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At least 163 records · Page 9

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NASA NTRS2013

North Pacific Decadal Variability in the GEOS-5 Atmosphere-Ocean Model

This study examines the mechanisms of the Pacific decadal oscillation (PDO) in the GEOS-5 general circulation model. The model simulates a realistic PDO pattern that is resolved as the first empirical orthogonal function (EOF) of winter sea surface temperature (SST). The simulated PDO is primarily forced by Aleutian low through Ekman transport and surface fluxes, and shows a red spectrum without any preferred periodicity. This differs from the observations, which indicate a greater role of El Nino-Southern Oscillation (ENSO) forcing, and likely reflects the too short time scale of the simulated ENSO. The geostrophic transport in response to the Aleutian low is limited to the Kuroshio-Oyashio Extension, and is unlikely the main controlling factor in this model, although it reinforces the Ekman-induced SST anomalies. The delay between the Aleutian low and the PDO is relatively short (1 year) suggesting that the fast Ekman response (rather than Rossby wave propagation) sets the SST pattern immediately following an Aleutian low fluctuation. The atmospheric feedback (response to the SST) is only about 25 of the forcing and never evolves into an Aleutian low completely, instead projecting onto the North Pacific Oscillation (NPO), a meridional dipole in sea level pressure (SLP). The lack of preferred periodicity and weak atmospheric response bothindicate a coupled oscillation is an unlikely mechanism for the PDO in this model. In agreement with recent studies, the NPO is correlated with the North Pacific Gyre Oscillation (NPGO), which is another leading EOF of the North Pacific SST. A possible connection between the PDO and the NPGO is discussed.

Pacific Decadal Variability↗

NASA NTRS2013

Trends and Variations of Ocean Surface Latent Heat Flux: Results from GSSTF2c Data Set

Trends and variations of Goddard Satellite-based Surface Turbulent Fluxes (GSSTF) version 2c (GSSTF2c) latent heat flux (LHF) are examined. This version of LHF takes account of the correction in Earth incidence angle. The trend of global mean LHF for GSSTF2c is much reduced relative to GSSTF version 2b Set 1 and Set 2 for the same period 1988-2008. Temporal increase of GSSTF2c LHF in the two decades is 11.0%, in which 3.1%, 5.8%, and 2.1% are attributed to the increase in wind, the increase in sea surface saturated air humidity, and the decrease in near-surface air humidity, respectively. The first empirical orthogonal function of LHF is a conventional El Nino Southern Oscillation (ENSO) mode. However, the trends in LHF are independent of conventional ENSO phenomena. After removing ENSO signal, the pattern of LHF trends is primarily determined by the pattern of air-sea humidity difference trends.

global mean↗

NASA NTRS2014

Real-Time Onboard Global Nonlinear Aerodynamic Modeling from Flight Data

Flight test and modeling techniques were developed to accurately identify global nonlinear aerodynamic models onboard an aircraft. The techniques were developed and demonstrated during piloted flight testing of an Aermacchi MB-326M Impala jet aircraft. Advanced piloting techniques and nonlinear modeling techniques based on fuzzy logic and multivariate orthogonal function methods were implemented with efficient onboard calculations and flight operations to achieve real-time maneuver monitoring and analysis, and near-real-time global nonlinear aerodynamic modeling and prediction validation testing in flight. Results demonstrated that global nonlinear aerodynamic models for a large portion of the flight envelope were identified rapidly and accurately using piloted flight test maneuvers during a single flight, with the final identified and validated models available before the aircraft landed.

Brandon, Jay M.↗

NASA NTRS2016

North Pacific Decadal Variability: Insights from a Biennial ENSO Environment

This study examines the mechanisms of the Pacific decadal oscillation (PDO) in the NASA GEOS-5 general circulation model (GCM). Similar to several other state-of-the-art GCMs, the El Niño-Southern Oscillation (ENSO) simulated by the GEOS-5 has a strong biennial periodicity. Since this is a model bias that precludes a strong role of ENSO, it provides a unique environment to assess the other leading mechanisms of North Pacific decadal variability. Despite the biennial ENSO periodicity, the model simulates a realistic PDO pattern in the North Pacific that is resolved as the first empirical orthogonal function (EOF) of winter mean sea surface temperature (SST). The spectrum of the PDO indicates no preferred periodicity. The SST anomalies associated with the PDO, particularly its basin wide structure, are primarily forced by the Aleutian low through Ekman transport. The slow geostrophic transport in association with the meridional adjustment of the subtropical gyre is limited to a narrow region in the Kuroshio-Oyashio extension, north of 40degN. The atmosphere's response to the PDO, while weak, projects onto the North Pacific Oscillation (NPO), a meridional dipole in sea level pressure. Both the lack of preferred periodicity and the weak atmospheric response indicate an air-sea coupled oscillation is an unlikely mechanism in this model. In agreement with recent studies, the NPO is correlated with the North Pacific Gyre Oscillation, which is another leading EOF of North Pacific SST variability. The results emphasize the role of atmospheric variability in the North Pacific SST modes, thereby bringing into question the potential for their predictability.

GCM↗

NASA NTRS2017

Efficient Testing Combining Design of Experiment and Learn-to-Fly Strategies

Rapid modeling and efficient testing methods are important in a number of aerospace applications. In this study efficient testing strategies were evaluated in a wind tunnel test environment and combined to suggest a promising approach for both ground-based and flight-based experiments. Benefits of using Design of Experiment techniques, well established in scientific, military, and manufacturing applications are evaluated in combination with newly developing methods for global nonlinear modeling. The nonlinear modeling methods, referred to as Learn-to-Fly methods, utilize fuzzy logic and multivariate orthogonal function techniques that have been successfully demonstrated in flight test. The blended approach presented has a focus on experiment design and identifies a sequential testing process with clearly defined completion metrics that produce increased testing efficiency.

Murphy, Patrick C.↗

NASA NTRS2017

Climate Controls on Tree Growth in the Western Mediterranean

The first large-scale network of tree-ring chronologies from the western Mediterranean (WM; 32 deg N-43 deg N, 10 deg W-17 deg E) is described and analyzed to identify the seasonal climatic signal in indices of annual ring width. Correlation and rotated empirical orthogonal function analyses are applied to 85 tree-ring series and corresponding gridded climate data to assess the climate signal embedded in the network. Chronologies range in length from 80 to 1129 years. Monthly correlations and partial correlations show overall positive associations for Pinus halepensis (PIHA) and Cedrus atlantica (CDAT) with winter (December-February) and spring (March-May) precipitation across this network. In both seasons, the precipitation correlation with PIHA is stronger, while CDAT chronologies tend to be longer. A combination of positive correlations between growth and winter-summer precipitation and negative partial correlations with growing season temperatures suggests that chronologies in at least part of the network reflect soil moisture and the integrated effects of precipitation and evapotranspiration signal. The range of climate response observed across this network reflects a combination of both species and geographic influences. Western Moroccan chronologies have the strongest association with the North Atlantic Oscillation.

chronology development↗

NASA NTRS2016

Degree of Ice Particle Surface Roughness Inferred from Polarimetric Observations

The degree of surface roughness of ice particles within thick, cold ice clouds is inferred from multidirectional, multi-spectral satellite polarimetric observations over oceans, assuming a column-aggregate particle habit. An improved roughness inference scheme is employed that provides a more noise-resilient roughness estimate than the conventional best-fit approach. The improvements include the introduction of a quantitative roughness parameter based on empirical orthogonal function analysis and proper treatment of polarization due to atmospheric scattering above clouds. A global 1-month data sample supports the use of a severely roughened ice habit to simulate the polarized reflectivity associated with ice clouds over ocean. The density distribution of the roughness parameter inferred from the global 1- month data sample and further analyses of a few case studies demonstrate the significant variability of ice cloud single-scattering properties. However, the present theoretical results do not agree with observations in the tropics. In the extra-tropics, the roughness parameter is inferred but 74% of the sample is out of the expected parameter range. Potential improvements are discussed to enhance the depiction of the natural variability on a global scale.

surface↗

NASA NTRS2017

An Investigation of Dust Storms Observed with the Mars Color Imager

Daily global imaging by the Mars Color Imager (MARCI) continues the record of the Mars Orbiter Camera (MOC) and has allowed creation of a long-duration record of Martian dust storms. We observe dust storms over the first two Mars years of the MARCI record, including tracking individual storms over multiple sols, as well as tracking the growth and recession of the seasonal polar caps. Using the combined 6 Mars year record of textured dust storms (storms with visible textures on the observed dust cloud tops), we study the relationship between textured dust storm activity and meteorology (as simulated by the MarsWRF general circulation model) and surface properties. We find that textured dust storms preferentially occur in places and seasons with above average surface wind stress. Textured dust storm occurrence also has a modest linear anti-correlation with surface albedo (0.43) and topography (0.40). Lastly, we perform an empirical orthogonal function (EOF) analysis on the distribution of occurrence of textured dust storms and find that over 50 of the variance in textured dust storm activity can be explained by two EOF modes. We associate the first EOF mode with cap-edge storms just before Ls = 180deg and the second EOF mode with flushing dust storms that occur from Ls = 180-210deg and again near Ls = 320deg.

Guzewich, Scott D.↗

NASA NTRS2017

Large-Scale Circulation and Climate Variability

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

Perlwitz, J.↗

NASA NTRS2018

Recovery of the Disrupted Quasi-Biennial Oscillation

There occurred a unique and significant disruption of the Quasi-Biennial Oscillation (QBO) during the Northern Hemisphere winter of 2015-16. Here we document the return of the QBO to its normal downward phase speed and period based on Singapore soundings, MERRA-2 re-analysis (Modern Era Retrospective Reanalysis for Research and Applications), and a simple QBO model. Daily averaged zonal winds from 100-10 hPa are used to characterized the behavior of the QBO's amplitude and phase as seen in the first two EOFs (Empirical Orthogonal Functions). These EOFs capture the QBO structure and evolution during the pre-disruption, disruption, and post-disruption times. Results show that the amplitude and phase returned to normal by June 2016, however the post-disruption QBO phase was delayed relative to the pre-disruption phase by four tenths of a QBO cycle (~11 months). A rapid, seasonal, phase shift of this magnitude is shown to be unique in the QBO observational record.

Coy, Lawrence↗

NASA NTRS2019

Long-Term, Non-Anthropogenic Groundwater Storage Changes Simulated by Three Global-Scale Hydrological Models

This study examined long-term, natural (i.e., excluding anthropogenic impacts) variability of groundwater storage worldwide. Groundwater storage changes were estimated by forcing three global-scale hydrological models with three 50+ year meteorological datasets. Evaluation using in situ groundwater observations from the U.S. and terrestrial water storage derived from the Gravity Recovery and Climate Experiment (GRACE) satellites showed that these models reasonably represented inter-annual variability of water storage, as indicated by correlations greater than 0.5 in most regions. Empirical orthogonal function analysis revealed influences of the El Niño Southern Oscillation (ENSO) on global groundwater storage. Simulated groundwater storage, including its global average, exhibited trends generally consistent with that of precipitation. Global total (natural) groundwater storage decreased over the past 5-7 decades with modeled rates ranging from 0.01 to 2.18 mm year-1. This large range can be attributed in part to groundwater’s low frequency (inter-decadal) variability, which complicates identification of real long-term trends even within a 50+ year time series. Results indicate that non-anthropogenic variability in groundwater storage is substantial, making knowledge of it fundamental to quantifying direct human impacts on groundwater storage.

Groundwater storage↗

NASA NTRS2011

TPSAS-NF1676L-12839-DND

Hyper-spectral remote sensors, such as Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI), provides top of atmospheric radiances with high information content on atmospheric and surface properties. In order to analyze these data in real time, fast, and accurate forward and inverse models are needed. We will describe a method of simultaneously retrieving atmospheric temperature, moisture, cloud, and surface properties using all available spectral channels without sacrificing computational speed. The method has been successfully applied to AIRS, IASI, and NAST-I data. By applying the same method to the current and future hyperspectral sounders, the derived products will have less errors due to biases introduced by different retrieval methods. We have compared the retrieved products to radiosondes, aircraft measurements and other validation dataset. Simulations have done to quantify retrieval errors associated with the retrievals. The essence of the method is to convert channel radiance spectra into super-channels by an Empirical Orthogonal Function (EOF) transformation. A Principal Component-based Radiative Transfer Model (PCRTM) developed at NASA Langley Research Center is used to calculate both the super-channel magnitudes and derivatives with respect to atmospheric profiles and other properties. The inversion algorithm is based on a non-linear Levenberg-Marquardt method with climatology covariance matrices and a priori information as constraints. One advantage of this approach is that it uses all information content from the hyper-spectral data so that the retrieval is less sensitive to instrument noise and eliminates the need for selecting a subset of the channels. The PCRTM forward model has also been used to performance end-to-end sensor performance simulations of the Climate Absolute Radiance and Refractivity Observatory (CLARREO).

Xu Liu↗

NASA NTRS2014

TPSAS-NF1676L-18357-DND

High-spectral resolution measurements (in the IR region) from space born infrared sensors can provide sufficient spectral information about cloud properties like cloud top pressure, cloud particle size and cloud optical thickness. Empirical orthogonal function (EOF) based regression scheme was used to retrieve cloud properties along with atmospheric state profiles. A channel based physical inversion scheme was also tried on cloud-contaminated radiances to improve retrieval accuracy achieved by regression scheme. Recently developed principle component (PC) based physical retrieval algorithm utilized the EOF transformation to compress both hyperspectral radiance spectra and atmospherical profiles into PC scores to greatly boost the computational speed while maintaining the information content. The accuracy of the (PC) based radiation transfer model (PCRTM) to simulate top-of the atmosphere(TOA) high-spectral resolution radiance spectra for both clear and cloudy sky conditions has been well tested by comparing with the other line-by-line radiation transfer model and using the observation data. The application of the PCRTM based physical inversion method on simulated IASI radiance under 'cloudy' conditions will be a good integrity test for the new algorithm.

X Liu↗

NASA NTRS2019

Long-Term, Non-Anthropogenic Groundwater Storage Changes Simulated by Three Global-Scale Hydrological Models

This study examined long-term, natural (i.e., excluding anthropogenic impacts) variability of groundwater storage worldwide. Groundwater storage changes were estimated by forcing three global-scale hydrological models with three 50+ year meteorological datasets. evaluation using in situ groundwater observations from the U.S. and terrestrial water storage derived from the Gravity Recovery and Climate experiment (GRACe) satellites showed that these models reasonably represented inter-annual variability of water storage, as indicated by correlations greater than 0.5 in most regions. Empirical orthogonal function analysis revealed influences of the El Niño Southern Oscillation (ENSO) on global groundwater storage. simulated groundwater storage, including its global average, exhibited trends generally consistent with that of precipitation. Global total (natural) groundwater storage decreased over the past 5–7 decades with modeled rates ranging from 0.01 to 2.18 mm year−1. this large range can be attributed in part to groundwater’s low frequency (inter-decadal) variability, which complicates identification of real long-term trends even within a 50+ year time series. Results indicate that non-anthropogenic variability in groundwater storage is substantial, making knowledge of it fundamental to quantifying direct human impacts on groundwater storage.

Bailing Li↗

NASA NTRS2020

Interannual Variations of TOA Albedo over the Arctic, Antarctic and Tibetan Plateau in 2000–2019

Recent changes in Earth’s climate system have significantly affected the radiation budget and its year-to-year variations at top of the atmosphere (TOA). Observing high-latitude TOA fluxes is still challenging from space, because spatial inhomogeneity of surface/atmospheric radiative processes and spectral variability can reflect sunlight very differently. In this study we analyze the 20-year TOA flux and albedo data from CERES and MISR over the Arctic, the Antarctic, and Tibetan Plateau (TP), and found overall great consistency in the TOA albedo trend and interannual variations. The observations reveal a lagged correlation between the Arctic and subarctic albedo fluctuations. The observed year-to-year variations are further used to evaluate the reanalysis data, which exhibit substantial shortcomings in representing the polar TOA flux variability. The observed Arctic flux variations are highly correlated with cloud fraction (CF), except in the regions where CF > 90% or where the surface is covered by ice. An empirical orthogonal function (EOF) analysis shows that the first five EOFs can account for ~50% of the Arctic TOA variance, whereas the correlation with climate indices suggests that Sea Ice Extent (SIE), North Atlantic Oscillation (NAO) and 55°N–65°N cloudiness are the most influential processes in driving the TOA flux variabilities.

interannual variations↗

NASA NTRS2020

Decadal Changes in the Interannual Variability of Heat Waves in East Asia Caused by Atmospheric Teleconnection Changes

The heat wave in East Asia is examined by using empirical orthogonal function analysis to isolate dominant heat-wave patterns in the ground-based temperature observations over the Korean Peninsula and China and related large-scale atmospheric circulations obtained from the National Centers for Environmental Prediction–National Center for Atmospheric Research Reanalysis 1 during 1973–2012. This study focuses particularly on the interannual variability of heat waves and its decadal change. The analysis identifies two major atmospheric teleconnection patterns playing an important role in developing typical heat-wave patterns in East Asia—the Scandinavian (SCAND) and the circumglobal teleconnection (CGT) patterns, which exhibit a significant decadal change in the interannual variability in the mid-1990s. Before the mid-1990s, heat-wave occurrence was closely related to the CGT pattern, whereas the SCAND pattern is more crucial to explain heat-wave variability in the recent period. The stationary wave model experiments suggest an intensification of the SCAND pattern in the recent period driven by an increase in land–atmosphere interaction over Eurasia and decadal change in the dominant heat-wave patterns in East Asia.

heat wave patterns↗

NASA NTRS2021

Reduced El NiñO Variability in the Mid-Pliocene According to the Pliomip2 Ensemble

The mid-Pliocene warm period (3.264–3.025 Ma) is the most recent geological period during which atmospheric CO 2 levels were similar to recent historical values (∼400 ppm). Several proxy reconstructions for the mid-Pliocene show highly reduced zonal sea surface temperature (SST) gradients in the tropical Pacific Ocean, indicating an El Niño-like mean state. However, past modelling studies do not show these highly reduced gradients. Efforts to understand mid-Pliocene climate dynamics have led to the Pliocene Model Intercomparison Project (PlioMIP). Results from the first phase (PlioMIP1) showed clear El Niño variability (albeit significantly reduced) and did not show the greatly reduced time-mean zonal SST gradient suggested by some of the proxies. In this work, we study El Niño–Southern Oscillation (ENSO) variability in the PlioMIP2 ensemble, which consists of additional global coupled climate models and updated boundary conditions compared to PlioMIP1. We quantify ENSO amplitude, period, spatial structure and “flavour”, as well as the tropical Pacific annual mean state in mid-Pliocene and pre-industrial simulations. Results show a reduced ENSO amplitude in the model-ensemble mean (−24 %) with respect to the pre-industrial, with 15 out of 17 individual models showing such a reduction. Furthermore, the spectral power of this variability considerably decreases in the 3–4-year band. The spatial structure of the dominant empirical orthogonal function shows no particular change in the patterns of tropical Pacific variability in the model-ensemble mean, compared to the pre-industrial. Although the time-mean zonal SST gradient in the equatorial Pacific decreases for 14 out of 17 models (0.2 ∘C reduction in the ensemble mean), there does not seem to be a correlation with the decrease in ENSO amplitude. The models showing the most “El Niño-like” mean state changes show a similar ENSO amplitude to that in the pre-industrial reference, while models showing more “La Niña-like” mean state changes generally show a large reduction in ENSO variability. The PlioMIP2 results show a reasonable agreement with both time-mean proxies indicating a reduced zonal SST gradient and reconstructions indicating a reduced, or similar, ENSO variability.

mid-Pliocene warm period↗

NASA NTRSDate not supplied

Aero-Propulsive Modeling for eVTOL Aircraft Using Wind Tunnel Testing with Multisine Inputs

A novel approach for modeling the aero-propulsive characteristics of an electric vertical takeoff and landing (eVTOL) aircraft was developed and demonstrated in wind tunnel testing. The approach was applied to the NASA LA-8 tandem tilt-wing eVTOL aircraft, using an efficient, hybrid experiment design composed of a static I-optimal response surface design for slowly-varying test variables, and dynamic orthogonal phase-optimized multisine excitations for the control surfaces and electric propulsors. Both the static and dynamic experiment designs were executed simultaneously to collect informative data for model identification. Statistically-weighted multivariate orthogonal function modeling was used to combine local modeling results computed in the frequency domain using data collected with dynamic excitations operating on the control effectors to form an aggregate aero-propulsive model. The final identified model exhibited good predictive capability when compared to validation data acquired separately from the data used to develop the model. The required test time using these new techniques was reduced by at least a factor of five compared to previous static wind tunnel testing for the LA-8 aircraft, while providing more informative data, greater parameterization flexibility, and high-quality models.

system identification↗