J. P. McFadden

University of California, Berkeley

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Dar A. Roberts

University of California, Santa Barbara

C. W. Carlson

University of Colorado System

V. Angelopoulos

Planetary Science Institute

F. Stuart Chapin

University of Alaska Fairbanks

Werner Eugster

ETH Zurich

M. H. Boehm

Friedrich Schiller University Jena

Sue Grimmond

University of Reading

D. E. Larson

University of California, Berkeley

R. E. Ergun

Laboratory for Atmospheric and Space Physics

Leena Järvi

University of Helsinki

Cooperative Institutions

University of California, Berkeley

University of Colorado Boulder

Laboratory for Atmospheric and Space Physics

Goddard Space Flight Center

Planetary Science Institute

Centre National de la Recherche Scientifique

University of California, Los Angeles

University of Michigan–Ann Arbor

University of Colorado System

University of Alaska Fairbanks

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Vegetation type is an important predictor of the arctic summer land surface energy budget

Nature Communications (2022)

Jacqueline Oehri Gabriela Schaepman‐Strub Jin‐Soo Kim Raleigh Grysko Heather Kropp

Abstract Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm −2 ) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.

Arctic vegetation

Vegetation types

Circumpolar star

Seasonality

Energy budget

Land Cover

10.1038/s41467-022-34049-3

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Citations (34)

Drought response of urban trees and turfgrass using airborne imaging spectroscopy

Remote Sensing of Environment (2020)

David L. Miller Michael Alonzo Dar A. Roberts C. Tague J. P. McFadden

Endmember

Shading

10.1016/j.rse.2020.111646

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Citations (45)

Energy release and transport in the near-Earth magnetotail associated with substorms: THEMIS observations

AGUFM (2010)

Yukinaga Miyashita S. Machida A. Ieda T. Takada K. Seki

Substorm

Source

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Trees Grow on Money: Urban Tree Canopy Cover and Environmental Justice

PLoS ONE (2015)

Kirsten Schwarz Michail Fragkias Christopher G. Boone Weiqi Zhou Melissa R. McHale

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman's correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns.

Urban Forestry

Tree (set theory)

Environmental Justice

10.1371/journal.pone.0122051

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Citations (514)

Surface Urban Energy and Water Balance Scheme (v2020a) in vegetated areas: parameter derivation and performance evaluation using FLUXNET2015 dataset

Geoscientific model development (2022)

Hamidreza Omidvar Ting Sun Sue Grimmond Dave Bilesbach T. Andrew Black

Abstract. To compare the impact of surface–atmosphere exchanges from rural and urban areas, fully vegetated areas (e.g. deciduous trees, evergreen trees and grass) commonly found adjacent to cities need to be modelled. Here we provide a general workflow to derive parameters for SUEWS (Surface Urban Energy and Water Balance Scheme), including those associated with vegetation phenology (via leaf area index, LAI), heat storage and surface conductance. As expected, attribution analysis of bias in SUEWS-modelled QE finds that surface conductance (gs) plays the dominant role; hence there is a need for more estimates of surface conductance parameters. The workflow is applied at 38 FLUXNET sites. The derived parameters vary between sites with the same plant functional type (PFT), demonstrating the challenge of using a single set of parameters for a PFT. SUEWS skill at simulating monthly and hourly latent heat flux (QE) is examined using the site-specific derived parameters, with the default NOAH surface conductance parameters (Chen et al., 1996). Overall evaluation for 2 years has similar metrics for both configurations: median hit rate between 0.6 and 0.7, median mean absolute error less than 25 W m−2, and median mean bias error ∼ 5 W m−2. Performance differences are more evident at monthly and hourly scales, with larger mean bias error (monthly: ∼ 40 W m−2; hourly ∼ 30 W m−2) results using the NOAH-surface conductance parameters, suggesting that they should be used with caution. Assessment of sites with contrasting QE performance demonstrates how critical capturing the LAI dynamics is to the SUEWS prediction skills of gs and QE. Generally gs is poorest in cooler periods (more pronounced at night, when underestimated by ∼ 3 mm s−1). Given the global LAI data availability and the workflow provided in this study, any site to be simulated should benefit.

FluxNet

Stomatal Conductance

Biometeorology

10.5194/gmd-15-3041-2022

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Citations (11)

Auroral polar cap boundary ion conic outflow observed on FAST

Journal of Geophysical Research Atmospheres (2001)

Yeou‐Koung Tung C. W. Carlson J. P. McFadden D. M. Klumpar G. K. Parks

We observe large ion outflow fluxes (> 10 8 cm −2 s −1 mapped to 100 km) flowing from the auroral polar cap boundary on many FAST auroral passes near midnight. The outflow is in the form of ion conies composed mostly of light ions with energies of hundreds of eV. A statistical study of 606 FAST orbits during January and February 1997 was done to determine the MLT distribution and ion outflow properties relative to substorms. We find that the ion conic events occur most frequently near midnight, and therefore their direct magnetic connection to the nightside central plasma sheet makes this ion outflow a candidate for the ionospheric source of the nightside plasma sheet. To study the relationship between the ion conic outflow events and auroral substorm conditions, we use global auroral images acquired from the ultraviolet imager (UVI) on Polar. We find that the outflow events are well correlated with substorm expansion phase, but ion conic outflow events also occur during generally active aurora, when onset and expansion phases were not clearly identifiable. By combining FAST data to determine ion outflow fluxes and ILAT extent and Polar UVI images to determine MLT extent, we estimate the total outflow due to these ion conic events to be 10 22 to 10 24 ions/s. By comparing with earlier ion outflow studies, we conclude that these polar cap boundary ion conic events are not the dominant or only ionospheric source of ion outflow over the entire auroral oval but are the dominant nightside auroral ion outflow.

Outflow

Substorm

Plasma sheet

Conic section

10.1029/2000ja900115

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Citations (58)

Observations of polar cap arcs on FAST

Journal of Geophysical Research Atmospheres (1999)

J. W. Bonnell R. C. Elphic S. Palfery R. J. Strangeway W. K. Peterson

FAST satellite observations of spatially localized regions of electron and ion precipitation with concomitant paired upward and downward field‐aligned currents and duskward electric field enhancements at high (> 80° invariant latitude) magnetic latitudes are presented. Each pass of several across the polar cap was made during a period of persistent northward interplanetary magnetic field, and was characterized by the presence of several of these precipitation regions. In each case, the precipitation regions were associated with jets of enhanced antisunward convection, with electron precipitation restricted to the upward current region, and no energetic electron outflow in the downward current region, and ion precipitation spread over broader regions, possibly by time‐of‐flight effects. We compare these low‐altitude features to those expected for source regions lying in a reconnection site at the lobe magnetopause, a bursty bulk flow in the plasma sheet, and a surface wave on the low‐latitude boundary layer (LLBL). We find that the lobe reconnection model successfully describes the observed electrodynamics of the arcs, as well as the electron and ion source temperatures, but can not readily explain the presence of precipitating O + and He + in addition to H + and He ++ . The plasma sheet source model can explain the composition of the ion precipitation but predicts higher electron and ion source temperatures than are observed, may require the coincidence of bursty bulk flows with extensions of the plasma sheet into the lobe, and may not be consistant with other observations of auroral phenomenology. The LLBL surface wave model does not readily explain the observed electrodynamics of the arcs and is not consistent with the observed offsets between electron and ion precipitation.

Plasma sheet

Electron precipitation

Current sheet

Substorm

Outflow

10.1029/1999ja900085

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Citations (26)

Statistical partitioning of a three-year time series of direct urban net CO 2 flux measurements into biogenic and anthropogenic components

Atmospheric Environment (2017)

Olaf Menzer J. P. McFadden

Ecosystem respiration