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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.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Pacific Tropical Decadal Variability Challenge for Climate Models

Understanding and forecasting Tropical Pacific Decadal-scale Variability (TPDV) strongly rely on climate model simulations. Using a Linear Inverse Modeling (LIM) diagnostic approach, we reveal Coupled Model Intercomparison Project Phase 6 models have significant challenges in reproducing the spatial structure and dominant mechanisms of TPDV. Specifically, while the models' ensemble mean pattern of TPDV resembles that of observations, the spread across models is very large and most models show significant differences from observations. In observations, removing the coupling between extratropics and tropics reduces TPDV by ~60%–70%, and removing the tropical thermocline variability makes the central tropical Pacific a key center of action for TPDV and El Niño Southern Oscillation variability. These characteristics are only confirmed in a subset of models. Differences between observations and simulations are outside the range of natural internal TPDV noise and pose important questions regarding our ability to model the impacts of natural internal low-frequency variability superimposed on long-term climate change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Test Plan for a Calibration Demonstration System for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change. One of the major objectives of CLARREO is to advance the accuracy of SI traceable absolute calibration at infrared and reflected solar wavelengths. This advance is required to reach the on-orbit absolute accuracy required to allow climate change observations to survive data gaps while remaining sufficiently accurate to observe climate change to within the uncertainty of the limit of natural variability. While these capabilities exist at NIST in the laboratory, there is a need to demonstrate that it can move successfully from NIST to NASA and/or instrument vendor capabilities for future spaceborne instruments. The current work describes the test plan for the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. The goal of the CDS is to allow the testing and evaluation of calibration approaches , alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result of efforts with the SOLARIS CDS will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections. The CLARREO mission addresses the need to observe high-accuracy, long-term climate change trends and advance the accuracy of SI traceable absolute calibration. The current work describes the test plan for the SOLARIS which is the calibration demonstration system for the reflected solar portion of CLARREO. SOLARIS provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections.

Thome, Kurtis↗
NASA NTRSDate not supplied

Ocean-Land Teleconnections and Chaotic Atmospheric Variability in Climate Models, with Implications for Real-World Behavior

This study introduces a unique approach to estimating a fundamental but unmeasurable property of Nature: ρo 2 , the fraction of the variance of a given meteorological variable that is determined by boundary forcing (specifically, SSTs) as opposed to chaotic atmospheric dynamics. Here, we focus on continental monthly-averaged near-surface air temperature, or T2M. Rather than determining the fractions of SST-explained T2M variance found for a specific atmospheric general circulation model (AGCM) and then assuming that these fractions also represent Nature, we perform an analysis that entails: (i) evaluating a specific AGCM’s ability to capture observed variability with an infinite number of ensemble members, (ii) quantifying the degree to which different modeling systems agree on SST-land teleconnections, and (iii) combining these results into our novel estimates of ρo 2 . The derived ρo 2 fields suggest, with caveats, that AGCMs tend to overestimate the fraction of explained T2M variance (the signal-to-total variance ratio) in the Tropics.

Randal D Koster↗
DOE OSTI2021

Effect of elevation, season and accelerated snowmelt on biogeochemical processes during isolated conifer needle litter decomposition

Increased drought and temperatures associated with climate change have implications for ecosystem stress with risk for enhanced carbon release in sensitive biomes. Litter decomposition is a key component of biogeochemical cycling in terrestrial ecosystems, but questions remain regarding the local response of decomposition processes to climate change. This is particularly complex in mountain ecosystems where the variable nature of the slope, aspect, soil type, and snowmelt dynamics play a role. Hence, the goal of this study was to determine the role of elevation, soil type, seasonal shifts in soil moisture, and snowmelt timing on litter decomposition processes. Experimental plots containing replicate deployments of harvested lodgepole and spruce needle litter alongside needle-free controls were established in open meadows at three elevations ranging from 2,800–3,500 m in Crested Butte, Colorado. Soil biogeochemistry variables including gas flux, porewater chemistry, and microbial ecology were monitored over three climatically variable years that shifted from high monsoon rains to drought. Results indicated that elevation and soil type influenced baseline soil biogeochemical indicators; however, needle mass loss and chemical composition were consistent across the 700 m elevation gradient. Rates of gas flux were analogously consistent across a 300 m elevation gradient. The additional variable of early snowmelt by 2–3 weeks had little impact on needle chemistry, microbial composition and gas flux; however, it did result in increased dissolved organic carbon in lodgepole porewater collections suggesting a potential for aqueous export. In contrast to elevation, needle presence and seasonal variability of soil moisture and temperature both played significant roles in soil carbon fluxes. Furthermore, during a pronounced period of lower moisture and higher temperatures, bacterial community diversity increased across elevation with new members supplanting more dominant taxa. Microbial ecological resilience was demonstrated with a return to pre-drought structure and abundance after snowmelt rewetting the following year. These results show similar decomposition processes across a 700 m elevation gradient and reveal the sensitivity but resilience of soil microbial ecology to low moisture conditions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2005

Revealing Relationships among Relevant Climate Variables with Information Theory

The primary objective of the NASA Earth-Sun Exploration Technology Office is to understand the observed Earth climate variability, thus enabling the determination and prediction of the climate's response to both natural and human-induced forcing. We are currently developing a suite of computational tools that will allow researchers to calculate, from data, a variety of information-theoretic quantities such as mutual information, which can be used to identify relationships among climate variables, and transfer entropy, which indicates the possibility of causal interactions. Our tools estimate these quantities along with their associated error bars, the latter of which is critical for describing the degree of uncertainty in the estimates. This work is based upon optimal binning techniques that we have developed for piecewise-constant, histogram-style models of the underlying density functions. Two useful side benefits have already been discovered. The first allows a researcher to determine whether there exist sufficient data to estimate the underlying probability density. The second permits one to determine an acceptable degree of round-off when compressing data for efficient transfer and storage. We also demonstrate how mutual information and transfer entropy can be applied so as to allow researchers not only to identify relations among climate variables, but also to characterize and quantify their possible causal interactions.

Knuth, Kevin H.↗
DOE OSTI2025

Radiative forcing from the 2020 shipping fuel regulation is large but hard to detect

Reduction in aerosol cooling unmasks greenhouse gas warming, exacerbating the rate of future warming. The strict sulfur regulation on shipping fuel implemented in 2020 (IMO2020) presents an opportunity to assess the potential impacts of such emission regulations and the detectability of deliberate aerosol perturbations for climate intervention. Here we employ machine learning to capture cloud natural variability and estimate a radiative forcing of +0.074 ±0.005 W m -2 related to IMO2020 associated with changes in shortwave cloud radiative effect over three low-cloud regions where shipping routes prevail. We find low detectability of the cloud radiative effect of this event, attributed to strong natural variability in cloud albedo and cloud cover. Regionally, detectability is higher for the southeastern Atlantic stratocumulus deck. These results raise concerns that future reductions in aerosol emissions will accelerate warming and that proposed deliberate aerosol perturbations such as marine cloud brightening will need to be substantial in order to overcome the low detectability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Characterization of wood fiber insulation for the development of wood fiber-insulated panels (WIPs) for use in building envelope

Wood fiber insulation (WFI) was studied as an eco-friendly alternative for fossil-based building insulation, focusing on its use in new wood fiber-insulated panels (WIPs). Rigid WFI boards with densities of 110, 140, and 180 kg/m³, including a 140 kg/m³ variant without paraffin wax, were evaluated. Key properties investigated included porosity, water vapor transmission, liquid water adsorption, and thermal conductivity. The porosity ranged between 85 and 92%, primarily influenced by density. Water vapor permeability ranged from 65 to 90 ng·s-1m-1Pa-1, while liquid water absorption was between 2.5 and 20% by volume, influenced by both wax and density. The thermal conductivity coefficient ranged from 0.038 to 0.055 W/(m·K). Bond strength tests with WFI (140 kg/m³ with wax) laminated to various materials using structural adhesives showed tensile perpendicular-to-grain strengths of 10 to 16 kPa and shear strengths of 60 to 90 kPa, with failure only occurring within the WFI. It was concluded that WFI is a promising material for novel WIPs, offering competitive hygrothermal properties and compatibility with structural adhesives. However, its bio-based nature suggests variability and complexity, necessitating further rigorous testing in various climates and in more complex assemblies.

Materials Science↗
NASA NTRS2005

Attribution of Recovery in Lower-Stratospheric Ozone

Multiple satellite and ground-based observations provide consistent evidence that the thickness of Earth's protective ozone layer has stopped declining since 1997, close to the time of peak stratospheric halogen loading. Regression analyses with Effective Equivalent Stratospheric Chlorine (EESC) in conjunction with further analyses using more sophisticated photochemical model calculations constrained by satellite data demonstrate that the cessation of ozone depletion between 18-25 km altitude is consistent with a leveling off of stratospheric abundances of chlorine and bromine, due to the Montreal Protocol and its amendments. However, ozone increases in the lowest part of the stratosphere, from the tropopause to 18 km, account for about half of the improvement in total column ozone during the past 9 years at northern hemisphere mid-latitudes. The increase in ozone for altitudes below 18 km is most likely driven by changes in transport, rather than driven by declining chlorine and bromine. Even with this evidence that the Montreal Protocol and its amendments are having the desired, positive effect on ozone above 18 km, total column ozone is recovering faster than expected due to the apparent transport driven changes at lower altitudes. Accurate prediction of future levels of stratospheric ozone will require comprehensive understanding of the factors that drive temporal changes at various altitudes, and partitioning of the recent transport-driven increases between natural variability and changes in atmospheric structure perhaps related to anthropogenic climate change.

Yang, Eun-Su↗
NASA NTRS2006

Attribution of Recovery in Lower-stratospheric Ozone

Multiple satellite and ground-based observations provide consistent evidence that the thickness of Earth's protective ozone layer has stopped declining since 1997, close to the time of peak stratospheric halogen loading. Regression analyses with Effective Equivalent Stratospheric Chlorine (EESC) in conjunction with further analyses using more sophisticated photochemical model calculations constrained by satellite data demonstrate that the cessation of ozone depletion between 18-25 km altitude is consistent with a leveling off of stratospheric abundances of chlorine and bromine, due to the Montreal Protocol and its amendments. However, ozone increases in the lowest part of the stratosphere, from the tropopause to 18 km, account for about half of the improvement in total column ozone during the past 9 years at northern hemisphere mid-latitudes. The increase in ozone for altitudes below 18 km is most likely driven by changes in transport, rather than driven by declining chlorine and bromine. Even with this evidence that the Montreal Protocol and its amendments are having the desired, positive effect on ozone above 18 km, total column ozone is recovering faster than expected due to the apparent transport driven changes at lower altitudes. Accurate prediction of future levels of stratospheric ozone will require comprehensive understanding of the factors that drive temporal changes at various altitudes, and partitioning of the recent transport-driven increases between natural variability and changes in atmospheric structure perhaps related to anthropogenic climate change.

Yang, Eun-Su↗
NASA NTRS2011

Observation of Hydrological Processes Using Remote Sensing: Volume 2: The Science of Hydrology - Chapter 2.14

Improving water management can make a significant contribution to achieving most of the Millennium Development Goals established by the UN General Assembly in 2000, especially those related to poverty, hunger, and major diseases. The World Summit on Sustainable Development (WSSD) in 2002 recognized this need. Water and sanitation in particular received great attention from the Summit. The Johannesburg Plan of Implementation recommended to improve water resources management and scientific understanding of the water cycle through joint cooperation and research. For this purpose, it is recommended to promote knowledge sharing, provide capacity building, and facilitate the transfer of technology including remote-sensing (RS) and satellite technologies, especially to developing countries and countries with economies in transition, and to support these countries in their efforts to monitor and assess the quantity and quality of water resources, for example, by establishing and/or further developing national monitoring networks and water resources databases and by developing relevant national indicators. The Johannesburg Plan also adopted integrated water resources management as the overarching concept in addressing and solving water-related issues. As a result of the commitments made in the Johannesburg Plan of Implementation, several global and regional initiatives have emerged. Current international initiatives such as the Global Monitoring for Environment and Security (GMES) program of the European Commission and the European Space Agency (ESA), and the Global Earth Observation System of Systems (GEOSS) 10-Year Implementation Plan, have all identified Earth observation (EO) of the water cycle as the key in helping to solve the world s water problems. The availability of spatial information on water quantity and quality will also enable closure of the water budget at river basin and continental scales to the point where effective water management is essential (e.g., as requested by the European Union s Water Framework Directive (WFD), as well as national policies). Geo-information science and EO are vital in achieving a better understanding of the water cycle and better monitoring, analysis, prediction, and management of the world s water resources. The major components of the water cycle of the Earth system and their possible observations are presented. Such observations are essential to understand the global water cycle and its variability, both spatially and temporally, and can only be achieved consistently by means of EOs. Additionally, such observations are essential to advance our understanding of coupling between the terrestrial, atmospheric, and oceanic branches of the water cycle, and how this coupling may influence climate variability and predictability. Water resources management directly interferes with the natural water cycle in the forms of building dams, reservoirs, water transfer systems, and irrigation systems that divert and redistribute part of the water storages and fluxes on land. The water cycle is mainly driven and coupled to the energy cycle in terms of phase changes of water (changes among liquid, water vapor, and solid phases) and transport of water by winds in addition to gravity and diffusion processes. The water-cycle components can be observed with in situ sensors as well as airborne and satellite sensors in terms of radiative quantities. Processing and conversion of these radiative signals are necessary to retrieve the water-cycle components.

Wilder, Peter↗
DOE OSTI2022

A Bayesian Deep Learning Approach to Near-Term Climate Prediction

Since model bias and associated initialization shock are serious shortcomings that reduce prediction skills in state-of-the-art decadal climate prediction efforts, we pursue a complementary machine-learning-based approach to climate prediction. The example problem setting we consider consists of predicting natural variability of the North Atlantic sea surface temperature on the interannual timescale in the pre-industrial control simulation of the Community Earth System Model. While previous works have considered the use of recurrent networks such as convolutional LSTMs and reservoir computing networks in this and other similar problem settings, we currently focus on the use of feedforward convolutional networks. In particular, we find that a feedforward convolutional network with a Densenet architecture is able to outperform a convolutional LSTM in terms of predictive skill. Next, we go on to consider a probabilistic formulation of the same network based on Stein variational gradient descent and find that in addition to providing useful measures of predictive uncertainty, the probabilistic (Bayesian) version improves on its deterministic counterpart in terms of predictive skill. Finally, we characterize the reliability of the ensemble of machine learning models obtained in the probabilistic setting by using analysis tools developed in the context of ensemble numerical weather prediction.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Variability of Clouds Over a Solar Cycle

One of the most controversial aspects of climate studies is the debate over the natural and anthropogenic causes of climate change. Historical data strongly suggest that the Little Ice Age (from 1550 to 1850 AD when the mean temperature was colder by about 1 C) was most likely caused by variability of the sun and not greenhouse molecules (e.g., CO2). However, the known variability in solar irradiance and modulation of cosmic rays provides too little energy, by many orders of magnitude, to lead to climate changes in the troposphere. The conjecture is that there is a 'trigger mechanism'. This idea may now be subjected to a quantitative test using recent global datasets. Using the best available modern cloud data from International Satellite Cloud Climatology Project (ISCCP), Svensmark and Friis-Christensen found a correlation of a large variation (3-4%) in global cloud cover with the solar cycle. The work has been extended by Svensmark and Marsh and Svensmark. The implied forcing on climate is an order of magnitude greater than any previous claims. Are clouds the long sought trigger mechanism? This discovery is potentially so important that it should be corroborated by an independent database, and, furthermore, it must be shown that alternative explanations (i.e., El Nino) can be ruled out. We used the ISCCP data in conjunction with the Total Ozone Mapping Spectrometer (TOMS) data to carry out in in depth study of the cloud trigger mechanism.

Yung, Yuk L.↗
NASA NTRSDate not supplied

Generating a 4D Global CH(4) Product by Assimilating TROPOMI column CH(4) in NASA’s GEOS GCM

Examination of temporal and spatial CH4 variability is crucial for better understanding the human and natural processes driving climate change and ultimately designing mitigation strategies. Here we present an analysis framework that uses NASA’s GEOS General Circulation Model (GCM) to construct a high-resolution, time varying picture of atmospheric CH4 consistent with measurements from a variety of platforms, both in situ and remotely sensed. The resulting time varying atmospheric CH4 product can (i) support interpretation of high-resolution point source detection approaches, (ii) provide reanalysis fields for CH4 and other greenhouse gases, and (iii) supply boundary conditions for regional models. Our approach starts with a set of CH4 emissions from various inventories that have been adjusted to match the global annual growth rate over recent decades. These emissions are transported by the GEOS GCM, which in turn is constrained by meteorology from NASA’s Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) product. The simulated atmospheric field is compared with CH4 measurements, such as those from the TROPOspheric Monitoring Instrument (TROPOMI), and adjustments calculated following a Bayesian protocol. The accuracy of the resultant optimal atmospheric CH4 field can be demonstrated by its improved agreement (compared to a direct simulation of the CH4 inventories) with a host of independent CH4 measurements, such as those from the Total Carbon Column Observation Network (TCCON) and in situ observations from surface and airborne platforms.

Nikolay V. Balashov↗
NASA NTRS1978

Internally and externally caused climate change

A numerical climate model is used to simulate climate change forced only by random fluctuations of the atmospheric heat transport. This short-term natural variability of the atmosphere is shown to be a possible 'cause' not only of the variability of the annual world average temperature about its mean, but also long-term excursions from the mean. Various external causes of climate change are also tested with the model and the results compared with observations for the past 100 years. Volcanic dust is shown to have been an important cause of climate change, while the effects of sunspot-related solar constant variation and anthropogenic forcing are not evident.

Robock, A.↗
NASA NTRS2018

A Reconstruction of Global Hydroclimate and Dynamical Variables Over the Common Era

Hydroclimate extremes critically affect human and natural systems, but there remain many unanswered questions about their causes and how to interpret their dynamics in the past and in climate change projections. These uncertainties are due, in part, to the lack of long-term, spatially resolved hydroclimate reconstructions and information on the underlying physical drivers for many regions. Here we present the first global reconstructions of hydroclimate and associated climate dynamical variables over the past two thousand years. We use a data assimilation approach tailored to reconstruct hydroclimate that optimally combines 2,978 paleoclimate proxy-data time series with the physical constraints of an atmosphere?ocean climate model. The global reconstructions are annually or seasonally resolved and include two spatiotemporal drought indices, near-surface air temperature, an index of North Atlantic variability, the location of the intertropical convergence zone, and monthly Nino indices. This database, called the Paleo Hydrodynamics Data Assimilation product (PHYDA), will provide a critical new platform for investigating the causes of past climate variability and extremes, while informing interpretations of future hydroclimate projections.

Natural hazards↗
DOE OSTI2023

Evaluation of global teleconnections in CMIP6 climate projections using complex networks

In climatological research, the evaluation of climate models is one of the central research subjects. As an expression of large-scale dynamical processes, global teleconnections play a major role in interannual to decadal climate variability. Their realistic representation is an indispensable requirement for the simulation of climate change, both natural and anthropogenic. Therefore, the evaluation of global teleconnections is of utmost importance when assessing the physical plausibility of climate projections. We present an application of the graph-theoretical analysis tool δ-MAPS, which constructs complex networks on the basis of spatio-temporal gridded data sets, here sea surface temperature and geopotential height at 500 hPa. Complex networks complement more traditional methods in the analysis of climate variability, like the classification of circulation regimes or empirical orthogonal functions, assuming a new non-linear perspective. While doing so, a number of technical tools and metrics, borrowed from different fields of data science, are implemented into the δ-MAPS framework in order to overcome specific challenges posed by our target problem. Those are trend empirical orthogonal functions (EOFs), distance correlation and distance multicorrelation, and the structural similarity index. δ-MAPS is a two-stage algorithm. In the first place, it assembles grid cells with highly coherent temporal evolution into so-called domains. In a second step, the teleconnections between the domains are inferred by means of the non-linear distance correlation. We construct 2 unipartite and 1 bipartite network for 22 historical CMIP6 climate projections and 2 century-long coupled reanalyses (CERA-20C and 20CRv3). Potential non-stationarity is taken into account by the use of moving time windows. The networks derived from projection data are compared to those from reanalyses. Our results indicate that no single climate projection outperforms all others in every aspect of the evaluation. But there are indeed models which tend to perform better/worse in many aspects. Differences in model performance are generally low within the geopotential height unipartite networks but higher in sea surface temperature and most pronounced in the bipartite network representing the interaction between ocean and atmosphere.

58 GEOSCIENCES↗
NASA NTRS2021

Effect of volcanic emissions on clouds during the 2008 and 2018 Kilauea degassing events

Volcanic eruptions in otherwise clean environments are “natural experiments” wherein the effects of aerosol emissions on clouds and climate can be partitioned from meteorological variability and anthropogenic activities. In this work, we combined satellite retrievals, reanalysis products, and atmospheric modeling to analyze the mechanisms of aerosol–cloud interactions during two degassing events at the Kilauea volcano in 2008 and 2018. The eruptive nature of the 2008 and 2018 degassing events was distinct from long-term volcanic activity for Kilauea. Although previous studies assessed the modulation of cloud properties from the 2008 event, this is the first time such an analysis has been reported for the 2018 event and that multiple degassing events have been analyzed and compared at this location. Both events resulted in significant changes in cloud effective radius and cloud droplet number concentration that were decoupled from local meteorology and in line with an enhanced cloud albedo. However, it is likely that the effects of volcanic emissions on liquid water path and cloud fraction were largely offset by meteorological variability. Comparison of cloud anomalies between the two events suggested a threshold response of aerosol–cloud interactions to overcome meteorological effects, largely controlled by aerosol loading. In both events, the ingestion of aerosols within convective parcels enhanced the detrainment of condensate in the upper troposphere, resulting in deeper clouds than observed under pristine conditions. Accounting for ice nucleation on ash particles led to enhanced ice crystal concentrations at cirrus levels and a slight decrease in ice water content, improving the correlation of the model results with the satellite retrievals. Overall, aerosol loading, plume characteristics, and meteorology contributed to changes in cloud properties during the Kilauea degassing events.

Katherine H. Breen↗
NASA NTRS1993

A discussion of plausible solar irradiance variations, 1700-1992

From satellite observations the solar total irradiance is known to vary. Sunspot blocking, facular emission, and network emission are three identified causes for the variations. In this paper we examine several different solar indices measured over the past century that are potential proxy measures for the Sun's irradiance. These indices are (1) the equatorial solar rotation rate, (2) the sunspot structure, the decay rate of individual sunspots, and the number of sunspots without umbrae, and (3) the length and decay rate of the sunspot cycle. Each index can be used to develop a model for the Sun's total irradiance as seen at the Earth. Three solar indices allow the irradiance to be modeled back to the mid-1700s. The indices are (1) the length of the solar cycle, (2) the normalized decay rate of the solar cycle, and (3) the mean level of solar activity. All the indices are well correlated, and one possible explanation for their nearly simultaneous variations is changes in the Sun's convective energy transport. Although changes in the Sun's convective energy transport are outside the realm of normal stellar structure theory (e.g., mixing length theory), one can imagine variations arising from even the simplest view of sunspots as vertical tubes of magnetic flux, which would serve as rigid pillas affecting the energy flow patterns by ensuring larger-scale eddies. A composite solar irradiance model, based upon these proxies, is compared to the northern hemisphere temperature depatures for 1700-1992. Approximately 71% of the decadal variance in the last century can be modeled with these solar indices, although this analysis does not include anthropogenic or other variations which would affect the results. Over the entire three centuries, approx. 50% of the variance is modeled. Both this analysis and previous similar analyses have correlations of model solar irradiances and measured Earth surface temperatures that are significant at better than the 95% confidence level. To understand our present climate variations, we must place the anthropogenic variations in the context of natural variability from solar, volcanic, oceanic, and other sources.

Hoyt, Douglas V.↗