Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “climate dynamics”

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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Pervasive ice sheet mass loss reflects competing ocean and atmosphere processes

Quantifying changes in Earth’s ice sheets and identifying the climate drivers are central to improving sea level projections. We provide unified estimates of grounded and floating ice mass change from 2003 to 2019 using NASA’s Ice, Cloud and land Elevation Satellite (ICESat) and ICESat-2 satellite laser altimetry. Our data reveal patterns likely linked to competing climate processes: Ice loss from coastal Greenland (increased surface melt), Antarctic ice shelves (increased ocean melting), and Greenland and Antarctic outlet glaciers (dynamic response to ocean melting) was partially compensated by mass gains over ice sheet interiors (increased snow accumulation). Losses outpaced gains, with grounded-ice loss from Greenland (200 billion tonnes per year) and Antarctica (118 billion tonnes per year) contributing 14 millimeters to sea level. Mass lost from West Antarctica’s ice shelves accounted for more than 30% of that region’s total.

Ben Smith↗
NASA NTRSDate not supplied

Parameterization of Vertical Cloud Distribution from C3M and MERRA Data Using ML Method

Clouds play a key role in regulating the hydrological cycle and the Earth's radiative energy budget. However, global climate models (GCMs) with a horizontal grid spacing on the order of 100 km have limitations in representing sub-grid cloud dynamics with spatial scales on the order of 1 km, leading to potential uncertainties in cloud radiative feedback on the global scale. In our research, we will leverage the capabilities of Deep Machine Learning (DML) methods to construct parameterizations of sub-grid volumetric cloud fraction (VCF), which is the frequency of occurrence on a grid volume accumulated in the horizontal and vertical directions. Our investigation delves into the intricate relationship between VCF obtained from the NASA CALIPSO-CloudSat-CERES-MODIS (CCCM) satellite observation data and 3-D MERRA-2 reanalysis meteorological profiling data (e.g., wind, relative humidity, temperature). Through a comprehensive one-year data training utilizing the Sequence to Sequence DML method, we have successfully disentangled the complicated cloud formation dynamics across diverse meteorological conditions through a day-to-day analysis framework. Preliminary findings reveal promising statistical agreements in geographical and vertical distributions and seasonal variations of volumetric cloud fraction between ML prediction and satellite measurements. These results underscore the aptitude of our DML model to discern underlying cloud physical processes and accurately represent sub-grid cloud formation dynamics. Additionally, we have also employed trained neural network to analyze uncertainties arising from errors in meteorological data, further enhancing the robustness of our VCF parameterization.

Shan Zeng↗
NASA NTRS2018

TPSAS-NF1676L-32008-DND

Thermosphere climate is controlled in part by cooling to space driven by infrared radiation, primarily from nitric oxide (NO, 5.3μm) and carbon dioxide (CO2, 15μm). The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on the Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics (TIMED) satellite has been measuring the vertical distribution of infrared radiation emitted by these species (and others) for nearly 17 years-–more than 6000 days. This data set spans much of Solar Cycle (SC) 23 and all of SC 24 to date. A thermosphere climate index (TCI) has been derived by noting the correlation between 60-day running averages of NO cooling power and three long-term solar and geomagnetic indexes: F10.7 cm solar radio flux, the Ap index of geoeffective solar activity, and the disturbance storm time (Dst) index. A multiple linear regression (MLR) fit of these three parameters to the NO cooling rate over the SABER mission has a better than 0.98 correlation. Applying the MLR constant and coefficients from that fit provides a good estimate of thermospheric cooling back to 1947, the extent of the data available for all three indexes. We examined the percentile distribution of the TCI in quintiles over the five complete solar cycles, and assigned.

Linda Hunt↗
NASA NTRS2021

Evolution of Tropical Cyclone Properties Across the Development Cycle of the GISS-E3 Global Climate Model

The next-generation global climate model from the NASA Goddard Institute for Space Studies, GISS-E3, contains many improvements to resolution and physics that allow for improved representation of tropical cyclones (TCs) in the model. This study examines the properties of TCs in two different versions of E3 at different points in its development cycle, run for 20 years at 0.5 degree resolution, and compares these TCs with observations, the previous generation GISS model, E2, and other climate models. E3 shares many TC biases common to global climate models, such as having too few tropical cyclones, but is much improved from E2. E3 produces strong enough TCs that observation-based wind speed thresholds can now be used to detect and track them, and some storms now reach hurricane intensity; neither of these was true of E2. Model development between the first and second versions of E3 further increased the number and intensity of TCs and reduced TC count biases globally and in most regions. One-year sensitivity tests to changes in various microphysical and dynamical tuning parameters are also examined. Increasing the entrainment rate for the more strongly-entraining plume in the convection scheme increases the number of TCs (though also affecting other climate variables, and in some cases increasing biases). Variations in divergence damping did not have a strong effect on simulated TC properties, contrary to expectations based on previous studies. Overall, the improvements in E3 make it more credible for studies of TC activity and its relationship to climate.

Tropical Cyclones↗
NASA NTRS2016

Climate Analytics as a Service

Exascale computing, big data, and cloud computing are driving the evolution of large-scale information systems toward a model of data-proximal analysis. In response, we are developing a concept of climate analytics as a service (CAaaS) that represents a convergence of data analytics and archive management. With this approach, high-performance compute-storage implemented as an analytic system is part of a dynamic archive comprising both static and computationally realized objects. It is a system whose capabilities are framed as behaviors over a static data collection, but where queries cause results to be created, not found and retrieved. Those results can be the product of a complex analysis, but, importantly, they also can be tailored responses to the simplest of requests. NASA's MERRA Analytic Service and associated Climate Data Services API provide a real-world example of climate analytics delivered as a service in this way. Our experiences reveal several advantages to this approach, not the least of which is orders-of-magnitude time reduction in the data assembly task common to many scientific workflows.

big data↗
NASA NTRS2018

Investigating Extreme Events in the NASA GEOS Multiscale Modeling System

Advances in computing capabilities and scientific development have come together to evolve general circulation models into multi-scale Earth system modeling tools. The Goddard Earth Observing System (GEOS) model is one such example of this evolution. The GEOS model is driven by the finite-volume cubed-sphere (FV3) non-hydrostatic dynamical core. Surrounding FV3 is a scale-aware physics package and data assimilation capability permitting multi-scale application of GEOS for sub-seasonal to seasonal climate prediction, medium range weather prediction, and global mesoscale modeling at convection allowing resolutions. GEOS also includes a comprehensive chemistry package representing a range of capabilities from basic chemistry and interactve aerosols and gaseous species, to carbon emissions and uptake, and complex ozone photochemistry. In this study, we apply the GEOS model to study the fidelity of these processes with increasing horizontal resolution and scale-aware processes in GEOS on extreme events. The GEOS model is run for 40-days beginning in August 2016 at three uniform global resolutions of 13-km (c768), 6-km (c1536) and 3-km (c3072) with 72 vertical levels up to 0.01mb. The model physics use the Grell-Freitas scale-aware convection scheme to dynamically reduce the role of parameterized deep convection as resolved scale processes in the model take over at higher resolutions. We will include high-resolution global emissions and fluxes of aerosols and carbon downscaled from recent satellite observations. We will compare these simulations with reanalyses and observations, focusing on rainfall, clouds and radiative forcing at hourly to monthly timescales. We will closely examine the probability distribution of precipitation intensities and radiative properties of clouds on a daily time scale. In addition, we will focus on extreme events, in particular the diurnal cycle of convection over the US and the frequency and physical nature of organized convection and heavy rain events across the globe.

Putman, William↗
NASA NTRS2020

Linkage among Ice Crystal Microphysics, Mesoscale Dynamics and Cloud and Precipitation Structures Revealed By Collocated Microwave Radiometer and Multi-Frequency Radar Observations

Ice clouds and falling snow are ubiquitous globally and play important roles in the Earth’s radiation budget and precipitation processes. Ice particle microphysical properties (e.g., size, habit and orientation) are not only influenced by ambient environment’s dynamic and thermodynamic conditions, but also intimately connect to the cloud radiative effects and particle fall speeds, which therefore impact up to the future climate projection and down to the details of the surface precipitation (e.g., onset-time, location, type and strength). Our previous work revealed that high-frequency Polarimetric radiance Difference (PD) from passive microwave sensors is a good indicator of the bulk aspect ratio of horizontally oriented ice particles that are often occur inside anvil clouds and/or stratiform precipitations. In this current work, we further investigate the dynamic/thermodynamic mechanisms and cloud/precipitation structures associated with ice-phase microphysics corresponding to different PD signals. In order to do so, collocated CloudSat radar (W-band) and Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM-DPR, Ku/Ka bands) observations as well as European Centre for Medium-Range Weather Forecasts (ECMWF) atmosphere background profiles are grouped according to the magnitude of PD for only stratiform precipitation and/or anvil cloud scenes. We found that horizontally-oriented snow aggregates or large snow particles are likely the major contributor to the high-PD signals at 166 GHz, while low-PD magnitudes can be attributed to small cloud ice, randomly oriented snow aggregates, riming snow or super-cooled water. Further, high (low) PD scenes are found to be associated with stronger (weaker) wind shear and higher (lower) ambient humidity, both of which help promote (prohibit) the growth of frozen particles and the organization of convective systems. An ensemble of squall line cases is studied at the end to demonstrate that the PD asymmetry in the leading and trailing edges of the deep convection line is closely tied to the anvil cloud and stratiform precipitation layers respectively, suggesting the potential usefulness of PD as a proxy of stratiform/convective precipitation flag, as well as a proxy of convection life stage.

Ice crystal microphysics↗
NASA NTRS1994

The Arctic Boundary Layer Expedition (ABLE-3B): July - August 1990

The Arctic Boundary Layer Expedition (ABLE) 3B used data from ground-based, aircraft, and satellite platforms to characterize the chemistry and dynamics of the troposphere in subarctic and Arctic regions of midcontinent and eastern Canada during July - August 1990. This paper reports the experimental design for ABLE 3B and a brief overview of results. The detailed results are presented in a series of papers in this issue. The chemical composition of the atmospheric mixed layer over remote tundra, boreal wetland, and forested environments was influenced by emissions of CH4 and nonmethane hydrocarbons from biogenic sources, emissions of gases and aerosols from local biomass burning, and transport of pollutants into the study areas from urban/industrial sources. Minimum concentrations of both trace gas and aerosol species in boundary layer air were associated with Arctic source areas. In the free troposphere the biospheric influence was undetectable, and major sources of chemical variability were related to long-range transport of pollutants into the study areas from biomass burning and industrial sources in Alaska and the Great Lakes regions, respectively. Minimum concentrations of both trace gas and aerosol species in the free troposphere were associated with a persistent, widespread air mass which both chemistry and air mass trajectory analyses suggested had originated in the tropical Pacific. Subsidence of air from the upper troposphere and lower stratosphere frequently enhanced ozone and influenced other trace gas and aerosol species at midtropospheric altitudes. The North American Arctic is a complex dynamical and chemical environment with considerable spatial and temporal variability in aerosol and trace gas concentrations. The use of atmospheric chemical indicators for climate change detection will require a much more comprehensive Arctic monitoring program than currently exists.

Harriss, R. C.↗
NASA NTRS2000

Climatology of the Finite-Volume CCM and Sensitivity Studies

A new model has been developed in the Data Assimilation Office at NASA Goddard Space Flight Center. It is intended for data assimilation and general circulation modeling, including representations of radiatively active trace gases such as stratospheric ozone. The model is based on the flux-form semi-Lagrangian' dynamical core, developed by Lin and Rood. In collaboration with the National Center for Atmospheric Research, the physical parametrization package from the Community Climate model, Version 3, has been included. This paper will discuss the climatology of a multi-year integration of the model, with observed boundary conditions (sea-surface temperature, sea ice, and incoming solar radiation). The standard model version has a resolution of 2.5 degrees longitude, 2 degrees latitude and has 55 levels between the surface and 80km. The mean climate and interannual variability of this model will be discussed, with emphasis on the middle atmosphere. The sensitivity to horizontal resolution will be examined, as will the impact of increasing and decreasing the vertical resolution. Changes which differ significantly from the interannual variations of the control run will be highlighted. Impacts of using long-term mean boundary conditions or values which vary from year to year will be discussed. Changes in the tropospheric circulation induced by lowering the upper boundary of the model will be discussed. The emphasis of the paper is on the climatology of the middle atmosphere and its impacts on the troposphere, with particular attention given to the climatologically important region near the tropopause.

Pawson, Steven↗
NASA NTRS2003

SHADOZ (Southern Hemisphere Additional Ozonesondes): A Tropical Ozonesonde-Radiosonde Network for the Atmospheric Community

A lack of sounding data has limited the accuracy of ozone satellite retrievals in the tropics and our understanding of chemical-dynamical interactions in a region strongly influenced by natural variability and anthropogenic activity. In 1998, NASA s Goddard Space Flight Center, NOAA's Climate Monitoring and Diagnostics Laboratory (CMDL) and a team of international sponsors established the SHADOZ (Southern Hemisphere ADditional OZonesondes) project to address the gap in tropical ozone soundings. SHADOZ augments launches at selected sites and provides a public archive of ozonesonde and radiosonde data from twelve tropical and subtropical stations at http://croc.gsfc.nasa.gov/shadoz. Instrumentation, data and a summary of the first scientific findings from SHADOZ are presented.

Thompson, Anne M.↗
NASA NTRS2016

The Nexus for Exoplanet System Science

NExSS is a research coordination network dedicated to the study of planetary habitability. A NASA cross-division initiative bringing astrophysicists, planetary scientists, Earth scientists, and heliophysicists together to bring a systems science approach to this problem. NExSS's goals being to investigate the diversity of planets, understanding how planet history, geology, and climate interact to create the conditions for life. Also, to put planets into an architectural context as stellar systems built over time by dynamical processes and sculpted by stars. Use experience from solar system (including Earth) history to identify where habitable niches are most likely to occur and which planets are most likely to be habitable. Leverage NASA investments in research and missions to accelerate discovery and characterization of potential life-bearing worlds.

coordination↗
NASA NTRS1989

Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series

Two dimensions of a dynamical system given by experimental time series are distinguished. Statistical dimension gives a theoretical upper bound for the minimal number of degrees of freedom required to describe the attractor up to the accuracy of the data, taking into account sampling and noise problems. The dynamical dimension is the intrinsic dimension of the attractor and does not depend on the quality of the data. Singular Spectrum Analysis (SSA) provides estimates of the statistical dimension. SSA also describes the main physical phenomena reflected by the data. It gives adaptive spectral filters associated with the dominant oscillations of the system and clarifies the noise characteristics of the data. SSA is applied to four paleoclimatic records. The principal climatic oscillations and the regime changes in their amplitude are detected. About 10 degrees of freedom are statistically significant in the data. Large noise and insufficient sample length do not allow reliable estimates of the dynamical dimension.

Vautard, R.↗
NASA NTRS2017

Comparing Proxy and Model Estimates of Hydroclimate Variability and Change over the Common Era

Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited because of a paucity of modern instrumental observations that are distributed unevenly across the globe and only span parts of the 20th and 21st centuries. Such data coverage is insufficient for characterizing hydroclimate and its associated dynamics because of its multidecadal to centennial variability and highly regionalized spatial signature. High-resolution (seasonal to decadal) hydroclimatic proxies that span all or parts of the Common Era (CE) and paleoclimate simulations from climate models are therefore important tools for augmenting our understanding of hydroclimate variability. In particular, the comparison of the two sources of information is critical for addressing the uncertainties and limitations of both while enriching each of their interpretations. We review the principal proxy data available for hydroclimatic reconstructions over the CE and highlight the contemporary understanding of how these proxies are interpreted as hydroclimate indicators. We also review the available last-millennium simulations from fully coupled climate models and discuss several outstanding challenges associated with simulating hydroclimate variability and change over the CE. A specific review of simulated hydroclimatic changes forced by volcanic events is provided, as is a discussion of expected improvements in estimated radiative forcings, models, and their implementation in the future. Our review of hydroclimatic proxies and last-millennium model simulations is used as the basis for articulating a variety of considerations and best practices for how to perform proxy-model comparisons of CE hydroclimate. This discussion provides a framework for how best to evaluate hydroclimate variability and its associated dynamics using these comparisons and how they can better inform interpretations of both proxy data and model simulations.We subsequently explore means of using proxy-model comparisons to better constrain and characterize future hydroclimate risks. This is explored specifically in the context of several examples that demonstrate how proxy-model comparisons can be used to quantitatively constrain future hydroclimatic risks as estimated from climate model projections.

Common Era↗
NASA NTRSDate not supplied

A Radiometric Consistent Spectral Fingerprinting Algorithm for Continuity Products of Hyperspectral Sounders

A radiometric consistent climate fingerprinting methodology has been developed to derive long-term temperature, water vapor, cloud, trace gases, and surface skin temperature anomaly time series from the hyper-spectral sounder measurements of multiple platforms. The spectral fingerprinting methodology requires the use of radiative kernels that are radiometrically consistent with observations. Radiative kernels are built using space-time averaged Jacobians that are physically retrieved from observations under all sky conditions. The physical retrieval algorithm uses the Principal Component based Radiative Transfer Model (PCRTM) for the forward simulation. The incorporation of multiple scattering simulation in PCRTM allows the direct radiative relationship between single field-of-view (FOV) radiance observations and corresponding thermal dynamic variables including cloud properties to be established. Therefore, radiance ?closure? can be achieved under all-sky conditions by the fingerprinting scheme. This methodology has been used to derive climate anomalies from the space-time averaged spectra of AIRS/AMSU and CrIS/ATMS. The use of a consistent fingerprinting scheme provides an effective mean of generating continuity product by merging observations from different platforms and therefore facilitating the long-term climate trend study.

Wan Wu↗
NASA NTRS2012

Multi-Satellite Synergy for Aerosol Analysis in the Asian Monsoon Region

Atmospheric aerosols represent one of the greatest uncertainties in environmental and climate research, particularly in tropical monsoon regions such as the Southeast Asian regions, where significant contributions from a variety of aerosol sources and types is complicated by unstable atmospheric dynamics. Although aerosols are now routinely retrieved from multiple satellite Sensors, in trying to answer important science questions about aerosol distribution, properties, and impacts, researchers often rely on retrievals from only one or two sensors, thereby running the risk of incurring biases due to sensor/algorithm peculiarities. We are conducting detailed studies of aerosol retrieval uncertainties from various satellite sensors (including Terra-/ Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, SeaWiFS, and Calipso-CALIOP), based on the collocation of these data products over AERONET and other important ground stations, within the online Multi-sensor Aerosol Products Sampling System (MAPSS) framework that was developed recently. Such analyses are aimed at developing a synthesis of results that can be utilized in building reliable unified aerosol information and climate data records from multiple satellite measurements. In this presentation, we will show preliminary results of. an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors, particularly focused on the Asian Monsoon region, along with some comparisons from the African Monsoon region.

Ichoku, Charles↗
NASA NTRS2012

The Race To Understand A Changing Planet

The Earth's climate is changing rapidly. In some respects, the rate of change is outpacing the predictions of only a few years ago. The challenge to Earth Science is to put forward credible projections of possible future climates so that the public and policy makers can make science-based decisions about energy development strategies. Models, observations and experiments all play strong roles in improving knowledge and increasing confidence in our predictions. The models have progressed from simple, coarse-resolution descriptions of atmospheric dynamics and physics only twenty years ago, to full-up Earth System models (ESMs) that include complete descriptions of the oceans and cryosphere. It has been convincingly argued that such complexity - the construction of realistic "toy" Earth's - is necessary to address the complex processes involved in climate change, including not only the physical atmosphere, oceans and cryosphere, but also the carbon cycle - both its natural and anthropogenic components - and the biosphere. Observations, particularly satellite observations, have more or less kept pace with the demands of the modelers, being able to observe progressively more and different facets of the Earth system, but the global satellite fleet is in need of an overhaul very soon. Lastly, field experiments and process studies confront the models with facts and allow us to develop more sophisticated and accurate satellite data algorithms. The challenges facing our relatively small Earth and planetary science communities are considerable and the stakes are significant. The stakeholders, now numbering 7 billion but soon to be 10 billion, will be relying on our results and capabilitie's to guide them into the future.

Sellers, Piers J.↗
NASA NTRS2015

On the Reconstruction of Palaeo-Ice Sheets: Recent Advances and Future Challenges

Reconstructing the growth and decay of palaeo-ice sheets is critical to understanding mechanisms of global climate change and associated sea-level fluctuations in the past, present and future. The significance of palaeo-ice sheets is further underlined by the broad range of disciplines concerned with reconstructing their behaviour, many of which have undergone a rapid expansion since the 1980s. In particular, there has been a major increase in the size and qualitative diversity of empirical data used to reconstruct and date ice sheets, and major improvements in our ability to simulate their dynamics in numerical ice sheet models. These developments have made it increasingly necessary to forge interdisciplinary links between sub-disciplines and to link numerical modelling with observations and dating of proxy records. The aim of this paper is to evaluate recent developments in the methods used to reconstruct ice sheets and outline some key challenges that remain, with an emphasis on how future work might integrate terrestrial and marine evidence together with numerical modelling. Our focus is on pan-ice sheet reconstructions of the last deglaciation, but regional case studies are used to illustrate methodological achievements, challenges and opportunities. Whilst various disciplines have made important progress in our understanding of ice-sheet dynamics, it is clear that data-model integration remains under-used, and that uncertainties remain poorly quantified in both empirically-based and numerical ice-sheet reconstructions. The representation of past climate will continue to be the largest source of uncertainty for numerical modelling. As such, palaeo-observations are critical to constrain and validate modelling. State-of-the-art numerical models will continue to improve both in model resolution and in the breadth of inclusion of relevant processes, thereby enabling more accurate and more direct comparison with the increasing range of palaeo-observations. Thus, the capability is developing to use all relevant palaeo-records to more strongly constrain deglacial (and to a lesser extent pre-LGM) ice sheet evolution. In working towards that goal, the accurate representation of uncertainties is required for both constraint data and model outputs. Close cooperation between modelling and data-gathering communities is essential to ensure this capability is realised and continues to progress.

Ice sheet reconstruction↗