameterization schemes so far. We introduced them into the DAO-GEOS-2 GCM with McRAS (Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme).

Sud, Y. C.↗
NASA NTRS2002

Evaluation of Transport in the Lower Tropical Stratosphere in a Global Chemistry and Transport Model

A general circulation model (GCM) relies on various physical parameterizations and provides a solution to the atmospheric equations of motion. A data assimilation system (DAS) combines information from observations with a GCM forecast and produces analyzed meteorological fields that represent the observed atmospheric state. An off-line chemistry and transport model (CTM) can use winds and temperatures from a either a GCM or a DAS. The latter application is in common usage for interpretation of observations from various platforms under the assumption that the DAS transport represents the actual atmospheric transport. Here we compare the transport produced by a DAS with that produced by the particular GCM that is combined with observations to produce the analyzed fields. We focus on transport in the tropics and middle latitudes by comparing the age-of-air inferred from observations of SF6 and CO2 with the age-of-air calculated using GCM fields and DAS fields. We also compare observations of ozone, total reactive nitrogen, and methane with results from the two simulations. These comparisons show that DAS fields produce rapid upward tropical transport and excessive mixing between the tropics and middle latitudes. The unrealistic transport produced by the DAS fields may be due to implicit forcing that is required by the assimilation process when there is bias between the GCM forecast and observations that are combined to produce the analyzed fields. For example, the GCM does not produce a quasi-biennial oscillation (QBO). The QBO is present in the analyzed fields because it is present in the observations, and systematic implicit forcing is required by the DAS. Any systematic bias between observations and the GCM forecast used to produce the DAS analysis is likely to corrupt the transport produced by the analyzed fields. Evaluation of transport in the lower tropical stratosphere in a global chemistry and transport model.

Douglass, Anne R.↗
NASA NTRS2016

On the Feasibility of Monitoring Carbon Monoxide in the Lower Troposphere from a Constellation of Northern Hemisphere Geostationary Satellites: Global Scale Assimilation Experiments (Part II)

This paper describes the second phase of an Observing System Simulation Experiment (OSSE) that utilizes the synthetic measurements from a constellation of satellites measuring atmospheric composition from geostationary (GEO) Earth orbit presented in part I of the study. Our OSSE is focused on carbon monoxide observations over North America, East Asia and Europe where most of the anthropogenic sources are located. Here we assess the impact of a potential GEO constellation on constraining northern hemisphere (NH) carbon monoxide (CO) using data assimilation. We show how cloud cover affects the GEO constellation data density with the largest cloud cover (i.e., lowest data density) occurring during Asian summer. We compare the modeled state of the atmosphere (Control Run), before CO data assimilation, with the known 'true' state of the atmosphere (Nature Run) and show that our setup provides realistic atmospheric CO fields and emission budgets. Overall, the Control Run underestimates CO concentrations in the northern hemisphere, especially in areas close to CO sources. Assimilation experiments show that constraining CO close to the main anthropogenic sources significantly reduces errors in NH CO compared to the Control Run. We assess the changes in error reduction when only single satellite instruments are available as compared to the full constellation. We find large differences in how measurements for each continental scale observation system affect the hemispherical improvement in long-range transport patterns, especially due to seasonal cloud cover. A GEO constellation will provide the most efficient constraint on NH CO during winter when CO lifetime is longer and increments from data assimilation associated with source regions are advected further around the globe.

Geo Stationary Constellation↗
NASA NTRS2018

The Use of MERRA-2 Near Surface Meteorology to Understand the Behavior of Planetary Boundary Layer Heights Derived from Wind Profiler Data over the US Great Plains

The atmospheric general circulation model (GCM) that underlies the MERRA-2 reanalysis includes a suite of physical parameterizations that describe the processes that occur in the planetary boundary layer (PBL). The data assimilation system assures that the atmospheric state variables used as input to these parameterizations are constrained to the best fit to all of the available observations. Many studies, however, have shown that the GCM-based estimates of MERRA-2 PBL heights are biased high, and so are not reliable for boundary layer studies.A 20-year record of PBL heights was derived from Wind Profiler (WP) backscatter data measured at a wide network of stations throughout the US Great Plains and has been validated against independent estimates. The behavior of these PBL heights shows geographical and temporal variations that are difficult to attribute to particular physical processes without additional information that are not part of the observational record.In the present study, we use information on physical processes from MERRA-2 to understand the behavior of the WP derived PBL heights. The behavior of the annual cycle of both MERRA-2 and WP PBL heights shows four classes of behavior: (i) canonical, characterized by a monthly progression in PBL height that follows the solar insolation, (ii) double peak, characterized by canonical behavior that is interrupted by a minimum in July, (iii) late peak, characterized by a suppressed heights in May and June, and return to canonical in July and August, and (iv) early peak where the PBL height rises with solar insolation but is suppressed later in the summer. The explanation for these behaviors and the relationship to local precipitation, temperature, sensible and latent heat fluxes, net radiation and aerosol load is articulated using information from MERRA-2.

Salmun, Haydee↗
NASA NTRS2017

The Use of MERRA-2 Near Surface Meteorology to Understand the Behavior of Planetary Boundary Layer Heights Derived from Wind Profiler Data over the US Great Plains

The atmospheric general circulation model (GCM) that underlies the MERRA-2 reanalysis includes a suite of physical parameterizations that describe the processes that occur in the planetary boundary layer (PBL). The data assimilation system assures that the atmospheric state variables used as input to these parameterizations are constrained to the best fit to all of the available observations. Many studies, however, have shown that the GCM-based estimates of MERRA-2 PBL heights are biased high, and so are not reliable for application related to constituent transport or the carbon cycle. A new 20-year record of PBL heights was derived from Wind Profiler (WP) backscatter data measured at a wide network of stations throughout the US Great Plains and has been validated against independent estimates. The behavior of these PBL heights shows geographical and temporal variations that are difficult to attribute to particular physical processes without additional information that are not part of the observational record. In the present study, we use information on physical processes from MERRA-2 to understand the behavior of the WP derived PBL heights. The behavior of the annual cycle of both MERRA-2 and WP PBL heights shows three classes of behavior: (i) canonical, where the annual cycle follows the annual cycle of the sun, (ii) delayed, where the PBL height reaches its annual maximum after the annual maximum of the solar insolation, and (iii) double maxima, where the PBL height begins to rise with the solar insolation but falls sometimes during the summer and then rises again. Although the magnitude of these types of variations is described by the WP PBL record, the explanation for these behaviors and the relationship to local precipitation, temperature, hydrology and sensible and latent heat fluxes is articulated using information from MERRA-2.

MERRA↗
DOE OSTI2024

Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign

Abstract. High-fidelity flow modeling with data assimilation enables accurate representation of the wind farm operating environment under realistic, nonstationary atmospheric conditions. Capturing the temporal evolution of the turbulent atmospheric boundary layer is critical to understanding the behavior of wind turbines under operating conditions with simultaneously varying inflow and control inputs. This paper has three parts: the identification of a case study during a field evaluation of wake steering; the development of a tailored mesoscale-to-microscale coupling strategy that resolved local flow conditions within a large-eddy simulation (LES), using observations that did not completely capture the wind and temperature fields throughout the simulation domain; and the application of this coupling strategy to validate high-fidelity aeroelastic predictions of turbine performance and wake interactions with and without wake steering. The case study spans 4.5 h after midnight local time, during which wake steering was toggled on and off five times, achieving yaw offset angles ranging from 0 to 17°. To resolve nonstationary nighttime conditions that exhibited shear instabilities, the turbulence field was evolved starting from the diurnal cycle of the previous day. These background conditions were then used to drive wind farm simulations with two different models: an LES with actuator disk turbines and a steady-state engineering wake model. Subsequent analysis identified two representative periods during which the up- and downstream turbines were most nearly aligned with the mean wind direction and had observed yaw offsets of 0 and 15°. Both periods corresponded to partial waking on the downstream turbine, which had errors in the LES-predicted power of 4 % and 6 %, with and without wake steering. The LES was also able to capture conditions during which an upstream turbine wake induced a speedup at a downstream turbine and increased power production by up to 13 %.

17 WIND ENERGY↗
NASA NTRS2008

The Evolution of the Stratopause during the 2006 Major Warming: Satellite Data and Assimilated Meteorological Analyses

Microwave Limb Sounder and Sounding of the Atmosphere with Broadband Emission Radiometry data provide the first opportunity to characterize the four-dimensional stratopause evolution throughout the life-cycle of a major stratospheric sudden warming (SSW). The polar stratopause, usually higher than that at midlatitudes, dropped by 30 km and warmed during development of a major "wave 1" SSW in January 2006, with accompanying mesospheric cooling. When the polar vortex broke down, the stratopause cooled and became ill-defined, with a nearly isothermal stratosphere. After the polar vortex started to recover in the upper stratosphere/lower mesosphere (USLM), a cool stratopause reformed above 75 km, then dropped and warmed; both the mesosphere above and the stratosphere below cooled at this time. The polar stratopause remained separated from that at midlatitudes across the core of the polar night jet. In the early stages of the SSW, the strongly tilted (westward with increasing altitude) polar vortex extended into the mesosphere, and enclosed a secondary temperature maximum extending westward and slightly equatorward from the highest altitude part of the polar stratopause over the cool stratopause near the vortex edge. The temperature evolution in the USLM resulted in strongly enhanced radiative cooling in the mesosphere during the recovery from the SSW, but significantly reduced radiative cooling in the upper stratosphere. Assimilated meteorological analyses from the European Centre for Medium-Range weather Forecasts (ECMWF) and Goddard Earth Observing System Version 5.0.1 (GEOS-5), which are not constrained by data at polar stratopause altitudes and have model tops near 80 km, could not capture the secondary temperature maximum or the high stratopause after the SSW; they also misrepresent polar temperature structure during and after the stratopause breakdown, leading to large biases in their radiative heating rates. ECMWF analyses represent the stratospheric temperature structure more accurately, suggesting a better representation of vertical motion; GEOS-5 analyses more faithfully describe stratopause level wind and wave amplitudes. The high-quality satellite temperature data used here provide the first daily, global, multiannual data sets suitable for assessing and, eventually, improving representation of the USLM in models and assimilation systems.

Manney, Gloria L.↗
NASA NTRS1988

Meteorological satellite products support for project COHMEX

The first year effort focussed on real-time support and satellite data collection during the field phase of COHMEX. Work efforts following the field phase of COHMEX concentrated on post-processing of the real-time data sets, and generation of enhanced, research-quality satellite data sets for selected COHMEX core days. These satellite-derived data sets will augment the special COHMEX conventional data base with high horizontal and temporal resolution information. The data sets will be examined for their usefulness in delineating important elements in the meteorological environment leading to convective activity. In addition, a limited research effort was conducted using the Cooperative Institute for Meteorological Satellite Studies (CIMSS) 4-d data assimilation system in conjunction with evaluating VISSR Atmospheric Sounder (VAS) and His-resolution Interferometer Sounder (HIS) data. The need to address the characteristics of the data types, and the problems they introduce into 4-d assimilation procedures is evident. The HIS instrument was flown aboard an ER-2 aircraft on several occasions during COHMEX. One of the flights was chosen for further study. Processed VAS soundings and COHMEX radiosonde data were also collected for this day. The case study included an evaluation of the HIS and VAS data and an impact study of the data on the assimilation system analysis.

Velden, Christopher S.↗
NASA NTRS2002

Wavelet Approximation in Data Assimilation

Estimation of the state of the atmosphere with the Kalman filter remains a distant goal because of high computational cost of evolving the error covariance for both linear and nonlinear systems. Wavelet approximation is presented here as a possible solution that efficiently compresses both global and local covariance information. We demonstrate the compression characteristics on the the error correlation field from a global two-dimensional chemical constituent assimilation, and implement an adaptive wavelet approximation scheme on the assimilation of the one-dimensional Burger's equation. In the former problem, we show that 99%, of the error correlation can be represented by just 3% of the wavelet coefficients, with good representation of localized features. In the Burger's equation assimilation, the discrete linearized equations (tangent linear model) and analysis covariance are projected onto a wavelet basis and truncated to just 6%, of the coefficients. A nearly optimal forecast is achieved and we show that errors due to truncation of the dynamics are no greater than the errors due to covariance truncation.

Tangborn, Andrew↗
NASA NTRS2003

Adjoint-Based Methods for Estimating CO2 Sources and Sinks from Atmospheric Concentration Data

Work to develop adjoint-based methods for estimating CO2 sources and sinks from atmospheric concentration data was initiated in preparation for last year's summer institute on Carbon Data Assimilation (CDAS) at the National Center for Atmospheric Research in Boulder, CO. The workshop exercises used the GSFC Parameterized Chemistry and Transport Model and its adjoint. Since the workshop, a number of simulations have been run to evaluate the performance of the model adjoint. Results from these simulations will be presented, along with an outline of challenges associated with incorporating a variety of disparate data sources, from sparse, but highly precise, surface in situ observations to less accurate, global future satellite observations.

Andrews, Arlyn E.↗