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At least 1,153 records · Page 64

Widespread Wildfires Over the Western United States in 2020 Linked to Emissions Reductions During COVID-19

Widespread wildfires struck western United States in 2020, directly damaging properties and threatening human lives. Meanwhile, the COVID-19 pandemic rapidly spread across the globe in 2020, which disrupted human activities and resulted in substantial reductions in anthropogenic emissions. Here, we investigate the effects of the emissions reductions of aerosols, precursors, and greenhouse gases during the pandemic on wildfire weather conditions in 2020 over western United States by using an earth system model together with observational data. We show that the COVID-19 emissions reductions in model experiments increased surface air temperature and decreased precipitation and relative humidity due to a weakened moisture transport, which explains 10-40% of the observed increase in the risk of wildfires over western United States in 2020. In conclusion, this study suggests that COVID-19-related abrupt emissions reductions have an unexpected influence on wildfires, highlighting a different but important role of human activities in affecting wildfire risks.

54 ENVIRONMENTAL SCIENCES↗

Annual Mean Arctic Amplification 1970–2020: Observed and Simulated by CMIP6 Climate Models

While the annual mean Arctic Amplification (AA) index varied between two and three during the 1970–2000 period, it reached values exceeding four during the first two decades of the 21st century. The AA did not change in a continuous fashion but rather in two sharp increases around 1986 and 1999. During those steps the mean global surface air temperature trend remained almost constant, while the Arctic trend increased. Although the “best” CMIP6 models reproduce the increasing trend of the AA in 1980s they do not capture the sharply increasing trend of the AA after 1999 including its rapid step-like increase. We propose that the first sharp AA increase around 1986 is due to external forcing, while the second step close to 1999 is due to internal climate variability, which models cannot reproduce in the observed time.

54 ENVIRONMENTAL SCIENCES↗

Energy Surplus and an Atmosphere‐Land‐Surface “Tug of War” Control Future Evapotranspiration

Abstract The 21st century evapotranspiration (ET) trends over the continental U.S. are assessed using innovative, energy‐based principles. Annual ET is projected to increase with high confidence at the rate of 20 mm for every 1℃ of rise in near‐surface air temperature, or 0.45 or 0.98 mm/year/year, depending on the emission scenario. The ET trajectory is dominated (58%) by the increase of land‐surface net radiative energy. An enhancement of the fraction of energy taken up by ET becomes a more important controller (53%) in late 21st century, under the high emission scenario. This increase is explained by the “tug of war” between atmospheric vapor demand and land‐surface ability to supply water. An assessment of future water availability (precipitation minus ET) shows no significant changes at the continental scale. This outcome nevertheless hides strong spatial variability, emphasizing the role of ET in shaping the distribution of water availability among human populations.

Xu, Donghui↗

Response of Extreme Rainfall to Atmospheric Warming and Wetting: Implications for Hydrologic Designs Under a Changing Climate

Understanding the processes of rainfall extremes and their response to anthropogenic climate change is pivotal for improved adaptation of unprecedented flood hazards around the world. Here we take the record-breaking 20 July 2021 storm over central China as an example. We investigate the response of this particular storm to atmospheric warming (i.e., increase in air temperature) and wetting (i.e., increase in atmospheric moisture content) based on a series of convection-permitting model simulations. Our results show non-monotonic changes of the space-time rainfall variability to either increased temperature or atmospheric moisture content. The most extreme rain rate is produced when relative humidity is increased by 20~40 % or temperature is increased by less than 2°C. The non-monotonic rainfall response is more clearly revealed at fine spatial (100-1000 km 2 ) and temporal scales (less than 6 hours) rather than over the entire domain (~10 4 km 2 ) and aggregated over the storm duration (around two days). This is mainly attributable to the distinct feedbacks from atmospheric dynamics (i.e., moisture convergence and interaction with regional topography) rather than regulated by thermodynamic changes alone. Furthermore, atmospheric warming poses notable changes in the vertical structure of storm cells, contributing to reduced areal reduction factors at small spatial scales and short durations, while atmospheric wetting additionally modifies storm evolution properties. Our modeling analyses challenge the existing practices for hydrologic designs under a changing climate, highlighting particular vulnerability for cities or small basins to short-duration rainfall extremes and the resultant flash flood hazards.

54 ENVIRONMENTAL SCIENCES↗

Convective Vortices and Dust Devils Detected and Characterized by Mars 2020

Abstract We characterize vortex and dust devils (DDs) at Jezero from pressure and winds obtained with the Mars Environmental Dynamics Analyzer (MEDA) instrument on Mars 2020 over 415 Martian days (sols) ( Ls = 6°–213°). Vortices are abundant (4.9 per sol with pressure drops >0.5 Pa correcting from gaps in coverage) and they peak at noon. At least one in every five vortices carries dust, and 75% of all vortices with Δ p > 2.0 Pa are dusty. Seasonal variability was small but DDs were abundant during a dust storm ( Ls = 152°–156°). Vortices are more frequent and intense over terrains with lower thermal inertia favoring high daytime surface‐to‐air temperature gradients. We fit measurements of winds and pressure during DD encounters to models of vortices. We obtain vortex diameters that range from 5 to 135 m with a mean of 20 m, and from the frequency of close encounters we estimate a DD activity of 2.0–3.0 DDs km −2 sol −1 . A comparison of MEDA observations with a Large Eddy Simulation of Jezero at Ls = 45° produces a similar result. Three 100‐m size DDs passed within 30 m of the rover from what we estimate that the activity of DDs with diameters >100 m is 0.1 DDs km −2 sol −1 , implying that dust lifting is dominated by the largest vortices in Jezero. At least one vortex had a central pressure drop of 9.0 Pa and internal winds of 25 ms −1 . The MEDA wind sensors were partially damaged during two DD encounters whose characteristics we elaborate in detail.

Hueso, R.↗

Physical Controls on the Hydrology of Perennially Ice-Covered Lakes, Taylor Valley, Antarctica (1996–2013)

The McMurdo Dry Valleys, Antarctica, are a polar desert populated with numerous closed-watershed, perennially ice-covered lakes primarily fed by glacial melt. Lake levels have varied by as much as 8 m since 1972 and are currently rising after a decade of decreasing. Precipitation falls as snow, so lake hydrology is dominated by energy available to melt glacier ice and to sublimate lake ice. To understand the energy and hydrologic controls on lake level changes and to explain the variability between neighboring lakes, only a few kilometers apart, we model the hydrology for the three largest lakes in Taylor Valley. Here, we apply a physically based hydrological model that includes a surface energy balance model to estimate glacial melt and lake sublimation to constrain mass fluxes to and from the lakes. Results show that lake levels are very sensitive to small changes in glacier albedo, air temperature, and wind speed. We were able to balance the hydrologic budget in two watersheds using meltwater inflow and sublimation loss from the ice-covered lake alone. A third watershed, closest to the coast, required additional inflow beyond model uncertainties. We hypothesize a shallow groundwater system within the active layer, fed by dispersed snow patches, contributes 23% of the inflow to this watershed. The lakes are out of equilibrium with the current climate. If the climate of our study period (1996–2013) persists into the future, the lakes will reach equilibrium starting in 2300, with levels 2–17 m higher, depending on the lake, relative to the 2020 level.

58 GEOSCIENCES↗

Integration of a Frost Mortality Scheme Into the Demographic Vegetation Model FATES

Frost is damaging to plants when air temperature drops below their tolerance threshold. The set of mechanisms used by cold-tolerant plants to withstand freezing is called “hardening” and typically take place in autumn to protect against winter damage. The recent incorporation of a hardening scheme in the demographic vegetation model FATES opens up the possibility to investigate frost mortality to vegetation. Previously, the hardening scheme was used to improve hydraulic processes in cold-tolerant plants. In this study, we expand upon the existing hardening scheme by implementing hardiness-dependent frost mortality into CLM5.0-FATES to study the impacts of frost on vegetation in temperate and boreal sites from 1950 to 2015. Our results show that the original freezing mortality approach of FATES, where each plant type had a fixed freezing tolerance threshold—an approach common to many other dynamic vegetation models, was restricted to predicting plant type distribution. The main results emerging from the new scheme are a high autumn and spring frost mortality, especially at colder sites, and increasing mid-winter frost mortality due to global warming, especially at warmer sites. We demonstrate that the new frost scheme is a major step forward in dynamically representing vegetation in ESMs by for the first time including a level of frost tolerance that is responding to the environment and includes some level of cost (implicitly) and benefit. By linking hardening and frost mortality in a land surface model, we open new ways to explore the impact of frost events in the context of global warming.

54 ENVIRONMENTAL SCIENCES↗

Emergent Trends Complicate the Interpretation of the United States Drought Monitor (USDM)

Abstract Effective drought management must be informed by an understanding of whether and how current drought monitoring and assessment practices represent underlying nonstationary climate conditions, either naturally occurring or forced by climate change. Here we investigate the emerging climatology and associated trends in drought classes defined by the United States Drought Monitor (USDM), a weekly product that, since 2000, has been used to inform drought management in the United States. The USDM classifies drought intensity based in part on threshold percentiles in key hydroclimate quantities. Here we assess how those USDM‐defined drought threshold percentiles have changed over the last 23 years, examining precipitation, runoff, soil moisture (SM), terrestrial water storage (TWS), vapor pressure deficit (VPD), and near‐surface air temperature. We also assess underlying trends in the frequency of drought classifications across the U.S. Our analysis suggests that the frequency of drought class occurrence is exceeding the threshold percentiles defined by the USDM in a number of regions in the United States, particularly in the American West, where the last 23 years have emerged as a prolonged dry period. These trends are also reflected in percentile‐based thresholds in precipitation, runoff, SM, TWS, VPD, and temperature. Our results emphasize that while the USDM appears to be accurately reflecting observed nonstationarity in the physical climate, such trends raise critical questions about whether and how drought diagnosis, classification, and monitoring should address long‐term intervals of wet and dry periods or trends.

Geology↗

Internal Variability Increased Arctic Amplification During 1980–2022

Abstract Since 1980, the Arctic surface has warmed four times faster than the global mean. Enhanced Arctic warming relative to the global average warming is referred to as Arctic Amplification (AA). While AA is a robust feature in climate change simulations, models rarely reproduce the observed magnitude of AA, leading to concerns that models may not accurately capture the response of the Arctic to greenhouse gas emissions. Here, we use CMIP6 data to train a machine learning algorithm to quantify the influence of internal variability in surface air temperature trends over both the Arctic and global domains. Application of this machine learning algorithm to observations reveals that internal variability increases the Arctic warming but slows global warming in recent decades, inflating AA since 1980 by 38% relative to the externally forced AA. Accounting for the role of internal variability reconciles the discrepancy between simulated and observed AA.

58 GEOSCIENCES↗

Regional and Teleconnected Impacts of Solar Radiation‐Topography Interaction Over the Tibetan Plateau

Abstract Solar radiation‐topography interaction plays an important role in surface energy balance over the Tibetan Plateau (TP). However, the impacts of such interaction over the TP on climate locally and in the Asian regions remain unclear. This study uses the Energy Exascale Earth System Model (E3SM) to evaluate the regional and teleconnected impacts of solar radiation‐topography interaction over the TP. Land‐atmosphere coupled experiments show that topography regulates the surface energy balance, snow processes, and surface climate over the TP across seasons. Accounting for solar radiation‐topography interaction improves E3SM simulation of surface climate. The winter cold bias in air temperature decreases from −4.57 to −3.79 K, and the wet bias in summer precipitation is mitigated in southern TP. The TP's solar radiation‐topography interaction further reduces the South and East Asian summer precipitation biases. Our results demonstrate the topographic roles in regional climate over the TP and highlight its teleconnected climate impacts.

54 ENVIRONMENTAL SCIENCES↗

Atmospheric Turbulent Intermittency Over the Arctic Sea‐Ice Surface During the MOSAiC Expedition

Turbulent motions in the Arctic stable boundary layer are characterized by intermittency, but they are rarely investigated due to limited observations, in particular over the sea‐ice surface. In the present study, we explore the characteristics of turbulent intermittency over the Arctic sea‐ice surface using data collected during the Multidisciplinary drifting Observation for the Study of Arctic Climate expedition from October 2019 to September 2020. We first develop a new algorithm, which performs well in identifying the spectral gap over the Arctic sea‐ice surface. Then the characteristics of intermittency are investigated. It is found that the strength of intermittency increases under the conditions of light surface wind speed, small surface wind speed gradient, and strong surface air temperature gradient. The momentum flux, sensible heat flux, and latent heat flux calculated by raw eddy‐covariance fluctuations are overestimated by 3%, 10%, and 24%, respectively, because submesoscale motions are included. Furthermore, the characteristics of the atmospheric boundary layer structure under various intermittency conditions reveal that strong low‐level jets are favorable to surface turbulent motions that result in weak intermittency, while strong temperature inversions above the surface layer suppress surface turbulent motions and lead to strong intermittency.

54 ENVIRONMENTAL SCIENCES↗

Alternating Conditional Expectations: Introducing a Non‐Parametric Statistical Method to Interpret Long‐Term Greenhouse Gas Flux Measurements Over Semi‐Arid and Wetland Ecosystems

Abstract We explore the potential of using a non‐parametric statistical method called Alternating Conditional Expectations, ACE, to quantify functional relationships in biogeosciences. Here, ACE is used to quantify the non‐linear and multi‐faceted responses of greenhouse gas fluxes to a set of biophysical forcings, when the shapes of those response surfaces are unknown. We evaluated the statistical method over two contrasting ecosystems and two contrasting time steps. One case involved quantifying the biophysical controls of water vapor and carbon dioxide (CO 2 ) fluxes over a semi‐arid oak savanna using daily integrated fluxes. The other case evaluated the responses of CO 2 and methane (CH 4 ) flux measurements to a set of biophysical forcings at a restored tidal wetland using thirty‐minute averages. The statistical model, based on 4 independent variables, explained up over 90% of the variation in daily integrated flux densities of water vapor and net carbon dioxide exchange at the savanna site. This fit was defined by distinct non‐linear responses to such drivers as gross primary production, photosynthetically active radiation, air temperature, vapor pressure deficit and soil moisture. At the tidal wetland site, we evaluated net carbon dioxide and methane fluxes with short‐term measurements to capture the influence of rising and falling tides and seasonality in biological activity. The statistical model defined the shape of the forcing of fluxes due to the roles of carbon exudates, water table depth, oxygen level in the water column, temperature and vegetation status. The statistical fits of the greenhouse gas fluxes were less precise than the savanna case. The fetch varies on a run‐to‐run basis as it is comprised of a heterogeneous mosaic of open water and vegetation. Furthermore, it is difficult to monitor the environmental conditions of the archaea and bacteria in the sediments that produce methane and carbon dioxide.

Environmental Sciences & Ecology↗

Ensemble Spread Behavior in Coupled Climate Models: Insights From the Energy Exascale Earth System Model Version 1 Large Ensemble

AbstractAssessing uncertainty in future climate projections requires understanding both internal climate variability and external forcing. For this reason, single‐model initial condition large ensembles (SMILEs) run with Earth System Models (ESMs) have recently become popular. Here we present a new 20‐member SMILE with the Energy Exascale Earth System Model version 1 (E3SMv1‐LE), which uses a “macro” initialization strategy choosing coupled atmosphere/ocean states based on inter‐basin contrasts in ocean heat content (OHC). The E3SMv1‐LE simulates tropical climate variability well, albeit with a muted warming trend over the twentieth century due to overly strong aerosol forcing. The E3SMv1‐LE's initial climate spread is comparable to other (larger) SMILEs, suggesting that maximizing inter‐basin ocean heat contrasts may be an efficient method of generating ensemble spread. We also compare different ensemble spread across multiple SMILEs, using surface air temperature and OHC. The Community Earth system Model version 1, the only ensemble which utilizes a “micro” initialization approach perturbing only atmospheric initial conditions, yields lower spread in the first ∼30 years. The E3SMv1‐LE exhibits a relatively large spread, with some evidence for anthropogenic forcing influencing spread in the late twentieth century. However, systematic effects of differing “macro” initialization strategies are difficult to detect, possibly resulting from differing model physics or responses to external forcing. Notably, the method of standardizing results affects ensemble spread: control simulations for most models have either large background trends or multi‐centennial variability in OHC. This spurious disequlibrium behavior is a substantial roadblock to understanding both internal climate variability and its response to forcing.

Stevenson, Samantha↗

On the Sensitivity of Coastal Hypoxia to Its External Physical Forcings

Abstract The development of low‐oxygen zones threatening marine life (hypoxia) occurs annually in multiple coastal regions of the world. The largest estuary of the continental United States, the Chesapeake Bay, typically has ≈10 km 3 of water with dioxygen concentrations <3 mg L −1 in July. As numerical methods for refining model resolutions in targeted areas are becoming common, there is interest in assessing the feasibility of simulating coastal hazards such as hypoxia in Earth System Models (ESMs). These coupled models are typically not constrained by observations and thus likely to feature systematic biases in their land, atmosphere, or ocean components. This study relies on four numerical experiments to evaluate the sensitivity of Chesapeake Bay hypoxia to changes or biases in its external physical forcings. Hypoxia exhibits only a minor decrease (−1.6%) after reducing the Bay's terrestrial freshwater discharge by 9.5% (but keeping terrestrial nutrient loadings the same). Changes in freshwater discharges have their largest impact on hypoxia during one extreme event (−37% during 2011 tropical storm Lee). Similarly, changing oceanic conditions on the shelf or their temporal frequency impact hypoxia by only 5%–6%, indicating that the latter is predominantly dictated by local conditions. Although these results are promising from the perspective of ESMs, additional components of ESMs will need to be evaluated before general conclusions can be reached. We notably speculate that the Bay's hypoxia would exhibit higher sensitivity to other forcings not examined here, notably air temperatures and nutrient loadings.

Meteorology & Atmospheric Sciences↗

Permafrost Formation in a Meandering River Floodplain

Abstract Permafrost influences 25% of land in the Northern Hemisphere, where it stabilizes the ground beneath communities and infrastructure and sequesters carbon. However, the coevolution of permafrost, river dynamics, and vegetation in Arctic environments remains poorly understood. As rivers meander, they erode the floodplain at cutbanks and build new land through bar deposition, creating sequences of landforms with distinct formation ages. Here we mapped these sequences along the Koyukuk River floodplain, Alaska, analyzing permafrost occurrence, and landform and vegetation types. We used radiocarbon and optically stimulated luminescence (OSL) dating to develop a floodplain age map. Deposit ages ranged from modern to 10 ka, with more younger deposits near the modern channel. Permafrost rapidly reached 50% areal extent in all deposits older than 200 years then gradually increased up to ∼85% extent for deposits greater than 4 Kyr old. Permafrost extent correlated with increases in black spruce and wetland abundance, as well as increases in permafrost extent within wetland, and shrub and scrub vegetation classes. We developed an inverse model to constrain permafrost formation rate as a function of air temperature. Permafrost extent initially increased by ∼25% per century, in pace with vegetation succession, before decelerating to <10% per millennia as insulating overbank mud and moss slowly accumulated. Modern permafrost extent on the Koyukuk floodplain therefore reflects a dynamic balance between widespread, time‐varying permafrost formation and rapid, localized degradation due to cutbank erosion that might trigger a rapid loss of permafrost with climatic warming.

54 ENVIRONMENTAL SCIENCES↗

Assessing Radiative Feedbacks and Their Contribution to the Arctic Amplification Measured by Various Metrics

Arctic amplification (AA), characterized by a more rapid surface air temperature (SAT) warming in the Arctic than the global average, is a major feature of global climate warming. Various metrics have been used to quantify AA based on SAT anomalies, trends, or variability, and they can yield quite different conclusions regarding the magnitude and temporal patterns of AA. This study examines and compares various AA metrics for their temporal consistency in the region north of 70°N from the early twentieth to the early 21st century using observational data and reanalysis products. We also quantify contributions of different radiative feedback mechanisms to AA based on short-term climate variability in reanalysis and model data using the Kernel-Gregory approach. Albedo and lapse rate feedbacks are positive and comparable, with albedo feedback being the leading contributor for all AA metrics. The net cloud feedback, which has large uncertainties, depends strongly on the data sets and AA metrics used. By quantifying the influence of internal variability on AA and related feedbacks based on global climate model ensemble simulations, we find that water vapor and cloud feedbacks are most heavily affected by internal variability.

54 ENVIRONMENTAL SCIENCES↗

The Abundance and Sources of Ice Nucleating Particles Within Alaskan Ice Fog

Abstract The Alaskan Layered Pollution and Chemical Analysis (ALPACA) field campaign included deployment of a suite of atmospheric measurements in January–February 2022 with the goal of better understanding atmospheric processes and pollution under cold and dark conditions in Fairbanks, Alaska. We report on measurements of particle composition, particle size, ice nucleating particle (INP) composition, and INP size during an ice fog period (29 January–3 February). During this period, coarse particulate matter (PM 10 ) concentrations increased by 150% in association with a decrease in air temperature, a stronger temperature inversion, and relatively stagnant conditions. Results also show a 18%–78% decrease in INPs during the ice fog period, indicating that particles had activated into the ice fog via nucleation. Peroxide and heat treatments performed on INPs indicated that, on average, the largest contributions to the INP population were heat‐labile (potentially biological, 63%), organic (31%), then inorganic (likely dust, 6%). Measurements of levoglucosan and bulk and single‐particle composition corroborate the presence of dust and aerosols from combustion sources. Heat‐labile and organic INPs decreased during the peak period of the ice fog, indicating those were preferentially activated, while inorganic INPs increased, suggesting they remained as interstitial INPs. In general, INP concentrations were unexpectedly high in Fairbanks compared to other locations in the Arctic during winter. The fact that these INPs likely facilitated ice fog formation in Fairbanks has implications for other high latitude locations subject to the hazards associated with ice fog.

Meteorology & Atmospheric Sciences↗

BioRT‐HBV 1.0: A Biogeochemical Reactive Transport Model at the Watershed Scale

Abstract Reactive Transport Models (RTMs) are essential tools for understanding and predicting intertwined ecohydrological and biogeochemical processes on land and in rivers. While traditional RTMs have focused primarily on subsurface processes, recent watershed‐scale RTMs have integrated ecohydrological and biogeochemical interactions between surface and subsurface. These emergent, watershed‐scale RTMs are often spatially explicit and require extensive data, computational power, and computational expertise. There is however a pressing need to create parsimonious models that require minimal data and are accessible to scientists with limited computational background. To that end, we have developed BioRT‐HBV 1.0, a watershed‐scale, hydro‐biogeochemical RTM that builds upon the widely used, bucket‐type HBV model known for its simplicity and minimal data requirements. BioRT‐HBV uses the conceptual structure and hydrology output of HBV to simulate processes including advective solute transport and biogeochemical reactions that depend on reaction thermodynamics and kinetics. These reactions include, for example, chemical weathering, soil respiration, and nutrient transformation. The model uses time series of weather (air temperature, precipitation, and potential evapotranspiration) and initial biogeochemical conditions of subsurface water, soils, and rocks as input, and output times series of reaction rates and solute concentrations in subsurface waters and rivers. This paper presents the model structure and governing equations and demonstrates its utility with examples simulating carbon and nitrogen processes in a headwater catchment. As shown in the examples, BioRT‐HBV can be used to illuminate the dynamics of biogeochemical reactions in the invisible, arduous‐to‐measure subsurface, and their influence on the observed stream or river chemistry and solute export. With its parsimonious structure and easy‐to‐use graphical user interface, BioRT‐HBV can be a useful research tool for users without in‐depth computational training. It can additionally serve as an educational tool that promotes pollination of ideas across disciplines and foster a diverse, equal, and inclusive user community.

Sadayappan, Kayalvizhi↗