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The desorptivity model of bulk soil-water evaporation

Available models of bulk evaporation from a bare-surfaced soil are difficult to apply to field conditions where evaporation is complicated by two main factors: rate-limiting climatic conditions and redistribution of soil moisture following infiltration. Both factors are included in the "desorptivity model', wherein the evaporation rate during the second stage (the soil-limiting stage) of evaporation is related to the desorptivity parameter, A. Analytical approximations for A are presented. The approximations are independent of the surface soil moisture. However, calculations using the approximations indicate that both soil texture and soil moisture content at depth significantly affect A. Because the moisture content at depth decreases in time during redistribution, it follows that the A parameter also changes with time. Consequently, a method to calculate a representative value of A was developed. When applied to field data, the desorptivity model estimated cumulative evaporation well. The model is easy to calculate, but its usefulness is limited because it requires an independent estimate of the time of transition between the first and second stages of evaporation. The model shows that bulk evaporation after the transition to the second stage is largely independent of climatic conditions.

Clapp, R. B.↗

Landsat Science: 40 Years of Innovation and Opportunity

Landsat satellites have provided unparalleled Earth-observing data for nearly 40 years, allowing scientists to describe, monitor and model the global environment during a period of time that has seen dramatic changes in population growth, land use, and climate. The success of the Landsat program can be attributed to well-designed instrument specifications, astute engineering, comprehensive global acquisition and calibration strategies, and innovative scientists who have developed analytical techniques and applications to address a wide range of needs at local to global scales (e.g., crop production, water resource management, human health and environmental quality, urbanization, deforestation and biodiversity). Early Landsat contributions included inventories of natural resources and land cover classification maps, which were initially prepared by a visual interpretation of Landsat imagery. Over time, advances in computer technology facilitated the development of sophisticated image processing algorithms and complex ecosystem modeling, enabling scientists to create accurate, reproducible, and more realistic simulations of biogeochemical processes (e.g., plant production and ecosystem dynamics). Today, the Landsat data archive is freely available for download through the USGS, creating new opportunities for scientists to generate global image datasets, develop new change detection algorithms, and provide products in support of operational programs such as Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (REDD). In particular, the use of dense (approximately annual) time series to characterize both rapid and progressive landscape change has yielded new insights into how the land environment is responding to anthropogenic and natural pressures. The launch of the Landsat Data Continuity Mission (LDCM) satellite in 2012 will continue to propel innovative Landsat science.

Cook, Bruce D.↗

Chapter 6: Sulfur on Mars from the Atmosphere to the Core

Observations of the martian surface from orbiting spacecraft and in situ landers and rovers, as well as analyses of martian meteorites in terrestrial laboratories, have consistently indicated that Mars is a sulfur-rich planet. The global inventory of sulfur, from the atmosphere to the core, carries widespread implications of potential geophysical, geochemical, climatological, and astrobiological significance. For example, the sulfur content of the core carries implications for core density; the speciation of igneous sulfur minerals reflects the oxidation state of the magma from which they formed; sulfur-bearing gases may have exerted control on the temperatures at the surface of early Mars; and the widespread availability of sulfur on Mars would have provided an abundant source for energy and nutrients to fuel sulfur-metabolizing microbes, such as those that arose during the emergence of primitive life on Earth. Here we provide an overview of martian sulfur and its relevance to these areas of interest, including a discussion of analytical techniques and results acquired by space missions and meteorite analyses to date. We review current studies modeling the potential effects of sulfur-bearing gases on the past martian climate and possible constraints on atmospheric composition implied by sulfur isotopic data. We also explore the importance of sulfur to the search for extinct or extant life on Mars. Finally, we summarize a few areas of interest to future work, including advances in space exploration technology and preparation for Mars sample return.

Climate↗

The rigid body obliquity history of Mars

The variations in the obliquity of Mars are considered to be the likely source of major climatic variations on that planet. This paper explores the range of uncertainty in the obliquity history of Mars associated with the present uncertainty in the axial precession rate, applying three different analytic techniques. It is shown that, within the observationally allowed range of axial precession rates, there are some intervals where the obliquity history of Mars is only weakly dependent on the precession rate, and other intervals where the obliquity is very sensitively dependent on the precession rate. A very wide range of obliquity histories are possible, including some which involve resonance passages within the relatively recent past. It is estimated that obliquities as high as 51.4 deg or as low as 0.2 deg may have occurred within the last ten million years.

Bills, Bruce G.↗

Infrared radiation parameterizations in numerical climate models

This study presents various approaches to parameterizing the broadband transmission functions for utilization in numerical climate models. One-parameter scaling is applied to approximate a nonhomogeneous path with an equivalent homogeneous path, and the diffuse transmittances are either interpolated from precomputed tables or fit by analytical functions. Two-parameter scaling is applied to parameterizing the carbon dioxide and ozone transmission functions in both the lower and middle atmosphere. Parameterizations are given for the nitrous oxide and methane diffuse transmission functions.

Chou, Ming-Dah↗

Multi-Scale Integrated Monitoring System for Enhancing Methane Emission Detection, Quantification & Prediction

This report details the progress and findings of a comprehensive study on reviewing existing solutions, identifying technology gaps, and formulating an “all-in-one” integrated strategy for developing the next-generation multiscale methane monitoring and modeling platform, conducted under grant number DE-FE0032292. Co-led by Dr. David Ebert, Dr. Binbin Weng, and Dr. Chenghao Wang at the University of Oklahoma, the project’s goal was to develop an integrated approach for building this engineering platform to detect, quantify, and mitigate methane emissions across various temporal scale, spatial scales, and sectors. The planning grant study began with an extensive review of various methane sensing and monitoring technologies and systems, surveying over 100 technology providers globally. This review revealed the prevalence of optical methods over chemical methods in commercially available sensors, with Non-Dispersive Infrared (NDIR), Tunable Diode Laser Absorption Spectroscopy (TDLAS), and Optical Gas Imaging (OGI) cameras being the most prevalent options. A trend towards more advanced optical techniques was observed, driven by increased regulatory focus and technological advancements. The technical evaluation of these sensing technologies provided crucial insights into their capabilities and limitations. The study examined emerging technologies such as Differential Absorption LiDAR (DIAL), which show promise for high-precision and long-range detection. The team then investigated the features and application bandwidth of various sensing platforms, including handheld, fixed/stationary, mobile, aerials, and spaceborne monitors. Pilot field studies were conducted to assess the capabilities of solutions for different emission scenarios. Field work with sensor deployments was conducted at three distinct site types: an oil & gas industry site, a cattle ranching operation, and a waste processing facility. The team also conducted a thorough review of methane flux inverse modeling approaches, focused on physically based methods. These approaches were categorized into simple, intermediate, and advanced methods. A realtime WRF-GHG (Weather Research and Forecasting-Greenhouse Gas) modeling system was developed and applied, incorporating multiple data sources to guide field experiments and inform methane plume detection. The project identified and analyzed numerous categories of methane data sources, including satellite measurements, ground-based sensors, and inventory databases. Key platforms examined include EDGAR, EPA GHGI, NASA TROPOMI, Carbon Mapper, and Climate TRACE, among others. The team proposed an architecture for a comprehensive methane monitoring platform. This system incorporates multi-source data acquisition, advanced data processing and assimilation, interactive visualization tools, and analytical capabilities for emissions forecasting and scenario analysis. The proposed platform aims to provide a user-friendly interface catering to various stakeholders, from researchers to policymakers. The architecture includes sophisticated data ingestion methods, a centralized data warehouse, and advanced analytical tools for data fusion and interpretation. To ensure the relevance and effectiveness of the proposed system, a comprehensive survey was conducted to gather stakeholder input on system requirements. Key findings include a strong need for integrating various data types and formats, a preference for real-time data updates and advanced visualization tools, and a demand for user-friendly interfaces catering to different expertise levels.

03 NATURAL GAS↗

Demonstration of new PCSD capabilities

The new, more flexible and more friendly graphics capabilities to be available in later releases of the Pilot Climate Data System were demonstrated. The LIMS-LAMAT data set was chosen to illustrate these new capabilities. Pseudocolor and animation were used to represent the third and fourth dimensions, expanding the analytical capabilities available through the traditional two-dimensional x-y plot. In the new version, variables for the axes are chosen by scrolling through viable selections. This scrolling feature is a function of the new user interface customization. The new graphics are extremely user friendly and should free the scientist to look at data and converse with it, without doing any programming. The system is designed to rapidly plot any variable versus any other variable and animate by any variable. Any one plot in itself is not extraordinary; however, the fact that a user can generate the plots instead of a programmer distinguishes the graphics capabilities of the PCDS from other software packages. In addition, with the new CDF design, the system will become more generic, and the new graphics will become much more rigorous in the area of correlative studies.

Gough, M.↗

The effect of polar caps on obliquity

Rubincam has shown that the Martian obliquity is dependent on the seasonal polar caps. In particular, Rubincam analytically derived this dependence and showed that the change in obliquity is directly proportional to the seasonal polar cap mass. Rubincam concludes that seasonal friction does not appear to have changed Mars' climate significantly. Using a computer model for the evolution of the Martian atmosphere, Haberle et al. have made a convincing case for the possibility of huge polar caps, about 10 times the mass of the current polar caps, that exist for a significant fraction of the planet's history. Since Rubincam showed that the effect of seasonal friction on obliquity is directly proportional to polar cap mass, a scenario with a ten-fold increase in polar cap mass over a significant fraction of the planet's history would result in a secular increase in Mars' obliquity of perhaps 10 degrees. Hence, the Rubincam conclusion of an insignificant contribution to Mars' climate by seasonal friction may be incorrect. Furthermore, if seasonal friction is an important consideration in the obliquity of Mars, this would significantly alter the predictions of past obliquity.

Lindner, B. L.↗

Proposed Science Requirements and Acquisition Priorities for the First Mars Sample Return

A sample return mission is an important next step in the exploration of Mars. The first sample return should come early in the program time-line because the science derived from earth-based analyses of samples provides crucial "ground truth" needed for further exploration planning, enhancement of remote measurements, and achieving science goals and objectives that include: (1) the search for environments that may support life and any indicators of the past or present existence of life, (2) understanding the history of water and climate on Mars, (3) understanding the evolution of Mars as a planet. Returned samples from Mars will have unique value because they can be studied by scientists worldwide using the most powerful analytical instruments available. Furthermore, returned Mars samples can be preserved for studies by future generations of scientists using new techniques and addressing new issues in Mars science. To ensure a high likelihood of success, the first sample return strategy should be simple and focused. We outline a fundamental set of sample requirements and acquisition priorities for Mars sample return.

Agee, C. B.↗

Near Real-Time Flood Monitoring and Impact Assessment Systems

Floods are the costliest natural disaster, causing approximately 6.8 million deaths in the twentieth century alone. Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD. Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries. Projections by the Intergovernmental Panel on Climate Change (IPCC) suggest that precipitation extremes, rainfall intensity, storm intensity, and variability are increasing due to climate change. Increasing hydrologic uncertainty will likely lead to unprecedented extreme flood events. As such, there is a vital need to enhance and further develop traditional techniques used to rapidly assess flooding and extend analytical methods to estimate impacted population and infrastructure. Measuring flood extent in situ is generally impractical, time consuming, and can be inaccurate. Remotely sensed imagery acquired from space-borne and airborne sensors provides a viable platform for consistent and rapid wall-to-wall monitoring of large flood events through time. Terabytes of freely available satellite imagery are made available online each day by NASA, ESA, and other international space research institutions. Advances in cloud computing and data storage technologies allow researchers to leverage these satellite data and apply analytical methods at scale. Repeat-survey earth observations help provide insight about how natural phenomena change through time, including the progression and recession of floodwaters. In recent years, cloud-penetrating radar remote sensing techniques (e.g., Synthetic Aperture Radar) and high temporal resolution imagery platforms (e.g., MODIS and its 1-day return period), along with high performance computing infrastructure, have enabled significant advances in software systems that provide flood warning, assessments, and hazard reduction potential. By incorporating social and economic data, researchers can develop systems that automatically quantify the socioeconomic impacts resulting from flood disaster events.

Ahamed, Aakash↗

Near Real-Time Flood Monitoring and Impact Assessment Systems

Floods are the costliest natural disaster (United Nations 2004), causing approximately6.8 million deaths in the twentieth century alone (Doocy et al. 2013).Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD(Munich Re 2013). Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries (Davies et al. 2014).Projections by the Intergovernmental Panel on Climate Change (IPCC) suggest that precipitation extremes, rainfall intensity, storm intensity, and variability are increasing due to climate change (IPCC 2007). Increasing hydrologic uncertainty will likely lead to unprecedented extreme flood events. As such, there is a vital need to enhance and further develop traditional techniques used to rapidly assessflooding and extend analytical methods to estimate impacted population and infrastructure.

flood↗

Sub-Mesoscales at Ocean Fronts: Dissipation of Eddy Kinetic Energy

D’Asaro et al. measured the dissipation of eddy kinetic energy at the Kuroshio ocean front, found it to be 1-2 orders of magnitude larger than the value predicted by the law of the wall and suggested that the enhancement is due to sub-mesoscales, SM. To assess their suggestion, we employ two SM models. In the first model the buoyancy flux is based on baroclinic instabilities only and there is no momentum flux (Reynolds stresses). The model is unable to reproduce the Kuroshio data. The second model includes baroclinic instabilities, wind stress and Reynolds stresses. It reproduces the data satisfactorily. The analytic formula for the dissipation that we present can be used in OGCMs to parameterize dissipation at ocean fronts other than Kuroshio, e.g., Gulf Stream and ACC, an extension that could improve the predictions of climate studies.

sub-mesoscale models↗

Predictive analytics of selections of russet potatoes

We explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high-yield, disease-resistant, and climate-resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state-of-the-art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1-score, and Matthews correlation coefficient (MCC) for model evaluation. The top-performing models, namely a feedforward neural network classifier (Neural Net), a histogram-based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data-generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC-ROC) and MCC. The simulation results highlight that non-linear models like SVM and HGBC consistently show higher AUC-ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision-making in breeding programs.

60 APPLIED LIFE SCIENCES↗

Electrochemical approaches for chemical and biological analysis on Mars

Obtaining in situ chemical data from planetary bodies such as Mars or Europa can present significant challenges. The one analytical technique that has many of the requisite characteristics to meet such a challenge is electroanalysis. Described here are three electroanalytical devices designed for in situ geochemical and biological analysis on Mars. The Mars Environmental Compatibility Assessment (MECA) was built and flight qualified for the now cancelled NASA Mars 2001 Lander. Part of MECA consisted of four "cells" containing arrays of electrochemical based sensors for measuring the ionic species in soil samples. A next-generation MECA, the Robotic Chemical Analysis Laboratory (RCAL), uses a carousel-type system to allow for greater customization of analytical procedures. A second instrument, proposed as part of the 2007 CryoScout mission, consists of a flow-through inorganic chemical analyzer (MICA). CryoScout is a torpedo-like device designed for subsurface investigation of the stratigraphic climate record embedded in Mars' north polar cap. As the CryoScout melts its way through the ice cap, MICA will collect and analyze the meltwater for a variety of inorganics and chemical parameters. By analyzing the chemistry locked in the layers of dust, salt, and ice, geologists will be able to determine the recent history of climate, water, and atmosphere on Mars and link it to the past. Finally, electroanalysis shows its abilities in the detection of possible microorganism on Mars or elsewhere in the solar system. To identify an unknown microorganism, one that may not even use Earth-type biochemistry, requires a detection scheme which makes minimal assumptions and looks for the most general features. Recent work has demonstrated that the use of an array of electrochemical sensors which monitors the changes in a solution via electrical conductivity, pH, and ion selective electrodes, can be used to detect minute chemical perturbations caused by the growth of bacteria and with the correct methodology provide unamibiguous detection of such life forms.

Non-NASA Center↗

Development and Commercialization of a Nanosegrated Oxygen Evolution Reaction Electrocatalyst (CRADA)

This collaborative project leverages advanced characterization tools, catalyst treatment and electrochemical testing capabilities at LBNL to help commercialize a bimetallic nanosegrated catalysts for oxygen evolution reaction in proton-exchange membrane water electrolyzers. This project also has three industrial partners who are involved in catalyst scale-up synthesis, large electrode fabrication and large electrode electrochemical testing. This project investigates a broad range of topics including electrocatalysis, ink rheology and electrode fabrication and testing. This knowledge could help bridge the performance and durability gap from laboratory-developed materials (such as electrocatalysts) to applications in commercial devices. The research results also bring fundamental understanding of possible degradation mechanisms that occur under extremely oxidative potentials including material and morphological changes. The project will help accelerate the deployment of proton-exchange membrane water electrolyzers. The public benefits could include creating jobs and increasing public awareness of potential clean technologies for green hydrogen production. Ultimately, the project will help national wide effort of flighting climate change and achieving carbon neutrality by 2050.

30 DIRECT ENERGY CONVERSION↗

A solar radiation model for use in climate studies

A solar radiation routine is developed for use in climate studies that includes absorption and scattering due to ozone, water vapor, oxygen, carbon dioxide, clouds, and aerosols. Rayleigh scattering is also included. Broadband parameterization is used to compute the absorption by water vapor in a clear atmosphere, and the k-distribution method is applied to compute fluxes in a scattering atmosphere. The reflectivity and transmissivity of a scattering layer are computed analytically using the delta-four-stream discrete-ordinate approximation. The two-stream adding method is then applied to compute fluxes for a composite of clear and scattering layers. Compared to the results of high spectral resolution and detailed multiple-scattering calculations, fluxes and heating rate are accurately computed to within a few percent. The high accuracy of the flux and heating-rate calculations is achieved with a reasonable amount of computing time. With the UV and visible region grouped into four bands, this solar radiation routine is useful not only for climate studies but also for studies on photolysis in the upper atmosphere and photosynthesis in the biosphere.

Chou, Ming-Dah↗

A Framework Using Applied Process Analysis Methods to Assess Water Security in the Vu Gia–Thu Bon River Basin, Vietnam

The Vu Gia–Thu Bon (VG–TB) river basin is facing numerous challenges to water security, particularly in light of the increasing impacts of climate change. These challenges, including salinity intrusion, shifts in rainfall patterns, and reduced water supply in downstream areas, are of great concern. This study comprehensively assessed the current state of water security in the basin using robust statistical analysis methods such as the Process Analysis Method (PAM), SMART principle, and Analytic Hierarchy Process (AHP). This resulted in the development of a comprehensive assessment framework for water security in the VG–TB river basin. This framework identified five key dimensions, with basin development activities (0.32), the ability to meet water needs (0.24), and natural disaster resilience (0.19) being the most crucial and water resource potential being the least crucial (0.11) according to the AHP methodology. The latter also highlighted 15 indicators, four of which are particularly influential, including waste resources (0.54), flood (0.53), water storage capacity (0.45), and basin governance (0.42). Furthermore, 28 variables with high weight factors were identified. This framework aligns with the UN-Water water security definition and addresses the global water sustainability criteria outlined in Sustainable Development Goal 6 (SDG6). It enables the computation of a comprehensive Water Security Index (WSI) for specific regions, providing a strong foundation for decision-making and policy formulation. It aims to enhance water security in the context of climate change and support sustainable basin development, thereby guiding future research and policy decisions in water resource management.

54 ENVIRONMENTAL SCIENCES↗

NASA Wrangler: Automated Cloud-Based Data Assembly in the RECOVER Wildfire Decision Support System

NASA Wrangler is a loosely-coupled, event driven, highly parallel data aggregation service designed to take advantageof the elastic resource capabilities of cloud computing. Wrangler automatically collects Earth observational data, climate model outputs, derived remote sensing data products, and historic biophysical data for pre-, active-, and post-wildfire decision making. It is a core service of the RECOVER decision support system, which is providing rapid-response GIS analytic capabilities to state and local government agencies. Wrangler reduces to minutes the time needed to assemble and deliver crucial wildfire-related data.

decision support↗