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NASA NTRS2014

Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Data Assimilation↗

NASA NTRS1992

The relationship between delta C-13 of organic matter and (CO2(aq)) in ocean surface water - Data from the JGOFS site in the northeast Atlantic Ocean and a model

Consistent with the hypothesis that plankton delta C-14 and (CO2(aq)) are inversely related, increases in both sinking and suspended particulate organic matter (POM) delta C-13 detected by the Joint Global Ocean Flux Study (JGOFS) were highly negatively correlated with mixed-layer (CO2(aq)). A model of plant delta C-13 by Farquhar et al. (1982) is adapted to show that under a constant phytoplankton demand for CO2 an inverse nonlinear suspended POM delta C-13 response to ambient (CO2(aq)) is expected. Differences between predicted and observed suspended POM delta C-13 vs. (CO2(aq)) trends and among observed relationships can be reconciled if biological CO2 demand is allowed to vary.

Rau, G. H.↗

NASA NTRS2019

Atmospheric Correction of Satellite Ocean-Color Imagery During the PACE Era

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will carry into space the Ocean Color Instrument (OCI), a spectrometer measuring at 5 nm spectral resolution in the ultraviolet (UV) to near infrared (NIR) with additional spectral bands in the shortwave infrared (SWIR), and two multi-angle polarimeters that will overlap the OCI spectral range and spatial coverage, i. e., the Spectrometer for Planetary Exploration (SPEXone) and the Hyper-Angular Rainbow Polarimeter (HARP2). These instruments, especially when used in synergy, have great potential for improving estimates of water reflectance in the post Earth Observing System (EOS) era. Extending the top-of-atmosphere (TOA) observations to the UV, where aerosol absorption is effective, adding spectral bands in the SWIR, where even the most turbid waters are black and sensitivity to the aerosol coarse mode is higher than at shorter wavelengths, and measuring in the oxygen A-band to estimate aerosol altitude will enable greater accuracy in atmospheric correction for ocean color science. The multi-angular and polarized measurements, sensitive to aerosol properties (e.g., size distribution, index of refraction), can further help to identify or constrain the aerosol model, or to retrieve directly water reflectance. Algorithms that exploit the new capabilities are presented, and their ability to improve accuracy is discussed. They embrace a modern, adapted heritage two-step algorithm and alternative schemes (deterministic, statistical) that aim at inverting the TOA signal in a single step. These schemes, by the nature of their construction, their robustness, their generalization properties, and their ability to associate uncertainties, are expected to become the new standard in the future. A strategy for atmospheric correction is presented that ensures continuity and consistency with past and present ocean-color missions while enabling full exploitation of the new dimensions and possibilities. Despite the major improvements anticipated with the PACE instruments, gaps/issues remain to be filled/tackled. They include dealing properly with whitecaps, taking into account Earth-curvature effects, correcting for adjacency effects, accounting for the coupling between scattering and absorption, modeling accurately water reflectance, and acquiring a sufficiently representative dataset of water reflectance in the UV to SWIR. Dedicated efforts, experimental and theoretical, are in order to gather the necessary information and rectify inadequacies. Ideas and solutions are put forward to address the unresolved issues. Thanks to its design and characteristics, the PACE mission will mark the beginning of a new era of unprecedented accuracy in ocean-color radiometry from space.

Robert J Frouin↗

NASA NTRS2019

Atmospheric Correction of Satellite Ocean-Color Imagery During the PACE Era

ocean color↗

NASA NTRS2022

Impact of Growth Phase, Pigment Adaptation, and Climate Change Conditions on the Cellular Pigment and Carbon Content of Fifty‐One Phytoplankton Isolates

Owing to their importance in aquatic ecosystems, the demand for models that estimate phytoplankton biomass and community composition in the global ocean has increased over the last decade. Moreover, the impacts of climate change, including elevated carbon dioxide (CO2), increased stratification, and warmer sea surface temperatures, will likely shape phytoplankton community composition in the global ocean. Chemotaxonomic methods are useful for modeling phytoplankton community composition from marker pigments normalized to chlorophyll a (Chl a). However, photosynthetic pigments, particularly Chl a, are sensitive to nutrient and light conditions. Cellular carbon is less sensitive, so using carbon biomass instead may provide an alternative approach. To this end, cellular pigment and carbon concentrations were measured in 51 strains of globally relevant, cultured phytoplankton. Pigment-to-Chl a and pigment-to-carbon ratios were computed for each strain. For 25 strains, measurements were taken during two growth phases. While some differences between growth phases were observed, they did not exceed within class differences. Multiple strains of Amphidinium carterae, Ditylum brightwellii and Heterosigma akashiwo were measured to determine whether time in culture influenced pigment and carbon composition. No appreciable trends in cellular pigment or carbon content were observed. Lastly, the potential impact of climate change conditions on the pigment ratios was assessed using a multistressor experiment that included increased mean light, temperature, and elevated pCO2 on three species: Thalassiosira oceanica, Ostreococcus lucimarinus, and Synechococcus. The largest differences were observed in the pigment-to-carbon ratios, while the marker pigments largely covaried with Chl a. The implications of these observations to chemotaxonomic applications are discussed.

Pigments↗

NASA NTRSDate not supplied

Overview of Submesoscale-Climate Connections

In this talk, I will present a brief overview of some recent results and current research priorities regarding the significant participation of upper ocean / submesoscale processes in regional to global Earth system dynamics in a warming climate, such as ocean overturning, biogeochemistry, and heat and carbon uptake as well as atmospheric, coastal, and cryospheric dynamics. In addition to reviewing the evidence for these links by topic, I will highlight how advances in both understanding and prediction are derived from the integrated triad of process studies, modeling, and regional and global observing systems. Finally, I will discuss how triadic investments focused on these upper ocean processes might lead to better-informed decision-making for climate change adaptation and mitigation strategies.

Overview↗

NASA NTRS2008

Diversity and Physiology of Siderophilic Cyanobacteria: Implication for the Bioenergetics

Prior to 2.4 Ga, global oceans were likely significantly enriched in soluble iron (Rouxel, Bekker, Edwards, 2005), a condition that is not conducive to the growth of most contemporary mesophilic cyanobacteria (CB). Recent studies of the mechanisms of iron-deficiency stress in CB suggest that contemporary mesophilic freshwater and marine B underwent long-term adaptation to a permanent decrease in soluble iron in the ocean environment (Boyer, et al., 1987; Braun, Hantke, and Koster, 1998). Of all extant environments, iron-depositing hot springs may constitute the most appropriate natural models for analysis of the transition of ancestral cyanobacteria (CB) or protocyanobacteria (PCB) (Olson, 2001) from anoxygenic photosynthesis to oxygenic one and biogeochemical processes in the late Archean and early Paleoproterozoic eras. In particular, Olson (2001) proposed the definition for PCB and postulated that the common ancestor of PCB and CB might well have used Fe(OH)+ as the principal electron donor for CO2 fixation (Widdel, et al., 1993; Ehrenreich and Widdel, 1994; Pierson and Olson, 1989; Olson, 2006). Olson (2001) proposed that the driving force for the evolution of RC2, in addition to RC1, was the necessity to use Fe(OH)+ effectively for CO2 fixation in the absence of reduced sulfur compounds. The global decrease of dissolved environmental reduced iron could have been the driving force for the transition from anoxygenic to oxygenic photosynthesis (Brown et al., 2007). Despite the insights into the ecology, evolutionary biology, paleogeobiochemistry, and astrobiology the examination of iron depositing hot springs (IDHS) could potentially provide, very few studies dedicated to the diversity and physiology of cyanobacteria inhabiting IDHS have been conducted. Here we describe the phylogeny, physiology and ultrastructure and biogeochemical activity of several recent CB isolates from two different greater Yellowstone area IDHS, e.g. LaDuke and Chocolate Pots. Phylogenetic analysis of 16S rRNA genes indicated that 6 of 12 new isolates examined could not be placed within established CB genera. Some of the isolates exhibited pronounced requirements for elevated iron concentrations, with maximum growth rates observed when 0.4-1 mM Fe(3+) was present in the media. However, the pronounced effect of iron limitation on the proliferation of siderophilic CB can be observed only after several passages through iron "free" media. TEM studies of several species of siderophilic CB revealed that the cultures JSC-3 and -11 are probably capable of some sort of pinocytosis of precipitated iron. This phenomenon may explain high tolerance of siderophilic CB to iron deficit. We also found that the stimulation of the growth of siderophilic CB by oxidized iron is accompanied by the decrease of O2 evolution by some species after addition Fe(2+) in iron "free" medium.

Brown, Igor↗

NASA NTRS1974

Estimation of sunlight penetration in the sea for remote sensing

There is a need for a simple theoretical approach to the calculation of sunlight penetration depths suitable for passive multispectral remote sensing of water resources. An earlier paper presented an approach which is readily adapted to this calculation and which provides reasonably good agreement with more accurate but time-consuming radiative transfer models. The needed modifications are described and the model is used to calculate the penetration of sunlight into clear ocean water at several wavelengths throughout the visible portion of the spectrum. Calculations for both clear and turbid water are carried out for the two visible channels of the multispectral scanner on NASA's ERTS-1 satellite. The effect of a reflective bottom on the upwelling light field is discussed. Measurement parameters needed for the passive remote determination of water depths are identified and the use of submerged reflective panels for surface truth measurements is discussed.

Mccluney, W. R.↗

NASA NTRS2020

Improved Groundwater Table and L-Band Brightness Temperature Estimates for Northern Hemisphere Peatlands Using New Model Physics and SMOS Observations in a Global Data Assimilation Framework

There is an urgent need to include northern peatland hydrology in global Earth system models to better understand land-atmosphere interactions and sensitivities of peatland functions to climate change, and, ultimately, to improve climate change predictions. In this study, we introduced for the first time peatland-specific model physics into an assimilation scheme for L-band brightness temperature (Tb) data from the Soil Moisture Ocean Salinity (SMOS) mission to improve groundwater table estimates. We conducted two sets of model-only and data assimilation experiments using the Catchment Land Surface Model (CLSM), applying (over peatlands only) in one of them a peatland-specific adaptation (PEATCLSM). The evaluation against in-situ measurements of peatland groundwater table depth indicates the superiority of PEATCLSM model physics and additionally improved performance after assimilating SMOS Tb observations. The better performance of PEATCLSM over nearly all Northern Hemisphere peatlands is further supported by the better agreement between SMOS Tb observations and Tb estimates from the model-only and data assimilation runs. Within the data assimilation scheme, PEATCLSM reduces Tb observation-minus-forecast residuals and leads to reduced data assimilation updates of water storage components and, thus, reduced water budget imbalances in the assimilation system.

SMOS↗

NASA NTRS2001

Models of Small-Scale Patchiness

Patchiness is perhaps the most salient characteristic of plankton populations in the ocean. The scale of this heterogeneity spans many orders of magnitude in its spatial extent, ranging from planetary down to microscale. It has been argued that patchiness plays a fundamental role in the functioning of marine ecosystems, insofar as the mean conditions may not reflect the environment to which organisms are adapted. Understanding the nature of this patchiness is thus one of the major challenges of oceanographic ecology. The patchiness problem is fundamentally one of physical-biological-chemical interactions. This interconnection arises from three basic sources: (1) ocean currents continually redistribute dissolved and suspended constituents by advection; (2) space-time fluctuations in the flows themselves impact biological and chemical processes, and (3) organisms are capable of directed motion through the water. This tripartite linkage poses a difficult challenge to understanding oceanic ecosystems: differentiation between the three sources of variability requires accurate assessment of property distributions in space and time, in addition to detailed knowledge of organismal repertoires and the processes by which ambient conditions control the rates of biological and chemical reactions. Various methods of observing the ocean tend to lie parallel to the axes of the space/time domain in which these physical-biological-chemical interactions take place. Given that a purely observational approach to the patchiness problem is not tractable with finite resources, the coupling of models with observations offers an alternative which provides a context for synthesis of sparse data with articulations of fundamental principles assumed to govern functionality of the system. In a sense, models can be used to fill the gaps in the space/time domain, yielding a framework for exploring the controls on spatially and temporally intermittent processes. The following discussion highlights only a few of the multitude of models which have yielded insight into the dynamics of plankton patchiness. In addition, this particular collection of examples is intended to furnish some exposure to the diversity of modeling approaches which can be brought to bear on the problem. These approaches range from abstract theoretical models intended to elucidate specific processes, to complex numerical formulations which can be used to actually simulate observed distributions in detail.

McGillicuddy, D. J.↗

NASA NTRSDate not supplied

Adding GPU Support to the Markov Chain Monte Carlo Code Catmip

In geophysics, we are confronted with many under-determined inverse problems. For example, all of our observations of earthquakes are made at the Earth’s surface. So, when we try to infer how slip during an earthquake evolves in space and time, we find that there are many potential slip histories that are consistent with our limited observations and our understanding of earthquake physics. One way to approach these problems is with Bayesian analysis which allows us to infer the ensemble of all potential slip models that satisfy the observations and our prior knowledge of earthquake physics. In Bayesian analysis, our prior knowledge is known as the prior probability density function or prior PDF, the fit to the data is known as the data likelihood, and the target PDF that satisfies both the prior PDF and data likelihood is known as the posterior PDF. However, simulating the posterior PDF typically requires using Markov Chain Monte Carlo (MCMC) to draw tens of billions of random realizations of earthquake slip models, which may not be computationally feasible. To make this and similar geophysical inversions computationally tractable, we developed the Cascading Adaptive Transitional Metropolis In Parallel (CATMIP) algorithm. CATMIP is an efficient parallel Markov Chain Monte Carlo (MCMC) sampler that is used for model fitting and uncertainty quantification in geophysics. Example use cases are earthquake rupture modeling, determining mineral composition on Mars, reconstructing the history of ocean salinity, and historical earthquake relocation. CATMIP employs many parallel instances of the Metropolis algorithm for sampling in a transitioning framework. Transitioning is a process in which a set of random samples at equilibrium with a known probability density function (PDF) are used as seeds for the Markov chains to sample successive target PDFs that incrementally move the distribution from the starting seeds to the final desired PDF that describes the relative plausibility of potential values for the model parameters. The algorithm is implemented as a Master-Worker model employing MPI for communication. The worker processes are loosely coupled with global parameters periodically optimized by the master process. This provides a very high amount of parallelism with little communication between updates. During the presentation we will discuss the history of the algorithm and elaborate the earthquake rupture modeling use case for the CATMIP package. Our first step toward GPU optimization was to optimize the code for the CPU. CPU profiling revealed that most of the compute time is spent in calls to level 2 BLAS routines and calls to GSL random number generators. We revised the algorithm to employ level 3 BLAS routines instead. In our presentation we will describe how this was accomplished. Adding GPU support to CATMIP consisted mostly of replacing the calls to GSL with calls to GPU vendor-provided library routines. A small number of loops were directly implemented in CUDA. In the presentation will provide implementation details. Finally, we will discuss methods for profiling and opportunities for further optimizing GPU execution. By creating a code with the flexibility to run on either a CPU or GPU architecture, CATMIP can be used on systems ranging from large CPU-based HPC environments to single servers with GPU acceleration and everything in between.

HECC↗

DOE OSTI2026

Tree-ring evidence marks year 2022 as the driest spring season in nearly four centuries in the Western Himalayas

The Hindukush-Karakoram-Himalayan region is a crucial freshwater source for billions across South Asia, yet its climate remains poorly understood due to limited long-term records. Winter and spring precipitation govern snow accumulation and downstream water availability in dry months particularly across the Western Himalayas (WH), but recent decades show intensifying droughts with unclear long-term context. Here, we have reconstructed a nearly four-century-long spring i.e. February to May (FMAM) precipitation for the Lahaul region of the (WH), an area dominated by the Western Disturbances. This record was developed using moisture-sensitive Cedrus deodara (Deodar) tree-rings from three high-elevation sites. A regional composite tree-ring-width chronology, developed through a Nested Principal Component Analysis and modeled with a nonlinear Generalized Additive Model (GAM) that explains 71 % of the variance during the calibration period. We identified the last two decades as the most precipitation deficit phase and the year 2022 showing the driest FMAM on record. The observed rise in the FMAM dry episodes post 1999 CE in our reconstruction, corresponds to the meteorological records. This recent drying is linked to a northward shift of the subtropical westerly jet and reduced moisture transport, both associated with unusual sea surface temperature patterns in the tropical Indian Ocean and the Western Pacific Ocean. Our results provide compelling evidence of long-term hydroclimatic instability in the WH and emphasize the value of tree-ring records in extending precipitation histories beyond the instrumental observations. Such reconstructions can be benchmarks to validate high-resolution climate models and formulate adaptation policies to mitigate future risks.

Cedrus deodara↗

NASA NTRS2003

Adaptation of a Hyperspectral Atmospheric Correction Algorithm for Multi-spectral Ocean Color Data in Coastal Waters

This SIMBIOS contract supports several activities over its three-year time-span. These include certain computational aspects of atmospheric correction, including the modification of our hyperspectral atmospheric correction algorithm Tafkaa for various multi-spectral instruments, such as SeaWiFS, MODIS, and GLI. Additionally, since absorbing aerosols are becoming common in many coastal areas, we are making the model calculations to incorporate various absorbing aerosol models into tables used by our Tafkaa atmospheric correction algorithm. Finally, we have developed the algorithms to use MODIS data to characterize thin cirrus effects on aerosol retrieval.

Gao, Bo-Cai↗

NASA NTRS1999

Meteorology of the Southern Global Plume: African and South American Fires Pollute the South Pacific

An immense global plume of CO meanders widely around the world in the Southern Hemisphere. It arises over Southern America and Africa and flows eastward. The first emissions are in tropical Brazil, and the plume circulates around the world to South America again. The plume was largely unexpected until there were aircraft studies made in NASA's Pacific Exploratory Mission - Tropics (Part A). This paper describes the meteorology of the Global Plume, as our simulation, with a synoptic model adapted to global transport, reveals it with a tracer-CO simulation. The observations and their simulation require a particular set of conditions of pollutant accumulation, cumulonimbus venting with required strengths at a narrow range of altitude. Additionally, a particular subtropical conduction region, over the Indian Ocean, Australia, and the westeRNmost South Pacific, relatively free of storms, appears to be a key part of the mechanism. These conclusions are the results of a synoptic reconstruction of the PEMT-A period, September- October, 1996.

Guo, Z.↗

NASA NTRS1993

Estimators of primary production for interpretation of remotely sensed data on ocean color

The theoretical basis is explained for some commonly used estimators of daily primary production in a vertically uniform water column. These models are recast into a canonical form, with dimensionless arguments, to facilitate comparison with each other and with an analytic solution. The limitations of each model are examined. The values of the photoadaptation parameter I(k) observed in the ocean are analyzed, and I(k) is used as a scale to normalize the surface irradiance. The range of this scaled irradiance is presented. An equation is given for estimation of I(k) from recent light history. It is shown how the models for water column production can be adapted for estimation of the production in finite layers. The distinctions between model formulation, model implementation and model evaluation are discussed. Recommendations are given on the choice of algorithm for computation of daily production according to the degree of approximation acceptable in the result.

Platt, Trevor↗

NASA NTRSDate not supplied

Toward High-Endurance Nonvolatile Reconfigurable Metasurfaces

The applications of adaptive optics extend across multiple sectors, encompassing areas such as LiDAR, biological and chemical sensing, and free-space optical communications. The advent of metasurfaces optics with reconfigurability has offered a versatile platform for the design of compact optical components, offering a compelling alternative to their conventional bulky counterparts. In this study, we introduce the PROWESS (Phase change Reconfigurable Optical WavEfront Synthesis System project at NASA LaRC), electrically reconfigurable metasurfaces using low-loss, high-contrast phase change material (PCM), Ge2Sb2Se4Te integrated with IR-transparent silicon microheater for various practical applications. The talk covers a reliable platform for switching large-scale PCM-based devices utilizing a microheater and an architecture for the metasurface switching within an integrated circuit configuration, which is compatible with standard foundry fabrication processes. The utilization of near- to midinfrared transparent silicon microheater in the proposed architecture opens possibilities for the development of reconfigurable transmissive optics such as filters, zoom lenses, and beam steering modules. We demonstrated switching of 140 µm × 140 µm PCM pixel, on a 200 µm × 200 µm silicon microheater for several thousand cycles. Further, we performed an in-depth investigation into the failure mechanism utilizing techniques such as transmission electron microscopy and thermal modeling. Guidelines for device performance improvement are proposed, and an improved design with larger endurance is shown in progress. With further progress, we aim to unlock the full potential of PCM-based devices and advance the field of adaptive optics with demonstrable examples including a reconfigurable beam steerer for ocean surface flash LiDAR and Navigation Doppler LiDAR for precise lunar landing missions.

metasurface optics↗

NASA NTRS2013

Ensemble Data Assimilation Without Ensembles: Methodology and Application to Ocean Data Assimilation

Two methods to estimate background error covariances for data assimilation are introduced. While both share properties with the ensemble Kalman filter (EnKF), they differ from it in that they do not require the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The first method is referred-to as SAFE (Space Adaptive Forecast error Estimation) because it estimates error covariances from the spatial distribution of model variables within a single state vector. It can thus be thought of as sampling an ensemble in space. The second method, named FAST (Flow Adaptive error Statistics from a Time series), constructs an ensemble sampled from a moving window along a model trajectory. The underlying assumption in these methods is that forecast errors in data assimilation are primarily phase errors in space and/or time.

Data Assimilation↗

DOE OSTI2026

Adaptive Stiffness Power Take-Off System for a Hydraulic Hose-Pump Point Absorber Wave Energy Converter

Two crucial challenges faced in the design of ocean wave energy converters (WECs) are maintaining high capacity factors and remaining robust in everchanging, harsh ocean environments. This study introduces a novel mechanism for achieving reactive WEC control with a soft hydraulic power take-off, thereby addressing both challenges. The device of interest involves a hydraulic pump, constructed from a fluidic flexible matrix composite (F2MC), which is cyclically stretched by driving waves and pressurizes working fluid through a turbine-generator. This class of fiber-reinforced stretch hoses is established for ocean use as robust moorings and shock absorbers. The dynamic properties of the F2MC pump depend on internal pressure, which can be controlled by a continuously variable transmission between the turbine and generator, allowing the system to be adapted for better performance over a wide range of wave conditions. This work presents a dynamic model for operation and adaptive behavior of this power take-off system, experimentally validates components of the model, and performs dynamic simulations of the system that show increases in power production and capacity factor compared to non-adaptive operation for a variety of driving wave conditions. This work develops the basis for future large-scale experimental testing and controller design of this system.

Wave energy conversion, fluidic flexible matrix co↗