Satellite Record Research Articles

A productive friction: Leveraging misalignments between local ecological knowledge and remotely sensed imagery for forest conservation planning

AbstractEarth's forests are continually monitored by both the satellite record and the lived experiences of nearly 2 billion forest‐proximate peoples. Generally, the satellite record summarizes production estimates, such as percent tree cover, at regular, relatively coarse scales. Conversely, local perceptions tend to capture changes at irregular and very fine scales. While the utility of both of these sources of information has been widely demonstrated in isolation, little work has explored in what contexts they are expected to correlate or deviate, or how they might be quantitatively integrated. Here, we collect gridded information on community perceived and remotely sensed mangrove cover change across 719 0.5‐km grids in Pemba Island, Tanzania. We reveal variation in the association between these two data sources across different wards (shehia) and explore the reasons for this variation using interviews and direct observation. We find that shehia with the greatest alignment between perceived and remotely sensed mangrove change tended to have little planting or natural regeneration of mangrove propagules and large areas of complete cover loss. Alternatively, in shehia with the lowest alignment, we find high levels of natural and/or human‐assisted mangrove recolonization and selective harvesting of individual trees and branches. These findings indicate that the alignment between local knowledge and satellite observations of mangrove cover change systematically increases with the scale of change in this system. Finally, we demonstrate a practical workflow for quantitatively leveraging these misalignments by optimizing across both data sources to identify restoration priority areas.

Remote Impacts of Cyclonic Eddies on Productivity Around the Main Hawaiian Islands

AbstractThe Hawaiian Island chain lies on the southern limb of the oligotrophic North Pacific Subtropical Gyre, an area characterized by low productivity. In this region, productivity is controlled by several factors, including the island mass effect and mesoscale eddies generated by wind stress curl in the lee of the islands. This study identifies high‐chlorophyll events that occur periodically off the northern coasts of the Main Hawaiian Islands. These events are present in the satellite record and can be reproduced using a regional dynamical model. Model results indicate events are characterized by increases in total phytoplankton and total zooplankton, and a shift in phytoplankton size structure. We show these events are uniquely driven by the presence of cyclonic mesoscale eddies located downstream, on the opposite side of the island chain. While these eddies are known to impact productivity locally, we reveal that nutrients upwelled by these eddies can also be transported around the islands, counter to the mean background flow. These results demonstrate how leeward cyclonic eddies can have far‐reaching, remote impacts on productivity around the Hawaiian Islands.

The Southern Ocean marine ice record of the early historical, circum-Antarctic voyages of Cook and Bellingshausen

Abstract. The circumnavigations of Cook (second voyage, 1772–1775) and Bellingshausen (1819–1821) were attempts to find any great southern land mass poleward of ∼ 50° S and consequently involved sailing for three or two summers, respectively, in polar latitudes around Antarctica. Extensive sea ice eventually blocked each voyage's southern probes, although Bellingshausen, unknowingly at the time, saw the Antarctic continent. However, these attempts meant sea ice and iceberg records from the early historical period were collected nearly simultaneously from around much of Antarctica. Here, these records are extracted from journals, analysed, and compared to each other and the modern satellite record of both forms of marine ice. They generally show an early historical period with a more northerly record of both forms of marine ice than normal for today, but to a geographically varying degree. However, the early historical period in the Pacific sector of the Southern Ocean saw marine ice generally within the range of modern observations for the same time of year, but the Weddell Sea and Indian Ocean marine ice, particularly on Cook's voyage, then extended several degrees further north than in today's extreme ice years.

The Influence of Stratospheric Hydration From the Hunga Eruption on Chemical Processing in the 2023 Antarctic Vortex

AbstractWe use measurements of trace gases from the Microwave Limb Sounder and polar stratospheric clouds (PSCs) from the Cloud‐Aerosol Lidar with Orthogonal Polarization to investigate how the extraordinary stratospheric water vapor enhancement from the 2022 Hunga eruption affected polar processing during the 2023 Antarctic winter. Although the dynamical characteristics of the vortex itself were generally unexceptional, the excess moisture initially raised PSC formation threshold temperatures above typical values. Cold conditions, especially in early July, prompted ice PSC formation and unusually severe irreversible dehydration at higher levels (500–700 K), while atypical hydration occurred at lower levels (380–460 K). Heterogeneous chemical processing was more extensive, both vertically (up to 750–800 K) and temporally (earlier in the season), than in prior Antarctic winters. The resultant HCl depletion and ClO enhancement redefined their previously observed ranges at and above 600 K. Albeit unmatched in the satellite record, the early‐winter upper‐level chlorine activation was insufficient to induce substantial ozone loss. Chlorine activation, denitrification, and dehydration processes ran to completion by July/August, with trace gas evolution mostly following the climatological mean thereafter, but with chlorine deactivation starting slightly later than usual. While cumulative ozone losses at 410–550 K were relatively large, probably because of the delayed chlorine deactivation, they were not unprecedented. Thus, ozone depletion was unremarkable throughout the lower stratosphere. Although Hunga enhanced PSC formation and chemical processing in early winter, saturation of lower stratospheric denitrification, dehydration, and chlorine activation (as is typical in the Antarctic) prevented an exceptionally severe ozone hole in 2023.

Anthropogenic Fingerprint Detectable in Upper Tropospheric Ozone Trends Retrieved from Satellite.

Tropospheric ozone (O3) is a strong greenhouse gas, particularly in the upper troposphere (UT). Limited observations point to a continuous increase in UT O3 in recent decades, but the attribution of UT O3 changes is complicated by large internal climate variability. We show that the anthropogenic signal ("fingerprint") in the patterns of UT O3 increases is distinguishable from the background noise of internal variability. The time-invariant fingerprint of human-caused UT O3 changes is derived from a 16-member initial-condition ensemble performed with a chemistry-climate model (CESM2-WACCM6). The fingerprint is largest between 30°S and 40°N, especially near 30°N. In contrast, the noise pattern in UT O3 is mainly associated with the El Niño-Southern Oscillation (ENSO). The UT O3 fingerprint pattern can be discerned with high confidence within only 13 years of the 2005 start of the OMI/MLS satellite record. Unlike the UT O3 fingerprint, the lower tropospheric (LT) O3 fingerprint varies significantly over time and space in response to large-scale changes in anthropogenic precursor emissions, with the highest signal-to-noise ratios near 40°N in Asia and Europe. Our analysis reveals a significant human effect on Earth's atmospheric chemistry in the UT and indicates promise for identifying fingerprints of specific sources of ozone precursors.

Multi-decadal climate variability and satellite biases have amplified model-observation discrepancies in tropical troposphere warming estimates

Most coupled model simulations substantially overestimate tropical tropospheric warming trends over the satellite era, undermining the reliability of model-projected future climate change. Here we show that the model-observation discrepancy over the satellite era has arisen in large part from multi-decadal climate variability and residual biases in the satellite record. Analyses indicate that although the discrepancy is closely linked to multi-decadal variability in the tropical Pacific sea surface temperatures, the overestimation remains over the satellite era in model simulations forced by observed time-varying sea surface temperatures with a La Niña-like pattern. Regarding moist thermodynamic processes governing tropical tropospheric warming, however, we find a broad model-observation consistency over a post-war period, suggesting that residual biases in the satellite record may contribute to model-observation discrepancy. These results underscore the importance of sustaining an accurate long-term observing system as well as constraining the model representation of tropical Pacific sea surface temperature change and variability.

Sources of low-frequency variability in observed Antarctic sea ice

Abstract. Antarctic sea ice has exhibited significant variability over the satellite record, including a period of prolonged and gradual expansion, as well as a period of sudden decline. A number of mechanisms have been proposed to explain this variability, but how each mechanism manifests spatially and temporally remains poorly understood. Here, we use a statistical method called low-frequency component analysis to analyze the spatiotemporal structure of observed Antarctic sea ice concentration variability. The identified patterns reveal distinct modes of low-frequency sea ice variability. The leading mode, which accounts for the large-scale, gradual expansion of sea ice, is associated with the Interdecadal Pacific Oscillation and resembles the observed sea surface temperature trend pattern that climate models have trouble reproducing. The second mode is associated with the central Pacific El Niño–Southern Oscillation (ENSO) and the Southern Annular Mode and accounts for most of the sea ice variability in the Ross Sea. The third mode is associated with the eastern Pacific ENSO and Amundsen Sea Low and accounts for most of the pan-Antarctic sea ice variability and almost all of the sea ice variability in the Weddell Sea. The third mode is also related to periods of abrupt Antarctic sea ice decline that are associated with a weakening of the circumpolar westerlies, which favors surface warming through a shoaling of the ocean mixed layer and decreased northward Ekman heat transport. Broadly, these results suggest that climate model biases in long-term Antarctic sea ice and large-scale sea surface temperature trends are related to each other and that eastern Pacific ENSO variability is a key ingredient for abrupt Antarctic sea ice changes.

Using telemetry data and the sea ice satellite record to identify vulnerabilities in critical moult habitat for emperor penguins in West Antarctica

AbstractWe tracked adult emperor penguins from Rothschild Island, west Antarctic Peninsula in 2015/2016 during a summer with extensive sea ice of long duration, contrasting with past years of reduced sea ice extent associated with the recent, rapid, warming trend across the region. We fitted ARGOS PTT devices to penguins of unknown breeding status. Of 33 penguins tracked, nine returned to the colony, presumably to provision offspring. Their foraging trips lasted 9.6 ± 3.7 days, with maximum distances of 75 ± 45 km from the colony within coastal waters. Also, 18 instruments transmitted until the initiation of the annual moult. Penguins travelled at ~ 2.3 km h−1 before slowing for moult. Post-moult, some devices continued to transmit, with speeds of ~ 0.8 km h−1, plausibly due to ice drift, which is rapid in this region. Penguins remained within the seasonal sea ice throughout, staying within 100 km of land, and generally within 5 to 10 km of features (open water, polynyas, leads, icebergs) that offered potential access to the ocean. Penguins were unlikely to have been constrained by the extensive sea ice habitat in 2015/2016. Similar habitats would also have been available in most years of the satellite record (since 1979); however, the moult locations in 2015/2016 would not have been available in many years, and penguins would have needed to find alternative moult locations during some years. Despite uncertainties, the moult period is a critical time for emperor penguins, particularly as sea ice declines, potentially affecting adult survival.

Identifying episodic carbon monoxide emission events in the MOPITT measurement dataset

Abstract. The Measurements Of Pollution In The Troposphere (MOPITT) instrument aboard NASA's Terra satellite has been measuring upwelling radiance in a nadir-viewing mode since March 2000. These radiance measurements are inverted to yield estimates of carbon monoxide (CO) profiles and total columns, providing the longest satellite record of this trace gas to date. The CO measurements from MOPITT have been used in a variety of ways, including trend analyses and the construction of CO budgets. However, their use is complicated by the influence of episodic emission events, which release large quantities of CO into the atmosphere with irregular timing, such as large sporadic wildfires of natural or anthropogenic origin. The chaotic nature of these events is a large source of variability in CO budgets and models, requiring that these events be well characterized in order to develop an improved understanding of the role they have in influencing tropospheric CO. This study describes the development of a multistep algorithm that is used to identify large episodic emission events using daily mean Level 2 (L2) MOPITT total column measurements gridded to a 0.5 by 0.5° spatial resolution. The core component of this procedure involves empirically determining the expectation density function (EDF) that describes the departure of daily-mean CO observations from the baseline behaviour of CO, as described by its periodic components and trends. The EDFs employed are not assumed to be symmetric but instead are constructed from a pair of superimposed normal distributions. Enhancement flag files are produced following this methodology, identifying the episodic events that show strong enhancement of CO outside of the range of expected CO behaviour and are now made available for the period 3 March 2000 to 31 July 2022. The distribution and frequency of these flagged measurements over this 22-year period are analyzed in order to illustrate the robustness of this method.

Characterization of Change in Tree Cover State and Condition over the Conterminous United States

Variability in the effects of disturbances and extreme climate events can lead to changes in tree cover over time, including partial or complete loss, with diverse ecological consequences. It is therefore critical to identify in space and time the change processes that lead to tree cover change. Studies of change are often hampered by the lack of data capable of consistently detecting different types of change. Using the Landsat satellite record to create a long time-series of land cover and land cover change, the U.S. Geological Survey Land Change Monitoring Assessment and Projection (LCMAP) project has made an annual time series of land cover across the conterminous United States for the period 1985 to 2018. Multiple LCMAP products analyzed together with map validation reference plots provide a robust basis for understanding tree cover change. In LCMAP (Collection 1.2), annual change detection is based on harmonic model breaks calculated at each Landsat pixel from the Continuous Change Detection and Classification (CCDC) algorithm. The results showed that the majority of CCDC harmonic model breaks (signifying change) indicated partial tree cover loss (associated with management practices such as tree cover thinning) as compared to complete tree cover loss (associated with practices like clearcut harvest or fire disturbance). Substantially fewer occurrences of complete tree cover loss were associated with change in land cover state. The area of annual tree cover change increased after the late 1990s and stayed high for the rest of the study period. The reference data showed that tree harvest dominated across the conterminous United States. The majority of tree cover change occurred in evergreen forests. Large estimates of disturbance-related tree cover change indicated that tree cover loss may have previously been underreported due to omission of partial tree cover loss in prior studies. This has considerable implications for forest carbon accounting along with tracking ecosystem goods and services.

Two decades of fire activity over the PEEX domain: a look from space, with contribution from models and ground-based measurements

ABSTRACT It has been suggested that forest fires will become more frequent/intense with changing climate, which would increase aerosol/gas emissions into the atmosphere. A better understanding of the relations between meteorological conditions, fires, and fire emissions will help estimate the climate response via forest fires. In this study, we use ERA5 meteorological products, including temperature, precipitation, and soil moisture, to explain the frequency of forest fires and the amount of radiant energy released per time unit by burning vegetation (fire radiative power, FRP). We explore the relationships between satellite-retrieved fire products and aerosol properties (aerosol optical depth, AOD), carbon monoxide (CO), formaldehyde (HCHO), and nitrogen dioxide (NO2) concentrations over the PEEX domain, which covers different vegetation zones (e.g. croplands/grasslands, forest, arctic tundra) of Pan-Eurasia and China. We analyse the concentrations of black carbon and absorbing organic carbon using ground-based AErosol RObotic NETwork. The analysis covers the months of May to August from 2002 to 2022. We show positive temperature trends in the Northern zone (>65°N) in June and August (1.56°C and 0.64°C, respectively); all statistically significant trends for precipitation and soil moisture are negative. This can explain increased fire activity in Siberia over the recent years (2019–2022). Over the whole PEEX domain, FC and FRP trends remain insignificant or negative; a decrease in AOD may address those negative trends. We show that intra-summer variations exist for cropland/grassland fires, which occur most often in May and August, while Siberian forest fires occur more often in July and August. We show that CO concentration has been gradually decreasing in the last two decades in May and June. CO trends are negative in May, June, and over summer for all regions, in July in Europe, China, the Southern zone (<55°N), and the PEEX domain. HCHO trends are not significant in all regions. NO2 trends are positive in May and negative in June in all zones. We calculated total column enhancement ratios for satellite observations influenced by wildfires. A common feature has been recognized with measurements and ratios utilized in SILAM (System for Integrated Modelling of Atmospheric Composition): AOD(or PM):CO and AOD(or PM):HCHO ratios for grass are clearly lower than for shrubs, opposite for AOD:NO2. We showed that emission ratios are increasing towards South and are 2–3 times higher for high (>0.5) AOD. Using a 21-year satellite record of the AOD and CO, an 18-year record of NO2, and a 16-year record of HCHO, we created background products of those variables over the PEEX domain. In the regions with low anthropogenic activity and conditions where long-range transport is not happening, anomalies in AOD, CO, and HCHO over biomass-burning areas may be assigned directly to the wildfire emissions.

Patterns in the temporal complexity of global chlorophyll concentration

Decades of research have relied on satellite-based estimates of chlorophyll-a concentration to identify oceanographic processes and plan in situ observational campaigns; however, the patterns of intrinsic temporal variation in chlorophyll-a concentration have not been investigated on a global scale. Here we develop a metric to quantify time series complexity (i.e., a measure of the ups and downs of sequential observations) in chlorophyll-a concentration and show that seemingly disparate regions (e.g., Atlantic vs Indian, equatorial vs subtropical) in the global ocean can be inherently similar. These patterns can be linked to the regularity of chlorophyll-a concentration change and the likelihood of anomalous events within the satellite record. Despite distinct spatial changes in decadal chlorophyll-a concentration, changes in time series complexity have been relatively consistent. This work provides different metrics for monitoring the global ocean and suggests that the complexity of chlorophyll-a time series can be independent of its magnitude.

The utility of simulated ocean chlorophyll observations: a case study with the Chlorophyll Observation Simulator Package (version 1) in CESMv2.2

Abstract. For several decades, a suite of satellite sensors has enabled us to study the global spatiotemporal distribution of phytoplankton through remote sensing of chlorophyll. However, the satellite record has extensive missing data, partially due to cloud cover; regions characterized by the highest phytoplankton abundance are also some of the cloudiest. To quantify potential sampling biases due to missing data, we developed a satellite simulator for ocean chlorophyll in the Community Earth System Model (CESM) that mimics what a satellite would detect if it were present in the model-generated world. Our Chlorophyll Observation Simulator Package (ChlOSP) generates synthetic chlorophyll observations at model runtime. ChlOSP accounts for missing data – due to low light, sea ice, and cloud cover – and it can implement swath sampling. Here, we introduce this new tool and present a preliminary study focusing on long timescales. Results from a 50-year pre-industrial control simulation of CESM–ChlOSP suggest that missing data impact the apparent mean state and variability of chlorophyll. The simulated observations exhibit a nearly −20 % difference in global mean chlorophyll compared with the standard model output, which is the same order of magnitude as the projected change in chlorophyll by the end of the century. Additionally, missing data impact the apparent seasonal cycle of chlorophyll in subpolar regions. We highlight four potential future applications of ChlOSP: (1) refined model tuning; (2) evaluating chlorophyll-based net primary productivity (NPP) algorithms; (3) revised time to emergence of anthropogenic chlorophyll trends; and (4) a test bed for the assessment of gap-filling approaches for missing satellite chlorophyll data.

2023's Antarctic sea ice extent is the lowest on record

AbstractAntarctic sea ice is a vitally important part of the regional and global climate. In 2023, sea ice extent fell to record lows, reaching unprecedented values for both the summer minimum, winter maximum and intervening freeze‐up period. Here, we show that the extreme values observed were truly remarkable within the context of the satellite record, despite the challenge of quantifying how rare such an event might be, and discuss some contributing factors. While this could be part of a decline in sea ice associated with human‐caused climate change, it is too early to say conclusively if this is the case.

Global Snow Seasonality Regimes from Satellite Records of Snow Cover

Abstract Snow cover provides distinct seasonal controls on the exchange of energy between Earth’s surface and atmosphere, and on hydrologic cycling, and holds considerable importance to communities and ecosystems worldwide. In this work, we tackle a comprehensive review of existing snow classification approaches and the development of new globally applicable snow cover–based rules for delineating snow seasonality classes. Snow classification rules are defined using machine learning approaches, which are then applied to the 22-yr record of snow cover (2000–22) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on a 0.01° global grid. For the MODIS period of record, we find the global land surface can be effectively partitioned into five snow seasonality classes: no snow, ephemeral, transitional, seasonal, and perennial snow regimes which on average cover extents of approximately 76 (52% of global land areas), 19 (13%), 16 (11%), 18 (13%), and 16 million km2 (11%), respectively. Using the multidecadal dataset, we explore changes within snow regimes and find significant increases in the areal extent of no snow (approximately +70 000 km2 yr−1) as well as apparent losses in perennial (−3600 km2 yr−1) and seasonal snow regime coverage (−38 000 km2 yr−1). The resulting classification maps have strong agreement with in situ snow depth observations and present similar patterns to existing snow and climate classifications with notable discrepancies in cold arid regions. The framework’s ability to accurately capture variations in snow persistence, snow accumulation, and melt cycling is shown, providing a reference to the current state of global snow seasonality. Significance Statement Following a review of existing snow classification approaches, this study focuses on improving our understanding of snow-cover variability on Earth by using satellite-based observations of snow-covered area to derive a new snow classification. Satellite observations provide the best means of measuring snow cover at a global scale, helping to identify regions where its influence on energy, water, and climate is changing. The results are compared to existing climate and snow summaries, ground observations of snow depth, and include trends in snow cover over recent decades (2000–22). The resulting datasets are also made available to the broader scientific community.

Greenhouse Gas Forcing and Climate Feedback Signatures Identified in Hyperspectral Infrared Satellite Observations

AbstractGlobal greenhouse gas forcing and feedbacks are the primary causes of climate change but have limited direct observations. Here we show that continuous, stable, global, hyperspectral infrared satellite measurements (2003–2021) display decreases in outgoing longwave radiation (OLR) in the CO2, CH4, and N2O absorption bands and increases in OLR in the window band and H2O absorption bands. By conducting global line‐by‐line radiative transfer simulations with 2003–2021 meteorological conditions, we show that increases in CO2, CH4, and N2O concentrations caused an instantaneous radiative forcing and stratospheric cooling adjustment that decreased OLR. The climate response, comprising surface and atmospheric feedbacks to radiative forcings and unforced variability, increased OLR. The spectral trends predicted by our climate change experiments using our general circulation model identify three bedrock principles of the physics of climate change in the satellite record: an increasing greenhouse effect, stratospheric cooling, and surface‐tropospheric warming.

Causal attribution of agricultural expansion in a small island system using approximate Bayesian computation

The extent and arrangement of land cover types on our planet directly affects biodiversity, carbon storage, water quality, and many other critical social and ecological conditions at virtually all scales. Given the fundamental importance of land cover, a key mandate for land system scientists is to describe the mechanisms by which pertinent cover types spread and shrink. Identifying causal drivers of change is challenging however, because land systems, such as small-scale agricultural communities, do not lend themselves well to controlled experimentation for logistical and ethical reasons. Even natural experiments in these systems can produce only limited causal inference as they often contain unobserved confounding drivers of land cover change and complex feedbacks between drivers and outcomes. Land system scientists commonly grapple with this complexity by using computer simulations to explicitly delineate hypothesized causal pathways that could have resulted in observed land cover change. Yet, land system science lacks a systematic method for comparing multiple hypothesized pathways and quantifying the probability that a given simulated causal process was in fact responsible for the patterns observed. Here we use a case study of agricultural expansion in Pemba, Tanzania to demonstrate how approximate Bayesian computation (ABC) provides a straightforward solution to this methodological gap. Specifically, we pair an individual-based simulation of land cover change in Pemba with ABC to probabilistically estimate the likelihood that observed deforestation from 2018 to 2021 was driven by soil degradation rather than external market forces. Using this approach, we can show not only how well a specific hypothesized mechanism fits with empirical data on land cover change, but we can also quantify the range of other mechanisms that could have reasonably produced the same outcome (i.e. equifinality). While ABC was developed for use in population genetics, we argue that it is particularly promising as a tool for causal inference for land system science given the wealth of data available in the satellite record. Thus, this paper demonstrates a robust process for identifying the emergent landscape-level signatures of complex social-ecological mechanisms.

Distinguishing Electromagnetic Ion Cyclotron (EMIC) Waves From Other Pc1 Signatures in Satellite Recordings by Means of the Swarm Satellite Constellation

AbstractIn this study we make use of the closely spaced Swarm A and C spacecraft to determine the main wave parameters of micro‐pulsation in the Pc1 range. Generally, the interpretation of wave events in satellite recordings suffers from the spatial/temporal ambiguity of such data. To resolve that problem, we use for the first time in the 0.2–5 Hz apparent frequency range high‐resolution magnetic field data from the Swarm A/C spacecraft pair. Particularly suitable for this analysis is the period of Counter Rotating Orbit Phase in 2021. During that period the along‐track distance between the spacecraft was varied from 2 to 40 s. Surprisingly many of the wavy signals at middle latitudes were identified as small‐scale (order of 10s km) quasi‐static field‐aligned current (FAC) structures. Some of the events turned out to be medium‐scale (100–200 km) waves oscillating at 1 Hz or less. A number of published electromagnetic ion cyclotron (EMIC) waves were checked on their consistency. One characteristic is their long wavelength (∼1,000 km). About half of the cases passed the check, the other did not satisfy the spatial homogeneity. The small‐scale FAC structures we believe to be driven by atmospheric gravity waves. While the medium‐scale waves we prefer to relate to the effects of the ionospheric Alfvén resonator.

Forced and internal components of observed Arctic sea-ice changes

Abstract. The Arctic sea-ice cover is strongly influenced by internal variability on decadal timescales, affecting both short-term trends and the timing of the first ice-free summer. Several mechanisms of variability have been proposed, but how these mechanisms manifest both spatially and temporally remains unclear. The relative contribution of internal variability to observed Arctic sea-ice changes also remains poorly quantified. Here, we use a novel technique called low-frequency component analysis to identify the dominant patterns of winter and summer decadal Arctic sea-ice variability in the satellite record. The identified patterns account for most of the observed regional sea-ice variability and trends, and they thus help to disentangle the role of forced and internal sea-ice changes over the satellite record. In particular, we identify a mode of decadal ocean–atmosphere–sea-ice variability, characterized by an anomalous atmospheric circulation over the central Arctic, that accounts for approximately 30 % of the accelerated decline in pan-Arctic summer sea-ice area between 2000 and 2012 but accounts for at most 10 % of the decline since 1979. For winter sea ice, we find that internal variability has dominated decadal trends in the Bering Sea but has contributed less to trends in the Barents and Kara seas. These results, which detail the first purely observation-based estimate of the contribution of internal variability to Arctic sea-ice trends, suggest a lower estimate of the contribution from internal variability than most model-based assessments.

Inland thinning of Byrd Glacier, Antarctica, during Ross Ice Shelf formation

AbstractGeomorphological records of past ice sheet change offer the opportunity to examine their centennial‐scale response to changing boundary conditions, which are not adequately captured in the satellite record. Here, we present the first reconstruction of ice surface lowering at Byrd Glacier, the largest outlet glacier of the Transantarctic Mountains. Using surface exposure ages from glacial erratic cobbles collected in two vertical transects along the Lonewolf Nunataks, we find the initial emergence of this set of nunataks occurred at ~15 ka, with a rapid pulse of thinning at ~8 ka. We compare our glacier thinning profiles with modelled ice sheet thickness and grounding line histories from two model ensembles to identify key processes responsible for ice sheet change. All model runs from the two ensembles predict grounding line retreat and inland thinning to occur in one rapid step from Last Glacial Maximum to present, in line with marine geology records, our exposure age data and derived glacier thinning rates. Experiments best matching the glacial thickness constraints, reconstructed from the surface exposure data, have faster basal sliding (i.e., promote greater sliding rates resulting in thinner ice). However, experiments best matching the timing and rapid rate of ice thinning derived from the same surface exposure data have higher basal friction. This apparent change in the modelled basal sliding regime, from when the ice surface is at maximum thickness, to the rapid thinning at ~8 ka, occurs as the grounding line retreats towards the Byrd Glacier and Ross Ice Shelf forms during the Holocene. This past context has implications for the stability of the modern grounding line of Byrd Glacier, which is characterised by high basal melt rates at the terminus—a process that has the potential to propagate glacier thinning far inland, impacting the overall (in)stability of the Byrd Glacier and Ross Ice Shelf.