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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Monitoring of mechanical changes in a pipe assembly with complex geometry using multi-mode acoustic signals

Guided wave ultrasonic testing has been widely used for nondestructive and long-range evaluation of diverse mechanical structures, such as pipes and plates. In general, a large number of guided wave modes exist even in the simplest geometries, and they exhibit highly dispersive characteristics. Thus, sophisticated excitation methods and elaborate modal analyses need to be implemented to excite, acquire, and process well-defined pure modes as part of such a measurement method. If the interrogated structure has complex geometry, for example, with cross-sectional variations or multiple joints, the utilization of pure modes becomes significantly more difficult. To overcome this difficulty, this paper proposes the use of multi-mode, multi-frequency guided waves for long-range inspection of structures with arbitrarily complex geometries. Furthermore, using broadband chirp signals and multi-mode time–frequency analysis in a prototypical complex pipe assembly that includes multiple pipe diameters, elbows, and flange connections, we experimentally show sensitive detection of mechanical changes (both material addition and loss). In addition, we demonstrate that the complexity of the structure can be modeled in the digital domain with sufficient detail to allow accurate numerical simulation of the acoustic response using this method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2012

Study of Movement and Seepage Along Levees Using DINSAR and the Airborne UAVSAR Instrument

We have studied the utility of high resolution SAR (synthetic aperture radar) for levee monitoring using UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) data collected along the dikes and levees in California's Sacramento-San Joaquin Delta and along the lower Mississippi River. Our study has focused on detecting and tracking changes that are indicative of potential problem spots, namely deformation of the levees, subsidence along the levee toe, and seepage through the levees, making use of polarimetric and interferometric SAR techniques. Here was present some results of those studies, which show that high resolution, low noise SAR imaging could supplement more traditional ground-based monitoring methods by providing early indicators of seepage and deformation.

levee health↗
NASA NTRS2005

Evaluation of Chemistry-Climate Model Results using Long-Term Satellite and Ground-Based Data

Chemistry-climate models attempt to bring together our best knowledge of the key processes that govern the composition of the atmosphere and its response to changes in forcing. We test these models on a process by process basis by comparing model results to data from many sources. A more difficult task is testing the model response to changes. One way to do this is to use the natural and anthropogenic experiments that have been done on the atmosphere and are continuing to be done. These include the volcanic eruptions of El Chichon and Pinatubo, the solar cycle, and the injection of chlorine and bromine from CFCs and methyl bromide. The test of the model's response to these experiments is their ability to produce the long-term variations in ozone and the trace gases that affect ozone. We now have more than 25 years of satellite ozone data. We have more than 15 years of satellite and ground-based data of HC1, HN03, and many other gases. I will discuss the testing of models using long-term satellite data sets, long-term measurements from the Network for Detection of Stratospheric Change (NDSC) , long-term ground-based measurements of ozone.

Stolarski, Richard S.↗
NASA NTRS1986

Dynamic remapping decisions in multi-phase parallel computations

The effectiveness of any given mapping of workload to processors in a parallel system is dependent on the stochastic behavior of the workload. Program behavior is often characterized by a sequence of phases, with phase changes occurring unpredictably. During a phase, the behavior is fairly stable, but may become quite different during the next phase. Thus a workload assignment generated for one phase may hinder performance during the next phase. We consider the problem of deciding whether to remap a paralled computation in the face of uncertainty in remapping's utility. Fundamentally, it is necessary to balance the expected remapping performance gain against the delay cost of remapping. This paper treats this problem formally by constructing a probabilistic model of a computation with at most two phases. We use stochastic dynamic programming to show that the remapping decision policy which minimizes the expected running time of the computation has an extremely simple structure: the optimal decision at any step is followed by comparing the probability of remapping gain against a threshold. This theoretical result stresses the importance of detecting a phase change, and assessing the possibility of gain from remapping. We also empirically study the sensitivity of optimal performance to imprecise decision threshold. Under a wide range of model parameter values, we find nearly optimal performance if remapping is chosen simply when the gain probability is high. These results strongly suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change; precise quantification of the decision model parameters is not necessary.

Nicol, D. M.↗
NASA NTRS1998

Evaluation and optimization of lidar temperature analysis algorithms using simulated data

The middle atmosphere (20 to 90 km altitude) ha received increasing interest from the scientific community during the last decades, especially since such problems as polar ozone depletion and climatic change have become so important. Temperature profiles have been obtained in this region using a variety of satellite-, rocket-, and balloon-borne instruments as well as some ground-based systems. One of the more promising of these instruments, especially for long-term high resolution measurements, is the lidar. Measurements of laser radiation Rayleigh backscattered, or Raman scattered, by atmospheric air molecules can be used to determine the relative air density profile and subsequently the temperature profile if it is assumed that the atmosphere is in hydrostatic equilibrium and follows the ideal gas law. The high vertical and spatial resolution make the lidar a well adapted instrument for the study of many middle atmospheric processes and phenomena as well as for the evaluation and validation of temperature measurements from satellites, such as the Upper Atmosphere Research Satellite (UARS). In the Network for Detection of Stratospheric Change (NDSC) lidar is the core instrument for measuring middle atmosphere temperature profiles. Using the best lidar analysis algorithm possible is therefore of crucial importance. In this work, the JPL and CNRS/SA lidar analysis software were evaluated. The results of this evaluation allowed the programs to be corrected and optimized and new production software versions were produced. First, a brief description of the lidar technique and the method used to simulate lidar raw-data profiles from a given temperature profile is presented. Evaluation and optimization of the JPL and CNRS/SA algorithms are then discussed.

Leblanc, Thierry↗
NASA NTRS2024

Evaluation of Vertical Patterns in Chlorophyll-A Derived From A Data Assimilating Model of Satellite-Based Ocean Color

Satellite-based sensors of ocean color have become the primary tool to infer changes in surface chlorophyll, while BGC-Argo floats are now filling the information gap at depth. Here we use BGC-Argo data to assess depth-resolved information on chlorophyll-a derived from an ocean biogeochemical model constrained by the assimilation of surface ocean color remote sensing. The data-assimilating model replicates well the general seasonality and meridional gradients in surface and depth-resolved chlorophyll-a inferred from the float array in the Southern Ocean. On average, the model tends to overestimate float-based chlorophyll, particularly at times and locations of high productivity such as the beginning of the spring bloom, subtropical deep chlorophyll maxima, and non-iron limited regions of the Southern Ocean. The highest model RMSE in the upper 50 m with respect to the float array is of 0.6 mg Chl m −3 , which should allow the detection of seasonal changes in float-based biomass (varying between 0.01 and >1 mg Chl m −3 ) but might hinder the identification of subtle changes in chlorophyll at narrow local scales. Both model and float profiling data show good agreement with in situ data from station ALOHA, with model estimates showing a slight accuracy edge in inferring depth-resolved observations. Uncertainties in float bio-optical estimates impede their use as a reliable benchmark for validation, but the general qualitative agreement between model and float data provides confidence in the ability of model to replicate biogeochemical features below the surface, where data is not directly constrained by the assimilation of satellite ocean color.

Lionel A Quintero↗
DOE OSTI2023

Diel, seasonal, and inter-annual variation in carbon dioxide effluxes from lakes and reservoirs

Abstract Accounting for temporal changes in carbon dioxide (CO 2 ) effluxes from freshwaters remains a challenge for global and regional carbon budgets. Here, we synthesize 171 site-months of flux measurements of CO 2 based on the eddy covariance method from 13 lakes and reservoirs in the Northern Hemisphere, and quantify dynamics at multiple temporal scales. We found pronounced sub-annual variability in CO 2 flux at all sites. By accounting for diel variation, only 11% of site-months were net daily sinks of CO 2 . Annual CO 2 emissions had an average of 25% (range 3%–58%) interannual variation. Similar to studies on streams, nighttime emissions regularly exceeded daytime emissions. Biophysical regulations of CO 2 flux variability were delineated through mutual information analysis. Sample analysis of CO 2 fluxes indicate the importance of continuous measurements. Better characterization of short- and long-term variability is necessary to understand and improve detection of temporal changes of CO 2 fluxes in response to natural and anthropogenic drivers. Our results indicate that existing global lake carbon budgets relying primarily on daytime measurements yield underestimates of net emissions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

ICESat Observations of Inland Surface Water Stage, Slope, and Extent: a New Method for Hydrologic Monitoring

River discharge and changes in lake, reservoir and wetland water storage are critical terms in the global surface water balance, yet they are poorly observed globally and the prospects for adequate observations from in-situ networks are poor (Alsdorf et al., 2003). The NASA-sponsored Surface Water Working Group has established a framework for advancing satellite observations of river discharge and water storage changes which focuses on obtaining measurements of water surface height (stage), slope, and extent. Satellite laser altimetry, which can achieve centimeter-level elevation precision for single, small laser footprints, provides a method to obtain these inland water parameters and contribute to global water balance monitoring. Since its launch in January, 2003 the Ice, Cloud, and land Elevation Satellite (ICESat), a NASA Earth Observing System mission, has achieved over 540 million laser pulse observations of ice sheet, ocean surface, land topography, and inland water elevations and cloud and aerosol height distributions. By recording the laser backscatter from 80 m diameter footprints spaced 175 m along track, ICESat acquires globally-distributed elevation profiles, using a 1064 nm laser altimeter channel, and cloud and aerosol profiles, using a 532 nm atmospheric lidar channel. The ICESat mission has demonstrated the following laser altimeter capabilities relevant to observations of inland water: (1) elevation measurements with a precision of 2 to 3 cm for flat surfaces, suitable for detecting river surface slopes along long river reaches or between multiple crossings of a meandering river channel, (2) from the laser backscatter waveform, detection of water surface elevations beneath vegetation canopies, suitable for measuring water stage in flooded forests, (3) single pulse absolute elevation accuracy of about 50 cm (1 sigma) for 1 degree sloped surfaces, with calibration work in progress indicating that a final accuracy of about 12 cm (1 sigma) will be achieved for clear atmosphere conditions, suitable for detection of stage changes through time, (4) ability to precisely point the spacecraft so as to position the laser profile on the Earth the surface with a cross-track accuracy of 50 m (1 sigma), enabling small water bodies and specific locations to be targeted and re-observed through time, (5) adequate signal levels from specular water surfaces up to 5 degrees off-nadir, enabling complete global access to any location on the Earth's surface from the ICESat repeat orbit by off-nadir pointing, and (6) day and night operation with successful laser ranging to the Earth's surface through thin to moderate cloud cover, enabling more frequent measurements than can be achieved by passive optical sensors. Here we illustrate these capabilities by showing ICESat observations through time for selected river and lake locations.

Harding, David J.↗
DOE OSTI2022

Sequentially calibrating a Bayesian microsimulation model to incorporate new information and assumptions

Background: Microsimulation models are mathematical models that simulate event histories for individual members of a population. They are useful for policy decisions because they simulate a large number of individuals from an idealized population, with features that change over time, and the resulting event histories can be summarized to describe key population-level outcomes. Model calibration is the process of incorporating evidence into the model. Calibrated models can be used to make predictions about population trends in disease outcomes and effectiveness of interventions, but calibration can be challenging and computationally expensive. Methods: This paper develops a technique for sequentially updating models to take full advantage of earlier calibration results, to ultimately speed up the calibration process. A Bayesian approach to calibration is used because it combines different sources of evidence and enables uncertainty quantification which is appealing for decision-making. We develop this method in order to re-calibrate a microsimulation model for the natural history of colorectal cancer to include new targets that better inform the time from initiation of preclinical cancer to presentation with clinical cancer (sojourn time), because model exploration and validation revealed that more information was needed on sojourn time, and that the predicted percentage of patients with cancers detected via colonoscopy screening was too low. Results: The sequential approach to calibration was more efficient than recalibrating the model from scratch. Incorporating new information on the percentage of patients with cancers detected upon screening changed the estimated sojourn time parameters significantly, increasing the estimated mean sojourn time for cancers in the colon and rectum, providing results with more validity. Conclusions: A sequential approach to recalibration can be used to efficiently recalibrate a microsimulation model when new information becomes available that requires the original targets to be supplemented with additional targets.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Benchmarking of Solar Irradiance Nowcast Performance Derived from All-Sky Imagers

Fluctuations of the incoming solar irradiance impact the power generation from photovoltaic and concentrating solar thermal power plants. Accurate solar nowcasting becomes necessary to detect these sudden changes of generated power and to provide the desired information for optimal exploitation of solar systems. In the framework of the International Energy Agency's Photovoltaic Power Systems Program Task 16, a benchmarking exercise has been conducted relying on a bouquet of solar nowcasting methodologies by all-sky imagers (ASI). In this paper, four ASI systems nowcast the Global Horizontal Irradiance (GHI) with a time forecast ranging from 1 to 20 min during 28 days with variable cloud conditions spanning from September to November 2019 in southern Spain. All ASIs demonstrated their ability to accurately nowcast GHI, with RMSE ranging from 6.9% to 18.1%. Under cloudy conditions, all ASIs' nowcasts outperform the persistence models. Under clear skies, three ASIs are better than persistence. Discrepancies in the observed nowcasting performance become larger at increasing forecast horizons. The findings of this study highlight the feasibility of ASIs to reliably nowcast GHI at different sky conditions, time intervals and horizons. Such nowcasts can be used either to estimate solar power at distant times or detect sudden GHI fluctuations.

all-sky imagers↗
NASA NTRS1992

Observation of Stratospheric Ozone with NIES Lidar System in Tsukuba, Japan

Lidars are expected to play important roles in an international monitoring network of the stratosphere such as the Network for the Detection of Stratospheric Change (NDSC). The National Institute for Environmental Studies (NIES) in Tsukuba constructed an ozone lidar system in March 1988 and started observation in August 1988. The lidar system has a 2-m telescope and injection locked XeCl and XeF excimer lasers which can measure ozone profiles (15-45 km) and temperature profiles (30-80 km). From December 1991, lidar observations have been carried out in which the second Stokes line of the stimulated Raman scattering of a KrF laser has been used. Ozone profiles obtained with the NIES lidar system are compared with the data provided by the SAGE II satellite sensor. Results showed good agreement for the individual and the zonal mean profiles. Variations of ozone with various time scales at each altitude can be studied using the data obtained with the NIES ozone lidar system. Seasonal variations are easily found at 20 km, 30 km, and 35 km, which are qualitatively understood as a result of dynamical and photochemical effects. Systematic errors of ozone profiles due to the Pinatubo stratospheric aerosols have been detected using multi-wavelength observation.

Nakane, H.↗
DOE OSTI2023

Characterizing the intracluster light over the redshift range 0.2 < z < 0.8 in the DES-ACT overlap

ABSTRACT We characterize the properties and evolution of bright central galaxies (BCGs) and the surrounding intracluster light (ICL) in galaxy clusters identified in the Dark Energy Survey and Atacama Cosmology Telescope Survey (DES-ACT) overlapping regions, covering the redshift range 0.20 < z < 0.80. Over this redshift range, we measure no change in the ICL’s stellar content (between 50 and 300 kpc) in clusters with log10(M200m,SZ/M⊙) >14.4. We also measure the stellar mass–halo mass (SMHM) relation for the BCG+ICL system and find that the slope, β, which characterizes the dependence of M200m,SZ on the BCG+ICL stellar mass, increases with radius. The outskirts are more strongly correlated with the halo than the core, which supports that the BCG+ICL system follows a two-phase growth, where recent growth (z < 2) occurs beyond the BCG’s core. Additionally, we compare our observed SMHM relation results to the IllustrisTNG300-1 cosmological hydrodynamic simulations and find moderate qualitative agreement in the amount of diffuse light. However, the SMHM relation’s slope is steeper in TNG300-1 and the intrinsic scatter is lower, likely from the absence of projection effects in TNG300-1. Additionally, we find that the ICL exhibits a colour gradient such that the outskirts are bluer than the core. Moreover, for the lower halo mass clusters (log10(M200m,SZ/M⊙) < 14.59), we detect a modest change in the colour gradient’s slope with lookback time, which combined with the absence of stellar mass growth may suggest that lower mass clusters have been involved in growth via tidal stripping more recently than their higher mass counterparts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Tracing priming effects in palsa peat carbon dynamics using a stable isotope-assisted metabolomics approach

Introduction: Peatlands store up to a third of global soil carbon, and in high latitudes their litter inputs are increasing and changing in composition under climate change. Although litter significantly influences peatland carbon and nutrient dynamics by changing the overall lability of peatland organic matter, the physicochemical mechanisms of this impact—and thus its full scope—remain poorly understood. Methods: We applied multimodal metabolomics (UPLC-HRMS, 1 H NMR) paired with 13 C Stable Isotope-Assisted Metabolomics (SIAM) to track litter carbon and its potential priming effects on both existing soil organic matter and carbon gas emissions. Through this approach, we achieved molecule-specific tracking of carbon transformations at unprecedented detail. Results: Our analysis revealed several key findings about carbon dynamics in palsa peat. Microbes responded rapidly to litter addition, producing a short-term increase in CO 2 emissions, fueled nearly exclusively by transformations of litter carbon. Litter inputs significantly contributed to the organic nitrogen pool through amino acids and peptide derivatives, which served as readily accessible nutrient sources for microbial communities. We traced the fate of plant-derived polyphenols including flavonoids like rutin, finding evidence of their degradation through heterocyclic C-ring fission, while accumulation of some polyphenols suggested their role in limiting overall decomposition. The SIAM approach detected subtle molecular changes indicating minimal and transient priming activity that was undetectable through conventional gas measurements alone. This transient response was characterized by brief microbial stimulation followed by rapid return to baseline metabolism. Pre-existing peat organic matter remained relatively stable; significant priming of its consumption was not observed, nor was its structural alteration. Discussion: This suggests that while litter inputs temporarily increase CO 2 emissions, they don’t sustain long-term acceleration of stored carbon decomposition or substantially decrease peat’s carbon store capacity. Our findings demonstrate how technological advancements in analytical tools can provide a more detailed view of carbon cycling processes in complex soil systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Tower-Based Remote Sensing Reveals Mechanisms Behind a Two-phased Spring Transition in a Mixed-Species Boreal Forest

The boreal forest is a major contributor to the global climate system, therefore, reducing uncertainties in how the forest will respond to a changing climate is critical. One source of uncertainty is the timing and drivers of the spring transition. Remote sensing can provide important information on this transition, but persistent foliage greenness, seasonal snow cover, and a high prevalence of mixed forest stands (both deciduous and evergreen species) complicate interpretation of these signals. We collected tower-based remotely sensed data (reflectance-based vegetation indices and Solar-Induced Chlorophyll Fluorescence [SIF]), stem radius measurements, gross primary productivity, and environmental conditions in a boreal mixed forest stand. Evaluation of this data set shows a two-phased spring transition. The first phase is the reactivation of photosynthesis and transpiration in evergreens, marked by an increase in relative SIF, and is triggered by thawed stems, warm air temperatures, and increased available soil moisture. The second phase is a reduction in bulk photoprotective pigments in evergreens, marked by an increase in the Chlorophyll-Carotenoid Index. Deciduous leaf-out occurs during this phase, marked by an increase in all remotely sensed metrics. The second phase is controlled by soil thaw. Our results demonstrate that remote sensing metrics can be used to detect specific physiological changes in boreal tree species during the spring transition. The two-phased transition explains inconsistencies in remote sensing estimates of the timing and drivers of spring recovery. Our results imply that satellite-based observations will improve by using a combination of vegetation indices and SIF, along with species distribution information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Changing-look Active Galactic Nuclei Powered by Disk Tearing

Changing-look active galactic nuclei (CLAGN) feature order-of-magnitude variability in both the continuum and broad line luminosities on months-to-years-long timescales, and are currently unexplained. Simulations have demonstrated that rotating black holes (BHs) sometimes tear apart tilted accretion disks. These tearing events violently restructure the disk on timescales much shorter than a viscous timescale, hinting at a connection to CLAGN. Here, we show that disk tearing can power changing-look events. We report synthetic observations of an extremely high-resolution, three-dimensional, general-relativistic magnetohydrodynamic simulation of a geometrically thin, tilted accretion disk around a rapidly rotating, 10 8 M ⊙ BH. We perform ray-tracing calculations that follow the thermal disk emission to both a line-of-sight camera and to a distribution of cameras in a prescribed torus-like broad-line region (BLR). The continuum photoionizes the BLR, and we calculate the resulting spectrum. Both the continuum and line luminosities undergo order-of-magnitude swings on months-to-years-long timescales. We find shorter, week-long variability driven by the geometric precession of the inner disk and an intraday quasiperiodic oscillation driven by radial breathing of the inner disk. When the torn disk precesses, it causes asymmetric illumination of the BLR, driving time-evolving red-to-blue asymmetries of the broad emission lines that may be a smoking gun for disk tearing. We also make predictions for future photometric observations from ULTRASAT and Vera Rubin Observatory, given a Shakura–Sunyaev–like effective temperature profile, both of which may play an important role in detecting future changing-look events. Future work should consider nonthermal emission, especially from the time-variable corona.

accretion↗
DOE OSTI2023

Quantum Sensing of Electric Fields Using Spin-Correlated Radical Ion Pairs

Quantum sensing affords the possibility of using quantum entanglement to probe electromagnetic fields with exquisite sensitivity. In this work, we show that a photogenerated spin-correlated radical ion pair (SCRP) can be used to sense an electric field change created at one radical ion of the pair using molecular recognition. The SCRP is generated within a covalent donor–chromophore–acceptor system PXX–PMI–NDI, 1, where PXX = peri-xanthenoxanthene, PMI = 1,6-bis(p-t-butylphenoxy)perylene-3,4-dicarboximide, and NDI = naphthalene-1,8:4,5-bis(dicarboximide). The electron-rich PXX donor in 1 acts as a guest molecule that can be encapsulated selectively by a tetracationic cyclophane ExBox4+ host to give a supramolecular complex 1 ⊂ ExBox 4+ . Selective photoexcitation of the PMI chromophore results in ultrafast generation of the PXX •+ –PMI–NDI •– SCRP. When PXX is encapsulated by ExBox 4+ , the cyclophane generates an electric field that repels the positive charge on PXX •+ within PXX •+ –PMI–NDI •– , reducing the SCRP distance, i.e., the distance between the centers-of-charge on the donor and acceptor. Pulse-EPR measurements are used to measure the coherent oscillations created primarily by the electron–electron dipolar coupling in the SCRP, which yields the distance between the two charges (spins) of PXX •+ –PMI–NDI •– . Here, the experimental results show that the distance between PXX •+ and NDI •– decreases when ExBox 4+ encapsulates PXX •+ , which demonstrates that the SCRP can function as a quantum sensor to detect electric field changes in the vicinity of the radical ions.

Anions↗
DOE OSTI2026

Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique

Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.

42 ENGINEERING↗
NASA NTRS2015

External Influences on Modeled and Observed Cloud Trends

Understanding the cloud response to external forcing is a major challenge for climate science. This crucial goal is complicated by intermodel differences in simulating present and future cloud cover and by observational uncertainty. This is the first formal detection and attribution study of cloud changes over the satellite era. Presented herein are CMIP5 (Coupled Model Intercomparison Project - Phase 5) model-derived fingerprints of externally forced changes to three cloud properties: the latitudes at which the zonally averaged total cloud fraction (CLT) is maximized or minimized, the zonal average CLT at these latitudes, and the height of high clouds at these latitudes. By considering simultaneous changes in all three properties, the authors define a coherent multivariate fingerprint of cloud response to external forcing and use models from phase 5 of CMIP (CMIP5) to calculate the average time to detect these changes. It is found that given perfect satellite cloud observations beginning in 1983, the models indicate that a detectable multivariate signal should have already emerged. A search is then made for signals of external forcing in two observational datasets: ISCCP (International Satellite Cloud Climatology Project) and PATMOS-x (Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres - Extended). The datasets are both found to show a poleward migration of the zonal CLT pattern that is incompatible with forced CMIP5 models. Nevertheless, a detectable multivariate signal is predicted by models over the PATMOS-x time period and is indeed present in the dataset. Despite persistent observational uncertainties, these results present a strong case for continued efforts to improve these existing satellite observations, in addition to planning for new missions.

clouds (meteorology)↗