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NASA NTRS2006

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

Chatterji, Gano B.↗

NASA NTRS2009

Severe Space Weather Events--Understanding Societal and Economic Impacts: A Workshop Report - Extended Summary

The effects of space weather on modern technological systems are well documented in both the technical literature and popular accounts. Most often cited perhaps is the collapse within 90 seconds of northeastern Canada's Hydro-Quebec power grid during the great geomagnetic storm of March 1989, which left millions of people without electricity for up to 9 hours. This event exemplifies the dramatic impact that severe space weather can have on a technology upon which modern society critically depends. Nearly two decades have passed since the March 1989 event. During that time, awareness of the risks of severe space weather has increased among the affected industries, mitigation strategies have been developed, new sources of data have become available, new models of the space environment have been created, and a national space weather infrastructure has evolved to provide data, alerts, and forecasts to an increasing number of users. Now, 20 years later and approaching a new interval of increased solar activity, how well equipped are we to manage the effects of space weather? Have recent technological developments made our critical technologies more or less vulnerable? How well do we understand the broader societal and economic impacts of severe space weather events? Are our institutions prepared to cope with the effects of a 'space weather Katrina,' a rare, but according to the historical record, not inconceivable eventuality? On May 22 and 23, 2008, a one-and-a-half-day workshop held in Washington, D.C., under the auspices of the National Research Council's (NRC's) Space Studies Board brought together representatives of industry, the federal government, and the social science community to explore these and related questions. The key themes, ideas, and insights that emerged during the presentations and discussions are summarized in 'Severe Space Weather Events--Understanding Societal and Economic Impacts: A Workshop Report' (The National Academies Press, Washington, D.C., 2008), which was prepared by the Committee on the Societal and Economic Impacts of Severe Space Weather Events: A Workshop. The present document is an expanded summary of that report.

Source record↗

NASA NTRS2010

Allophane on Mars: Significance for Chemical Weathering and Soil Development

It has been suggested that allophane or related poorly crystalline aluminosilicates are present on Mars, and that they comprise the high-silica phase detected by the Thermal Emission Spectrometer (TES) in Surface Type 2 materials (Michalski et al., 2005). Using new laboratory spectra of allophanic materials, we (Rampe et al., this meeting) have detected allophane on the Martian surface via spectral modeling of TES data. We find that ST2 materials in the Northern Plains are consistent with a significant amount of high-silica allophane-like materials. In addition, we find that allophane may be present in some areas of ancient highlands (TES surface type 1), but spectra of those regions are more consistent with aluminous allophane. The presence of allophane and its chemical variability have important implications for chemical weathering and soil development on Mars. Allophane-like materials are amorphous or poorly crystalline hydrous aluminosilicates formed from chemical weathering of glasses, feldspars, and other silicates (cf. Parfitt, 2009). True allophane is a combination of SiO2, Al2O3 and H2O where Al:Si ranges from ~0.5-2. Aluminosilicate gels are amorphous and chemically similar to allophane but can have higher SiO2 contents. The presence of allophane indicates low-temperature chemical weathering and provides constraints on alteration conditions, limiting pH to circum-neutral (~4.5-8). Our model results indicate that weathering occurred in the relatively young northern plains of Mars. The high-silica allophane-like material present there implies little silica mobility through the soil column, which suggests that weathering involved small amounts of liquid water, consistent with our previous models of weathering in ice-rich soils (Kraft et al., 2007). The aluminous allophane indicated by our spectral models to be present in the highlands suggest that those regions experienced greater amounts of SiO2 leaching and weathering in those soils may have involved much larger amounts of water. The presence of allophane-like materials suggests that these weathering regimes were not influenced by the acidic weathering that appears to have affected other areas of Mars and has been proposed as a planetwide alteration process (Hurowitz and McLennan, 2007). Soil development in basaltic material (typically tephra) on Earth usually leads to formation of andosols. Although we do not suggest a one-to-one analogy between dark basaltic Martian soils and andosols, there may be important similarities, as andosols are typified by significant production of allophane as well as poorly crystalline Fe-hydroxides. The detection of allophane on Mars suggests a positive utility of an andosol model for Martian soils, particularly when coupled with the ubiquitous presence of Feoxide materials on Mars. An andosol model of soil formation is mineralogically consistent with palagonite models for the formation of Martian dust (cf. Banin et al., 1992; Morris et al., 2001), which suggests a possible genetic relationship of dust and bright soils to the broader soil layer of Mars.

Kraft, M. D.↗

NASA NTRS2010

Space Weather Models, Tools and Services at the Community Coordinated Modeling Center

The Community Coordinated Modeling center (CCMC) is a multi-agency partnership to support the research and developmental work necessary to substantially increase space weather modeling capabilities and to facilitate advanced models deployment in forecasting operations. The CCMC conducts unbiased model testing and validation and evaluates model readiness for operational environment. Space weather models and coupled model chains hosted at the CCMC range from the solar corona to the Earth's upper atmosphere. CCMC has developed a number of real-time modeling systems, as well as a large number of modeling and data products tailored to address the space weather needs of NASA's robotic missions. The presentation will demonstrate the rapid progress towards development the system allowing using products derived from space weather models in applications associated with National Space Weather needs. The adaptable Integrated Space Weather Analysis (ISWA) System developed at CCMC for NASA-relevant space weather information combines forecasts based on advanced space weather models hosted at CCMC with concurrent space environment information. The system is also enabling post-impact analysis and flexible dissemination of space weather information.

Kuznetsova, M. M.↗

NASA NTRS2003

Adaptation of Mesoscale Weather Models to Local Forecasting

Methodologies have been developed for (1) configuring mesoscale numerical weather-prediction models for execution on high-performance computer workstations to make short-range weather forecasts for the vicinity of the Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) and (2) evaluating the performances of the models as configured. These methodologies have been implemented as part of a continuing effort to improve weather forecasting in support of operations of the U.S. space program. The models, methodologies, and results of the evaluations also have potential value for commercial users who could benefit from tailoring their operations and/or marketing strategies based on accurate predictions of local weather. More specifically, the purpose of developing the methodologies for configuring the models to run on computers at KSC and CCAFS is to provide accurate forecasts of winds, temperature, and such specific thunderstorm-related phenomena as lightning and precipitation. The purpose of developing the evaluation methodologies is to maximize the utility of the models by providing users with assessments of the capabilities and limitations of the models. The models used in this effort thus far include the Mesoscale Atmospheric Simulation System (MASS), the Regional Atmospheric Modeling System (RAMS), and the National Centers for Environmental Prediction Eta Model ( Eta for short). The configuration of the MASS and RAMS is designed to run the models at very high spatial resolution and incorporate local data to resolve fine-scale weather features. Model preprocessors were modified to incorporate surface, ship, buoy, and rawinsonde data as well as data from local wind towers, wind profilers, and conventional or Doppler radars. The overall evaluation of the MASS, Eta, and RAMS was designed to assess the utility of these mesoscale models for satisfying the weather-forecasting needs of the U.S. space program. The evaluation methodology includes objective and subjective verification methodologies. Objective (e.g., statistical) verification of point forecasts is a stringent measure of model performance, but when used alone, it is not usually sufficient for quantifying the value of the overall contribution of the model to the weather-forecasting process. This is especially true for mesoscale models with enhanced spatial and temporal resolution that may be capable of predicting meteorologically consistent, though not necessarily accurate, fine-scale weather phenomena. Therefore, subjective (phenomenological) evaluation, focusing on selected case studies and specific weather features, such as sea breezes and precipitation, has been performed to help quantify the added value that cannot be inferred solely from objective evaluation.

Manobianco, John T.↗

NASA NTRS2012

Using ISCCP Weather States to Decompose Cloud Radiative Effects

The presentation will examine the shortwave (SW) and longwave (LW) cloud radiative effect CRE (aka "cloud radiative forcing") at the top-of-the-atmosphere and surface of ISCCP weather states (aka "cloud regimes") in three distinct geographical zones, one tropical and two mid-latitude. Our goal is to understand and quantify the contribution of the different cloud regimes to the planetary radiation budget. In the tropics we find that the three most convectively active states are the ones with largest SW, LW and net TOA CRE contributions to the overall daytime tropical CRE budget. They account for 59%, 71% and 55% of the total CRE, respectively. The boundary layer-dominated weather states account for only 34% of the total SW CRE and 41% of the total net CRE, so to focus only on them in cloud feedback studies may be imprudent. We also find that in both the northern and southern midlatitude zones only two weather states, the first and third most convectively active with large amounts of nimbostratus-type clouds, contribute ",40% to both the SW and net TOA CRE budgets, highlighting the fact that cloud regimes associated with frontal systems are not only important for weather (precipitation) but also for climate (radiation budget). While all cloud regimes in all geographical zones have a slightly larger SFC than TOA SW CRE, implying cooling of the surface and slight warming of the atmosphere, their LW radiative effects are more subtle: in the tropics the weather states with plentiful high clouds warm the atmosphere while those with copious amounts of low clouds cool the atmosphere. In both midlatitude zones only the weather states with peak cloud fractions at levels above 440 mbar warm the atmosphere while all the rest cool it. These results make the connection of the contrasting CRE effects to the atmospheric dynamics more explicit - "storms" tend to warm the atmosphere whereas fair weather clouds cool it, suggesting a positive feedback of clouds on weather systems. The breakdown of CRE by cloud regime are however not entirely similar between the two midlatitude zones. Despite the existence of an additional state in the nort!lern midlatitudes, only four weather states have net daytime CREs with absolute values above 100 Watts per square meter compared to six in the south. This reminds us that the environment where clouds occur also has a crucial role in determining their radiative effects. All the above make evident that reproducing grand averages of current CRE by climate models in only part of the challenge. If existing cloud regimes and shifts in their distributions and frequency of occurrence in a changed climate are not properly simulated, the radiative role of clouds will not be adequately predicted.

Oreopoulos, L.↗

NASA NTRS2013

Detecting Nanophase Weathering Products with CheMin: Reference Intensity Ratios of Allophane, Aluminosilicate Gel, and Ferrihydrite

X-ray diffraction (XRD) data collected of the Rocknest samples by the CheMin instrument on Mars Science Laboratory suggest the presence of poorly crystalline or amorphous materials [1], such as nanophase weathering products or volcanic and impact glasses. The identification of the type(s) of X-ray amorphous material at Rocknest is important because it can elucidate past aqueous weathering processes. The presence of volcanic and impact glasses would indicate that little chemical weathering has occurred because glass is highly susceptible to aqueous alteration. The presence of nanophase weathering products, such as allophane, nanophase iron-oxides, and/or palagonite, would indicate incipient chemical weathering. Furthermore, the types of weathering products present could help constrain pH conditions and identify which primary phases altered to form the weathering products. Quantitative analysis of phases from CheMin data is achieved through Reference Intensity Ratios (RIRs) and Rietveld refinement. The RIR of a mineral (or mineraloid) that relates the scattering power of that mineral (typically the most intense diffraction line) to the scattering power of a separate mineral standard such as corundum [2]. RIRs can be calculated from XRD patterns measured in the laboratory by mixing a mineral with a standard in known abundances and comparing diffraction line intensities of the mineral to the standard. X-ray amorphous phases (e.g., nanophase weathering products) have broad scattering signatures rather than sharp diffraction lines. Thus, RIRs of X-ray amorphous materials are calculated by comparing the area under one of these broad scattering signals with the area under a diffraction line in the standard. Here, we measured XRD patterns of nanophase weathering products (allophane, aluminosilicate gel, and ferrihydrite) mixed with a mineral standard (beryl) in the CheMinIV laboratory instrument and calculated their RIRs to help constrain the abundances of these phases in the Rocknest samples.

Rampe, E. B.↗

NASA NTRS2013

Severe Weather Tool using 1500 UTC Cape Canaveral Air Force Station Soundings

People and property at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) are at risk when severe weather occurs. Strong winds, hail and tornadoes can injure individuals and cause costly damage to structures if not properly protected. NASA's Launch Services Program and Ground Systems Development and Operations Program and other KSC programs use the daily and weekly severe weather forecasts issued by the 45th Weather Squadron (45 WS) to determine if they need to limit an activity such as working on gantries, or protect property such as a vehicle on a pad. The 45 WS requested the Applied Meteorology Unit (AMU) develop a warm season (May-September) severe weather tool for use in the Meteorological Interactive Data Display System (MIDDS) based on the late morning, 1500 UTC (1100 local time), CCAFS (XMR) sounding. The 45 WS frequently makes decisions to issue a severe weather watch and other severe weather warning support products to NASA and the 45th Space Wing in the late morning, after the 1500 UTC sounding. The results of this work indicate that certain stability indices based on the late morning XMR soundings can depict differences between days with reported severe weather and days with no reported severe weather. The AMU determined a frequency of reported severe weather for the stability indices and implemented an operational tool in MIDDS.

Bauman, William H., III↗

NASA NTRS2011

Flight Departure Delay and Rerouting Under Uncertainty in En Route Convective Weather

Delays caused by uncertainty in weather forecasts can be reduced by improving traffic flow management decisions. This paper presents a methodology for traffic flow management under uncertainty in convective weather forecasts. An algorithm for assigning departure delays and reroutes to aircraft is presented. Departure delay and route assignment are executed at multiple stages, during which, updated weather forecasts and flight schedules are used. At each stage, weather forecasts up to a certain look-ahead time are treated as deterministic and flight scheduling is done to mitigate the impact of weather on four-dimensional flight trajectories. Uncertainty in weather forecasts during departure scheduling results in tactical airborne holding of flights. The amount of airborne holding depends on the accuracy of forecasts as well as the look-ahead time included in the departure scheduling. The weather forecast look-ahead time is varied systematically within the experiments performed in this paper to analyze its effect on flight delays. Based on the results, longer look-ahead times cause higher departure delays and additional flying time due to reroutes. However, the amount of airborne holding necessary to prevent weather incursions reduces when the forecast look-ahead times are higher. For the chosen day of traffic and weather, setting the look-ahead time to 90 minutes yields the lowest total delay cost.

Mukherjee, Avijit↗

NASA NTRS2015

Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloud‐computing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to high‐performance computing environments, supporting multi‐node systems required for near real‐time, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an on‐demand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, on‐demand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes pre‐compiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRF‐EMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higher‐resolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Short‐term Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building activities in environmental monitoring and prediction across a growing number of regional hubs throughout the world. Capacity‐building applications that extend numerical weather prediction to developing countries are intended to provide near real‐time applications to benefit public health, safety, and economic interests, but may have a greater impact during disaster events by providing a source for local predictions of weather‐related hazards, or impacts that local weather events may have during the recovery phase.

Molthan, Andrew↗

NASA NTRSDate not supplied

Analyzing Space Weather at Mars with MAVEN

To understand the processes driving Martian atmospheric escape to space, the MAVEN mission has been monitoring solar inputs at Mars since the spacecraft went into orbit in September 2014. MAVEN’s payload provides in situ measurements of solar wind ions and electrons, solar energetic particles, extreme ultraviolet radiation, and magnetic fields. With this comprehensive suite of instruments, the MAVEN team has monitored space weather at Mars for nearly a decade, over various parts of Solar Cycles 24 and 25. MAVEN observations have determined that space weather activity can deposit enough energy into the Martian system to enhance atmospheric escape by an order of magnitude. As the mission continues, monitoring space weather at Mars has become increasingly important to understand the Sun’s influence on the Martian environment. The MAVEN team provides regular reports of space weather activity, such as the occurrence and arrival time of coronal mass ejections as well as flare magnitude and peak times, to the Mars community when predictions suggest that a space weather-impacting event may be directed towards Mars. MAVEN provides observations of solar activity on the ‘far side’ of the Sun when Earth and Mars are near solar conjunction to augment measurements of solar observatories (e.g., SDO, STEREO, GOES, PSP, Solar Orbiter), providing a more global coverage of solar activity. Additionally, MAVEN is working closely with the Community Coordinated Modeling Center (CCMC) and the Moon to Mars (M2M) Space Weather Analysis Office, both located at NASA GSFC, to form the Mars Space Weather Collaboration. This collaboration utilizes MAVEN observations of space weather activity to facilitate model and prediction validation while creating tools that are available to the science community. These activities are in support of future human and robotic exploration as we identify needs to enhance current capabilities for analyzing space weather at Mars.

Gina A DiBraccio↗

DOE OSTI2020

Relating the depth of the water table to the depth of weathering

Weathering of bedrock creates and occludes permeability, affecting subsurface water flow. Often, weathering intensifies above the water table. On the other hand, weathering can also commence below the water table. To explore relationships between weathering and the water table, a simplified weathering model for an eroding hillslope was formulated that takes into account both saturated and unsaturated subsurface water flow (but does not fully account for changes in dissolved gas chemistry). The phreatic line was calculated using solutions to mathematical treatments for both zones. In the model, the infiltration rate at the hill surface sets both the original and the eventual steady-state position of the water table with respect to the weathering reaction front. Depending upon parameters, the weathering front can locate either above or below the water table at steady state. Erosion also affects the water table position by changing porosity and permeability even when other hydrological conditions (e.g. hydraulic conductivity of parent material, infiltration rate at the surface) do not change. The total porosity in a hill (water storage capacity) was found to increase with infiltration rate (all else held constant). Furthermore, this effect was diminished by increasing the erosion rate. We also show examples of how the infiltration rate affects the position of the water table and how infiltration rate affects weathering advance.

58 GEOSCIENCES↗

DOE OSTI2021

Rock weathering controls the potential for soil carbon storage at a continental scale

Abstract As rock-derived primary minerals weather to form soil, they create reactive, poorly crystalline minerals that bind and store organic carbon. By implication, the abundance of primary minerals in soil might influence the abundance of poorly crystalline minerals, and hence soil organic carbon storage. However, the link between primary mineral weathering, poorly crystalline minerals, and soil carbon has not been fully tested, particularly at large spatial scales. To close this knowledge gap, we designed a model that links primary mineral weathering rates to the geographic distribution of poorly crystalline minerals across the USA, and then used this model to evaluate the effect of rock weathering on soil organic carbon. We found that poorly crystalline minerals are most abundant and most strongly correlated with organic carbon in geographically limited zones that sustain enhanced weathering rates, where humid climate and abundant primary minerals co-occur. This finding confirms that rock weathering alters soil mineralogy to enhance soil organic carbon storage at continental scales, but also indicates that the influence of active weathering on soil carbon storage is limited by low weathering rates across vast areas.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Ecohydrologic processes and soil thickness feedbacks control limestone-weathering rates in a karst landscape

Here, chemical weathering of bedrock plays an essential role in the formation and evolution of Earth's critical zone. Over geologic time, the negative feedback between temperature and chemical weathering rates contributes to the regulation of Earth climate. The challenge of understanding weathering rates and the resulting evolution of critical zone structures lies in complicated interactions and feedbacks among environmental variables, local ecohydrologic processes, and soil thickness, the relative importance of which remains unresolved. We investigate these interactions using a reactive-transport kinetics model, focusing on a low-relief, wetland-dominated karst landscape (Big Cypress National Preserve, South Florida, USA) as a case study. Across a broad range of environmental variables, model simulations highlight primary controls of climate and soil biological respiration, where soil thickness both supplies and limits transport of biologically derived acidity. Consequently, the weathering rate maximum occurs at intermediate soil thickness. The value of the maximum weathering rate and the precise soil thickness at which it occurs depend on several environmental variables, including precipitation regime, soil inundation, vegetation characteristics, and rate of groundwater drainage. Simulations for environmental conditions specific to Big Cypress suggest that wetland depressions in this landscape began to form around beginning of the Holocene with gradual dissolution of limestone bedrock and attendant soil development, highlighting large influence of age-varying soil thickness on weathering rates and consequent landscape development. While climatic variables are often considered most important for chemical weathering, our results indicate that soil thickness and biotic activity are equally important. Weathering rates reflect complex interactions among soil thickness, climate, and local hydrologic and biotic processes, which jointly shape the supply and delivery of chemical reactants, and the resulting trajectories of critical zone and karst landscape development.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Chemical reactions, porosity, and microfracturing in shale during weathering: The effect of erosion rate

The rate of chemical weathering has been observed to increase with the rate of physical erosion in published comparisons of many catchments, but the mechanisms that couple these processes are not well understood. We investigated this question in our research by examining the chemical weathering and porosity profiles from catchments developed on marine shale located in Pennsylvania, USA (Susquehanna Shale Hills Critical Zone Observatory, SSHCZO); California, USA (Eel River Critical Zone Observatory, ERCZO); and Taiwan (Fushan Experimental Forest). The protolith compositions, protolith porosities, and the depths of regolith at these sites are roughly similar while the catchments are characterized by large differences in erosion rate (1–3 mm yr ₋1 in Fushan &laquo 0.2–0.4 mm yr ₋1 in ERCZO &laquo 0.01–0.025 mm yr ₋1 in SSHCZO). The natural experiment did not totally isolate erosion as a variable: mean annual precipitation varied along the erosion gradient (4.2 m yr ₋1 in Fushan > 1.9 m yr ₋1 in ERCZO > 1.1 m yr ₋1 in SSHCZO), so the fastest eroding site experiences nearly twice the mean annual temperature of the other two. Even though erosion rates varied by about 100×, the depth of pyrite and carbonate depletion (defined here as regolith thickness) is roughly the same, consistent with chemical weathering of those minerals keeping up with erosion at the three sites. These minerals were always observed to be the deepest to react, and they reacted until 100% depletion. In two of three of the catchments where borehole observations were available for ridges, these minerals weathered across narrow reaction fronts. On the other hand, for the rock-forming clay mineral chlorite, the depth interval of weathering was wide and the extent of depletion observed at the land surface decreased with increasing erosion/precipitation. Thus, chemical weathering of the clay did not keep pace with erosion rate. But perhaps the biggest difference among the shales is that in the fast-eroding sites, microfractures account for 30–60% of the total porosity while in the slow-eroding shale, dissolution could be directly related to secondary porosity. We argue that the microfractures increase the influx of oxygen at depth and decrease the size of diffusion-limited internal domains of matrix, accelerating weathering of pyrite and carbonate under high erosion-rate conditions. Thus, microfracturing is a process that can couple physical erosion and chemical weathering in shales.

58 GEOSCIENCES↗

DOE OSTI2024

A Machine Learning Bias Correction on Large–Scale Environment of High–Impact Weather Systems in E3SM Atmosphere Model

Large–scale dynamical and thermodynamical processes are common environmental drivers of high–impact weather systems causing extreme weather events. However, such large–scale environmental conditions often display systematic biases in climate simulations, posing challenges to evaluating high–impact weather systems and extreme weather events. In this paper, a machine learning (ML) approach was employed to bias correct the large–scale wind, temperature, and humidity simulated by the atmospheric component of the Energy Exascale Earth System Model (E3SM) at ~1° resolution. The usefulness of the ML approach for extreme weather analysis was demonstrated with a focus on three high–impact weather systems, including tropical cyclones (TCs), extratropical cyclones (ETCs), and atmospheric rivers (ARs). We show that the ML model can effectively reduce climate bias in large–scale wind, temperature, and humidity while preserving their responses to imposed climate change perturbations. The bias correction is found to directly improve water vapor transport associated with ARs, and representations of thermodynamical flows associated with ETCs. When the bias–corrected large–scale winds are used to drive a synthetic TC track forecast model over the Atlantic basin, the resulting TC track density agrees better with that of the TC track model driven by observed winds. In addition, the ML model insignificantly interferes with the mean climate change signals of large–scale storm environments as well as the occurrence and intensity of three weather systems. This study suggests that the proposed ML approach can be used to improve the downscaling of extreme weather events by providing more realistic large–scale storm environments simulated by low–resolution climate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

diyepw: A Python package for Do-It-Yourself EnergyPlus weather file generation

diyepw allows for quick and easy generation of a set of EnergyPlus weather (EPW) files for a given location over a given historical period. The user can obtain weather files using an open-source, automated workflow by simply specifying the location of interest using the World Meteorological Organization weather station ID number, and specifying a year or set of years for which to generate EPW files. Building energy modelers can use these auto-generated weather files in building performance simulations to represent the actual observed weather conditions in the location(s) of interest, based on meteorological observations obtained from the National Oceanic and Atmospheric Administration's Integrated Surface Database. Because observed weather data are not available for every meteorological variable specified in the EPW format, diyepw starts with a widely-used set of typical meteorological year (TMY) files, using them as the template to generate new EPW files by substituting in the observed values of selected meteorological variables that are known to affect building energy performance. Its output is a weather file or group of weather files that conform to the data standards associated with the EPW format so they can be used with any building performance simulation software employing EnergyPlus as its simulation engine.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2014

Space Weathering on Icy Satellites in the Outer Solar System

Space weathering produces well-known optical effects in silicate minerals in the inner Solar System, for example, on the Moon. Space weathering from solar wind and UV (ultraviolet radiation) is expected to be significantly weaker in the outer Solar System simply because intensities are low. However, cosmic rays and micrometeoroid bombardment would be similar to first order. That, combined with the much higher volatility of icy surfaces means there is the potential for space weathering on icy outer Solar System surfaces to show optical effects. The Cassini spacecraft orbiting Saturn is providing evidence for space weathering on icy bodies. The Cassini Visible and Infrared Mapping Spectrometer (VIMS) instrument has spatially mapped satellite surfaces and the rings from 0.35-5 microns and the Ultraviolet Imaging Spectrograph (UVIS) instrument from 0.1 to 0.2 microns. These data have sampled a complex mixing space between H2O ice and non-ice components and they show some common spectral properties. Similarly, spectra of the icy Galilean satellites and satellites in the Uranian system have some commonality in spectral properties with those in the Saturn system. The UV absorber is spectrally similar on many surfaces. VIMS has identified CO2, H2 and trace organics in varying abundances on Saturn's satellites. We postulate that through the spatial relationships of some of these compounds that they are created and destroyed through space weathering effects. For example, the trapped H2 and CO2 observed by VIMS in regions with high concentrations of dark material may in part be space weathering products from the destruction of H2O and organic molecules. The dark material, particularly on Iapetus which has the highest concentration in the Saturn system, is well matched by space-weathered silicates in the .4 to 2.6 micron range, and the spectral shapes closely match those of the most mature lunar soils, another indicator of space weathered material.

Space weathering↗