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All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China. Multiple observation platforms (e.g., upper-air soundings, Doppler radar, ships, wind profilers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional scale model (with grid size of 20 km) and Goddard Cumulus Ensemble (GCE) model (with 1 km grid size) are used to perform multi-day integration to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during SCSMEX Sensitivity tests on various land surface models, sea surface temperature (SST) variations, and cloud processes are performed to understand the precipitation processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. These tests have indicated that the land surface model has a major impact on the circulation over the S. China Sea. Cloud processes can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. The GCE-model results captured many observed precipitation characteristics because it used a fine grid size. For example, the model simulated rainfall temporal variation compared quite well to the sounding-estimated rainfall. The results show there are more latent heat fluxes prior to the onset of the monsoon. However, more rainfall was simulated after the onset of the monsoon. This modeling study indicates the latent heat fluxes (or evaporation) have more of an impact on precipitation processes and rainfall in the regional climate model simulations than in the cloud-resolving model simulations. Research is underway to determine if the difference in the grid sizes or the moist processes used in these two models is responsible for the differing influence of surface fluxes an precipitation processes.

Tao, W.-K.↗
NASA NTRS2011

Future Opportunities and Challenges in Remote Sensing of Drought

The value of satellite remote sensing for drought monitoring was first realized more than two decades ago with the application of Normalized Difference Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) for assessing the effect of drought on vegetation. Other indices such as the Vegetation Health Index (VHI) were also developed during this time period, and applied to AVHRR NDVI and brightness temperature data for routine global monitoring of drought conditions. These early efforts demonstrated the unique perspective that global imagers such as AVHRR could provide for operational drought monitoring through their near-daily, global observations of Earth's land surface. However, the advancement of satellite remote sensing of drought was limited by the relatively few spectral bands of operational global sensors such as AVHRR, along with a relatively short period of observational record. Remote sensing advancements are of paramount importance given the increasing demand for tools that can provide accurate, timely, and integrated information on drought conditions to facilitate proactive decision making (NIDIS, 2007). Satellite-based approaches are key to addressing significant gaps in the spatial and temporal coverage of current surface station instrument networks providing key moisture observations (e.g., rainfall, snow, soil moisture, ground water, and ET) over the United States and globally (NIDIS, 2007). Improved monitoring capabilities will be particularly important given increases in spatial extent, intensity, and duration of drought events observed in some regions of the world, as reported in the International Panel on Climate Change (IPCC) report (IPCC, 2007). The risk of drought is anticipated to further increase in some regions in response to climatic changes in the hydrologic cycle related to evaporation, precipitation, air temperature, and snow cover (Burke et al., 2006; IPCC, 2007; USGCRP, 2009). Numerous national, regional, and global efforts such as the Famine and Early Warning System (FEWS), National Integrated Drought Information System (NIDIS), and Group on Earth Observations (GEO), as well as the establishment of regional drought centers (e.g., European Drought Observatory) and geospatial visualization and monitoring systems (e.g, NASA SERVIR) have been undertaken to improve drought monitoring and early warning systems throughout the world. The suite of innovative remote sensing tools that have recently emerged will be looked upon to fill important data and knowledge gaps (NIDIS, 2007; NRC, 2007) to address a wide range of drought-related issues including food security, water scarcity, and human health.

Wardlow, Brian D.↗
NASA NTRS1999

Global-Scale Hydrology: Simple Characterization of Complex Simulation

Atmospheric general circulation models (AGCMS) are unique and valuable tools for the analysis of large-scale hydrology. AGCM simulations of climate provide tremendous amounts of hydrological data with a spatial and temporal coverage unmatched by observation systems. To the extent that the AGCM behaves realistically, these data can shed light on the nature of the real world's hydrological cycle. In the first part of the seminar, I will describe the hydrological cycle in a typical AGCM, with some emphasis on the validation of simulated precipitation against observations. The second part of the seminar will focus on a key goal in large-scale hydrology studies, namely the identification of simple, overarching controls on hydrological behavior hidden amidst the tremendous amounts of data produced by the highly complex AGCM parameterizations. In particular, I will show that a simple 50-year-old climatological relation (and a recent extension we made to it) successfully predicts, to first order, both the annual mean and the interannual variability of simulated evaporation and runoff fluxes. The seminar will conclude with an example of a practical application of global hydrology studies. The accurate prediction of weather statistics several months in advance would have tremendous societal benefits, and conventional wisdom today points at the use of coupled ocean-atmosphere-land models for such seasonal-to-interannual prediction. Understanding the hydrological cycle in AGCMs is critical to establishing the potential for such prediction. Our own studies show, among other things, that soil moisture retention can lead to significant precipitation predictability in many midlatitude and tropical regions.

Koster, Randal D.↗
NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 10

The Problem of Incomplete Mixing of Interstellar Components in the Solar Nebula: Very High Precision Isotopic Measurements with Isoprobes P and T. Finally: Presolar Graphite Grains Identified in Orgueil. Basaltic Ring Structures as an Analog for Ring Features in Athabasca Valles, Mars. Experimental Studies of the Water Sorption Properties of Mars-Relevant Porous Minerals and Sulfates. Silicon Isotope Ratio Variations in CAI Evaporation Residues Measured by Laser Ablation Multicollector ICPMS. Crater Count Chronology and Timing of Ridged Plains Emplacement at Schiaparelli Basin, Mars. Martian Valley Networks and Associated Fluvial Features as Seen by the Mars Express High Resolution Stereo Camera (HRSC). Fast-Turnoff Transient Electromagnetic (TEM) Field Study at the Mars Analog Site of Rio Tinto, Spain. Time Domain Electromagnetics for Mapping Mineralized and Deep Groundwater in Mars Analog Environments. Mineralogical and Seismological Models of the Lunar Mantle. Photometric Observations of Soils and Rocks at the Mars Exploration Rover Landing Sites. Thermal Infrared Spectral Deconvolution of Experimentally Shocked Basaltic Rocks Using Experimentally Shocked Plagioclase Endmembers.

Source record↗
NASA NTRS1993

Scaling, soil moisture and evapotranspiration in runoff models

The effects of small-scale heterogeneity in land surface characteristics on the large-scale fluxes of water and energy in the land-atmosphere system has become a central focus of many of the climatology research experiments. The acquisition of high resolution land surface data through remote sensing and intensive land-climatology field experiments (like HAPEX and FIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small scale heterogeneities and whether 'effective' parameters can be used in the macroscale models. To address this question of scaling, the probability distribution for evaporation is derived which illustrates the conditions for which scaling should work. A correction algorithm that may appropriate for the land parameterization of a GCM is derived using a 2nd order linearization scheme. The performance of the algorithm is evaluated.

Wood, Eric F.↗
NASA NTRS1994

A season of heat, water vapor, total hydrocarbon, and ozone fluxes at a subarctic fen

High-latitude environments are thought to play several critical roles in the global balance of radiatively active trace gases. Adequate documentation of the source and sink strengths for trace gases requires long time series of detailed measurements, including heat and moisture budgets. A fen near Schefferville, Quebec, was instrumented during the summer of 1990 for the measurement of the surface energy, radiation, and moisture balances as well as for eddy correlation estimates of ozone and methane flux. Despite the limited fetch at this site, analysis of the tower flux 'footprint' indicates that at least 80% of the flux observed originates from sources within the fen. Sensible heat fluxes averaged 25% of the daytime net radiation at the site, while the latent heat flux, determined from the energy balance, was 63%; the Bowen ratio varied from 0.2 to 0.8 from day to day, without a seasonal trend to the variation. The competing effects of rooted macrophyte development (with concomitant effects on roughness and transpiration) and the normal shift in synoptic pattern around day 200 to warm, dry conditions results in a lack of net seasonal effect on the energy partitioning. Over the period from days 170 to 230, the evaporation (167 mm) was double the rainfall, while the decline in water level was 107 mm, leaving a net runoff of 0.44 mm/d. The total hydrocarbon flux was 75-120 mg m(exp -2)/d, following a diurnal pattern similar to heat or moisture flux, while the daytime ozone flux was about -1.11 x 10(exp 11) molecules cm(exp -2)/s. A period near the end of the experiment, during week 30, produced the strongest total hydrocarbon flux, associated with warmer deep (1 m) soil temperatures, lower fen water levels, and the late summer shift in wind direction at that time. An early summer 'flush' of total hydrocarbon was not observed.

Moore, Kathleen E.↗
DOE OSTI2022

Fused anti-soiling and anti-reflective coatings

A method for applying a coating to a surface includes the step of providing a reaction mixture comprising a silicon alkoxide and an alcohol. A reaction limiting amount of water is added. The silicon alkoxides and water are allowed to react to form silica precursor particles during an initial reaction period. A coating precursor composition is prepared by adding an acid soluble in the alcohol to the reaction mixture during a second reaction period after the initial reaction period. The precursor silica particles grow to form silica nanofeatures having a major dimension that is larger than a major dimension of the silica precursor particles. The coating precursor composition is applied to a surface, and the alcohol and water are allowed to evaporate and the silica nanofeatures to adhere to the surface and form a nanostructured layer on the surface. A coating precursor composition and a coated article are also disclosed.

Lee, Dominic F.↗
NASA NTRS2020

Evidence for Multiple Diagenetic Episodes in Ancient Fluvial‐Lacustrine Sedimentary Rocks in Gale Crater, Mars

The Curiosity rover's exploration of rocks and soils in Gale crater has provided diverse geochemical and mineralogical data sets, underscoring the complex geological history of the region. We report the crystalline, clay mineral, and amorphous phase distributions of four Gale crater rocks from an 80‐m stratigraphic interval. The mineralogy of the four samples is strongly influenced by aqueous alteration processes, including variations in water chemistries, redox, pH, and temperature. Localized hydrothermal events are evidenced by gray hematite and maturation of amorphous SiO 2 to opal‐CT. Low‐temperature diagenetic events are associated with fluctuating lake levels, evaporative events, and ground water infiltration. Among all mudstones analyzed in Gale crater, the diversity in diagenetic processes is primarily captured by the mineralogy and X‐ray amorphous chemistry of the drilled rocks. Variations indicate a transition from magnetite to hematite and an increase in matrix‐associated sulfates suggesting intensifying influence from oxic, diagenetic fluids up section. Furthermore, diagenetic fluid pathways are shown to be strongly affected by unconformities and sedimentary transitions, as evidenced by the intensity of alteration inferred from the mineralogy of sediments sampled adjacent to stratigraphic contacts.

C N Achilles↗
NASA NTRS2005

Toward an Improved Understanding of the Global Fresh Water Budget

The major components of the global fresh water cycle include the evaporation from the land and ocean surfaces, precipitation onto the Ocean and land surfaces, the net atmospheric transport of water from oceanic areas over land, and the return flow of water from the land back into the ocean. The additional components of oceanic water transport are few, principally, the mixing of fresh water through the oceanic boundary layer, transport by ocean currents, and sea ice processes. On land the situation is considerably more complex, and includes the deposition of rain and snow on land; water flow in runoff; infiltration of water into the soil and groundwater; storage of water in soil, lakes and streams, and groundwater; polar and glacial ice; and use of water in vegetation and human activities. Knowledge of the key terms in the fresh water flux budget is poor. Some components of the budget, e.g. precipitation, runoff, storage, are measured with variable accuracy across the globe. We are just now obtaining precise measurements of the major components of global fresh water storage in global ice and ground water. The easily accessible fresh water sources in rivers, lakes and snow runoff are only adequately measured in the more affluent portions of the world. presents proposals are suggesting methods of making global measurements of these quantities from space. At the same time, knowledge of the global fresh water resources under the effects of climate change is of increasing importance and the human population grows. This paper provides an overview of the state of knowledge of the global fresh water budget, evaluating the accuracy of various global water budget measuring and modeling techniques. We review the measurement capabilities of satellite instruments as compared with field validation studies and modeling approaches. Based on these analyses, and on the goal of improved knowledge of the global fresh water budget under the effects of climate change, we suggest priorities for future improvements in global fresh water budget monitoring. The priorities are based on the potential of new approaches to provide improved measurement and modeling systems, and on the need to measure and understand the potential for a speed-up of the global water cycle under the effects of climate change.

Hildebrand, Peter H.↗
NASA NTRS2022

Irrigation and Warming Drive the Decreases in Surface Albedo Over High Mountain Asia

Human and climate induced land surface changes resulting from irrigation, snow cover decreases, and greening impact the surface albedo over High Mountain Asia (HMA). Here we use a partial information decomposition approach and remote sensing data to quantify the effects of the changes in leaf area index, soil moisture, and snow cover on the surface albedo in HMA, home to over a billion people, from 2003 to 2020. The study establishes strong evidence of anthropogenic agricultural water use over irrigated lands (e.g., Ganges-Brahmaputra) which causes the highest surface albedo decreases (≤1%/year). Greening and decreased snow cover from warming also drive changes in visible and near-infrared surface albedo in different areas of HMA. The significant role of irrigation and greening in influencing albedo suggests the potential of a positive feedback cycle where albedo decreases lead to increased evaporative demand and increased stress on water resources.

Climate sciences↗
DOE OSTI2025

GNSS-based Vegetation Optical Depth, Tree Sway, and Evapotranspiration data from the Niwot Ridge Subalpine Forest (US-NR1) AmeriFlux site

This data package contains data and information about Global Navigation Satellite System (GNSS)-based Vegetation Optical Depth (VOD), tree sway motion, and eddy-covariance evapotranspiration (ET) data collected at the Niwot Ridge Subalpine Forest AmeriFlux site (US-NR1). The raw GNSS data were collected between May 2022 and August 2023. Other processed datasets such as tree sway motion and ET data are also included. The goal was to study the water content within a subalpine forest and, more specifically, examine the canopy evaporation process. This data archive includes all data that were used within the following Biogeosciences discussion paper that further summarizes the research objectives and conclusions:Burns, S.P., V. Humphrey, E.D. Gutmann, M.S. Raleigh, D.R. Bowling, and P.D. Blanken, 2025: Using GNSS-based vegetation optical depth, tree sway motion, and eddy-covariance to examine evaporation of canopy-intercepted rainfall in a subalpine forest. EGUsphere [preprint],https://doi.org/10.5194/egusphere-2025-1755This data archive also supplements the 30-min Lawrence Berkeley National Laboratory (LBNL) AmeriFlux dataset for US-NR1 (i.e., https://doi.org/10.17190/AMF/1246088) and updates what was in the 2020 ESS-DIVE US-NR1 archive (https://doi.org/10.15485/1671825) to include data from the years 2020-2025. More specifically, the following updates are provided: (i) five-minute statistics (means, variances, covariances) of all data measured by the US-NR1 data system between Sep 2020 and Jun 2025 in netCDF format, (ii) the electronic logbook of US-NR1 site visits, (iii) a web calendar (in HTML format) documenting activity at the site (a replica of https://urquell.colorado.edu/calendar/), (iv) photos taken at the site between years 2020 and present day (Aug 2025), and (v) several auxiliary datasets, primary related to trees near the site, soil properties, soil moisture and soil temperature, and subcanopy radiation data. The data package is setup so that the web calendar, photos, and electronic logbook can be easily accessed on a local computer using a web browser. The provided data files are in either BINEX or SBF format (for the raw GNSS data), netCDF, CSV, ASCII, or MATLAB format. To obtain a better understanding about the archive, please start by reading the following PDF which is included within the data archive:README_ESS_DIVE_USNR1_2025_readme_first.pdf.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Production of simple molecules on the surface of Mercury

Lunar sample studies have shown that solar-wind irradiation of the lunar surface has produced a variety of low-molecular-weight compounds. Analysis of the lunar soils has revealed the presence of H2, CH4, H2O, N2, CO, CO2, He, Ne and other components which are extralunar. Irradiation experiments on lunar materials and analogs have shown that solar-wind and solar-flare irradiation of the lunar surface produces selected low-molecular-weight components. Solar-wind irradiation of Mercury's surface should also produce a wide variety of low-molecular-weight species because of the increased solar flux, which results from Mercury being nearer the sun than the moon. The thermal regime of Mercury's surface would result in thermal evaporation of low-temperature components followed by 'cold-trapping' on the night-time side of the planet. Such desorption-adsorption processes assist chemical weathering of Mercury's regolith.

Gibson, E. K., Jr.↗
NASA NTRS1994

Snow hydrology in a general circulation model

A snow hydrology has been implemented in an atmospheric general circulation model (GCM). The snow hydrology consists of parameterizations of snowfall and snow cover fraction, a prognostic calculation of snow temperature, and a model of the snow mass and hydrologic budgets. Previously, only snow albedo had been included by a specified snow line. A 3-year GCM simulation with this now more complete surface hydrology is compared to a previous GCM control run with the specified snow line, as well as with observations. In particular, the authors discuss comparisons of the atmospheric and surface hydrologic budgets and the surface energy budget for U.S. and Canadian areas. The new snow hydrology changes the annual cycle of the surface moisture and energy budgets in the model. There is a noticeable shift in the runoff maximum from winter in the control run to spring in the snow hydrology run. A substantial amount of GCM winter precipitation is now stored in the seasonal snowpack. Snow cover also acts as an important insulating layer between the atmosphere and the ground. Wintertime soil temperatures are much higher in the snow hydrology experiment than in the control experiment. Seasonal snow cover is important for dampening large fluctuations in GCM continental skin temperature during the Northern Hemisphere winter. Snow depths and snow extent show good agreement with observations over North America. The geographic distribution of maximum depths is not as well simulated by the model due, in part, to the coarse resolution of the model. The patterns of runoff are qualitatively and quantitatively similar to observed patterns of streamflow averaged over the continental United States. The seasonal cycles of precipitation and evaporation are also reasonably well simulated by the model, although their magnitudes are larger than is observed. This is due, in part, to a cold bias in this model, which results in a dry model atmosphere and enhances the hydrologic cycle everywhere.

Marshall, Susan↗
DOE OSTI2025

Denoising Autoencoder for Reconstructing Sensor Observation Data and Predicting Evapotranspiration: Noisy and Missing Values Repair and Uncertainty Quantification

Abstract Machine learning (ML) methods applied in scientific research often deal with interrelated features in high‐dimensional data. Reducing data noise and redundancy is needed to increase prediction accuracy and efficiency especially when dealing with data from field sensors. We explored an unsupervised learning method, the denoising autoencoder (DAE), to extract the underlying data structure from noisy raw data in the context of predicting hydrologic quantities from multiple field sensors. These sensors have intrinsic instrumental noise and occasional malfunctions that cause missing values. Our DAE neural network reconstructed meteorological sensor data containing noise and missing values to predict evapotranspiration in a mountainous watershed. The DAE reconstructed the sensor variables with a mean coefficient of determination value of 0.77 across 15 dimensions representing individual sensors. It reduced variance and bias uncertainties compared to a classical autoencoder model. The reconstruction quality varied across dimensions depending on their cross‐correlation and alignment with the underlying data structure. Uncertainties arising from the model structure were overall higher than those resulting from data corruption. We attached the DAE structure to a downstream ET‐prediction neural network in three formats and achieved reasonably accurate ET predictions . The use of the DAE notably reduced variance uncertainty in ET prediction. However, excessive variance reduction may be accompanied by an increase in bias due to the intrinsic bias‐variance tradeoff. Our method of evaluating and reducing uncertainties in aggregated data from different sources can be used to improve predictive models, process understanding, and uncertainty quantification for better water resource management. Plain Language Summary We present a machine learning method, namely the denoising autoencoder, which reduces the effects of data noise and missing values typically present in scientific data sets collected through sensor measurements. This method selects the most relevant information from noisy raw data collected by the instruments and fills in missing values. To demonstrate the effectiveness of our method, we applied it to predict evapotranspiration, a hydrologic variable that represents the water moved from the land surface to the atmosphere through a combination of evaporation and plant water use (transpiration). We also used a random sampling technique (the Monte Carlo method) to compare the uncertainty in the predictions when using the raw and noisy data versus the reconstructed data. The denoising process produced more accurate predictions of evapotranspiration with less uncertainty. Improved predictions of evapotranspiration can lead to a better understanding and accounting of water budgets. This ML approach is broadly suitable for a wide variety of applications that involve noisy sensor data with missing values. Key Points We used a denoising autoencoder (DAE) neural network to reduce noise in meteorological and soil sensor observations by on average We used Monte Carlo sampling to estimate the bias and variance of all model outputs, including uncertainty sources from data and the model We attached the DAE component to a downstream neural network to predict ET with the variance reduced by , compared to that without the DAE

denoising autoencoder↗
DOE OSTI2023

Earlier Ecological Drought Detection by Involving the Interaction of Phenology and Eco-Physiological Function

Meteorological drought indices like the Standardized Precipitation Evaporation Index (SPEI) are frequently used to diagnose “ecological drought,” despite the fact that they were not explicitly designed for this purpose. More recently developed indices like the Evaporative Stress Index (ESI), which is based on the degree of coupling between actual to potential evapotranspiration, may better capture dynamic plant response to moisture limitations. However, the skill of these indices at describing plant water stress is rarely evaluated at sub-seasonal timescales over which drought evolves. Moreover, it remains unclear how variability in phenological timing impacts and complicates early drought detection. Here, we compared the ability of ESI and SPEI to reflect the dynamics of ecological drought in forests and grasslands, based on anomalies of Gross Primary Productivity (GPP), surface conductance (G s , a proxy for stomatal conductance), soil moisture, and vapor pressure deficit. ESI performed better than SPEI in capturing the dynamics of GPP and G s , but still missed early ecological drought signals due to biases linked to earlier onset of spring leaf development. Thus, we developed a modified variant of the ESI (ESI LAI ) that accounts for the complicating effects of phenological shifts in leaf area index (LAI). The ESI LAI detected drought onset up to 7–10 weeks earlier than SPEI and ESI. Additionally, drought onset dates determined from ESI LAI are close to (±2 weeks) the dates determined from LAI-corrected anomalies of G s , and GPP, as well as the onset dates of soil water deficit and atmospheric aridity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Land-Atmosphere Interactions: Successes, Problems and Prospects

After two decades of active research, a much better understanding of the broader role of biospheric processes on the local climate has emerged. A surface-albedo increase, particularly in desert border regions of the subtropics (as well as the deforested tropical regions), leads to a net surface energy deficit, which in turn leads to a relative sinking and reduced rainfall. On the other hand, studies of the influence of altered ratios of evapotranspiration and sensible fluxes, in situations where the net solar income is unchanged, show that evapotranspiration is a more desirable flux for increased precipitation and vitality of the biosphere. Besides providing water vapor and convective available potential energy (CAPE) to the lower troposphere, evapotranspiration helps in building larger CAPE before "turning on" the moist-convection. Larger CAPE in the lower troposphere enables convection to reach into the deeper atmosphere thereby heating the upper troposphere; indeed, moist-convection is also accompanied by the evaporation of falling precipitation that cools and moistens the lower atmosphere. While convective, as opposed to stratiform, precipitation reduces the fractional cloud cover; it also allows more solar radiation to reach the surface thereby invigorating surface fluxes. These, together with moist convection and associated downdrafts help to maintain the characteristic upper temperature limit(s) of the moist-land as well as oceanic regions. Regardless of the above understanding, several important problems continue to hinder the accurate simulation of a realistic land atmosphere interaction in a numerical model (both GCM and/or Meso-scale models). Among the unsolved problems are parameterization of sub-grid scale land processes that include small-scale variability of soil moisture, snow-cover and snow-physics, the biodiversity of the biosphere, orography, local drainage characteristics under natural conditions, and surface flow over the natural terrain. A well-known non-linear response of surface fluxes to these variations makes the problem of parameterizing land-atmosphere interaction processes hard-to-address and simulate, particularly in a GCM. In our presentation, we will discuss how orographic, snow-cover, and water table interactions can be included into a Simple Biosphere Model such as SiB/SSiB. Figure I shows how, in the Russian region, spring snowmelt affects the soil moisture profile. Corresponding figure 2 shows how interaction with the water table decreases the natural evapotranspiration in the Sahel region simulation. While these simulations need better validation with data, the simulations reveal that surface processes are sensitive to these parameterizations. With these developments, we continue to advance our understanding of the interaction of land with the atmosphere aloft, but the intrinsic variability of the newer parameters, e. g., hydraulic properties of the soil, diminish the positive influences of these advances on the improved climate simulation with GCMs.

Sud, Y. C.↗
NASA NTRS1998

Soil temperatures and stability of ice-cemented ground in the McMurdo Dry Valleys, Antarctica

Year-round temperature measurements at 1600 m elevation during 1994 in the Asgard Range Antarctica, indicate that the mean annual frost point of the ice-cemented ground, 25 cm below the surface, is -21.7 +/- 0.2 degrees C and the mean annual frost point of the atmosphere is -27.5 +/- 1.0 degrees C. The corresponding mean annual temperatures are -24.9 degrees C and -23.3 degrees C. These results imply that there is a net flux of water vapour from the ice to the atmosphere resulting in a recession of the ice-cemented ground by about 0.4-0.6 mm yr-1. The level of the ice-cemented permafrost is about 12 cm below the level of dry permafrost. The summer air temperatures would have to increase about 7 degrees C for thawing temperatures to just reach the top of the subsurface ice. Either subsurface ice at this location is evaporating over time or there are sporadic processes that recharge the ice and maintain equilibrium over long timescales.

NASA Discipline Exobiology↗
DOE OSTI2024

HSQC spectra of lignin isolated from poplar roots

Here we present a curated dataset of two-dimensional heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra of lignin isolated from roots of a greenhouse grown natural population of an energy crop poplar (Populus trichocarpa). Dormant cuttings of field-grown poplar were grown in 6-liter pots in a peat-based media containing bark, perlite, vermiculite, dolomite lime and a wetting agent in an environmentally controlled greenhouse. Temperatures were between 21 and 23 °C, with supplemental lighting to support a 16-h day length using 1000-watt high-pressure sodium lights in greenhouse. Once established, all plants were cut-back, allowed to regrow and harvested at the same time following an eight-month long growth period. Plants were harvested and the belowground roots were washed off soils, blotted, dried in an oven at 70 °C for 3 days, and Wiley milled (mesh size 20). The roots were Soxhlet-extracted with toluene/ethanol for 24 h to remove extractives. The extracted roots were ball-milled in a Retsch PM100 planetary ball mill using a porcelain jar with ceramic balls at 600 rpm for 2 h (in 5 min on and 5 min off cycles to avoid excessive sample heating). The ball-milled materials were then subjected to enzymatic hydrolysis for 48 h followed by centrifugation and washing with deionized water. The solid residue was extracted twice with 96% (v/v) 1,4-dioxane/water mixture at room temperature overnight. The extracts were combined, rotary evaporated, and freeze-dried to recover lignin. The dry lignin samples were dissolved in deuterated dimethyl sulfoxide (d6) and transferred into a 5 mm tube. 13C–1H HSQC experiments were performed in a Bruker Avance III HD 500 MHz NMR spectrometer operating at a frequency of 125.12 MHz for the 13C nucleus using a standard Bruker pulse sequence on a Prodigy platform cryoprobe. The NMR spectra were acquired under the following acquisition conditions: 220 ppm spectral width in F1 (13C) dimension with 256 data points and 12 ppm spectral width in F2 (1H) dimension with 1024 data points, a 90° pulse, a one bond C–H coupling constant of 145 Hz, a 1.0 s pulse delay, and 64 scans. Spectra were processed using the Bruker TopSpin software. Additional meta data is embedded in the raw spectra figures.

HSQC, lignin, poplar, roots, CBI↗