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Large meteors (or superbolides [Ceplecha Z, et al. (1999) Meteoroids 1998 :37–54]), although rare in recorded history, give sobering testimony to civilization’s inherent vulnerability. A not-so-subtle reminder came on the morning of February 15, 2013, when a large meteoroid hurtled into the Earth’s atmosphere, forming a superbolide near the city of Chelyabinsnk, Russia, ∼1,500 km east of Moscow, Russia [Ivanova MA, et al. (2013) Abstracts of the 76th Annual Meeting of the Meteoritical Society, 5366]. The object exploded in the stratosphere, and the ensuing shock wave blasted the city of Chelyabinsk, damaging structures and injuring hundreds. Details of trajectory are important for determining its specific source, the likelihood of future events, and potential mitigation measures. Earth-viewing environmental satellites can assist in these assessments. Here we examine satellite observations of the Chelyabinsk superbolide debris trail, collected within minutes of its entry. Estimates of trajectory are derived from differential views of the significantly parallax-displaced [e.g., Hasler AF (1981) Bull Am Meteor Soc 52:194–212] debris trail. The 282.7 ± 2.3° azimuth of trajectory, 18.5 ± 3.8° slope to the horizontal, and 17.7 ± 0.5 km/s velocity derived from these satellites agree well with parameters inferred from the wealth of surface-based photographs and amateur videos. More importantly, the results demonstrate the general ability of Earth-viewing satellites to provide valuable insight on trajectory reconstruction in the more likely scenario of sparse or nonexistent surface observations.

Fluctuations in environmental parameters are increasingly being recognized as essential features of any habitat. The quantification of whether environmental fluctuations are prevalently predictable or unpredictable is remarkably relevant to understanding the evolutionary responses of organisms. However, when characterizing the relevant features of natural habitats, ecologists typically face two problems: (1) gathering long-term data and (2) handling the hard-won data. This paper takes advantage of the free access to long-term recordings of remote sensing data (27 years, Landsat TM/ETM+) to assess a set of environmental models for estimating environmental predictability. The case study included 20 Mediterranean saline ponds and lakes, and the focal variable was the water-surface area. This study first aimed to produce a method for accurately estimating the water-surface area from satellite images. Saline ponds can develop salt-crusted areas that make it difficult to distinguish between soil and water. This challenge was addressed using a novel pipeline that combines band ratio water indices and the short near-infrared band as a salt filter. The study then extracted the predictable and unpredictable components of variation in the water-surface area. Two different approaches, each showing variations in the parameters, were used to obtain the stochastic variation around a regular pattern with the objective of dissecting the effect of assumptions on predictability estimations. The first approach, which is based on Colwell's predictability metrics, transforms the focal variable into a nominal one. The resulting discrete categories define the relevant variations in the water-surface area. In the second approach, we introduced General Additive Model (GAM) fitting as a new metric for quantifying predictability. Both approaches produced a wide range of predictability for the studied ponds. Some model assumptions-which are considered very different a priori-had minor effects, whereas others produced predictability estimations that showed some degree of divergence. We hypothesize that these diverging estimations of predictability reflect the effect of fluctuations on different types of organisms. The fluctuation analysis described in this manuscript is applicable to a wide variety of systems, including both aquatic and non-aquatic systems, and will be valuable for quantifying and characterizing predictability, which is essential within the expected global increase in the unpredictability of environmental fluctuations. We advocate that a priori information for organisms of interest should be used to select the most suitable metrics for estimating predictability, and we provide some guidelines for this approach.

The Reference Elevation Model of Antarctica (REMA) is the first continental-scale digital elevation model (DEM) at a resolution of less than 10 m. REMA is created from stereophotogrammetry with submeter resolution optical, commercial satellite imagery. The higher spatial and radiometric resolutions of this imagery enable high-quality surface extraction over the low-contrast ice sheet surface. The DEMs are registered to satellite radar and laser altimetry and are mosaicked to provide a continuous surface covering nearly 95 % the entire continent. The mosaic includes an error estimate and a time stamp, enabling change measurement. Typical elevation errors are less than 1 m, as validated by the comparison to airborne laser altimetry. REMA provides a powerful new resource for Antarctic science and provides a proof of concept for generating accurate high-resolution repeat topography at continental scales.

Glaciers distinct from the Greenland and Antarctic ice sheets are shrinking rapidly, altering regional hydrology 1 , raising global sea level 2 and elevating natural hazards 3 . Yet, owing to the scarcity of constrained mass loss observations, glacier evolution during the satellite era is known only partially, as a geographic and temporal patchwork 4 , 5 . Here we reveal the accelerated, albeit contrasting, patterns of glacier mass loss during the early twenty-first century. Using largely untapped satellite archives, we chart surface elevation changes at a high spatiotemporal resolution over all of Earth’s glaciers. We extensively validate our estimates against independent, high-precision measurements and present a globally complete and consistent estimate of glacier mass change. We show that during 2000–2019, glaciers lost a mass of 267 ± 16 gigatonnes per year, equivalent to 21 ± 3 per cent of the observed sea-level rise 6 . We identify a mass loss acceleration of 48 ± 16 gigatonnes per year per decade, explaining 6 to 19 per cent of the observed acceleration of sea-level rise. Particularly, thinning rates of glaciers outside ice sheet peripheries doubled over the past two decades. Glaciers currently lose more mass, and at similar or larger acceleration rates, than the Greenland or Antarctic ice sheets taken separately 7 – 9 . By uncovering the patterns of mass change in many regions, we find contrasting glacier fluctuations that agree with the decadal variability in precipitation and temperature. These include a North Atlantic anomaly of decelerated mass loss, a strongly accelerated loss from northwestern American glaciers, and the apparent end of the Karakoram anomaly of mass gain 10 . We anticipate our highly resolved estimates to advance the understanding of drivers that govern the distribution of glacier change, and to extend our capabilities of predicting these changes at all scales. Predictions robustly benchmarked against observations are critically needed to design adaptive policies for the local- and regional-scale management of water resources and cryospheric risks, as well as for the global-scale mitigation of sea-level rise. Analysis of satellite stereo imagery uncovers two decades of mass change for all of Earth’s glaciers, revealing accelerated glacier shrinkage and regionally contrasting changes consistent with decadal climate variability.

Ocean-driven basal melting of Antarctica’s floating ice shelves accounts for about half of their mass loss in steady state, where gains in ice-shelf mass are balanced by losses. Ice-shelf thickness changes driven by varying basal melt rates modulate mass loss from the grounded ice sheet and its contribution to sea level, and the changing meltwater fluxes influence climate processes in the Southern Ocean. Existing continent-wide melt-rate datasets have no temporal variability, introducing uncertainties in sea level and climate projections. Here, we combine surface height data from satellite radar altimeters with satellite-derived ice velocities and a new model of firn-layer evolution to generate a high-resolution map of time-averaged (2010–2018) basal melt rates and time series (1994–2018) of meltwater fluxes for most ice shelves. Total basal meltwater flux in 1994 (1,090 ± 150 Gt yr–1) was similar to the steady-state value (1,100 ± 60 Gt yr–1), but increased to 1,570 ± 140 Gt yr–1 in 2009, followed by a decline to 1,160 ± 150 Gt yr–1 in 2018. For the four largest ‘cold-water’ ice shelves, we partition meltwater fluxes into deep and shallow sources to reveal distinct signatures of temporal variability, providing insights into climate forcing of basal melting and the impact of this melting on the Southern Ocean.Meltwater entering the Southern Ocean from Antarctic ice shelves varies substantially from year to year, with consequences for Southern Ocean circulation and climate, according to remote sensing estimates of ice-shelf basal melting rates.

Astronomers have discovered thousands of planets outside the Solar System 1 , most of which orbit stars that will eventually evolve into red giants and then into white dwarfs. During the red giant phase, any close-orbiting planets will be engulfed by the star 2 , but more distant planets can survive this phase and remain in orbit around the white dwarf 3 , 4 . Some white dwarfs show evidence for rocky material floating in their atmospheres 5 , in warm debris disks 6 – 9 or orbiting very closely 10 – 12 , which has been interpreted as the debris of rocky planets that were scattered inwards and tidally disrupted 13 . Recently, the discovery of a gaseous debris disk with a composition similar to that of ice giant planets 14 demonstrated that massive planets might also find their way into tight orbits around white dwarfs, but it is unclear whether these planets can survive the journey. So far, no intact planets have been detected in close orbits around white dwarfs. Here we report the observation of a giant planet candidate transiting the white dwarf WD 1856+534 (TIC 267574918) every 1.4 days. We observed and modelled the periodic dimming of the white dwarf caused by the planet candidate passing in front of the star in its orbit. The planet candidate is roughly the same size as Jupiter and is no more than 14 times as massive (with 95 per cent confidence). Other cases of white dwarfs with close brown dwarf or stellar companions are explained as the consequence of common-envelope evolution, wherein the original orbit is enveloped during the red giant phase and shrinks owing to friction. In this case, however, the long orbital period (compared with other white dwarfs with close brown dwarf or stellar companions) and low mass of the planet candidate make common-envelope evolution less likely. Instead, our findings for the WD 1856+534 system indicate that giant planets can be scattered into tight orbits without being tidally disrupted, motivating the search for smaller transiting planets around white dwarfs. A giant planet candidate roughly the size of Jupiter but more than 14 times as massive is observed by TESS and other instruments to be transiting the white dwarf star WD 1856+534.

The Pope, Smith, and Kohler glaciers, in the Amundsen Sea Embayment of West Antarctica, have experienced enhanced ocean-induced ice-shelf melt, glacier acceleration, ice thinning, and grounding line retreat in the past thirty years. Here we present observations of the grounding line retreat of these glaciers since 2014 using a constellation of interferometric radar satellites combined with precision surface elevation data. We find that the grounding lines develop spatially-variable, kilometre-scale, tidally-induced migration zones. After correction for tidal effects, we detect a sustained pattern of retreat coincident with high melt rates of un-grounded ice, marked by episodes of more rapid retreat. In 2017, Pope Glacier retreated 3.5 km in 3.6 months, or 11.7 km/yr. In 2016-2018, Smith West retreated at 2 km/yr and Kohler at 1.3 km/yr. While the retreat slowed down in 2018-2020, these retreat rates are faster than anticipated by numerical models on yearly time scales. We hypothesize that the rapid retreat is caused by un-represented, vigorous ice-ocean interactions acting within newly-formed cavities at the ice-ocean boundary.

Time-variable gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions have opened up a new avenue of opportunities for studying large-scale mass redistribution and transport in the Earth system. Over the past 19 years, GRACE/GRACE-FO time-variable gravity measurements have been widely used to study mass variations in different components of the Earth system, including the hydrosphere, ocean, cryosphere, and solid Earth, and significantly improved our understanding of long-term variability of the climate system. We carry out a comprehensive review of GRACE/GRACE-FO satellite gravimetry, time-variable gravity fields, data processing methods, and major applications in several different fields, including terrestrial water storage change, global ocean mass variation, ice sheets and glaciers mass balance, and deformation of the solid Earth. We discuss in detail several major challenges we need to face when using GRACE/GRACE-FO time-variable gravity measurements to study mass changes, and how we should address them. We also discuss the potential of satellite gravimetry in detecting gravitational changes that are believed to originate from the deep Earth. The extended record of GRACE/GRACE-FO gravity series, with expected continuous improvements in the coming years, will lead to a broader range of applications and improve our understanding of both climate change and the Earth system.

Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties-sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen-in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models-multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)-were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources.

We present the CHAOS-7 model of the time-dependent near-Earth geomagnetic field between 1999 and 2020 based on magnetic field observations collected by the low-Earth orbit satellites Swarm, CryoSat-2, CHAMP, SAC-C and Ørsted, and on annual differences of monthly means of ground observatory measurements. The CHAOS-7 model consists of a time-dependent internal field up to spherical harmonic degree 20, a static internal field which merges to the LCS-1 lithospheric field model above degree 25, a model of the magnetospheric field and its induced counterpart, estimates of Euler angles describing the alignment of satellite vector magnetometers, and magnetometer calibration parameters for CryoSat-2. Only data from dark regions satisfying strict geomagnetic quiet-time criteria (including conditions on IMF Bz and By at all latitudes) were used in the field estimation. Model parameters were estimated using an iteratively reweighted regularized least-squares procedure; regularization of the time-dependent internal field was relaxed at high spherical harmonic degree compared with previous versions of the CHAOS model. We use CHAOS-7 to investigate recent changes in the geomagnetic field, studying the evolution of the South Atlantic weak field anomaly and rapid field changes in the Pacific region since 2014. At Earth’s surface a secondary minimum of the South Atlantic Anomaly is now evident to the south west of Africa. Green’s functions relating the core–mantle boundary radial field to the surface intensity show this feature is connected with the movement and evolution of a reversed flux feature under South Africa. The continuing growth in size and weakening of the main anomaly is linked to the westward motion and gathering of reversed flux under South America. In the Pacific region at Earth’s surface between 2015 and 2018 a sign change has occurred in the second time derivative (acceleration) of the radial component of the field. This acceleration change took the form of a localized, east–west oriented, dipole. It was clearly recorded on ground, for example at the magnetic observatory at Honolulu, and was seen in Swarm observations over an extended region in the central and western Pacific. Downward continuing to the core–mantle boundary, we find this event originated in field acceleration changes at low latitudes beneath the central and western Pacific in 2017.