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NASA NTRSDate not supplied

Development of an Extended Reality (XR) Tool for Earth Science Visualization

In this presentation, we will discuss our work in adapting the NASA open source XR software, the Mixed Reality Exploration Toolkit (MRET), to an earth science domain. MRET is a NASA open source XR software for rapidly building extended reality (XR) environments for NASA domain problems, e.g., pulling in CAD models of thermal vac chamber and Roman Space Telescope to do fit checks. Primarily used for hardware integration & test, we have been adapting and extending MRET for science problems. Traditionally, scientists view and analyze the result of calculated or measured observables with static 1-D, 2-D or 3-D plots. It can be difficult to identify, track and understand the evolution of key features due to poor viewing angles and the nature of flat computer screens. Additionally, numerical models, such as the NASA GEOS climate model, are almost exclusively formulated and analyzed on Eulerian grids with points fixed in space and time. However, atmospheric phenomena such as convective clouds, hurricanes and wildfire smoke plumes move with the 3-D flow field, and it is often difficult and unnatural to understand these phenomena in an Eulerian reference frame as opposed to the Lagrangian reference frame in which nature operates. As part of an Earth Science Technology Office (ESTO) proposal, we have been adapting MRET to be a scientific exploration and analysis XR tool with integrated Lagrangian Dynamics (LD) for the Goddard Earth Observing System (GEOS) numerical weather prediction model. We believe this will help scientists identify, track, and understand the evolution of Earth Science phenomena. This presentation will discuss current results in our work in developing this XR tool for Earth Science.

Thomas G Grubb↗
NASA NTRSDate not supplied

Development of an Extended Reality (XR) Tool for Earth Science Visualization

In this presentation, we will discuss our work in adapting the NASA open source XR software, the Mixed Reality Exploration Toolkit (MRET), to an earth science domain. MRET is a NASA open source XR software for rapidly building extended reality (XR) environments for NASA domain problems, e.g., pulling in CAD models of thermal vac chamber and Roman Space Telescope to do fit checks. Primarily used for hardware integration & test, we have been adapting and extending MRET for science problems. Traditionally, scientists view and analyze the result of calculated or measured observables with static 1-D, 2-D or 3-D plots. It can be difficult to identify, track and understand the evolution of key features due to poor viewing angles and the nature of flat computer screens. Additionally, numerical models, such as the NASA GEOS climate model, are almost exclusively formulated and analyzed on Eulerian grids with points fixed in space and time. However, atmospheric phenomena such as convective clouds, hurricanes and wildfire smoke plumes move with the 3-D flow field, and it is often difficult and unnatural to understand these phenomena in an Eulerian reference frame as opposed to the Lagrangian reference frame in which nature operates. As part of an Earth Science Technology Office (ESTO) proposal, we have been adapting MRET to be a scientific exploration and analysis XR tool with integrated Lagrangian Dynamics (LD) for the Goddard Earth Observing System (GEOS) numerical weather prediction model. We believe this will help scientists identify, track, and understand the evolution of Earth Science phenomena. This presentation will discuss current results in our work in developing this XR tool for Earth Science.

Thomas Grubb↗
NASA NTRS2002

Microphysics, Radiation and Surface Processes in the Goddard Cumulus Ensemble (GCE) Model

One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (size about 2-200 km). The CRMs also allow explicit interaction between out-going longwave (cooling) and in-coming solar (heating) radiation with clouds. Observations can provide the initial conditions and validation for CRM results. The Goddard Cumulus Ensemble (GCE) Model, a CRM, has been developed and improved at NASA/Goddard Space Flight Center over the past two decades. The GCE model has been used to understand the following: 1) water and energy cycles and their roles in the tropical climate system; 2) the vertical redistribution of ozone and trace constituents by individual clouds and well organized convective systems over various spatial scales; 3) the relationship between the vertical distribution of latent heating (phase change of water) and the large-scale (pre-storm) environment; 4) the validity of assumptions used in the representation of cloud processes in climate and global circulation models; and 5) the representation of cloud microphysical processes and their interaction with radiative forcing over tropical and midlatitude regions. Four-dimensional cloud and latent heating fields simulated from the GCE model have been provided to the TRMM Science Data and Information System (TSDIS) to develop and improve algorithms for retrieving rainfall and latent heating rates for TRMM and the NASA Earth Observing System (EOS). More than 90 referred papers using the GCE model have been published in the last two decades. Also, more than 10 national and international universities are currently using the GCE model for research and teaching. In this talk, five specific major GCE improvements: (1) ice microphysics, (2) longwave and shortwave radiative transfer processes, (3) land surface processes, (4) ocean surface fluxes and (5) ocean mixed layer processes are presented. The performance of these new GCE improvements will be examined. Observations are used for model validation.

Tao, Wei-Kuo↗
NASA NTRS2024

Aera-Mip: Emission Pathways, Remaining Budgets, and Carbon Cycle Dynamics Compatible With 1.5 and 2 °C Global Warming Stabilization

While international climate policies now focus on limiting global warming to well below 2 °C or pursuing a 1.5 °C level of global warming, the climate modelling community has not provided an experimental design in which all Earth system models (ESMs) converge and stabilize at the same prescribed global warming levels. This gap hampers accurate estimations based on comprehensive ESMs of the carbon emission pathways and budgets needed to meet such agreed warming levels and of the associated climate impacts under temperature stabilization. Here, we apply the Adaptive Emission Reduction Approach (AERA) with ESMs to provide such simulations in which all models converge at 1.5 and 2.0 °C warming levels by adjusting their emissions over time. These emission-driven simulations provide a wide range of emission pathways and resulting atmospheric CO 2 projections for a given warming level, uncovering uncertainty ranges that were previously missing in the traditional Coupled Model Intercomparison Project (CMIP) scenarios with prescribed greenhouse gas concentration pathways. Meeting the 1.5 °C warming level requires a 40 % (full model range: 7 % to 76 %) reduction in multi-model mean CO 2 -forcing-equivalent (CO 2 -fe) emissions from 2025 to 2030, a 98 % (57 % to 127 %) reduction from 2025 to 2050, and a stabilization at 1.0 (−1.7 to 2.9) PgC yr−1 from 2100 onward after the 1.5 °C global warming level is reached. Meeting the 2.0 °C warming level requires a 47 % (8 % to 92 %) reduction in multi-model mean CO 2 -fe emissions until 2050 and a stabilization at 1.7 (−1.5 to 2.7) PgC yr−1 from 2100 onward. The on-average positive emissions under stabilized global temperatures are the result of a decreasing transient climate response to cumulative CO 2 -fe emissions over time under stabilized global warming. This evolution is consistent with a slightly negative zero emissions commitment – initially assumed to be zero – and leads to an increase in the post-2025 CO 2 -fe emission budget by a factor of 2.2 (−0.8 to 6.9) by 2150 for the 1.5 °C warming level and a factor of 1.4 (0.9 to 2.4) for the 2.0 °C warming level compared to its first estimate in 2025. The median CO 2 -only carbon budget by 2150, relative to 2020, is 800 GtCO 2 for the 1.5 °C warming level and 2250 GtCO 2 for the 2.0 °C warming level. These median values exceed the median IPCC AR6 estimates by 60 % for the 1.5 °C warming level and 67 % for 2.0 °C. Some of the differences may be explained by the choice of the mitigation scenario for non-CO 2 radiative agents. Our simulations highlight shifts in carbon uptake dynamics under stabilized temperature, such as a cessation of the carbon sinks in the North Atlantic and in tropical forests. On the other hand, the Southern Ocean remains a carbon sink centuries after temperatures stabilize. Overall, this new type of warming-level-based emission-driven simulation offers a more coherent assessment across climate models and opens up a wide range of possibilities for studying both the carbon cycle and climate impacts, such as extreme events, under climate stabilization.

Adaptive Emission Reduction Approach↗
NASA NTRS2023

StratoFIRE: Modeling Wildfire Smoke in the Stratosphere

The most extreme manifestation of a fire–weather interaction is the formation of pyrocumulonimbus (pyroCb) thunderstorms, triggered by super-heated updrafts, which can eject smoke at altitudes exceeding 20 Km. In this study, we investigated climate-related impacts from the most intensive pyroCb-triggered injection of smoke in the stratosphere: the Australian New Year wildfires in 2019/2020. We first provide a general overview of the vision and objectives of the StratoFIRE project. With the aid of the global chemistry-climate model EMAC, we then simulate radiative and chemical perturbations in the stratosphere in relation to 0.9 Tg smoke in the stratosphere assuming different injection heights, from 13 to 16 Km. The simulation of stratospheric optical depth perturbations were found to be sensitive to the assumed injection height, with a maximum height at 16 Km showing the best agreement with the GLOSSAC and SAGE-ISS aerosol extinction observations.

PyroCb↗
NASA NTRS1988

The GISS global climate-middle atmosphere model. I - Model structure and climatology

A coupled global climate/middle atmosphere model (GCMAM) is developed by extending the Hansen et al. (1983) GISS global climate model to include the middle atmosphere up to 85 km. The model includes numerical solutions of the primitive equations, calculations of the radiative and surface fluxes, and a complete hydrologic cycle with convective and cloud-cover parameterizations. In addition, a parameterized gravity wave drag cycle is incorporated, in which gravity-wave momentum fluxes due to flow over topography, wind shear, and convection are calculated at each grid box, using theoretical relationships between the grid-scale variables and expected source strengths. The results of the GCMAM demonstrate that the model produces a reasonable simulation of the stratosphere. It is shown that the improvements over the previous version were achieved largely through the incorporation of the parameterized gravity wave drag.

Rind, D.↗
NASA NTRS2013

Implications of CO Bias for Ozone and Methane Lifetime in a CCM

A low bias in carbon monoxide compared to observations at high latitudes is a common feature of chemistry climate models. CO bias can both indicate and contribute to a bias in modeled OH and methane lifetime. This study examines possible causes of CO bias in the ACCMIP simulation of the GEOSCCM, and considers how attributing the CO bias to uncertainty in CO emissions versus biases in other constituents impacts the relationship between CO bias and methane lifetime. We use a simplified model of CO tagged by source with specified OH to quantify the sensitivity of the CO bias to changes in CO emissions or OH concentration, comparing the modeled CO to surface and MOPITT observations. The simplified model shows that decreasing OH in the northern hemisphere removes most of the global mean and inter-hemispheric bias in surface CO. We then use results from this analysis to explore how adjusting CO sources in the CCM impacts the concentrations of ozone, OH and methane. The CCM simulation also exhibits biases in ozone and water vapor compared to observations. We use a parameterized CO-OH-CH4 model that takes ozone and water vapor as inputs to the parameterization to examine whether correcting water and ozone biases can alter OH enough to remove the CO bias. Through this analysis, we aim to better quantify the relationship between CO bias and model biases in ozone concentrations and methane lifetime.

carbon monoxide↗
NASA NTRS2013

Climate Informatics

The impacts of present and potential future climate change will be one of the most important scientific and societal challenges in the 21st century. Given observed changes in temperature, sea ice, and sea level, improving our understanding of the climate system is an international priority. This system is characterized by complex phenomena that are imperfectly observed and even more imperfectly simulated. But with an ever-growing supply of climate data from satellites and environmental sensors, the magnitude of data and climate model output is beginning to overwhelm the relatively simple tools currently used to analyze them. A computational approach will therefore be indispensable for these analysis challenges. This chapter introduces the fledgling research discipline climate informatics: collaborations between climate scientists and machine learning researchers in order to bridge this gap between data and understanding. We hope that the study of climate informatics will accelerate discovery in answering pressing questions in climate science.

Climate change↗
NASA NTRS2020

Local and Remote Mean and Extreme Temperature Response to Regional Aerosol Emissions Reductions

The climatic implications of regional aerosol and precursor emissions reductions implemented to protect human health are poorly understood. We investigate the mean and extreme temperature response to regional changes in aerosol emissions using three coupled chemistry–climate models: NOAA GFDL CM3, NCAR CESM1, and NASA GISS-E2. Our approach contrasts a long present-day control simulation from each model (up to 400 years with perpetual year 2000 or 2005 emissions) with 14 individual aerosol emissions perturbation simulations (160–240 years each). We perturb emissions of sulfur dioxide (SO2) and/or carbonaceous aerosol within six world regions and assess the statistical significance of mean and extreme temperature responses relative to internal variability determined by the control simulation and across the models. In all models, the global mean surface temperature response (perturbation minus control) to SO2 and/or carbonaceous aerosol is mostly positive (warming) and statistically significant and ranges from +0.17 K (Europe SO2) to -0.06 K (US BC). The warming response to SO2 reductions is strongest in the US and Europe perturbation simulations, both globally and regionally, with Arctic warming up to 1 K due to a removal of European anthropogenic SO2 emissions alone; however, even emissions from regions remote to the Arctic, such as SO2 from India, significantly warm the Arctic by up to 0.5 K. Arctic warming is the most robust response across each model and several aerosol emissions perturbations. The temperature response in the Northern Hemisphere midlatitudes is most sensitive to emissions perturbations within that region. In the tropics, however, the temperature response to emissions perturbations is roughly the same in magnitude as emissions perturbations either within or outside of the tropics. We find that climate sensitivity to regional aerosol perturbations ranges from 0.5 to 1.0 K (W m(exp -2))(exp -1) depending on the region and aerosol composition and is larger than the climate sensitivity to a doubling of CO2 in two of three models. We update previous estimates of regional temperature potential (RTP), a metric for estimating the regional temperature responses to a regional emissions perturbation that can facilitate assessment of climate impacts with integrated assessment models without requiring computationally demanding coupled climate model simulations. These calculations indicate a robust regional response to aerosol forcing within the Northern Hemisphere midlatitudes, regardless of where the aerosol forcing is located longitudinally. We show that regional aerosol perturbations can significantly increase extreme temperatures on the regional scale. Except in the Arctic in the summer, extreme temperature responses largely mirror mean temperature responses to regional aerosol perturbations through a shift of the temperature distributions and are mostly dominated by local rather than remote aerosol forcing.

Westervelt, Daniel M.↗
NASA NTRS2023

On the Remote Impacts of Mid-Holocene Saharan Vegetation on South American Hydroclimate: A Modeling Intercomparison

Proxy reconstructions from the mid-Holocene (MH: 6,000 years ago) indicate an intensification of the West African Monsoon and a weakening of the South American Monsoon, primarily resulting from orbitally-driven insolation changes. However, model studies that account for MH orbital configurations and greenhouse gas concentrations can only partially reproduce these changes. Most model studies do not account for the remarkable vegetation changes that occurred during the MH, in particular over the Sahara, precluding realistic simulations of the period. Here, we study precipitation changes over northern Africa and South America using four fully coupled global climate models by accounting for the Saharan greening. Incorporating the Green Sahara amplifies orbitally-driven changes over both regions, and leads to an improvement in proxy-model agreement. Our work highlights the local and remote impacts of vegetation and the importance of considering vegetation changes in the Sahara when studying and modeling global climate.

Paleoclimate modeling↗
NASA NTRS2020

Dependence of Atmospheric Transport into the Arctic on the Extent of the Hadley Cell

Recent studies have shown a large spread in the transport of atmospheric tracers into the Arctic among a suite of chemistry climate models, and have suggested that this is related to the multi–model spread in the meridional extent of the Hadley Cell (HC). Here we examine the HC–transport relationship using an idealized model, where we can vary the mean circulation and isolate its impact on transport to the Arctic. It is shown that the poleward transport depends on the relative position between the northern edge of the HC and the tracer source, with maximum poleward transport occurring when the HC edge lies near the middle of the source region. Such dependence highlights the critical role of near–surface transport by Eulerian mean circulation rather than eddy mixing in the free troposphere. These results suggest that variations in the HC extent and the tracer source region are both important for modeling Arctic composition.

Atmospheric transport↗
NASA NTRS2006

Recovery of the Antarctic Ozone Hole

The Antarctic ozone hole develops each year and culminates by early Spring. Antarctic ozone values have been monitored since 1979 using satellite observations from the TOMS and OMI instruments. The severity of the hole has been assessed using the minimum total ozone value from the October monthly mean (depth of the hole), the average size during the September-October period, and the ozone mass deficit. Ozone is mainly destroyed by halogen catalytic cycles, and these losses are modulated by temperature variations in the collar of the polar lower stratospheric vortex. In this presentation, we show the relationships of halogens and temperature to both the size and depth of the hole. Because atmospheric halogen levels are responding to international agreements that limit or phase out production, the amount of halogens in the stratosphere should decrease over the next few decades. We use two methods to estimate ozone hole recovery. First, we use projections of halogen levels combined with age-of-air estimates in a parametric model. Second, we use a coupled chemistry climate model to assess recovery. We find that the ozone hole is recovering at an extremely slow rate and that large ozone holes will regularly recur over the next 2 decades. Furthermore, full recovery to 1980 levels will not occur until approximately 2068. We will also show some error estimates of these dates and the impact of climate change on the recovery.

Newman, Paul A.↗
NASA NTRS2016

Analysis of Ozone in Cloudy Versus Clear Sky Conditions

Convection impacts ozone concentrations by transporting ozone vertically and by lofting ozone precursors from the surface, while the clouds and lighting associated with convection affect ozone chemistry. Observations of the above-cloud ozone column (Ziemke et al., 2009) derived from the OMI instrument show geographic variability, and comparison of the above-cloud ozone with all-sky tropospheric ozone columns from OMI indicates important regional differences. We use two global models of atmospheric chemistry, the GMI chemical transport model (CTM) and the GEOS-5 chemistry climate model, to diagnose the contributions of transport and chemistry to observed differences in ozone between areas with and without deep convection, as well as differences in clean versus polluted convective regions. We also investigate how the above-cloud tropospheric ozone from OMI can provide constraints on the relationship between ozone and convection in a free-running climate simulation as well as a CTM.

Cloud↗
NASA NTRS2024

Decreased Northern Hemisphere Precipitation from Consecutive CO 2 Doublings Is Associated with Significant AMOC Weakening

Previous studies found many climate properties such as northern hemisphere (NH) surface temperature and precipitation respond non-monotonically when CO2 is increased from 1× to 8×CO2 relative to pre-industrial levels. Here, we explore the robustness of the non-monotonicity in the NH precipitation response in 11 coupled climate models. Eight models show a decrease in NH precipitation under repeated CO2 doubling, indicating that the non-monotonic response is a common but not universal result. Although common, the critical CO2 level where the NH precipitation decrease first occurs differs widely across models, ranging from 2×CO2 to 8×CO2. These models also show a prominent weakening in the Atlantic meridional overturning circulation (AMOC) at the same critical CO2 level, with the AMOC weakening leading the precipitation decrease. The sensitivities of NH precipitation and the AMOC to CO2 doublings are positively correlated, especially when the AMOC weakens beyond 10 Sv. This suggests that the differences in models' AMOC response can explain their contrasting NH precipitation responses, where models with a large AMOC weakening have decreased NH precipitation. Regionally, this decrease in NH precipitation is the most prominent over the North Atlantic, Europe and the tropical Pacific. Our results suggest that special care must be taken with the use of pattern scaling to inform regional climate decision-making.

Atlantic meridional overturning circulation↗
NASA NTRS2013

PROcess Based Diagnostics PROBE

Many of the aspects of the climate system that are of the greatest interest (e.g., the sensitivity of the system to external forcings) are emergent properties that arise via the complex interplay between disparate processes. This is also true for climate models most diagnostics are not a function of an isolated portion of source code, but rather are affected by multiple components and procedures. Thus any model-observation mismatch is hard to attribute to any specific piece of code or imperfection in a specific model assumption. An alternative approach is to identify diagnostics that are more closely tied to specific processes -- implying that if a mismatch is found, it should be much easier to identify and address specific algorithmic choices that will improve the simulation. However, this approach requires looking at model output and observational data in a more sophisticated way than the more traditional production of monthly or annual mean quantities. The data must instead be filtered in time and space for examples of the specific process being targeted.We are developing a data analysis environment called PROcess-Based Explorer (PROBE) that seeks to enable efficient and systematic computation of process-based diagnostics on very large sets of data. In this environment, investigators can define arbitrarily complex filters and then seamlessly perform computations in parallel on the filtered output from their model. The same analysis can be performed on additional related data sets (e.g., reanalyses) thereby enabling routine comparisons between model and observational data. PROBE also incorporates workflow technology to automatically update computed diagnostics for subsequent executions of a model. In this presentation, we will discuss the design and current status of PROBE as well as share results from some preliminary use cases.

PROBE↗
NASA NTRSDate not supplied

Midlatitude cyclone processes as a key to understanding climate sensitivity

Global climate models (GCMs) differ greatly in their shortwave cloud feedback. One feature that is consistent across GCMs is a positive shortwave cloud feedback in the subtropics, and a negative shortwave cloud feedback across the midlatitudes. Confidence has grown in the mechanisms that lead to, and the strength of, the subtropical shortwave cloud feedback, but the midlatitude negative shortwave cloud feedback is not well-constrained or well-understood. It is critical to reduce uncertainty in midlatitude shortwave cloud feedback. A more positive midlatitude shortwave cloud feedback in the sixth coupled model intercomparison project (CMIP6) has been found to be one of the primary causes of the increased climate sensitivity of CMIP6 models relative to CMIP5. We show that changes in midlatitude cyclones in future climates are the primary cause of the negative shortwave cloud feedback and are thus key to understanding the high climate sensitivity in the most recent GCMs. Warming-induced changes in cloud liquid water path in midlatitude cyclones can almost entirely be explained by Clausius-Clapeyron increasing moisture convergence into cyclones. One concern with simulating midlatitude cyclones is the lack of predictive skill at low resolution. A more realistic relationship between moisture flux and cyclone liquid content is found at high horizontal resolution (∆x<25km), but the cloud feedback within cyclones can be explained by increased moisture convergence across low- and high-resolution models. Observations and models agree that the extratropical shortwave cloud feedback is moderated by precipitation processes in cyclones. This rules out a large contribution from ice-to-liquid transitions, as has been hypothesized in previous studies. Understanding and constraining these precipitation processes is crucial to constraining the response of midlatitude cyclones to warming and by extension climate sensitivity.

Cyclones↗