SEARCH · Engineering Papers

Results for “CLIMATES”

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 703 records · Page 39

All sources NASA NTRS DOE OSTI

NASA NTRS2016

Climate and Fuel Controls on North American Paleofires: Smoldering to Flaming in the Late-Glacial-Holocene Transition

Smoldering and flaming fires, which emit different proportions of organic (OC) and black carbon (BC, in the form of char and soot), have long been recognized in modern wildfire observations but never in a paleo-record, and little is known about their interactions with climate. Here we show that in the late glacial-early Holocene transition period, when the climate was moist, relatively high quantities of char were deposited in Linsley Pond, Connecticut, USA while soot was more abundant during the warmer and drier early Holocene interval. The highest soot mass accumulation rates (MARs) occurred at the beginning of the Holocene as fuel availability increased through the climatic transition when boreal forests were locally extirpated. These variations with time are related to the different formation pathways of char and soot, which are governed by combustion efficiency. This study provides an approach for differentiating smoldering from flaming combustion in paleo-wildfire reconstructions. Our results suggest that climate and fuel loads control the occurrence of different wildfire types and precipitation may play a key role.

Han, Y. M.↗

NASA NTRS2017

Quantifying the Influence of Global Warming on Unprecedented Extreme Climate Events

Efforts to understand the influence of historical global warming on individual extreme climate events have increased over the past decade. However, despite substantial progress, events that are unprecedented in the local observational record remain a persistent challenge. Leveraging observations and a large climate model ensemble, we quantify uncertainty in the influence of global warming on the severity and probability of the historically hottest month, hottest day, driest year, and wettest 5-d period for different areas of the globe. We find that historical warming has increased the severity and probability of the hottest month and hottest day of the year at >80% of the available observational area. Our framework also suggests that the historical climate forcing has increased the probability of the driest year and wettest 5-d period at 57% and 41% of the observed area, respectively, although we note important caveats. For the most protracted hot and dry events, the strongest and most widespread contributions of anthropogenic climate forcing occur in the tropics, including increases in probability of at least a factor of 4 for the hottest month and at least a factor of 2 for the driest year. We also demonstrate the ability of our framework to systematically evaluate the role of dynamic and thermodynamic factors such as atmospheric circulation patterns and atmospheric water vapor, and find extremely high statistical confidence that anthropogenic forcing increased the probability of record-low Arctic sea ice extent.

Diffenbaugh, Noah S.↗

NASA NTRS2017

Our Globally Changing Climate

Since the Third U.S. National Climate Assessment (NCA3) was published in May 2014, new observations along multiple lines of evidence have strengthened the conclusion that Earth's climate is changing at a pace and in a pattern not explainable by natural influences. While this report focuses especially on observed and projected future changes for the United States, it is important to understand those changes in the global context (this chapter). The world has warmed over the last 150 years, especially over the last six decades, and that warming has triggered many other changes to Earth's climate. Evidence for a changing climate abounds, from the top of the atmosphere to the depths of the oceans. Thousands of studies conducted by tens of thousands of scientists around the world have documented changes in surface, atmospheric, and oceanic temperatures; melting glaciers; disappearing snow cover; shrinking sea ice; rising sea level; and an increase in atmospheric water vapor. Rainfall patterns and storms are changing, and the occurrence of droughts is shifting.

Wuebbles, D. J.↗

NASA NTRS2018

Constraining the Climate and Ocean PH of the Early Earth with a Geological Carbon Cycle Model

The early Earth's environment is controversial. Climatic estimates range from hot to glacial, and inferred marine pH spans strongly alkaline to acidic. Better understanding of early climate and ocean chemistry would improve our knowledge of the origin of life and its coevolution with the environment. Here, we use a geological carbon cycle model with ocean chemistry to calculate self-consistent histories of climate and ocean pH. Our carbon cycle model includes an empirically justified temperature and pH dependence of seafloor weathering, allowing the relative importance of continental and seafloor weathering to be evaluated. We find that the Archean climate was likely temperate (0-50deg C) due to the combined negative feedbacks of continental and seafloor weathering. Ocean pH evolves monotonically from 6.6(sup + 0.6) (sub -0.4) (2 sigma) at 4.0 Ga to 7.0(sup +0.7) (sub-0.5) (2 sigma) at the Archean-Proterozoic boundary, and to 7.9(sup +0.1) (sub -0.2) (2 sigma) at the Proterozoic-Phanerozoic boundary. This evolution is driven by the secular decline of pCO2, which in turn is a consequence of increasing solar luminosity, but is moderated by carbonate alkalinity delivered from continental and seafloor weathering. Archean seafloor weathering may have been a comparable carbon sink to continental weathering, but is less dominant than previously assumed, and would not have induced global glaciation. We show how these conclusions are robust to a wide range of scenarios for continental growth, internal heat flow evolution and outgassing history, greenhouse gas abundances, and changes in the biotic enhancement of weathering.

Krissansen-Totton, Joshua↗

NASA NTRS2018

Identifying Climate-Smart Agriculture Research Needs

Climate-smart agriculture (CSA) is an approach to help agricultural systems worldwide, concurrently addressing three challenge areas: increased adaptation to climate change, mitigation of climate change, and ensuring global food security - through innovative policies, practices, and financing. It involves a set of objectives and multiple transformative transitions for which there are newly identified knowledge gaps. We address these questions raised by CSA within three areas: conceptualization, implementation, and implications for policy and decision-makers. We also draw up scenarios on the future of the CSA concept in relation to the 4 per 1000 Initiative (Soils for Food Security and Climate) launched at UNFCCC 21st Conference of the Parties (COP 21). Our analysis shows that there is still a need for further interdisciplinary research on the theoretical foundation of the CSA concept and on the necessary transformations of agriculture and land use systems. Contrasting views about implementation indicate that CSA focus on the ''triple win'' (adaptation, mitigation, food security) needs to be assessed in terms of science-based practices. CSA policy tools need to incorporate an integrated set of measures supported by reliable metrics. Environmental and social safeguards are necessary to make sure that CSA initiatives conform to the principles of sustainability, both at the agriculture and food system levels.

mitigation↗

NASA NTRS2018

Understanding Climate-Vegetation Interactions in Global Rainforests Through a GP-Tree Analysis

The tropical rainforests are the largest reserves of terrestrial carbon and, therefore, the future of these rainforests is a question that is of immense importance in the geoscience research community. With the recent severe Amazonian droughts in 2005 and 2010 and on-going drought in the Congo region for more than two decades, there is growing concern that these forests could succumb to precipitation reduction, causing extensive carbon release and feedback to the carbon cycle. However, there is no single ecosystem model that quantifies the relationship between vegetation health in these rainforests and climatic factors. Small scale studies have used statistical correlation measure and simple linear regression to model climate-vegetation interactions, but suffer from the lack of comprehensive data representation as well as simplistic assumptions about dependency of the target on the covariates. In this paper we use genetic programming (GP) based symbolic regression for discovering equations that govern the vegetation climate dynamics in the rainforests. Expecting micro-regions within the rainforests to have unique characteristics compared to the overall general characteristics, we use a modified regression-tree based hierarchical partitioning of the space to build individual models for each partition. The discovery of these equations reveal very interesting characteristics about the Amazon and the Congo rainforests. Our method GP-tree shows that the rainforests exhibit tremendous resiliency in the face of extreme climatic events by adapting to changing conditions.

genetic programming↗

NASA NTRS2019

New York City Panel on Climate Change 2019 Report Chapter 8: Indicators and Monitoring

The Indicators and Monitoring chapter of the first New York City Panel on Climate Change Report began with the paradigm: What cannot be measured cannot be managed (Rosenzweig et al., 2010). This statement is as valid today as it was then.The NPCC1 (2010) Indicators and Monitoring chapter addressed the need for assembling a suite of indicators to monitor climate change and adaptation in order to inform climate change decision making. It outlined criteria for selection of indicators (policy relevance, analytic soundness, measurability), defined categories of indicators (physical climate change; risk exposure, vulnerability, and impacts; adaptation; new research), and provided examples of specific indicators. Table 8.1 is a summary table of indicator development contribution from the NPCC1 I&M chapter (Jacob et al., 2011). The chapter explored the institutional requirements for indicator data availability, continuity, archiving, and public accessibility.

Blake, Reginald↗

NASA NTRS2018

The Importance of Understanding the Last Glacial Maximum for Climate Change

The last glacial maximum (LGM) at approximately 23–18k (k—thousand calendar years) provides an important contrast to our present and pre-industrial climate in a warming world. Global observational datasets of LGM land and sea surface conditions have been synthesized and present some interesting challenges both for providing another scenario for understanding climate change and for climate sensitivity. These challenges are ongoing, as data increase and modeling improves. By definition, the LGM is defined as the time during the last glacial interval in which maximum ice was sequestered in ice sheets as visible in the marine isotopic records. Maximum cooling is visible from pollen and macrofossil records 14C dated to this interval, and ice sheets and alpine glaciers are roughly at their maximum extent throughout the globe. The ice cores extracted from Greenland and Antarctica have given us high-resolution records of greenhouse gases, dust, and isotopes of hydrogen and oxygen which reveal the progression out of the LGM at 18k as climate warmed.

Peteet, Dorothy↗

NASA NTRS2019

Twentieth Century Redistribution in Climatic Drivers of Global Tree Growth

Energy and water limitations of tree growth remain insufficiently understood at large spatiotemporal scales, hindering model representation of interannual or longer-term ecosystem processes. By assessing and statistically scaling the climatic drivers from 2710 tree-ring sites, we identified the boreal and temperate land areas where tree growth during 1930–1960 CE responded positively to temperature (20.8 ± 3.7 Mio km2; 25.9 ± 4.6%), precipitation (77.5 ± 3.3 Mio km2; 96.4 ± 4.1%), and other parameters. The spatial manifestation of this climate response is determined by latitudinal and altitudinal temperature gradients, indicating that warming leads to geographic shifts in growth limitations. We observed a significant (P < 0.001) decrease in temperature response at cold-dry sites between 1930–1960 and 1960–1990 CE, and the total temperature-limited area shrunk by −8.7 ± 0.6 Mio km2. Simultaneously, trees became more limited by atmospheric water demand almost worldwide. These changes occurred under mild warming, and we expect that continued climate change will trigger a major redistribution in growth responses to climate.

Babst, Flurin↗

NASA NTRS2020

The Role of the SO2 Radiative Effect in Sustaining the Volcanic Winter and Soothing the Toba Impact on Climate

Volcanic eruptions are an important climate driver. The impact of Pinatubo-sized eruptions has been observed and is well constrained. The magnitude and duration of volcanic winter effects after super-eruptions such as Toba remain disputed due to disagreement between the strong cooling predicted by models, and much milder climate perturbations according to the paleo data. Here we present a re-evaluated climate impact of a Toba-sized super-eruption based on up-to-date GISS ModelE simulations. In this study, we account for all known primary mechanisms that govern the evolution of the volcanic plume and their nonlinear interactions. The SO2 radiative effects are evaluated for the first time in coupled climate simulations with the interactive atmospheric chemistry module. We found that SO2 effects on photochemistry, dynamics, and radiative forcing are especially prominent. Due to strong absorption in ultraviolet, SO2 feedback on photochemistry partially offsets the limiting effect associated with aerosol microphysical processes. SO2 greenhouse warming soothes the radiative cooling exerted by sulfate aerosols. SO2 absorption in the shortwave and longwave causes radiative heating and lofting of the volcanic plume, and boosts the efficiency of SO2 impact on photochemistry. Our analysis shows that SO2 lifetime and magnitude of effects scale up and increase with the amount of emitted material. For a Pinatubo-sized eruption, SO2 feedbacks on chemistry and dynamics are relevant only during the initial stage of the volcanic plume evolution, while local SO2 concentrations are high. For a Toba-sized eruption, SO2 effects are as important as sulfate aerosols, and produce a less extreme volcanic winter.

Sergey Osipov↗

NASA NTRS2020

Possible Climate Histories of Venus Type Worlds

There are two well-known scenarios for Venus’ climate evolution. In one Venus had a long-lived magma ocean phase in its first 100Myr with a steam and CO2 dominated atmosphere. The faint young sun with its high XUV flux would cause photodissociation of the steam atmosphere and hydrodynamic escape would cause most of the hydrogen to escape & left-over oxygen would be absorbed by the magma ocean. Hence Venus would have started out hot and dry and the high D/H ratio measured by Pioneer Venus would be from this period of water loss. The other scenario is that Venus’ magma ocean lifetime would have been roughly the same length of time as Earth’s (~1Myr) and water would have condensed on its surface in its early history and had a short period of habitability before increasing solar insolation through time drove it into a runaway greenhouse. However, results from 2016 showed that if Venus remains in the slowly rotating climate dynamics regime (as seen in exoplanet related climate studies) its cloud albedo feedback would have kept it temperate for possibly billions of years. The only way to confirm which one of these scenarios occurred for Venus is to visit it and make the necessary measurements of noble and volatile gases. But exoplanet observations of young exo-Venus type worlds around young F,G,K dwarf stars may constrain which scenario is more probable for a population of such planets. We present a vision of Venus’ climate history that places it and its exoVenus cousins in an ‘Optimistic Venus Zone’ for ~3 billion years within the conventionally named ‘Venus Zone’ and hence encourage the exoplanet communit as possible habitable environments.

Way, M. J.↗

NASA NTRS2020

Analyzing Changes in the Complexity of Climate in the Last Four Decades Using MERRA-2 Radiation Data

The energy balance of the Earth is controlled by the shortwave and longwave radiation emitted to space. Changes in the thermodynamic state of the system over time afect climate and are noticeable when viewing the system as a whole. In this paper, we study the changes in the complexity of climate in the last four decades using data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). First, we study the complexity of the shortwave and longwave radiation felds independently using Approximate Entropy and Sample Entropy, observing that the rate of complexity change is faster for shortwave radiation. Then, we study the causality of those changes using Transfer Entropy to capture the non-linear dynamics of climate, showing that the changes are mainly driven by the variations in shortwave radiation. The observed behavior of climatic complexity could be explained by the changes in cloud amount, and we research that possibility by investigating its evolution from a complexity perspective using data from the International Satellite Cloud Climatology Project (ISCCP).

Delgado-Bonal, Alfonso↗

NASA NTRS2020

Observational Constraints on the Effective Climate Sensitivity from the Historical Period

The observed warming in the atmosphere and ocean can be used to estimate the climate sensitivity linked to present-day feedbacks, which is referred to as the effective climate sensitivity (Shist). However, such an estimate is affected by uncertainty in the radiative forcing, particularly aerosols, over the historical period. Here, we make use of detection and attribution techniques to derive the surface air temperature and ocean warming that can be attributed directly to greenhouse gas increases. These serve as inputs to a simple energy budget to infer the likelihood of Shist in response to observed greenhouse gases increases over two time periods (1862–2012 and 1955–2012). The benefit of using greenhouse gas attributable quantities is that they are not subject to uncertainties in the aerosol forcing (other than uncertainty in the attribution to greenhouse gas versus aerosol forcing not captured by the multi-model aerosol response pattern). The resulting effective climate sensitivity estimate, Shist, ranges from 1.3 °Cto 3.1 °C(5%–95% range) over the full instrumental period (1862–2012) for our best estimate, and gets slightly wider when considering further uncertainties. This estimate increases to 1.7 °C–4.6 °C if using the shorter period (1955–2012).We also evaluate the climate model simulated surface air temperature and ocean heat content increase in response to greenhouse gas forcing over the same periods, and compare them with the observationally-constrained values.We find that that the ocean warming simulated in greenhouse gas only simulations in models considered here is consistent with that attributed to greenhouse gas increases from observations, while one model simulates more greenhouse gas-induced surface air warming than observed. However, other models with sensitivity outside our range show greenhouse gas warming that is consistent with that attributed in observations, emphasising that feedbacks during the historical period may differ from the feedbacks at CO2 doubling and from those at true equilibrium.

Tokarska, Katarzyna B↗

NASA NTRS2020

Historical (1850‐2014) Aerosol Evolution and Role on Climate Forcing Using the GISS Modele2.1 Contribution to CMIP6

The Earth’s climate is rapidly changing. Over the past centuries, aerosols, via their ability to absorb or scatter solar radiation and alter clouds, played an important role in counterbalancing some of the greenhouse gas (GHG) caused global warming. The multi-century anthropogenic aerosol cooling effect prevented present-day climate from reaching even higher surface air temperatures and subsequent more dramatic climate impacts. Trends in aerosol concentrations and optical depth show that in many polluted regions such as Europe and the United States of America, aerosol precursor emissions decreased back to levels of the 1950s. More recent polluting countries such as China may have reached a turning point in recent years as well, while India still follows an upward trend. Here we study aerosol trends in the CMIP6 simulations of the GISS ModelE2.1 climate model using a fully coupled atmosphere composition onfiguration, including interactive gas-phase chemistry, and either an aerosol microphysical (MATRIX) or a mass-based (OMA) aerosol module. Results show that whether global aerosol radiative forcing is already declining depends on the aerosol scheme used. Using the aerosol microphysical scheme, where the aerosol system reacts more strongly to the trend in sulfur dioxide (SO2) emissions, global peak direct aerosol forcing was reached in the 1980’s, whereas the mass-based scheme simulates peak direct aerosol forcing around 2010.

Aerosol forcing↗

NASA NTRS2021

Non-Monotonic Response of the Climate System to Abrupt CO2 Forcing

We explore the climate system response to abrupt CO2 forcing, spanning the range 1 × to 8×CO2, with two state-of-the-art coupled atmosphere-ocean-sea-ice-land models: the NASA Goddard Institute for Space Studies Model E2.1-G (GISS-E2.1-G) and the Community Earth System Model (CESM-LE). We find that the effective climate sensitivity is a non-monotonic function of CO2 in both models, reaching a minimum at 3×CO2 for GISS-E2.1-G, and 4×CO2 for CESM-LE. A similar non-monotonic response is found in Northern Hemisphere surface temperature, sea-ice, precipitation, the latitude of zero precipitation minus-evaporation, and the strength of the Hadley cell. Interestingly, the Atlantic meridional overturning circulation collapses when non-monotonicity appears and does not recover for larger CO2 forcings. Analyzing the climate response over the same CO2 range with slab ocean versions of the same models, we demonstrate that the climate system's non-monotonic response is linked to ocean dynamics.

Non-monotonic response↗

NASA NTRS2020

The Resilience of Habitable Climates Around Circumbinary Stars

Here we use a 3‐D climate system model to study the habitability of Earth‐like planets orbiting in circumbinary systems. In the most extreme cases, Earth‐like planets in circumbinary systems could experience variations in the incident stellar flux of up to ~50% on ~100‐day timescales. However, we find that Earth‐like planets, having abundant surface liquid water, are generally effective at buffering against these time‐dependent changes in the stellar irradiation due to the high thermal inertia of oceans compared with the relatively short periods of circumbinary‐driven variations in the received stellar flux. Ocean surface temperatures exhibit little to no variation in time; however, land surfaces can experience modest changes in temperature, thus exhibiting an additional mode of climate variability driven by the circumbinary variations. Still, meaningful oscillations in surface temperatures are only found for circumbinary system architectures featuring the largest physically possible amplitudes in the stellar flux variation. In the most extreme cases, an Earth‐like planet could experience circumbinary‐driven variations in the global mean land surface temperature of up to ~5 K, and variations of local daytime maximum temperatures of up to ~12 K on seasonal timescales, while the global mean ocean temperatures vary by less than ~2 K. Such seasonal temperature swings over land areas could potentially pose adaptability challenges for extant life. Still, habitable planets in circumbinary systems appear to be remarkably resilient against circumbinary‐driven climate variations and can avoid any true climate catastrophes.

Eric T Wolf↗

NASA NTRS2020

Attribution of Chemistry-Climate Model Initiative (CCMI) Ozone Radiative Flux Bias from Satellites

The top-of-atmosphere (TOA) outgoing longwave flux over the 9.6-μm ozone band is a fundamental quantity for understanding chemistry-climate coupling. However, observed TOA fluxes are hard to estimate as they exhibit considerable variability in space and time that depend on the distributions of clouds, ozone (O3), water vapor (H2O), air temperature (Ta), and surface temperature (Ts). Benchmarking present day fluxes and quantifying the relative influence of their drivers is the first step for estimating climate feedbacks from ozone radiative forcing and predicting radiative forcing evolution. To that end, we constructed observational instantaneous radiative kernels (IRKs) under clear-sky conditions, representing the sensitivities of the TOA flux in the 9.6-μm ozone band to the vertical distribution of geophysical variables, including O3, H2O, Ta, and Ts based upon the Aura Tropospheric Emission Spectrometer (TES) measurements. Applying these kernels to present-day simulations from the Chemistry-Climate Model Initiative (CCMI) project as compared to a 2006 reanalysis assimilating satellite observations, we show that the models have large differences in TOA flux, attributable to different geophysical variables. In particular, model simulations continue to diverge from observations in the tropics, as reported in previous studies of the Atmospheric Chemistry Climate Model Inter-comparison Project (ACCMIP) simulations. The principal culprits are tropical mid and upper tropospheric ozone followed by tropical lower tropospheric H2O. Five models out of the eight studied here have TOA flux biases exceeding 100 mWm-2 attributable to tropospheric ozone bias. Another set of five models have flux biases over 50 mWm-2 due to H2O. On the other hand, Ta radiative bias is negligible in all models (no more than 30 mWm-2). We found that AM3 and CMAM have the lowest TOA flux biases globally but are a result of cancellation of opposite biases due to difference processes. Overall, the multi-model ensemble mean bias is –133±98 mWm-2, indicating that they are too atmospherically opaque due to trapping too much radiation in the atmosphere by overestimated tropical tropospheric O3 and H2O. Having too much O3 and H2O in the troposphere would have different impacts on the sensitivity of TOA flux to O3 and these competing effects add more uncertainties on the ozone radiative forcing. We find that the inter-model TOA outgoing longwave radiation (OLR) difference is well anti-correlated with their ozone band flux bias. This suggests that there is significant radiative compensation in the calculation of model outgoing longwave radiation.

Aura Tropospheric Emission Spectrometer (TES) meas↗

NASA NTRS2021

Cold Season Performance of the NU-WRF Regional Climate Model in the Great Lakes Region

As Earth’s largest collection of freshwater, the Laurentian Great Lakes have enormous ecological and socio-economic value. Their basin has become a regional hotspot of climatic and limnological change, potentially threatening its vital natural resources. Consequentially, there is a need to assess the current state of climate models regarding their performance across the Great Lakes region and develop the next generation of high-resolution regional climate models to address complex limnological processes and lake-atmosphere interactions. In response to this need, the current paper focuses on the generation and analysis of a 20-member ensemble of 3-km National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (NU-WRF) simulations for the 2014-2015 cold season. The study aims to identify the model’s strengths and weaknesses; optimal configuration for the region; and the impacts of different physics parameterizations, coupling to a 1D lake model, time-variant lake-surface temperatures, and spectral nudging. Several key biases are identified in the cold-season simulations for the Great Lakes region, including an atmospheric cold bias that is amplified by coupling to a 1D lake model but diminished by applying the Community Atmosphere Model radiation scheme and Morrison microphysics scheme; an excess precipitation bias; anomalously early initiation of fall lake turnover and subsequent cold lake bias; excessive and overly persistent lake ice cover; and insufficient evaporation over Lakes Superior and Huron. The research team is currently addressing these key limitations by coupling NU-WRF to a 3D lake model in support of the next generation of regional climate models for the critical Great Lakes Basin.

Michael Notaro↗