SEARCH · Search NASA

Results for “Climate process”

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.

SourceResearch connectionFrom yearThrough year

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

At least 631 records · Page 35

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Stable Machine‐Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection‐Permitting Simulations

Modern climate projections often suffer from inadequate spatial and temporal resolution due to computational limitations, resulting in inaccurate representations of sub-grid processes. A promising technique to address this is the multiscale modeling framework (MMF), which embeds a kilometer-resolution cloud-resolving model (CRM) within each atmospheric column of a host climate model to replace traditional convection and cloud parameterizations. Machine learning offers a unique opportunity to make MMF more accessible by emulating the embedded CRM and reducing its substantial computational cost. Although many studies have demonstrated proof-of-concept success of achieving stable hybrid simulations, it remains a challenge to achieve near operational-level success with real geography and comprehensive variable emulation that includes, for example, explicit cloud condensate coupling. In this study, we present a stable hybrid model capable of integrating for at least 5 years with near operational-level complexity, including coarse-grid geography, seasonality, explicit cloud condensate and wind predictions, and land coupling. Our model demonstrates skillful online performance, achieving a 5-year zonal mean tropospheric temperature bias within 2 K, water vapor bias within 1 g/kg, and a precipitation root mean square error of 0.96 mm/day. Key factors contributing to our online performance include an expressive U-Net architecture and physical thermodynamic constraints for microphysics. With microphysical constraints mitigating unrealistic cloud formation, our work is the first to demonstrate realistic multi-year cloud condensate climatology under the MMF framework. Despite these advances, online diagnostics reveal persistent biases in certain regions, highlighting the need for innovative strategies to further optimize online performance.

Hu, Zeyuan [NVIDIA Corporation, Santa Clara, CA (U↗

NASA NTRS1998

Status of and Outlook for Largescale Modeling of Atmosphere-Ice-Ocean Interactions in the Arctic

Arctic air masses have direct impacts on the weather and climatic extremes of midlatitude areas such as central North America. Arctic physical processes pose special and very important problems for global atmospheric models used for climate simulation and numerical weather prediction. At present, the observational database is inadequate to support research aimed at overcoming these problems. Three interdependent Arctic field programs now being planned will help to remedy this situation: SHEBA, which will operate an ice camp in the Arctic for a year-, ARM, which will supply instruments for use at the SHEBA ice camp and which will also conduct longer-term measurements near Barrow, Alaska; and FIRE, which will conduct one or more aircraft campaigns, in conjunction with remote-sensing investigations focused on the SHEBA ice camp. This paper provides an introductory overview of the physics of the Arctic from the perspective of large-scale modelers, outlines some of the modeling problems that arise in attempting to simulate these processes, and explains how the data to be provided by the three field programs can be used to test and improve large-scale models.

Randall, David↗

NASA NTRS2019

Integrating Remote Sensing Observations with NASA's GEOS-5 Modeling Framework in Support of Retrospective Analyses and Seasonal Prediction of Biosphere-Atmosphere CO2 Flux

The absorption of nearly half of all anthropogenic carbon dioxide (CO2) emissions by terrestrial and marine ecosystems has played a critical role in mitigating climate change. However, a persistent lack of understanding of these uptake processes impedes attribution, and thereby introduces large uncertainties into projections of the trajectory of carbon and climate in coming decades. A better understanding and quantification of the seasonal and interannual variability of carbon flux between the atmosphere and ocean and terrestrial biospheres is critically needed to improve predictions from Earth system models. We propose to bring together a diverse suite of remote sensing observations, mechanistic models, and NASA's Goddard Earth Observing System, version 5 (GEOS-5) model to address two objective 1) quantify the processes controlling the temporal variability of biosphere-atmosphere CO2 flux on seasonal and interannual timescales from 1989 to 2018 and 2) evaluating the predictability of the components of carbon flux on seasonal timescales. Because GEOS-5 has been developed to incorporate a variety of Earth system observations and includes a complete and physically consistent depiction of the atmosphere, land, and ocean carbon cycles, it represents a unique and ideal synthesis framework for this effort. By expanding the realism of processes that could be included in GEOS-5 seasonal forecasts, this effort supports NASA's goals toward an integrated Earth system modeling and prediction framework.We propose to integrate a number of observations into the GEOS-5 modeling system to refine retrospective estimates of both terrestrial and marine carbon flux and to test hypotheses regarding the effects of climate drivers on terrestrial carbon flux. This will include assimilating several satellite ocean color products in the NASA Ocean Biogeochemistry Model (NOBM) to improve the representation of ocean biology. We will also utilize remote sensing datasets to increase the temporal resolution of global land-use change estimates and fire emissions to better constrain the temporal variability of the terrestrial carbon cycle. This information will be incorporated into two NASA terrestrial biosphere models Catchment-CN, a dynamic vegetation model that is integrated within GEOS-5 and the Ecosystem Demography (ED) model, a core modeling resource supporting the Global Ecosystem Dynamics Investigation (GEDI) mission to map biomass. Fluxes will be evaluated through 1) comparison to top-down flux estimates inferred from surface CO2 observations and 2) comparison against available aircraft and satellite observations.By combining predictions of net ecosystem exchange and air-sea CO2 flux from land and ocean models with statistical predictions of land use change, fire, and fossil fuel emissions, we propose to create the first dynamical CO2 forecast on seasonal timescales. Because of the experimental nature of this endeavor, an important project objective will be to evaluate the limits to the predictability of different carbon cycle processes over lead times of 1-12 months using different satellite and surface data streams.

Ott, Lesley↗

DOE OSTI2025

Aerosol-Cloud Interactions and the Intersection of Climate Forcing and Feedback

The goal of this project has been to understand at the process level how the interaction of aerosols and cloud microphysics may alter the cloud response to climate change from the scale of turbulence to the global scale. Atmospheric aerosols (suspended particulates) have a unique role to play in the climate system. Anthropogenic aerosols may be an air pollution hazard and degrade human health. Their presence also results in the direct scattering or absorption of sunlight, with small net impacts on climate. But aerosols are also a key part of cloud formation, as the locations on which cloud droplets and ice crystals form. Understanding these Aerosol Cloud Interactions (ACI) is a critical uncertainty for climate models, including the Energy Exascale Earth System Model (E3SM), and affects how well models like E3SM can simulate the past and future. This work aims to understand cloud microphysics as well as the interaction of aerosol forcing and cloud feedback through improving our understanding of aerosol-cloud interactions (ACI) by looking at their uncertainty in critical environments at the process level. It will also contribute to the development of E3SM. Specific goals include: first, high level analysis of Perturbed Parameter Ensemble (PPE) simulations already available from the Community Earth System Model (CESM) and E3SM. Second, detailed analysis of recent changes to temperature and the role of aerosols.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2017

The Impact of Anthropogenic Land Use and Land Cover Change on Regional Climate Extremes

Recent research highlights the role of land surface processes in heat waves, droughts, and other extreme events. Here we use an earth system model (ESM) from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the regional impacts of historical anthropogenic land useland cover change (LULCC) on combined extremes of temperature and humidity. A bivariate assessment allows us to consider aridity and moist enthalpy extremes, quantities central to human experience of near-surface climate conditions. We show that according to this model, conversion of forests to cropland has contributed to much of the upper central US and central Europe experiencing extreme hot, dry summers every 2-3 years instead of every 10 years. In the tropics, historical patterns of wood harvesting, shifting cultivation and regrowth of secondary vegetation have enhanced near surface moist enthalpy, leading to extensive increases in the occurrence of humid conditions throughout the tropics year round. These critical land use processes and practices are not included in many current generation land models, yet these results identify them as critical factors in the energy and water cycles of the midlatitudes and tropics.

Near-surface↗

NASA NTRS2016

Enabling Research Tools for Sustained Climate Assessment

The U.S. Global Change Research Program Sustained Assessment process benefits from long-term investments in Earth science research that enable the scientific community to conduct assessment-relevant science. To this end, NASA initiated several research programs over the past five years to support the Earth observation community in developing indicators, datasets, research products, and tools to support ongoing and future National Climate Assessments. These activities complement NASA's ongoing Earth science research programs. One aspect of the assessment portfolio funds four "enabling tools" projects at NASA research centers. Each tool leverages existing capacity within the center, but has developed tailored applications and products for National Climate Assessments. The four projects build on the capabilities of a global atmospheric reanalysis (MERRA-2), a continental U.S. land surface reanalysis (NCA-LDAS), the NASA Earth Exchange (NEX), and a Regional Climate Model Evaluation System (RCMES). Here, we provide a brief overview of each enabling tool, highlighting the ways in which it has advanced assessment science to date. We also discuss how the assessment community can access and utilize these tools for National Climate Assessments and other sustained assessment activities.

Research↗

NASA NTRS2016

The Impact of ENSO on Trace Gas Composition in the Upper Troposphere to Lower Stratosphere

The El Nino-Southern Oscillation (ENSO) is the dominant mode of interannual variability in the tropical troposphere and its effects extend well into the stratosphere. Its impact on atmospheric dynamics and chemistry cause important changes to trace gas constituent distributions. A comprehensive suite of satellite observations, reanalyses, and chemistry climate model simulations are illuminating our understanding of processes like ENSO. Analyses of more than a decade of observations from NASAs Aura and Aqua satellites, combined with simulations from the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) and other Chemistry Climate Modeling Initiative (CCMI) models, and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis have provided key insights into the response of atmospheric composition to ENSO. While we will primarily focus on ozone and water vapor responses in the upper troposphere to lower stratosphere, the effects of ENSO ripple through many important trace gas species throughout the atmosphere. The very large 2015-2016 El Nino event provides an opportunity to closely examine these impacts with unprecedented observational breadth. An improved quantification of natural climate variations, like those from ENSO, is needed to detect and quantify anthropogenic climate changes.

ENSO↗

DOE OSTI2026

The birth of a field through a marriage of scales: urban meteorological modeling meets regional climate modeling

Urban meteorological modeling and regional climate modeling developed largely independently, with each discipline addressing different aspects of atmospheric processes across space and time. In this review, I show that urban climate modeling did not arise as a simple scaling extension of urban meteorological modeling or an add-on to regional climate modeling, but instead emerged through the selective inheritance of complementary strengths from its parents after both disciplines reached sufficient methodological maturity. By tracing the parallel evolution of these disciplines, I demonstrate that urban climate modeling inherited the physically explicit treatment of the built environment developed within urban meteorological modeling, and the hierarchical scale translation and climatological framing that matured within regional climate modeling, allowing urban effects to influence climate-relevant outcomes. Building on this synthesis, I propose an objective, and methodologically-grounded definition of urban climate modeling that distinguishes it from urban meteorological modeling. This distinction is increasingly important as urban climate data informs decisions with long-lived societal consequences, and as ambiguity in terminology risks conflating fundamentally different modeling frameworks with distinct physical meaning and decision relevance. In addition to a clarifying definition, this review outlines a research framework for advancing urban climate modeling through scale-aware coupling strategies that preserve physically consistent urban-atmosphere interactions.

regional climate↗

DOE OSTI2024

Simulation-based inference for parameter estimation of complex watershed simulators

High-resolution, spatially distributed process-based (PB) simulators are widely employed in the study of complex catchment processes and their responses to a changing climate. However, calibrating these PB simulators using observed data remains a significant challenge due to several persistent issues, including the following: (1) intractability stemming from the computational demands and complex responses of simulators, which renders infeasible calculation of the conditional probability of parameters and data, and (2) uncertainty stemming from the choice of simplified representations of complex natural hydrologic processes. Here, we demonstrate how simulation-based inference (SBI) can help address both of these challenges with respect to parameter estimation. SBI uses a learned mapping between the parameter space and observed data to estimate parameters for the generation of calibrated simulations. To demonstrate the potential of SBI in hydrologic modeling, we conduct a set of synthetic experiments to infer two common physical parameters – Manning's coefficient and hydraulic conductivity – using a representation of a snowmelt-dominated catchment in Colorado, USA. We introduce novel deep-learning (DL) components to the SBI approach, including an “emulator” as a surrogate for the PB simulator to rapidly explore parameter responses. We also employ a density-based neural network to represent the joint probability of parameters and data without strong assumptions about its functional form. While addressing intractability, we also show that, if the simulator does not represent the system under study well enough, SBI can yield unreliable parameter estimates. Approaches to adopting the SBI framework for cases in which multiple simulator(s) may be adequate are introduced using a performance-weighting approach. The synthetic experiments presented here test the performance of SBI, using the relationship between the surrogate and PB simulators as a proxy for the real case.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2005

Effects of Aerosol on Atmospheric Dynamics and Hydrologic Processes during Boreal Spring and Summer

Global and regional climate impacts of present-day aerosol loading during boreal spring are investigated using the NASA finite volume General Circulation Model (fvGCM). Three-dimensional distributions of loadings of five species of tropospheric aerosols, i.e., sulfate, black carbon, organic carbon, soil dust, and sea salt are prescribed from outputs of the Goddard Ozone Chemistry Aerosol Radiation and Transport model (GOCART). The aerosol loadings are used to calculate the extinction coefficient, single scattering albedo, and asymmetric factor at eleven spectral wavelengths in the radiative transfer code. We find that aerosol-radiative forcing during boreal spring excites a wavetrain-like pattern in tropospheric temperature and geopotential height that emanates from Northern Africa, through Eurasia, to northeastern Pacific. Associated with the teleconnection is strong surface cooling over regions with large aerosol loading, i.e., China, India, and Africa. Low-to-mid tropospheric heating due to shortwave absorption is found in regions with large loading of dust (Northern Africa, and central East Asia), and black carbon (South and East Asia). In addition pronounced surface cooling is found over the Caspian Sea and warming over Eurasian and northeastern Asia, where aerosol loadings are relatively low. These warming and cooling are components of teleconnection pattern produced primarily by atmospheric heating from absorbing aerosols, i.e., dust from North Africa and.black carbon from South and East Asia. Effects of aerosols on atmospheric hydrologic cycle in the Asian monsoon region are also investigated. Results show that absorbing aerosols, i.e., black carbon and dust, induce large-scale upper-level heating anomaly over the Tibetan Plateau in April and May, ushering in an early onset of the Indian summer monsoon. Absorbing aerosols also enhance lower-level heating and anomalous ascent over northern India, intensifying the Indian monsoon. Overall, the aerosol-induced large-scale surface temperature cooling leads to a reduction of monsoon rainfall over the East Asia continent, and adjacent oceanic regions.

Lau, William K. M.↗

NASA NTRS2005

Effects of Aerosol on Atmospheric Dynamics and Hydrologic Processes During Boreal Spring and Summer

Global and regional climate impacts of present-day aerosol loading during boreal spring are investigated using the NASA finite volume General Circulation Model (fvGCM). Three-dimensional distributions of loadings of five species of tropospheric aerosols, i.e., sulfate, black carbon, organic carbon, soil dust, and sea salt are prescribed from outputs of the Goddard Ozone Chemistry Aerosol Radiation and Transport model (GOCART). The aerosol loadings are used to calculate the extinction coefficient, single scattering albedo, and asymmetric factor at eleven spectral wavelengths in the radiative transfer code. We find that aerosol-radiative forcing during boreal spring excites a wavetrain-like pattern in tropospheric temperature and geopotential height that emanates from Northern Africa, through Eurasia, to northeastern Pacific. Associated with the teleconnection is strong surface cooling over regions with large aerosol loading, i.e., China, India, and Africa. Low-to-mid tropospheric heating due to shortwave absorption is found in regions with large loading of dust (Northern Africa, and central East Asia), and black carbon (South and East Asia). In addition pronounced surface cooling is found over the Caspian Sea and warming over Eurasian and northeastern Asia, where aerosol loadings are relatively low. These warming and cooling are components of teleconnection pattern produced primarily by atmospheric heating from absorbing aerosols, i.e., dust from North Africa and black carbon from South and East Asia. Effects of aerosols on atmospheric hydrologic cycle in the Asian monsoon region are also investigated. Results show that absorbing aerosols, i.e., black carbon and dust, induce large-scale upper-level heating anomaly over the Tibetan Plateau in April and May, ushering in an early onset of the Indian summer monsoon. Absorbing aerosols also enhance lower-level heating and anomalous ascent over northern India, intensifying the Indian monsoon. Overall, the aerosol-induced large-scale surface tempera- cooling leads to a reduction of monsoon rainfall over the East Asia continent, and adjacent oceanic regions.

Lau, William K. M.↗

NASA NTRS2018

CLIMATE LECTURE 5: The Role of Clouds in Climate

David Rind has played a central role in the science of the modeling of climate change. He was the scientific driving force behind the development and evaluation of the first Goddard Institute for Space Studies (GISS) global climate model (GCM), Model II. Model II was one of the three original GCMs whose projections of climate change in response to a doubling of CO2 concentration were the basis for the influential Charney Report that produced the first assessment of global climate sensitivity. David used Model II to pioneer the scientific field of climate dynamics, performing a broad range of investigations of processes controlling individual elements of the general circulation and how they changed over a wide range of past and potential future climates. The defining characteristic of Davids papers is his unique talent for tracking down the myriad links and causal chains among different parts of the nonlinear climate system. Rather than viewing climate using a simple forcing-and-response paradigm, David showed that the global energy, water, and even momentum cycles are coupled via the general circulation and its transports.

Del Genio, Anthony D.↗

NASA NTRSDate not supplied

Evaluating the Global Water and Energy Cycles in Reanalyses Using Ensemble Spread

Reanalyses provide continuous observation based global data over weather and climate time scales through observational assimilation. Ensemble forecasts are a component of modern data assimilation systems, providing information to the analysis process. Storing this spread over the duration of a climate reanalysis will provide insight to the variations of the model that underlies the reanalysis data. Global water and energy cycles (WECs) are a critical aspect of both weather and climate, yet there are some large gaps in the observation of key components as well as their representation in models and reanalyses. NASA’s Water and Energy cycle Studies (NEWS) program is developing a corrected and balanced budget data set that is closed at monthly and regional scales during the 21st century, so far. In this paper, we will evaluate reanalysis WEC components against the initial NEWS collection of observation, but integrate the analysis spread from the reanalysis data assimilation as a new perspective on the evaluation. The initial evaluation will cover a few more recent years using ERA5 10 member spread. As the GMAO’s production of the Modern-Era Retrospective analysis for Research and Applications 21st Century (MERRA-21C) progresses, the effort will include the MERRA-21C 32 member spread. Ultimately, we will explore the potential of the ensemble spread as a measure of uncertainty in the reanalysis.

Michael Bosilovich↗

DOE OSTI2024

Autocalibration of the E3SM Version 2 Atmosphere Model Using a PCA-Based Surrogate for Spatial Fields

Global Climate Model tuning (calibration) is a tedious and time-consuming process, with high-dimensional input and output fields. Experts typically tune by iteratively running climate simulations with hand-picked values of tuning parameters. Many, in both the statistical and climate literature, have proposed alternative calibration methods, but most are impractical or difficult to implement. We present a practical, robust, and rigorous calibration approach on the atmosphere-only model of the Department of Energy's Energy Exascale Earth System Model (E3SM) version 2. Our approach can be summarized into two main parts: (a) the training of a surrogate that predicts E3SM output in a fraction of the time compared to running E3SM, and (b) gradient-based parameter optimization. To train the surrogate, we generate a set of designed ensemble runs that span our input parameter space and use polynomial chaos expansions on a reduced output space to fit the E3SM output. We use this surrogate in an optimization scheme to identify values of the input parameters for which our model best matches gridded spatial fields of climate observations. To validate our choice of parameters, we run E3SMv2 with the optimal parameter values and compare prediction results to expertly-tuned simulations across 45 different output fields. This flexible, robust, and automated approach is straightforward to implement, and we demonstrate that the resulting model output matches present day climate observations as well or better than the corresponding output from expert tuned parameter values, while considering high-dimensional output and operating in a fraction of the time.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2002

Soil Moisture and Snow Cover: Active or Passive Elements of Climate

A key question is the extent to which surface effects such as soil moisture and snow cover are simply passive elements or whether they can affect the evolution of climate on seasonal and longer time scales. We have constructed ensembles of predictability studies using the NCAR CCM3 in which we compared the relative roles of initial surface and atmospheric conditions over the central and western U.S. in determining the subsequent evolution of soil moisture and of snow cover. Results from simulations with realistic soil moisture anomalies indicate that internal climate variability may be the strongest factor, with some indication that the initial atmospheric state is also important. Model runs with exaggerated soil moisture reductions (near-desert conditions) showed a much larger effect, with warmer surface temperatures, reduced precipitation, and lower surface pressures; the latter indicating a response of the atmospheric circulation. These results suggest the possibility of a threshold effect in soil moisture, whereby an anomaly must be of a sufficient size before it can have a significant impact on the atmospheric circulation and climate. Results from simulations with realistic snow cover anomalies indicate that the time of year can be crucial. When introduced in late winter, these anomalies strongly affected the subsequent evolution of snow cover. When introduced in early winter, however, little or no effect is seen on the subsequent snow cover. Runs with greatly exaggerated initial snow cover indicate that the high reflectivity of snow is the most important process by which snow cover can impact climate, through lower surface temperatures and increased surface pressures. The results to date were obtained for model runs with present-day conditions. We are currently analyzing runs made with projected forcings for the 21st century to see if these results are modified in any way under likely scenarios of future climate change. An intriguing new statistical technique involving 'clustering' is developed to assist in this analysis.

Oglesby, Robert J.↗

NASA NTRS2023

A 1D Model for Nucleation of Ice From Aerosol Particles: An Application to a Mixed-Phase Arctic Stratus Cloud Layer

Mixed-phase clouds (MPCs) have been identified as significant contributors to uncertainties in climate projections, attributable to model representation of processes controlling the formation and loss of supercooled water droplets and ice particles from the atmosphere. Arctic MPCs are commonly widespread and long-lived, with sustained ice crystal formation processes that challenge current understanding. This study examines the ice-nucleating particle (INP) reservoir dynamics governing immersion-mode heterogeneous freezing in an observed case of Arctic MPCs using a simplified 1D aerosol-cloud model. The model setup includes prescribed dynamical forcings and thermodynamic profiles, and represents INPs as multicomponent and polydisperse particle size distributions. Diagnostic and prognostic approaches to immersion freezing parameterization are compared, including time-independent (singular) number- and surface area-based descriptions and a time-dependent description following classical nucleation theory (CNT). The choice of freezing parameterization defines the size of the INP reservoir. The CNT-based description yields an orders of magnitude larger INP reservoir than the singular parameterizations, which is the dominant factor for sustained ice crystal formation. The efficiency of the freezing process and cloud cooling are of secondary importance. A diagnostic treatment neglecting INP loss is only accurate when the INP reservoir size is large and INP depletion weak. Since a larger INP reservoir sustains ice crystal formation substantially longer, and ice water path scales with ice crystal concentrations for the conditions considered, resolving the source of differences in INP reservoir dynamics due to model implementation is a high priority for advancing climate model physics.

aerosol↗

NASA NTRS2019

Examining Seasonal Trends of the Martian Polar Warming with the NASA Ames Mars Global Climate Model

The presented work focuses on polar warming as a diagnostic of the mean circulation to increase our understanding of processes that control the mean meridional circulation and transport in the Mars’ middle atmosphere. The NASA Ames Mars Global Climate Model is utilized to isolate physical processes to determine their impact on polar warming and its seasonal trends.

Brecht, Amanda S.↗

NASA NTRS2018

ModelE Orbits & Calendars

The GISS climate model, ModelE, [an atmosphere-ocean model] has been extended to support the simulation of climates for exoplanets. As part of this process, a more general calendaring system has been implemented that is derived from orbital parameters. The calendar design attempts to preserve the basic notions of the 4 seasons as well as the time of day. These slides provide the basic underlying assumptions for the design and detail how to configure the model to use non-Earth orbital parameters. [One of a series of videos taken of the ROCKE-3D (Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics), a 3-Dimensional General Circulation Model (GCM) exoplanet modeling tutorial sessions, May 21-22, 2018, (this slide set was prepared for Day 2, Parts 1 and 2, May 22, 2018) on YouTube (https://www.youtube.com)]

Clune, Tom↗