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NASA NTRS1987

A microwave radiometer weather-correcting sea ice algorithm

A new algorithm for estimating the proportions of the multiyear and first-year sea ice types under variable atmospheric and sea surface conditions is presented, which uses all six channels of the SMMR. The algorithm is specifically tuned to derive sea ice parameters while accepting error in the auxiliary parameters of surface temperature, ocean surface wind speed, atmospheric water vapor, and cloud liquid water content. Not only does the algorithm naturally correct for changes in these weather conditions, but it retrieves sea ice parameters to the extent that gross errors in atmospheric conditions propagate only small errors into the sea ice retrievals. A preliminary evaluation indicates that the weather-correcting algorithm provides a better data product than the 'UMass-AES' algorithm, whose quality has been cross checked with independent surface observations. The algorithm performs best when the sea ice concentration is less than 20 percent.

Walters, J. M.↗

NASA NTRS1991

Antarctic Sea ice variations and seasonal air temperature relationships

Data through 1987 are used to determine the regional and seasonal dependencies of recent trends of Antarctic temperature and sea ice. Lead-lag relationships involving regional sea ice and air temperature are systematically evaluated, with an eye toward the ice-temperature feedbacks that may influence climatic change. Over the 1958-1087 period the temperature trends are positive in all seasons. For the 15 years (l973-l987) for which ice data are available, the trends are predominantly positive only in winter and summer, and are most strongly positive over the Antarctic Peninsula. The spatially aggregated trend of temperature for this latter period is small but positive, while the corresponding trend of ice coverage is small but negative. Lag correlations between seasonal anomalies of the two variables are generally stronger with ice lagging the summer temperatures and with ice leading the winter temperatures. The implication is that summer temperatures predispose the near-surface waters to above-or below-normal ice coverage in the following fall and winter.

Weatherly, John W.↗

NASA NTRS2003

AIRS Level 2 Data Products

The Atmospheric InfraRed Sounder (AIRS) Standard Retrieval Product consists of retrieved cloud and surface properties; profiles of retrieved temperature, water vapor, and ozone; and a flag indicating the presence of cloud ice or water. They contain quality assessment flags in addition to retrieved quantities and are generated for all locations where atmospheric soundings are taken. An AIRS granule consists of 6 minutes of data. This corresponds to approximately 1/15 of an orbit but exactly 45 scan lines of AMSU-A data or 135 scan lines of AIRS and HSB data.

Vicente, Gilberto↗

NASA NTRS2004

Neural network uncertainty assessment using Bayesian statistics: a remote sensing application

Neural network (NN) techniques have proved successful for many regression problems, in particular for remote sensing; however, uncertainty estimates are rarely provided. In this article, a Bayesian technique to evaluate uncertainties of the NN parameters (i.e., synaptic weights) is first presented. In contrast to more traditional approaches based on point estimation of the NN weights, we assess uncertainties on such estimates to monitor the robustness of the NN model. These theoretical developments are illustrated by applying them to the problem of retrieving surface skin temperature, microwave surface emissivities, and integrated water vapor content from a combined analysis of satellite microwave and infrared observations over land. The weight uncertainty estimates are then used to compute analytically the uncertainties in the network outputs (i.e., error bars and correlation structure of these errors). Such quantities are very important for evaluating any application of an NN model. The uncertainties on the NN Jacobians are then considered in the third part of this article. Used for regression fitting, NN models can be used effectively to represent highly nonlinear, multivariate functions. In this situation, most emphasis is put on estimating the output errors, but almost no attention has been given to errors associated with the internal structure of the regression model. The complex structure of dependency inside the NN is the essence of the model, and assessing its quality, coherency, and physical character makes all the difference between a blackbox model with small output errors and a reliable, robust, and physically coherent model. Such dependency structures are described to the first order by the NN Jacobians: they indicate the sensitivity of one output with respect to the inputs of the model for given input data. We use a Monte Carlo integration procedure to estimate the robustness of the NN Jacobians. A regularization strategy based on principal component analysis is proposed to suppress the multicollinearities in order to make these Jacobians robust and physically meaningful.

Neural Networks (Computer)↗

NASA NTRS2016

Spectral Longwave Cloud Radiative Forcing as Observed by AIRS

AIRS V6 products contain the spectral contributions to Outgoing Longwave Radiation (OLR), clear-sky OLR (OLR(sub CLR)), and Longwave Cloud Radiative Forcing (LWCRF) in 16 bands from 100 cm(exp -1) to 3260 cm(exp -1). We show climatologies of selected spectrally resolved AIRS V6 products over the period of September 2002 through August 2016. Spectrally resolved LWCRF can better describe the response of the Earth system to cloud and cloud feedback processes. The spectral LWCRF enables us to estimate the fraction of each contributing factor to cloud forcing, i.e.: surface temperature, mid to upper tropospheric water vapor, and tropospheric temperature. This presentation also compares the spatial characteristics of LWCRF from AIRS, CERES_EBAF Edition-2.8, and MERRA-2. AIRS and CERES LWCRF products show good agreement. The OLR bias between AIRS and CERES is very close to that of OLR(sub CLR). This implies that both AIRS and CERES OLR products accurately account for the effect of clouds on OLR.

Cloud radiative forcing↗

NASA NTRS2021

Extreme Lake-Effect Snow from a GPM Microwave Imager Perspective: Observational Analysis and Precipitation Retrieval Evaluation

This study focuses on the ability of the Global Precipitation Measurement (GPM) passive microwave sensors to detect and provide quantitative precipitation estimates (QPE) for extreme lake-effect snowfall events over the United States lower Great Lakes region. GPM Microwave Imager (GMI) high frequency channels can clearly detect intense shallow convective snowfall events. However, GMI Goddard PROfiling (GPROF) QPE retrievals produce inconsistent results when compared against the Multi-Radar/Multi-Sensor (MRMS) ground-based radar reference dataset. While GPROF retrievals adequately capture intense snowfall rates and spatial patterns of one event, GPROF systematically underestimates intense snowfall rates in another event. Furthermore, GPROF produces abundant light snowfall rates that do not conform with MRMS observations. Ad-hoc precipitation rate thresholds are suggested to partially mitigate GPROF’s overproduction of light snowfall rates. The sensitivity and retrieval efficiency of GPROF to key parameters (2-meter temperature, total precipitable water, and background surface type) used to constrain the GPROF a-priori retrieval database are investigated. Results demonstrate that typical lake-effect snow environmental and surface conditions, especially coastal surfaces, are underpopulated in the database and adversely affect GPROF retrievals. For the two presented case studies, using snow cover a-priori database in the locations of originally deemed as coastline improves retrieval. This study suggests that it is particularly important to have more accurate GPROF surface classifications and better representativeness of the a-priori databases to improve intense lake-effect snow detection and retrieval performance.

Lisa Milani↗

NASA NTRS2021

Evaluation of High Mountain Asia-Land Data Assimilation System (Version 1) from 2003 to 2016, Part I: A Hyper-Resolution Terrestrial Modeling System

This first paper of the two-part series focuses on demonstrating the accuracy of a hyper-resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region. To this end, this study systematically evaluates four sets of model simulations at point scale, basin scale, and domain scale obtained from different spatial resolutions including 0.01° (∼1-km) and 0.25° (∼25-km). The assessment is conducted via comparisons against ground-based observations and satellite-derived reference products. The key variables of interest include surface net shortwave radiation, surface net longwave radiation, skin temperature, near-surface soil temperature, snow depth, snow water equivalent, and total runoff. In the evaluation against ground-based measurements, the superiority of the 0.01° estimates are mostly demonstrated across relatively complex terrain. Specifically, hyper-resolution modeling improves the skill in meteorological forcing estimates (except precipitation) by 9% relative to coarse-resolution estimates. The model forced by downscaled forcings in its entirety yields the highest skill in model output states as well as precipitation, which improves the skill obtained by coarse-resolution estimates by 7%. These findings, on one hand, corroborate the importance of employing the hyper-resolution versus coarse-resolution modeling in areas characterized by complex terrain. On the other hand, by evaluating four sets of model simulations forced with different precipitation products, this study emphasizes the importance of accurate hyper-resolution precipitation products to drive model simulations.

Yuan Xue↗

NASA NTRS1994

High performance miniature hygrometer and method thereof

An uncoated interdigitated transducer is cooled from a temperature above the dew point to a temperature below the dew point, while a parameter of a signal of the transducer is measured. The reduction in temperature causes a monotonic change in transducer signal because that signal is sensitive primarily to the water loading of the transducer surface as water forms on that surface due to the reduction in temperature. As the dew point is approached with temperature reduction, the slope of the curve of transducer signal with respect to temperature, remains relatively constant. However, as the dew point is reached the slope of that curve increases and because of changes in the structure of the water layer on the surface of the transducer, at the dew point the transducer responds with a clear shift in the rate at which the transducer signal changes. The temperature at which the second derivative of signal vs. temperature peaks can be readily used to identify with extreme accuracy, the precise dew point. The measurement technique employed by the present invention is relatively immune to surface contamination which remains significantly unchanged during the brief measurement period.

VanZandt, Thomas R.↗

DOE OSTI2020

Improving a Multilevel Turbulence Closure Model for a Shallow Lake in Comparison With Other 1-D Models

Lakes differ from lands in water availability, heat capacity, albedo, and roughness, which affect local surface-atmospheric interactions. This study modified a multilevel upper ocean model (UOM) for lake applications and evaluated its performance in Lake Taihu (China) with comprehensive measurements against three popular one-dimensional (1-D) lake models. These models were based on different concepts, including the self-similarity (FLake), the wind-driven eddy diffusion (LISSS), the k-ε turbulence closure (SIMSTRAT), and a simplified turbulence closure (UOM). The surface flux scheme in these models was unified to exclude the discrepancies in representing air-lake exchanges. All models in their default formulations presented obvious cold water temperature biases and largely underestimated the lake surface temperature (LST) diurnal range. For each model, these deficiencies were significantly reduced by incorporating new physics schemes or calibrated tunable parameters based on systematic sensitivity tests. The primary modifications for UOM included (1) a new scheme of decreased surface roughness lengths to better characterize the shallow lake, (2) a solar radiation penetration scheme with increased light extinction coefficient and surface absorption fraction to account for the high water turbidity, and (3) turbulent Prandtl number increased by a factor of 20 to reduce the turbulent vertical mixing. All other models were improved in these three aspects (roughness, extinction, and mixing) within their original formulations. Given these improvements, UOM showed superior performance to other models in capturing LST diurnal cycle and daily to seasonal variations, as well as summer-autumn vertical stratification changes. The new UOM is well suited for application in shallow lakes.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2017

Large Anomalies in Lower Stratospheric Water Vapor and Ice During the 2015–2016 El Niño

The strong and unusual El Niño of 2015-2016 produced a remarkable perturbation to the hydrologic budget of the tropical tropopause layer (14-19 km). This region regulates stratospheric water vapor, which has a direct radiative impact on surface temperatures. To first order, the coldest tropical tropopause temperature regulates the amount of water vapor entering the stratosphere by controlling the amount of dehydration in the rising air. Here we show that tropical convective cloud ice and associated cirrus evaporating at unusually high altitudes might also have a role in stratospheric hydration. The 2015-2016 El Niño produced decadal record water vapor amounts in the tropical Western Pacific, coincident with warm tropopause temperature anomalies. In the Central Pacific, convective cloud ice was observed 2 km above the anomalously cold tropopause. A trajectory-based dehydration model based on two reanalysis temperature and wind fields can account for only about 0.5-0.6 ppmv of the ~0.9 ppmv tropical lower stratospheric moistening observed during this event. This suggests that unresolved convective dynamics and/or associated sublimation of lofted ice particles also contributed to lower stratospheric moistening. These observations suggest that convective moistening could contribute to future climate change-induced stratospheric water vapor increases.

Atmospheric chemistry↗

NASA NTRS1983

Satellite sensing capabilities for surface temperature and meteorological parameters over the ocean

Remote meteorological measurements over the oceans have been used extensively for weather forecasting, ship safety, and global-scale studies of climate and sea conditions. A review is conducted regarding the satellite-sensing capabilities for sea-surface temperature and tropospheric marine meteorological mesurements. The tropospheric measurements are concerned with vertical temperature profiles, integrated water vapor and liquid water, rain, aerosols and surface winds. Attention is also given to several environmental-monitoring applications where satellite sensed synoptic data might be combined with ground and airborne chemical measurements to provide improved assessments of regional and global ennvironmental quality and climatology. Special emphasis is given to current satellite measurement accuracies (errors) and to programs involving U.S. technology. Aspects of sea-surface temperature are treated in detail in connection with extensive studies concentrated in this area.

Darnell, W. L.↗

NASA NTRS2011

Preliminary Error Budget for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) plans to observe climate change trends over decadal time scales to determine the accuracy of climate projections. The project relies on spaceborne earth observations of SI-traceable variables sensitive to key decadal change parameters. The mission includes a reflected solar instrument retrieving at-sensor reflectance over the 320 to 2300 nm spectral range with 500-m spatial resolution and 100-km swath. Reflectance is obtained from the ratio of measurements of the earth s surface to those while viewing the sun relying on a calibration approach that retrieves reflectance with uncertainties less than 0.3%. The calibration is predicated on heritage hardware, reduction of sensor complexity, adherence to detector-based calibration standards, and an ability to simulate in the laboratory on-orbit sources in both size and brightness to provide the basis of a transfer to orbit of the laboratory calibration including a link to absolute solar irradiance measurements. 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 projections such as those in the IPCC Report. A rigorously known accuracy of both decadal change observations as well as climate projections is critical in order to enable sound policy decisions. The CLARREO Project will implement a spaceborne earth observation mission designed to provide rigorous SI traceable observations (i.e., radiance, reflectance, and refractivity) that are sensitive to a wide range of key decadal change variables, including: 1) Surface temperature and atmospheric temperature profile 2) Atmospheric water vapor profile 3) Far infrared water vapor greenhouse 4) Aerosol properties and anthropogenic aerosol direct radiative forcing 5) Total and spectral solar irradiance 6) Broadband reflected and emitted radiative fluxes 7) Cloud properties 8) Surface albedo There are two methods the CLARREO mission will rely on to achieve these critical decadal change benchmarks: direct and reference inter-calibration. A quantitative analysis of the strengths and weaknesses of the two methods has led to the recommended CLARREO mission approach. The project consists of two satellites launched into 90-degree, precessing orbits separated by 90 degrees. The instrument suite receiver on each spacecraft includes one emitted infrared spectrometer, two reflected solar spectrometers: dividing the spectrum from ultraviolet through near infrared, and one global navigation receiver for radio occultation. The measurements will be acquired for a period of three years minimum, with a five-year lifetime goal, enabling follow-on missions to extend the climate record over the decades needed to understand climate change. The current work concentrates on the reflected solar instrument giving an overview of its design and calibration approach. The calibration description includes the approach to achieving an SI-traceable system on orbit. The calibration overview is followed by a preliminary error budget based on techniques currently in place at the National Institute of Standards and Technology (NIST).

Thome, Kurtis↗

NASA NTRS1984

Evaluation and development of new VAS remote sensing algorithms

An algorithm, developed to permit the simultaneous retrieval of temperature/moisture profiles and surface skin temperature by direct analytical solution of the radiative transfer equation, alleviates the problem associated with the interdependencies of water vapor retrieval on temperature retrieval and their dependencies on surface emissions. Simultaneous solution of all these quantities is achieved in one calculation using the available radiance observations. Since only a single matrix inversion is required for the specification of all parameters, the solution is computationally efficient. Ancillary observations of temperature and/or moisture from surface sensors on aircraft can be readily incorporated into the solution. Simulation tests of the method indicate improved performance over the previous iterative technique, particularly for the lower troposphere and for water vapor.

Smith, W. L.↗

NASA NTRS1983

Interaction of hydrogen chloride and water with oxide surfaces. III - Titanium dioxide

The adsorption of hydrogen chloride and water vapors on five TiO2 powders in both the anatase and rutile crystalline forms was studied as a function of temperature, pressure, and outgas conditions. The adsorbents were characterized utilizing X-ray powder diffraction, scanning electron microscopy, surface area analysis, indicator method, microelectrophoresis, XPS, and infrared spectroscopy. It was found that both outgas temperature and adsorption temperature influenced the adsorption of water vapor on TiO2, while water vapor adsorption on TiO2 was completely reversible. It is argued that the number of hydroxyl groups present on the surface determines the adsorption capacity of water on the different titanium dioxides. It was found that heats of immersion in water were affected significantly by outgas temperature. Hydrogen chloride adsorption isotherms at 30 C measured on TiO2 after outgassing at 100-400 C showed that a part of the total HCl adsorbed was irreversibly adsorbed. The highest HCl adsorption capacity per unit area was exhibited by anatase, while pure rutile exhibited the lowest adsorption capacity.

Siriwardane, R. V.↗

DOE OSTI2022

Effects of Plasma on Physical Properties of Water: Nanocrystalline-to-Amorphous Phase Transition and Improving Produce Washing

Washing fresh produce using Plasma-activated water recently became a promising eco-friendly alternative to using chemical additives such as Chlorine. We discuss the produce-washing experiments that illustrate that addition of plasma to washing water is a multi-faced phenomena. Not only it increases the sterilization ability of water by killing pathogens, but it also has improved washibility: the ability to remove pathogens from the cleaning surface. We propose an explanation of these features based on the recently discoveries that many physical and chemical properties of water change their temperature dependence between about 35 and 60 degrees Celsius. In particular, heat conductance, light absorption, and surface tension all change their temperature dependence. These drastic changes were associated with water gradually changing its mesoscopic structure: while at the higher temperatures water is a uniform media (amorphous state), at the temperatures below transition it consists of many nano-to-micro-scale clusters (crystalline state). This transition is similar to the second order phase transition. In the present paper we propose that treating water with non-thermal plasma (adding plasma-created active compounds) can lower the temperature of the transition and thus cause a significant change in such physical quantities as surface tension, viscosity, freezing rate, and wettability and washability.

He, Jinjie↗

NASA NTRS1991

Remote measurement of soil moisture over vegetation using infrared temperature measurements

Better methods for remote sensing of surface evapotranspiration, soil moisture, and fractional vegetation cover were developed. The objectives were to: (1) further develop a model of water movement through the soil/plant/atmosphere system; (2) use this model, in conjunction with measurements of infrared surface temperature and vegetation fraction; (3) determine the magnitude of radiometric temperature response to water stress in vegetation; (4) show at what point one can detect that sensitivity to water stress; and (5) determine the practical limits of the methods. A hydrological model that can be used to calculate soil water content versus depth given conventional meteorological records and observations of vegetation cover was developed. An outline of the results of these initiatives is presented.

Carlson, Toby N.↗

DOE OSTI2022

Dataset for 'Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning', Water 2022

This data package presents forcing data, model code, and model output for classical machine learning models that predict monthly stream water temperature as presented in the manuscript ‘Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning’, Water (Weierbach et al., 2022). Specifically, for input forcing datasets we include two files each generated using the BASIN-3D data integration tool (Varadharajan et al., 2022) for stations in the Pacific Northwest and Mid Atlantic Hydrologic regions. Model code (written in python with the use of jupyter notebooks) includes codes for data preprocessing, training Multiple Linear Regression, Support Vector Regression, and Extreme Gradient Boosted Tree models, and additional notebooks for analysis of model output. We include specific model output files which represent modeling configurations presented in the manuscript also presented in an hdf5 format. Together, these data make up the workflow for predictions across three scenarios (single station, regional, and predictions in unmonitored basins) presented in the manuscript and allow for reproducibility of modeling procedures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Operando Unveiling of Hydrogen Spillover Mechanisms on Tungsten Oxide Surfaces

Hydrogen spillover is an important process in catalytic hydrogenation reactions, facilitating H 2 activation and modulating surface chemistry of reducible oxide catalysts. This study focuses on the operando unveiling of platinum-induced hydrogen spillover on monoclinic tungsten trioxide (γ-WO 3 ), employing ambient pressure X-ray photoelectron spectroscopy, density functional theory calculations and microkinetic modeling to investigate the dynamic evolution of surface states at varied temperatures. At room temperature, hydrogen spillover results in the formation of W 5+ and hydrogen intermediates (hydroxyl species and adsorbed water), facilitated by Pt metal clusters. With increasing temperature, water desorption, reverse hydrogen spillover and surface-to-bulk diffusion of hydrogen atoms compete with each other, leading initially to reoxidation and then further reduction of W atoms in the near-surface. The combined experimental results and simulations provide a comprehensive understanding of the mechanisms underlying hydrogen interaction with reducible metal oxides, lending insights of relevance to the design of enhanced hydrogenation catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗