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At least 1,531 records · Page 85

The Global Water Monitor: Lake, Wetland, and River Reach Monitoring for Resource Management and Hazard Observation

The Global Water Monitor is a monitoring program offering surface water-related products for lakes, reservoirs, river reaches, and wetlands, https://blueice.gsfc.nasa.gov/gwm. These products are derived from multiple satellite-based altimetry and multispectral imaging platforms. The primary measurements are water level, slope, and extent, derived from a series of NASA and other agency instruments (Sentinel-3,-6, ICESat-2, SWOT, MODIS). The system serves stakeholders, the US Department of Agriculture Foreign Agricultural Service and the US Geological Survey, as well as various international, national, state, and intelligence agencies, engineers, ecologists, and hydrological researchers. Considering the sensitivity of ground-based data and the remote accessibility of many basins, the satellites offer global coverage, accuracy, and continuity of measurements. Observation of storage fluctuations in lakes and reservoirs provides users with knowledge of short and long-term drought conditions that can affect both water and energy resources. Emphasis is on changing climatic conditions, water sharing between nations, and regional stability. Measurements across a wetland complex can assist with efforts to assess hydrological dynamics with a focus on conservation efforts that aid both natural ecology and the sharing of precious water resources – the latter potentially being required in a basin across the municipal, crop irrigation, aquaculture, livestock, and power station spectrum. Observations of river reaches assists in the collection of basic hydraulic information, particularly in gauge-poor regions, for modelling efforts and the estimation of discharge, and at high-latitudes satellite-based river observations serve projects that warn of spring melts and flood hazards. We look at how recent improvements in instrument technology and mission operations are assisting with acquiring true global coverage and cross-validation efforts, and how stakeholders interact with the project in terms of setting requirements, product format, and accessibility methods. Examples show the application of the products across a range of programs, and in addition to meeting operational requirements, how the multi-decadal surface water levels are creating a high-quality timeline of Earth Data Records.

Lakes↗

Choosing the Best Carbon Factor for the Job: Exploring Available Carbon Emissions Factors and the Impact of Factor Selection

Over 600 local governments in the United States, including nearly half of the largest 100 cities, have enacted climate action plans that include carbon reduction goals and greenhouse gas inventories (Markolf et al. 2020). The magnitude of these goals ranges from modest reduction targets to carbon neutrality. None will be met without significant contributions from the buildings sector. Understanding how energy efficiency and building electrification impact greenhouse gas emissions requires local, time-sensitive, and forward-looking carbon emissions factors for electricity use in buildings. There are a variety of emissions factors currently available from various sources, including average emissions factors and historical short-run marginal emissions factors. Long-run marginal emissions factors and future-year short-run marginal emissions factors are also now available from the National Renewable Energy Laboratory's (NREL's) Cambium data sets. In this paper, we describe the different carbon emissions factors available, including both conventional sources and newly available options. We discuss the types of analyses each emissions factor is best suited to support. Then, using residential energy efficiency and electrification load profiles, we demonstrate how different conclusions result from different choices of carbon emissions factors. For two grid regions, we explore takeaways of using current versus future-year emissions, short-run versus long-run, and levelized versus single-year values. We include a framework for selecting the best carbon emissions factor for the job.

carbon emissions factors↗

Choosing the Best Carbon Factor for the Job: Exploring Available Carbon Emissions Factors and the Impact of Factor Selection: Preprint

Over 600 local governments in the United States, including nearly half of the largest 100 cities, have enacted climate action plans that include carbon reduction goals and greenhouse gas inventories (Markolf et al. 2020). The magnitude of these goals ranges from modest reduction targets to carbon neutrality. None will be met without significant contributions from the buildings sector. Understanding how energy efficiency and building electrification impact greenhouse gas emissions requires local, time-sensitive, and forward-looking carbon emissions factors for electricity use in buildings. There are a variety of emissions factors currently available from various sources, including average emissions factors and historical short-run marginal emissions factors. Long-run marginal emissions factors and future-year short-run marginal emissions factors are also now available from the National Renewable Energy Laboratory's (NREL's) Cambium data sets. In this paper, we describe the different carbon emissions factors available, including both conventional sources and newly available options. We discuss the types of analyses each emissions factor is best suited to support. Then, using residential energy efficiency and electrification load profiles, we demonstrate how different conclusions result from different choices of carbon emissions factors. For two grid regions, we explore takeaways of using current versus future-year emissions, short-run versus long-run, and levelized versus single-year values. We include a framework for selecting the best carbon emissions factor for the job.

carbon emissions factors↗

An Open-Source Decarbonization Analytics Framework: Designing for Low-Carbon Emission Districts and Communities: Preprint

This paper introduces an open-source analytics framework designed to assist in creating low or net-zero carbon buildings and urban districts. Integrated within URBANopt, an open-source platform for energy analysis in districts and communities, this framework equips researchers, architects, engineers, and other stakeholders with tools to evaluate the carbon footprint implications of their design choices. The framework enables the analysis of various scenarios, incorporating both historical and future emission factors, and can span across different climate zones, each with distinct grid and emissions characteristics. The results showcase the framework's capability to evaluate the impact of design upgrades and control strategies on carbon emissions in districts and communities. An illustrative analysis using a hypothetical district in Denver, Colorado, shows reduced emissions from energy efficiency upgrades and control strategies, highlighting the sensitivity in their effects on emissions and energy use.

buildings energy efficiency↗

Nonlinear Climate Responses to Increasing CO2 and Anthropogenic Aerosols Simulated by CESM1

Abstract Atmospheric CO2 and anthropogenic aerosols (AA) have increased simultaneously. Because of their opposite radiative effects, these increases may offset each other, which may lead to some nonlinear effects. Here the seasonal and regional characteristics of this nonlinear effect from the CO2 and AA forcings are investigated using the fully coupled Community Earth System Model. Results show that nonlinear effects are small in the global mean of the top-of-the-atmosphere radiative fluxes, surface air temperature, and precipitation. However, significant nonlinear effects exist over the Arctic and other extratropical regions during certain seasons. When both forcings are included, Arctic sea ice in September–November decreases less than the linear combination of the responses to the individual forcings due to a higher sea ice sensitivity to the CO2-induced warming than the sensitivity to the AA-induced cooling. This leads to less Arctic warming in the combined-forcing experiment due to reduced energy release from the Arctic Ocean to the atmosphere. Some nonlinear effects on precipitation in June–August are found over East Asia, with the northward-shifted East Asian summer rain belt to oppose the CO2 effect. In December–February, the aerosol loading over Europe in the combined-forcing experiment is higher than that due to the AA forcing, resulting from CO2-induced circulation changes. The changed aerosol loading results in regional thermal responses due to aerosol direct and indirect effects, weakening the combined changes of temperature and circulation. This study highlights the need to consider nonlinear effects from historical CO2 and AA forcings in seasonal and regional climate attribution analyses.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity and vulnerability to summer heat extremes in major cities of the United States

Many cities are experiencing increases in extreme heat because of global temperature rise combined with the urban heat island effect. The heterogeneity of urban morphology also leads to fine-scale variability in potential for heat exposure. Yet, how this rise in temperature and local variability together impacts urban residents differently at exposure-relevant scales is still not clear. Here we map the Universal Thermal Climate Index, a more complete indicator of human heat stress at an unprecedentedly fine spatial resolution (1 m), for 14 major cities in the United States using urban microclimate modeling. We examined the different heat exposure levels across different socioeconomic and racial/ethnic groups in these cities, finding that income level is most consistently associated with heat stress. We further conducted scenario simulations for a hypothetical 1 °C increase of air temperature in all cities. Results show that a 1 °C increase would have a substantial impact on human heat stress, with impacts that differ across cities. The results of this study can help us better evaluate the impact of extreme heat on urban residents at decision-relevant scales.

54 ENVIRONMENTAL SCIENCES↗

Orphaned oil and gas well methane emission rates quantified using Gaussian plume inversions of ambient observations

Abstract. Annually, ∼ 3.6 million abandoned oil and gas wells in the US emit a combined ∼ 2.6 Tg methane (CH4), adversely affecting climate and regional air quality. However, these estimates depend on emission factors derived from measuring subpopulations of wells that vary by orders of magnitude due to very limited field sampling and poorly characterized distributions. Currently, US protocols to remediate orphaned wells lacks standardized quantification methods needed to both prioritize plugging and account for emission reductions. Therefore, sensitive, reliable, affordable, and scalable CH4 flux quantification methods are needed. We report the use of a simple Gaussian plume method where the dispersion parameters are constrained by in situ ground measurements of CH4 concentration at four locations 7.5–49 m downwind of the orphan well as well as local winds to estimate the leak rate from an orphan well. We derive a flux of 10.53 ± 1.16 kg CH4 h−1 during a venting procedure in April 2023 that agrees with the directly measured volumetric flow rate of 9.00 ± 0.25 kg CH4 h−1. This is 71 % greater than the 5.3 kg CH4 h−1 flux measured 7 months prior. Additionally, we discovered a secondary leak through the surface casing inferred as 0.43–0.67 kg CH4 h−1 both by our ground Gaussian analysis and by transecting the plume with an uncrewed aerial system (UAS). We show that in situ determination of the dispersion parameters used in our Gaussian inversions allows us to measure methane emissions to 15 % accuracy, significantly reducing errors when compared to the standard practice of assuming stability class. Our results help develop simpler methods and protocols for robust orphan well emission quantification that can be used for reporting.

Follansbee, Emily↗

Nimbus 7 earth radiation budget wide field of view climate data set improvement. I - The earth albedo from deconvolution of shortwave measurements

A deconvolution method for extracting the top of the atmosphere (TOA) mean, daily albedo field from a set of wide-FOV (WFOV) shortwave radiometer measurements is proposed. The method is based on constructing a synthetic measurement for each satellite observation. The albedo field is represented as a truncated series of spherical harmonic functions, and these linear equations are presented. Simulation studies were conducted to determine the sensitivity of the method. It is observed that a maximum of about 289 pieces of data can be extracted from a set of Nimbus 7 WFOV satellite measurements. The albedos derived using the deconvolution method are compared with albedos derived using the WFOV archival method; the developed albedo field achieved a 20 percent reduction in the global rms regional reflected flux density errors. The deconvolution method is applied to estimate the mean, daily average TOA albedo field for January 1983. A strong and extensive albedo maximum (0.42), which corresponds to the El Nino/Southern Oscillation event of 1982-1983, is detected over the south central Pacific Ocean.

Hucek, Richard R.↗

Single-column Model Intercomparison for a Stably Stratified Atmospheric Boundary Layer

The parameterization of the stably stratified atmospheric boundary layer is a difficult issue, which has a large impact on the medium-range weather forecasts and on climate integrations. A non-strongly stratified arctic case is simulated by nineteen single-column turbulence schemes. The statistics from the Large-eddy simulation (LES) intercomparison made for the same case by eight different models are used as a guiding reference. The single-column parameterizations include research schemes and operational schemes from major forecast and climate research centres. First order schemes, a large number of turbulence kinetic energy closures, and other proposals have submitted results. There is a large spread in the results; in general, the operational schemes mix more efficiently than the research ones, and the TKE and other higher order closures give results closer to the LES statistics. The sensitivities of the schemes to the parameters of their turbulence closures are partially explored.

Cuxart, J.↗

The Use of Meteorlogical Data to Improve Contrail Detection in Thermal Imagery over Ireland.

Aircraft induced contrails have been found to have a net warming influence on the climate system, with strong regional dependence. Persistent linear contrails are detectable in 1 Km thermal imagery and, using an automated Contrail Detection Algorithm (CDA), can be identified on the basis of their different properties at the 11 and 12 m w av.el enTgthshe algorithm s ability to distinguish contrails from other linear features depends on the sensitivity of its tuning parameters. In order to keep the number of false identifications low, the algorithm imposes strict limits on contrail size, linearity and intensity. This paper investigates whether including additional information (i.e. meteorological data) within the CDA may allow for these criteria to be less rigorous, thus increasing the contrail-detection rate, without increasing the false alarm rate.

Whelan, Gillian M.↗

How Will Sea Ice Loss Affect the Greenland Ice Sheet? On the Puzzling Features of Greenland Ice-Core Isotopic Composition

The modern cryosphere, Earth's frozen water regime, is in fast transition. Greenland ice cores show how fast theses changes can be, presenting evidence of up to 15 C warming events over timescales of less than a decade. These events, called Dansgaard/Oeschger (D/O) events, are believed to be associated with rapid changes in Arctic sea ice, although the underlying mechanisms are still unclear. The modern demise of Arctic sea ice may, in turn, instigate abrupt changes on the Greenland Ice Sheet. The Arctic Sea Ice and Greenland Ice Sheet Sensitivity (Ice2Ice Chttps://ice2ice.b.uib.noD) initiative, sponsored by the European Research Council, seeks to quantify these past rapid changes to improve our understanding of what the future may hold for the Arctic. Twenty scientists gathered in Copenhagen as part of this initiative to discuss the most recent observational, technological, and model developments toward quantifying the mechanisms behind past climate changes in Greenland. Much of the discussion focused on the causes behind the changes in stable water isotopes recorded in ice cores. The participants discussed sources of variability for stable water isotopes and framed ways that new studies could improve understanding of modern climate. The participants also discussed how climate models could provide insights into the relative roles of local and nonlocal processes in affecting stable water isotopes within the Greenland Ice Sheet. Presentations of modeling results showed how a change in the source or seasonality of precipitation could occur not only between glacial and modern climates but also between abrupt events. Recent fieldwork campaigns illustrate an important role of stable isotopes in atmospheric vapor and diffusion in the final stable isotope signal in ice. Further, indications from recent fieldwork campaigns illustrate an important role of stable isotopes in atmospheric vapor and diffusion in the final stable isotope signal in ice. This feature complicates the quantitative interpretation of ice core signals but also makes the stable ice isotope signal a more robust regional indicator of climate, speakers noted. Meeting participants agreed that to further our understanding of these relationships, we need more process-focused field and laboratory campaigns.

Greenland↗

Measurement of SST and SSS Using Frequencies in the Range 0.3 – 2.0 GHz

Wide bandwidth radiometer systems that make measurements at multiple frequencies in the range 300 MHz to 2 GHz have been proposed to address parameters important for understanding issues in the cryosphere associated with climate change such as ice sheet thickness and temperature. It is also possible with such a system to retrieve sea surface salinity (SSS) which is important for understanding the impact of climate change on ocean circulation at high latitude. In contemporary sensors for retrieving SSS, such as SMOS and SMAP, sea surface temperature (SST), another parameter important for understanding ocean circulation and necessary in the retrieval of salinity, is treated as an ancillary parameter obtained from an independent source. However, both SSS and SST have peaks in sensitivity below 1 GHz; and it has been shown that measurements at multiple frequencies in this portion of the spectrum can take advantage of this peak in sensitivity to improve the accuracy of the retrieval of SSS. In this manuscript it will be shown that there is also the potential to retrieve SST and, in cold water, the possibility for improved accuracy over existing retrievals.

SST↗

Cosmogenic 10Be constraints on deglacial snowline rise in the Southern Alps, New Zealand

We report geochronological dating of glacial landforms, such as terminal and lateral moraines, is useful for determining the extent and timing of past glaciation and for reconstructing the magnitude and rate of past climate changes. In the Southern Alps of New Zealand, well-dated glacial geomorphological records constrain the last glacial cycle across much of the Waitaki River basin (e.g. Ōhau, Pukaki, Tekapo) but its southern sector such as the Ahuriri River valley remains comparatively unconstrained. Recently, there has been debate on the scale and rapidity of mountain glacier retreat during the last glacial termination, particularly the 20–17 ka period in New Zealand. Missing from this debate is well-constrained equilibrium-line altitude (ELA) and associated temperature reconstructions, particularly over the period around 17 ka, which can help us to develop a more complete picture of how past temperature changes drove glacier retreat. Here we report the first glacial chronology dataset from the Last Glacial Maximum (LGM) and subsequent deglaciation from the Ahuriri River valley, Southern Alps, New Zealand (44°23'54"S, 169°39'48"E) based on 38 beryllium-10 ( 10 Be) surface-exposure ages from terminal moraine systems and glaciated bedrock situated at the lower and middle sections of the valley. Our results show that the former Ahuriri Glacier reached its maximum extent at 19.8 ± 0.3 ka, which coincides with the global Last Glacial Maximum. By 16.7 ± 0.3 ka, the glacier had retreat ~18 km up-valley suggesting at least ~43% glacier-length loss relative to its full LGM extent. This deglaciation was accompanied by the formation of a shallow proglacial lake. Using the accumulation area ratio (AAR) method, we estimate that the ELA was lower than present by ~880 m (~1120 m a.s.l.) at 19.8 ± 0.3 ka, and ~770 m lower (~1230 m a.s.l.) at 16.7 ± 0.3 ka. Applying an estimate for temperature lapse rate, this ELA anomaly implies that local air temperature was 5 ± 1 °C colder than present (1981–2010) at 19.8 ± 0.3 ka, while it was 4.4 ± 0.9 °C colder at 16.7 ± 0.3 ka, assuming no change in precipitation. The substantial glacier retreat in response to a relatively small accompanying increases in ELA (110 m) and temperature (0.6 °C) may have been a result of the high glacier-length sensitivity of this glacier system due to its low gradient of former ice surface. Our low warming estimate differs markedly from other deglaciation studies, specifically from Rakaia River valley, which reports a much larger temperature increase at the onset of the last deglaciation. This precisely-dated moraine record along with reconstructed ELA as proxies for atmospheric conditions, provides new insight into post LGM glacier behaviour and climate conditions in New Zealand.

58 GEOSCIENCES↗

Implications of CO Bias for Ozone and Methane Lifetime in a CCM

A low bias in carbon monoxide compared to observations at high latitudes is a common feature of chemistry climate models. CO bias can both indicate and contribute to a bias in modeled OH and methane lifetime. This study examines possible causes of CO bias in the ACCMIP simulation of the GEOSCCM, and considers how attributing the CO bias to uncertainty in CO emissions versus biases in other constituents impacts the relationship between CO bias and methane lifetime. We use a simplified model of CO tagged by source with specified OH to quantify the sensitivity of the CO bias to changes in CO emissions or OH concentration, comparing the modeled CO to surface and MOPITT observations. The simplified model shows that decreasing OH in the northern hemisphere removes most of the global mean and inter-hemispheric bias in surface CO. We then use results from this analysis to explore how adjusting CO sources in the CCM impacts the concentrations of ozone, OH and methane. The CCM simulation also exhibits biases in ozone and water vapor compared to observations. We use a parameterized CO-OH-CH4 model that takes ozone and water vapor as inputs to the parameterization to examine whether correcting water and ozone biases can alter OH enough to remove the CO bias. Through this analysis, we aim to better quantify the relationship between CO bias and model biases in ozone concentrations and methane lifetime.

carbon monoxide↗

Influence of Heat Flow from the Planetary Interior on Surface Habitability

an primordial and/or radiogenic heat flow from a rocky planet’s interior help maintain a surface environment amenable to life?On rocky Earth-like planets with shallow oceans (≤5 km depth) that are on the outer edge of the habitable zone, the additional energy provided might make the difference between a world supporting regional habitat space and a world uninhabitable by any known life-form. To test this hypothesis, we introduce heat flux from the planetary interior as a forcing to the NASA/GISSROCKE-3D exoplanet GCM, and explore whether it can enhance the habitability of marginal terrestrial rocky planets (e.g.,paleo Earth in a “snowball” climate state).GCM simulations of modern Earth have not included geothermal heat flux as a climate forcing, as it is more than an order of magnitude less than the 2.9 W/m heating caused by anthropogenic greenhouse gases [Flanner, GRL 2009]. Modern Earth measurements in the oceans [Downes et al., GRL 2019] and results from ocean GCMs [Barnes et al., Ocean Model. 2017]suggest that localized higher heat flux can have measurable thermodynamic and dynamic impacts, such as weakening deep ocean stratification and increased poleward ocean heat transports. A similar result with ROCKE-3D would be important, since our snowball Earth simulations without heat flux produce features like ocean stratification that should have hampered the survival of life. We have created a set of spatially variable geothermal heat fluxes at varying horizontal resolutions based on modern Earth heat flow patterns [Davies, Geochem. Geophys. Geosys. 2013] to test the sensitivity of the ROCKE-3D GCM initially in a modern Earth context. Preliminary results show that even modest heat fluxes have a measurable impact on deep ocean temperatures (upto +0.9°C locally) and that this heat can be transported at depth along ocean circulation paths. Estimates of heat flux impacts on vertical ocean mixing and surface ocean conditions require long simulations at the higher spatial resolutions needed to express heat flow at the scale of most ocean ridges. Ongoing simulations are focused on testing the impacts of horizontal resolution and flux scaling on surface environments, especially for “snowball” climate scenarios.

Heat flow↗

The Ocean Colour Climate Change Initiative: I. A Methodology for Assessing Atmospheric Correction Processors Based on In-Situ Measurements

The Ocean Colour Climate Change Initiative intends to provide a long-term time series of ocean colour data and investigate the detectable climate impact. A reliable and stable atmospheric correction procedure is the basis for ocean colour products of the necessary high quality. In order to guarantee an objective selection from a set of four atmospheric correction processors, the common validation strategy of comparisons between in-situ and satellite derived water leaving reflectance spectra, is extended by a ranking system. In principle, the statistical parameters such as root mean square error, bias, etc. and measures of goodness of fit, are transformed into relative scores, which evaluate the relationship of quality dependent on the algorithms under study. The sensitivity of these scores to the selected database has been assessed by a bootstrapping exercise, which allows identification of the uncertainty in the scoring results. Although the presented methodology is intended to be used in an algorithm selection process, this paper focusses on the scope of the methodology rather than the properties of the individual processors.

Climate Change↗

AWARE: The Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) performed comprehensive meteorological and aerosol measurements and ground-based atmospheric remote sensing at two Antarctic stations using the most advanced instrumentation available. A suite of cloud research radars, lidars, spectral and broadband radiometers, aerosol chemical and microphysical sampling equipment, and meteorological instrumentation was deployed at McMurdo Station on Ross Island from December 2015 through December 2016. A smaller suite of radiometers and meteorological equipment, including radiosondes optimized for surface energy budget measurement, was deployed on the West Antarctic Ice Sheet between 4 December 2015 and 17 January 2016. AWARE provided Antarctic atmospheric data comparable to several well-instrumented high Arctic sites that have operated for many years and that reveal numerous contrasts with the Arctic in aerosol and cloud microphysical properties. These include persistent differences in liquid cloud occurrence, cloud height, and cloud thickness. Antarctic aerosol properties are also quite different from the Arctic in both seasonal cycle and composition, due to the continent’s isolation from lower latitudes by Southern Ocean storm tracks. Antarctic aerosol number and mass concentrations are not only non-negligible but perhaps play a more important role than previously recognized because of the higher sensitivities of clouds at the very low concentrations caused by the large-scale dynamical isolation. Antarctic aerosol chemical composition, particularly organic components, has implications for local cloud microphysics. The AWARE dataset, fully available online in the ARM Program data archive, offers numerous case studies for unique and rigorous evaluation of mixed-phase cloud parameterization in climate models.

54 ENVIRONMENTAL SCIENCES↗

New insights into the drainage of inundated ice-wedge polygons using fundamental hydrologic principles

Abstract. The pathways and timing of drainage from the inundated centers of ice-wedge polygons in a warming climate have important implications for carbon flushing, advective heat transport, and transitions from methane to carbon dioxide dominated emissions. Here, we expand on previous research using a recently developed analytical model of drainage from a low-centered polygon. Specifically, we perform (1) a calibration to field data identifying necessary model refinements and (2) a rigorous model sensitivity analysis that expands on previously published indications of polygon drainage characteristics. This research provides intuition on inundated polygon drainage by presenting the first in-depth analysis of drainage within a polygon based on hydrogeological first principles. We verify a recently developed analytical solution of polygon drainage through a calibration to a season of field measurements. Due to the parsimony of the model, providing the potential that it could fail, we identify the minimum necessary refinements that allow the model to match water levels measured in a low-centered polygon. We find that (1) the measured precipitation must be increased by a factor of around 2.2, and (2) the vertical soil hydraulic conductivity must decrease with increasing thaw depth. Model refinement (1) accounts for runoff from rims into the ice-wedge polygon pond during precipitation events and possible rain gauge undercatch, while refinement (2) accounts for the decreasing permeability of deeper soil layers. The calibration to field measurements supports the validity of the model, indicating that it is able to represent ice-wedge polygon drainage dynamics. We then use the analytical solution in non-dimensional form to provide a baseline for the effects of polygon aspect ratios (radius to thaw depth) and coefficient of hydraulic conductivity anisotropy (horizontal to vertical hydraulic conductivity) on drainage pathways and temporal depletion of ponded water from inundated ice-wedge polygon centers. By varying the polygon aspect ratio, we evaluate the relative effect of polygon size (width), inter-annual increases in active-layer thickness, and seasonal increases in thaw depth on drainage. The results of our sensitivity analysis rigorously confirm a previous analysis indicating that most drainage through the active layer occurs along an annular region of the polygon center near the rims. This has important implications for transport of nutrients (such as dissolved organic carbon) and advection of heat towards ice-wedge tops. We also provide a comprehensive investigation of the effect of polygon aspect ratio and anisotropy on drainage timing and patterns, expanding on previously published research. Our results indicate that polygons with large aspect ratios and high anisotropy will have the most distributed drainage, while polygons with large aspect ratios and low anisotropy will have their drainage most focused near their periphery and will drain most slowly. Polygons with small aspect ratios and high anisotropy will drain most quickly. These results, based on parametric investigation of idealized scenarios, provide a baseline for further research considering the geometric and hydraulic complexities of ice-wedge polygons.

Harp, Dylan R. (ORCID:0000000197778000)↗