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Journal articleSorland SL, Brogli R, Pothapakula PK, et al., 2021, , GEOSCIENTIFIC MODEL DEVELOPMENT, Vol: 14, Pages: 5125-5154, ISSN: 1991-959X
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Journal articleKaweeyanun N, Masters A, Jia X, 2021, , Journal of Geophysical Research: Space Physics, Vol: 126, Pages: 1-14, ISSN: 2169-9380
Ganymede is the only Solar System moon that generates a permanent magnetic field. Dynamics within the Ganymedean magnetosphere is thought to be driven by energy-transfer interactions on its upstream magnetopause. Previously in Kaweeyanun et al. (2020), https://doi.org/10.1029/2019GL086228 we created a steady-state analytical model of Ganymede's magnetopause and predicted global-scale magnetic reconnection to occur frequently throughout the surface. This paper subsequently provides the first assessment of Kelvin-Helmholtz (K-H) instability growth on the magnetopause. Using the same analytical model, we find that linear K-H waves are expected on both Ganymedean magnetopause flanks. Once formed, the waves propagate downstream at roughly half the speed of the external Jovian plasma flow. The Ganymedean K-H instability growth is asymmetric between magnetopause flanks due to the finite Larmor radius effect arising from large gyroradii of Jovian plasma ions. A small but notable enhancement is expected on the sub-Jovian flank according to the physical understanding of bulk plasma and local ion flows alongside comparisons to the well-observed magnetopause of Mercury. Further evaluation shows that nonlinear K-H vortices should be strongly suppressed by concurring global-scale magnetic reconnection at Ganymede. Reconnection is therefore the dominant cross-magnetopause energy-transfer mechanism and driver of global-scale plasma convection within Ganymede's magnetosphere.
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Journal articleReid J, Cargill PJ, Johnston CD, et al., 2021, , Monthly Notices of the Royal Astronomical Society, Vol: 505, Pages: 4141-4150, ISSN: 0035-8711
A ‘proof of principle’ is presented, whereby the Ohmic and viscous heating determined by a three-dimensional (3D) MHD model of a coronal avalanche are used as the coronal heating input for a series of field-aligned, one-dimensional (1D) hydrodynamic models. Three-dimensional coronal MHD models require large computational resources. For current numerical parameters, it is difficult to model both the magnetic field evolution and the energy transport along field lines for coronal temperatures much hotter than 1MK鈦, because of severe constraints on the time step from parallel thermal conduction. Using the 3D MHD heating derived from a simulation and evaluated on a single field line, the 1D models give coronal temperatures of 1MK and densities 1014--1015m−3 for a coronal loop length of 80Mm鈦. While the temperatures and densities vary smoothly along the field lines, the heating function leads to strong asymmetries in the plasma flows. The magnitudes of the velocities in the 1D model are comparable with those seen in 3D reconnection jets in our earlier work. Advantages and drawbacks of this approach for coronal modelling are discussed.
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Journal articleRasca AP, Farrell WM, MacDowall RJ, et al., 2021, , ASTROPHYSICAL JOURNAL, Vol: 916, ISSN: 0004-637X
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- Citations: 6
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Journal articleNew AL, Smeed DA, Czaja A, et al., 2021, , ENVIRONMENTAL RESEARCH LETTERS, Vol: 16, ISSN: 1748-9326
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- Citations: 13
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Journal articleHellinger P, Papini E, Verdini A, et al., 2021, , ASTROPHYSICAL JOURNAL, Vol: 917, ISSN: 0004-637X
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- Citations: 11
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Journal articleMasters A, Dunn W, Stallard T, et al., 2021, , Journal of Geophysical Research: Space Physics, Vol: 126, Pages: 1-10, ISSN: 2169-9380
Auroral emissions have been extensively observed at the Earth, Jupiter, and Saturn. These planets all have appreciable atmospheres and strong magnetic fields, and their auroras predominantly originate from a region encircling each magnetic pole. However, Jupiter’s auroras poleward of these “main” emissions are brighter and more dynamic, and the drivers responsible for much of these mysterious polar auroras have eluded identification to date. We propose that part of the solution may stem from Jupiter’s stronger magnetic field. We model large-scale Alfvénic perturbations propagating through the polar magnetosphere toward Jupiter, showing that the resulting <0.1° deflections of the magnetic field closest to the planet could trigger magnetic reconnection as near as ∼0.2 Jupiter radii above the cloud tops. At Earth and Saturn this physics should be negligible, but reconnection electric field strengths above Jupiter’s poles can approach ∼1 V m−1, typical of the solar corona. We suggest this near-planet reconnection could generate beams of high-energy electrons capable of explaining some of Jupiter’s polar auroras.
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Journal articleSchwartz SJ, Ergun R, Kucharek H, et al., 2021, , JOURNAL OF GEOPHYSICAL RESEARCH-SPACE PHYSICS, Vol: 126, ISSN: 2169-9380
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- Citations: 4
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Journal articleChoi TH, Brindley H, Ekins-Daukes N, et al., 2021, , Renewable Energy, Vol: 173, Pages: 1070-1086, ISSN: 0960-1481
We describe four schemes designed to estimate spectrally resolved direct normal irradiance (DNI) formulti-junction concentrator photovoltaic systems applications. The schemes have increasing levels ofcomplexity in terms of aerosol and circumsolar irradiance (CSI) treatment, ranging from a climatologicalaerosol classification with no account of CSI, to an approach which includes explicit aerosol typing andtype dependent CSI contribution. When tested against ground-based broadband and spectral measurements at five sites spanning a range of aerosol conditions, the most sophisticated scheme yields anaverage bias of þ 0:068%, well within photometer calibration uncertainties. The average spread of erroris 2:5%. These statistics are markedly better than the climatological approach, which carries an averagebias of 1:76% and a spread of 4%. They also improve on an intermediate approach which uses Angstrom€exponents to estimate the spectral variation in aerosol optical depth across the solar energy relevantwavelength domain. This approach results in systematic under and over-estimations of DNI at short andlong wavelengths respectively. Incorporating spectral CSI particularly benefits sites which experience asignificant amount of coarse aerosol. All approaches we describe use freely available reanalyses andsoftware tools, and can be easily applied to alternative aerosol measurements, including those fromsatellite.
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Journal articleBrooks DH, Harra L, Bale SD, et al., 2021, , ASTROPHYSICAL JOURNAL, Vol: 917, ISSN: 0004-637X
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- Citations: 9
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Journal articleZank GP, Zhao L-L, Adhikari L, et al., 2021, , PHYSICS OF PLASMAS, Vol: 28, ISSN: 1070-664X
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- Citations: 74
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Journal articleLiu YY, Fu HS, Cao JB, et al., 2021, , ASTROPHYSICAL JOURNAL, Vol: 916, ISSN: 0004-637X
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- Citations: 20
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Journal articleStansby D, Green LM, van Driel-Gesztelyi L, et al., 2021, , SOLAR PHYSICS, Vol: 296, ISSN: 0038-0938
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- Citations: 8
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Journal articleCeppi P, Nowack P, 2021, , Proceedings of the National Academy of Sciences, Vol: 118, ISSN: 0027-8424
Global warming drives changes in Earth’s cloud cover, which, in turn, may amplify or dampen climate change. This “cloud feedback” is the single most important cause of uncertainty in Equilibrium Climate Sensitivity (ECS)—the equilibrium global warming following a doubling of atmospheric carbon dioxide. Using data from Earth observations and climate model simulations, we here develop a statistical learning analysis of how clouds respond to changes in the environment. We show that global cloud feedback is dominated by the sensitivity of clouds to surface temperature and tropospheric stability. Considering changes in just these two factors, we are able to constrain global cloud feedback to 0.43 ± 0.35 W⋅m<jats:sup>−2</jats:sup>⋅K<jats:sup>−1</jats:sup> (90% confidence), implying a robustly amplifying effect of clouds on global warming and only a 0.5% chance of ECS below 2 K. We thus anticipate that our approach will enable tighter constraints on climate change projections, including its manifold socioeconomic and ecological impacts.
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Journal articleThomas C, Voulgarakis A, Lim G, et al., 2021, , Weather and Climate Dynamics, Vol: 2, Pages: 581-608, ISSN: 2698-4016
Atmospheric blocking events are mid-latitude weather patterns, which obstruct the usual path of the polar jet streams. They are often associated with heat waves in summer and cold snaps in winter. Despite being central features of mid-latitude synoptic-scale weather, there is no well-defined historical dataset of blocking events. Various blocking indices (BIs) have thus been suggested for automatically identifying blocking events in observational and in climate model data. However, BIs show significant regional and seasonal differences so that several indices are typically applied in combination to ensure scientific robustness. Here, we introduce a new BI using self-organizing maps (SOMs), an unsupervised machine learning approach, and compare its detection skill to some of the most widely applied BIs. To enable this intercomparison, we first create a new ground truth time series classification of European blocking based on expert judgement. We then demonstrate that our method (SOM-BI) has several key advantages over previous BIs because it exploits all of the spatial information provided in the input data and reduces the dependence on arbitrary thresholds. Using ERA5 reanalysis data (1979–2019), we find that the SOM-BI identifies blocking events with a higher precision and recall than other BIs. In particular, SOM-BI already performs well using only around 20 years of training data so that observational records are long enough to train our new method. We present case studies of the 2003 and 2019 European heat waves and highlight that well-defined groups of SOM nodes can be an effective tool to diagnose such weather events, although the domain-based approach can still lead to errors in the identification of certain events in a fashion similar to the other BIs. We further test the red blocking detection skill of SOM-BI depending on the meteorological variable used to study blocking, including geopotential height, sea level pressure and four variables related to
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Journal articleThomas C, Voulgarakis A, Lim G, et al., 2021, , Weather and Climate Dynamics, Vol: 2, ISSN: 2698-4016
Atmospheric blocking events are mid-latitudeweather patterns, which obstruct the usual path of the polar jet streams. They are often associated with heat wavesin summer and cold snaps in winter. Despite being centralfeatures of mid-latitude synoptic-scale weather, there is nowell-defined historical dataset of blocking events. Variousblocking indices (BIs) have thus been suggested for automatically identifying blocking events in observational and inclimate model data. However, BIs show significant regionaland seasonal differences so that several indices are typicallyapplied in combination to ensure scientific robustness. Here,we introduce a new BI using self-organizing maps (SOMs),an unsupervised machine learning approach, and compare itsdetection skill to some of the most widely applied BIs. Toenable this intercomparison, we first create a new groundtruth time series classification of European blocking basedon expert judgement. We then demonstrate that our method(SOM-BI) has several key advantages over previous BIs because it exploits all of the spatial information provided in theinput data and reduces the dependence on arbitrary thresholds. Using ERA5 reanalysis data (1979–2019), we find thatthe SOM-BI identifies blocking events with a higher precision and recall than other BIs. In particular, SOM-BI alreadyperforms well using only around 20 years of training data sothat observational records are long enough to train our newmethod. We present case studies of the 2003 and 2019 European heat waves and highlight that well-defined groups ofSOM nodes can be an effective tool to diagnose such weatherevents, although the domain-based approach can still lead toerrors in the identification of certain events in a fashion similar to the other BIs. We further test the red blocking detectionskill of SOM-BI depending on the meteorological variableused to study blocking, including geopotential height, sealevel pressure and four variables related to potential vorticity,and t
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Journal articleZazzeri G, Xu X, Graven H, 2021, , Environmental Science and Technology (Washington), Vol: 55, Pages: 8535-8541, ISSN: 0013-936X
Radiocarbon (14C) measurements offer a unique investigative tool to study methane emissions by identifying fossil-fuel methane in air. Fossil-fuel methane is devoid of 14C and, when emitted to the atmosphere, causes a strong decrease in the ratio of radiocarbon to total carbon in methane (Δ14CH4). By observing the changes in Δ14CH4, the fossil fraction of methane emissions can be quantified. Presently, there are very few published Δ14CH4 measurements, mainly because it is challenging to collect and process the large volumes of air needed for radiocarbon measurements. We present a new sampling system that collects enough methane carbon for high precision Δ14CH4 measurements without having to transport large volumes of air. The system catalytically combusts CH4 into CO2 and adsorbs the combustion-derived CO2 onto a molecular sieve trap, after first removing CO2, CO, and H2O. Tests using reference air show a Δ14CH4 measurement repeatability of 5.4‰, similar or better than the precision in the most recent reported measurements. We use the system to produce the first Δ14CH4 measurements in central London and show that day-to-day differences in Δ14CH4 in these samples can be attributed to fossil methane input. The new system could be deployed in a range of settings to investigate CH4 sources.
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Journal articleChen Y-J, Hwang Y-T, Ceppi P, 2021, , Journal of Climate, Vol: 34, Pages: 7857-7874, ISSN: 0894-8755
Based on theory and climate model experiments, previous studies suggest most of the uncertainties in projected future changes in meridional energy transport and zonal mean surface temperature can be attributed to cloud feedback. To investigate how radiative and dynamical adjustments modify the influence of cloud-radiative changes on energy transport, this study applies a cloud-locking technique in a fully-coupled climate model, CESM. Under global warming, the impacts of cloud-radiative changes on the meridional energy transport are asymmetric in the two hemispheres. In the Northern Hemisphere, the cloud-radiative changes have little impact on energy transport, because 89% of the cloud-induced heating is balanced locally by increasing outgoing longwave radiation. In the Southern Hemisphere, on the other hand, cloud-induced dynamical changes in the atmosphere and the ocean cause enhanced poleward energy transport, accounting for most of the increase in energy transport under warming. Our experiments highlight that the local longwave radiation adjustment induced by temperature variation can partially offset the impacts of cloud-radiative changes on energy transport, making the estimated impacts smaller than those obtained from directly integrating cloud-radiative changes in previous studies. It is also demonstrated that the cloud-radiative impacts on temperature and energy transport can be significantly modulated by the oceanic circulation, suggesting the necessity of considering atmospheric-oceanic coupling when estimating the impacts of cloud-radiative changes on the climate system.
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Journal articleGreaves JS, Richards AMS, Bains W, et al., 2021, , Nature Astronomy, Vol: 5, Pages: 726-728, ISSN: 2397-3366
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Journal articleJoyce CJ, McComas DJ, Schwadron NA, et al., 2021, , ASTRONOMY & ASTROPHYSICS, Vol: 651, ISSN: 0004-6361
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- Citations: 11
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Journal articleMadanian H, Schwartz SJ, Fuselier SA, et al., 2021, , ASTROPHYSICAL JOURNAL LETTERS, Vol: 915, ISSN: 2041-8205
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- Citations: 5
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Journal articleYao Z, Dunn WR, Woodfield EE, et al., 2021, , SCIENCE ADVANCES, Vol: 7, ISSN: 2375-2548
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- Citations: 14
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Journal articleDuan D, He J, Bowen TA, et al., 2021, , Letters of the Astrophysical Journal, Vol: 915, Pages: 1-7, ISSN: 2041-8205
The anisotropy of solar wind turbulence is a critical issue in understanding the physics of energy transfer between scales and energy conversion between fields and particles in the heliosphere. Using the measurement of Parker Solar Probe (PSP), we present an observation of the anisotropy at kinetic scales in the slow, Alfvénic, solar wind in the inner heliosphere. The magnetic compressibility behaves as expected for kinetic Alfvénic turbulence below the ion scale. A steepened transition range is found between the inertial and kinetic ranges in all directions with respect to the local background magnetic field direction. The anisotropy of k⊥ 鈮 k鈭 is found evident in both transition and kinetic ranges, with the power anisotropy P⊥/P鈭 > 10 in the kinetic range leading over that in the transition range and being stronger than that at 1 au. The spectral index varies from αt鈭 = −5.7 ± 1.0 to αt⊥ = −3.7 ± 0.3 in the transition range and αk鈭 = −3.12 ± 0.22 to αk⊥ = −2.57 ± 0.09 in the kinetic range. The corresponding wavevector anisotropy has the scaling of ${k}_{\parallel }\sim {k}_{\perp }^{0.71\pm 0.17}$ in the transition range, and changes to ${k}_{\parallel }\sim {k}_{\perp }^{0.38\pm 0.09}$ in the kinetic range, consistent with the kinetic Alfvénic turbulence at sub-ion scales.
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Journal articleWang R, Vasko IY, Mozer FS, et al., 2021, , JOURNAL OF GEOPHYSICAL RESEARCH-SPACE PHYSICS, Vol: 126, ISSN: 2169-9380
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- Citations: 29
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Journal articleGristey JJ, Su W, Loeb NG, et al., 2021, , Remote Sensing, Vol: 13, ISSN: 2072-4292
Observing the Earth radiation budget (ERB) from satellites is crucial for monitoring and understanding Earth’s climate. One of the major challenges for ERB observations, particularly for reflected shortwave radiation, is the conversion of the measured radiance to the more energetically relevant quantity of radiative flux, or irradiance. This conversion depends on the solar-viewing geometry and the scene composition associated with each instantaneous observation. We first outline the theoretical basis for algorithms to convert shortwave radiance to irradiance, most commonly known as empirical angular distribution models (ADMs). We then review the progression from early ERB satellite observations that applied relatively simple ADMs, to current ERB satellite observations that apply highly sophisticated ADMs. A notable development is the dramatic increase in the number of scene types, made possible by both the extended observational record and the enhanced scene information now available from collocated imager information. Compared with their predecessors, current shortwave ADMs result in a more consistent average albedo as a function of viewing zenith angle and lead to more accurate instantaneous and mean regional irradiance estimates. One implication of the increased complexity is that the algorithms may not be directly applicable to observations with insufficient accompanying imager information, or for existing or new satellite instruments where detailed scene information is not available. Recent advances that complement and build on the base of current approaches, including machine learning applications and semi-physical calculations, are highlighted.
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Journal articleFarrell WM, Rasca AP, MacDowall RJ, et al., 2021, , ASTROPHYSICAL JOURNAL, Vol: 915, ISSN: 0004-637X
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- Citations: 6
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Journal articleChen L, Ma B, Wu D, et al., 2021, , ASTROPHYSICAL JOURNAL LETTERS, Vol: 915, ISSN: 2041-8205
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- Citations: 7
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Journal articleHalekas JS, Bercic L, Whittlesey P, et al., 2021, , ASTROPHYSICAL JOURNAL, Vol: 916, ISSN: 0004-637X
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- Citations: 22
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Journal articleKuhn- Regnier A, Voulgarakis A, Nowack P, et al., 2021, , Biogeosciences, Vol: 18, Pages: 3861-3879, ISSN: 1726-4170
The seasonal and longer-term dynamics of fuel accumulation affect fire seasonality and the occurrence of extreme wildfires. Failure to account for their influence may help to explain why state-of-the-art fire models do not simulate the length and timing of the fire season or interannual variability in burnt area well. We investigated the impact of accounting for different timescales of fuel production and accumulation on burnt area using a suite of random forest regression models that included the immediate impact of climate, vegetation, and human influences in a given month and tested the impact of various combinations of antecedent conditions in four productivity-related vegetation indices and in antecedent moisture conditions. Analyses were conducted for the period from 2010 to 2015 inclusive. Inclusion of antecedent vegetation conditions representing fuel build-up led to an improvement of the global, climatological out-of-sample R2 from 0.579 to 0.701, but the inclusion of antecedent vegetation conditions on timescales ≥ 1 year had no impact on simulated burnt area. Current moisture levels were the dominant influence on fuel drying. Additionally, antecedent moisture levels were important for fuel build-up. The models also enabled the visualisation of interactions between variables, such as the importance of antecedent productivity coupled with instantaneous drying. The length of the period which needs to be considered varies across biomes; fuel-limited regions are sensitive to antecedent conditions that determine fuel build-up over longer time periods (∼ 4 months), while moisture-limited regions are more sensitive to current conditions that regulate fuel drying.
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Journal articleKuhn-R茅gnier A, Voulgarakis A, Nowack P, et al., 2021, , Biogeosciences, Vol: 8, ISSN: 1726-4170
The seasonal and longer-term dynamics of fuel accumulation affect fire seasonality and the occurrence of extreme wildfires. Failure to account for their influence mayhelp to explain why state-of-the-art fire models do not simulate the length and timing of the fire season or interannual variability in burnt area well. We investigated the impact of accounting for different timescales of fuel production and accumulation on burnt area using a suite of random forest regression models that included the immediateimpact of climate, vegetation, and human influences in agiven month and tested the impact of various combinationsof antecedent conditions in four productivity-related vegetation indices and in antecedent moisture conditions. Analyses were conducted for the period from 2010 to 2015 inclusive. Inclusion of antecedent vegetation conditions representing fuel build-up led to an improvement of the global,climatological out-of-sample R2from 0.579 to 0.701, but theinclusion of antecedent vegetation conditions on timescales≥ 1 year had no impact on simulated burnt area. Currentmoisture levels were the dominant influence on fuel drying. Additionally, antecedent moisture levels were importantfor fuel build-up. The models also enabled the visualisationof interactions between variables, such as the importanceof antecedent productivity coupled with instantaneous drying. The length of the period which needs to be consideredvaries across biomes; fuel-limited regions are sensitive to antecedent conditions that determine fuel build-up over longertime periods (∼ 4 months), while moisture-limited regionsare more sensitive to current conditions that regulate fuel drying.
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