The 50 most-cited articles in Geophysical Research Letters, 2020

Abstract Equilibrium climate sensitivity, the global surface temperature response to CO doubling, has been persistently uncertain. Recent consensus places it likely within 1.5–4.5 K. Global climate models (GCMs), which attempt to represent all relevant physical processes, provide the most direct means of estimating climate sensitivity via CO quadrupling experiments. Here we show that the closely related effective climate sensitivity has increased substantially in Coupled Model Intercomparison Project phase 6 (CMIP6), with values spanning 1.8–5.6 K across 27 GCMs and exceeding 4.5 K in 10 of them. This (statistically insignificant) increase is primarily due to stronger positive cloud feedbacks from decreasing extratropical low cloud coverage and albedo. Both of these are tied to the physical representation of clouds which in CMIP6 models lead to weaker responses of extratropical low cloud cover and water content to unforced variations in surface temperature. Establishing the plausibility of these higher sensitivity models is imperative given their implied societal ramifications.

Abstract Since June, 2018, the Gravity Recovery and Climate Experiment Follow‐On (GRACE‐FO) is extending the 15‐year monthly mass change record of the GRACE mission, which ended in June 2017. The GRACE‐FO instrument and flight system performance has improved over GRACE. Better attitude solutions and enhanced pointing performance result in reduced fuel consumption and gravity range rate post‐fit residuals. One accelerometer requires additional calibrations due to unexpected measurement noise. The GRACE‐FO gravity and mass change fields from June 2018 through December 2019 continue the GRACE record at an equivalent precision and spatiotemporal sampling. During this period, GRACE‐FO observed large interannual terrestrial water variations associated with excess rainfall (Central US, Middle East), drought (Europe, Australia), and ice melt (Greenland). These observations are consistent with independent mass change estimates, providing high confidence that no intermission biases exist from GRACE to GRACE‐FO, despite the 11‐month gap. GRACE‐FO has also successfully demonstrated…

Abstract Spaceborne NO 2 column observations from two high‐resolution instruments, Tropospheric Monitoring Instrument (TROPOMI) on board Sentinel‐5 Precursor and Ozone Monitoring Instrument (OMI) on Aura, reveal unprecedented NO 2 decreases over China, South Korea, western Europe, and the United States as a result of public health measures enforced to contain the coronavirus disease outbreak (Covid‐19) in January–April 2020. The average NO 2 column drop over all Chinese cities amounts to −40% relative to the same period in 2019 and reaches up to a factor of ~2 at heavily hit cities, for example, Wuhan, Jinan, while the decreases in western Europe and the United States are also significant (−20% to −38%). In contrast with this, although Iran is also strongly affected by the disease, the observations do not show evidence of lower emissions, reflecting more limited health measures.

Abstract We examine CMIP6 simulations of Arctic sea‐ice area and volume. We find that CMIP6 models produce a wide spread of mean Arctic sea‐ice area, capturing the observational estimate within the multimodel ensemble spread. The CMIP6 multimodel ensemble mean provides a more realistic estimate of the sensitivity of September Arctic sea‐ice area to a given amount of anthropogenic CO 2 emissions and to a given amount of global warming, compared with earlier CMIP experiments. Still, most CMIP6 models fail to simulate at the same time a plausible evolution of sea‐ice area and of global mean surface temperature. In the vast majority of the available CMIP6 simulations, the Arctic Ocean becomes practically sea‐ice free (sea‐ice area <1 × 10 6 km 2 ) in September for the first time before the Year 2050 in each of the four emission scenarios SSP1‐1.9, SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5 examined here.

Abstract Increases in burned area across the western United States (US) since the mid‐1980s have been widely documented and linked partially to climate factors, yet evaluations of trends in fire severity are lacking. Here we evaluate fire severity trends and their interannual relationships to climate for western US forests from 1985 to 2017. Significant increases in annual area burned at high severity (AAB hs ) were observed across most ecoregions, with an overall eightfold increase in AAB hs across western US forests. The relationships we identified between the annual fire severity metrics and climate, as well as the observed and projected trend toward warmer and drier fire seasons, suggest that climate change will contribute to increased fire severity in future decades where fuels remain abundant. The growing prevalence of high‐severity fire in western US forests has important implications to forest ecosystems, including an increased probability of fire‐catalyzed conversions from forest to alternative vegetation types.

Abstract Quantifying how climate change drives drought is a priority to inform policy and adaptation planning. We show that the latest Coupled Model Intercomparison Project (CMIP6) simulations project coherent regional patterns in meteorological drought for two emissions scenarios to 2100. We find robust projected changes in seasonal drought duration and frequency (robust over >45% of the global land area), despite a lack of agreement across models in projected changes in mean precipitation (24% of the land area). Future drought changes are larger and more consistent in CMIP6 compared to CMIP5. We find regionalized increases and decreases in drought duration and frequency that are driven by changes in both precipitation mean and variability. Conversely, drought intensity increases over most regions but is not simulated well historically by the climate models. The more robust projections of meteorological drought compared to mean precipitation in CMIP6 provides significant new opportunities for water resource planning.

Abstract During the COVID‐19 outbreak that took place in early 2020, the economic activities in China were drastically reduced and accompanied by a strong reduction in the emission of primary air pollutants. On the basis of measurements made at the monitoring stations operated by the China National Environmental Monitoring Center, we quantify the reduction in surface PM 2.5 , NO 2 , CO, and SO 2 concentrations in northern China during the lockdown, which started on 23 January 2020. We find that, on the average, the levels of surface PM 2.5 and NO 2 have decreased by approximately 35% and 60%, respectively, between the period 1 and 22 January 2020 and the period 23 January and 29 February 2020. At the same time, the mean ozone concentration has increased by a factor 1.5–2. In urban area of Wuhan, where drastic measures were adopted to limit the spread of the coronavirus, similar changes in the concentrations of PM 2.5 , NO 2 , and ozone are found.

Abstract Compound drought and heatwaves can cause significant damage to the environment, economy, and society. In this study, we quantify the spatio‐temporal changes in compound drought and heatwave (CDHW) events by integrating weekly self‐calibrated Palmer Drought Severity Index (sc_PDSI) and daily maximum temperatures during the period 1983 to 2016. Multiple data products are used to examine the robustness of sc_PDSI in the compound event analysis. The results consistently suggest significant increases in drought‐related heatwaves and affected global land area in recent (warmer) periods. Several regions across the globe witnessed rise in CDHW frequency (one to three events/year), duration (2–10 days/year), and severity. This increasing pattern is spatially asymmetric, and greater amplification is observed across the Northern hemisphere due to recent warming. Furthermore, the background aridity influences the spatiotemporal evolution of CDHW events. The results can be applied to minimize the impacts of extreme CDHWs in critical geographical regions.

Abstract We explore the representation of the Atlantic Meridional Overturning Circulation (AMOC) in 27 models from the CMIP6 multimodel ensemble. Comparison with RAPID and SAMBA observations suggests that the ensemble mean represents the AMOC strength and vertical profile reasonably well. Linear trends over the entire historical period (1850–2014) are generally neutral, but many models exhibit an AMOC peak around the 1980s. Ensemble mean AMOC decline in future (SSP) scenarios is stronger in CMIP6 than CMIP5 models. In fact, AMOC decline in CMIP6 is surprisingly insensitive to the scenario at least up to 2060. We find an emergent relationship among a majority of models between AMOC strength and 21st century AMOC decline. Constraining this relationship with RAPID observations suggests that the AMOC might decline between 6 and 8 Sv (34–45%) by 2100. A smaller group of models projects much less AMOC weakening of only up to 30%.

Abstract Fully coupled climate models have long shown a wide range of Antarctic sea ice states and evolution over the satellite era. Here, we present a high‐level evaluation of Antarctic sea ice in 40 models from the most recent phase of the Coupled Model Intercomparison Project (CMIP6). Many models capture key characteristics of the mean seasonal cycle of sea ice area (SIA), but some simulate implausible historical mean states compared to satellite observations, leading to large intermodel spread. Summer SIA is consistently biased low across the ensemble. Compared to the previous model generation (CMIP5), the intermodel spread in winter and summer SIA has reduced, and the regional distribution of sea ice concentration has improved. Over 1979–2018, many models simulate strong negative trends in SIA concurrently with stronger‐than‐observed trends in global mean surface temperature (GMST). By the end of the 21st century, models project clear differences in sea ice between forcing scenarios.

Abstract The double‐intertropical convergence zone (ITCZ) bias is one of the most outstanding errors in all previous generations of climate models. Here, the annual double‐ITCZ bias and the associated precipitation bias in the latest climate models for Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6) are examined in comparison to their previous generations (CMIP Phase 3 [CMIP3] and CMIP Phase 5 [CMIP5]). All three generations of CMIP models share similar systematic annual multi‐model ensemble mean precipitation errors in the tropics. The notorious double‐ITCZ bias and its big inter‐model spread persist in CMIP3, CMIP5, and CMIP6 models. Based on several tropical precipitation bias indices, the double‐ITCZ bias is slightly reduced from CMIP3 or CMIP5 to CMIP6. In addition, the annual equatorial Pacific cold tongue persists in all three generations of CMIP models, but its inter‐model spread is reduced from CMIP3 to CMIP5 and from CMIP5 to CMIP6.

Abstract Modeling dynamic geophysical phenomena is at the core of Earth and environmental studies. The geoscientific community relying mainly on physical representations may want to consider much deeper adoption of artificial intelligence (AI) instruments in the context of AI's global success and emergence of big Earth data. A new perspective of using hybrid physics‐AI approaches is a grand vision, but actualizing such approaches remains an open question in geoscience. This study develops a general approach to improving AI geoscientific awareness, wherein physical approaches such as temporal dynamic geoscientific models are included as special recurrent neural layers in a deep learning architecture. The illustrative case of runoff modeling across the conterminous United States demonstrates that the physics‐aware DL model has enhanced prediction accuracy, robust transferability, and good intelligence for inferring unobserved processes. This study represents a firm step toward realizing the vision of tackling Earth system challenges by physics‐AI integration.

Abstract Hydrogen is currently assessed as a future clean fuel in a hydrogen economy. However, one key problem with implementing a full‐scale hydrogen economy is hydrogen storage (as hydrogen is highly compressible and volatile). One solution for this problem is hydrogen geo‐storage, where compressed hydrogen is injected into geological formations, and the hydrogen can be withdrawn again at any time. However, there is a serious lack of data for realistic geologic conditions, including for hydrogen‐rock wettability, which is proven to determine injectivities, withdrawal rates, storage capacities, and containment security. We thus measured this parameter at various geo‐storage conditions. For a realistic storage scenario in a deep sandstone aquifer, we found that the rock (quartz) was weakly water‐wet or intermediate‐wet. Increasing pressure, temperature, and organic surface concentration increased hydrogen wettability. This study, thus, provides fundamental data and aids in the industrial‐scale implementation of a future hydrogen economy.

Abstract Initial data from the Formosa Satellite‐7/Constellation Observing System for Meteorology Ionosphere and Climate (FORMOSAT‐7/COSMIC‐2, hereafter C2), a recently launched equatorial constellation of six satellites carrying advanced radio occultation receivers, exhibit high signal‐to‐noise ratio, precision, and accuracy, and the ability to provide high vertical resolution profiles of bending angles and refractivity, which contain information on temperature and water vapor in the challenging tropical atmosphere. After an initial calibration/validation phase, over 100,000 soundings of bending angles and refractivity that passed quality control in October 2019 are compared with independent data, including radiosondes, model forecasts, and analyses. The comparisons show that C2 data meet expectations of high accuracy, precision, and capability to detect superrefraction. When fully operational, the C2 satellites are expected to produce ~5,000 soundings per day, providing freely available observations that will enable improved forecasts of weather, including tropical cyclones, and…

Abstract We examine data continuity between the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On (FO) missions over Greenland and Antarctica using independent data from the mass budget method, which calculates the difference between ice sheet surface mass balance and ice discharge at the periphery. For both ice sheets, we find consistent GRACE/GRACE‐FO time series across the data gap, at the continental and regional scales, and the data gap is confidently filled with mass budget method data. In Greenland, the GRACE‐FO data reveal an exceptional summer loss of 600 Gt in 2019 following two cold summers. In Antarctica, ongoing high mass losses in the Amundsen Sea Embayment of West Antarctica, the Antarctic Peninsula, and Wilkes Land in East Antarctica cumulate to 2130, 560, and 370 Gt, respectively, since 2002. A cumulative mass gain of 980 Gt in Queen Maud Land since 2009, however, led to a pause in the acceleration in mass loss from Antarctica after 2016.

Abstract Satellite laser ranging (SLR) observations have long been relied upon for measuring changes in Earth's dynamic oblateness, . This major component of Earth's time‐variable gravity field is not well observed by the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On (GRACE‐FO) missions, leading to the common practice of replacing their values with those obtained by SLR. The coefficient, which has a large impact on the recovered Antarctic Ice Sheet mass changes, is shown here to be poorly observed by GRACE/GRACE‐FO when either mission is operating without two fully functional accelerometers. The GRACE spacecraft pair operated nominally until October 2016 when one accelerometer was powered off due to battery limitations, while GRACE‐FO is currently excluding one accelerometer from the data processing due to elevated noise levels. Beginning with the launch of Laser Relativity Satellite in 2012, SLR‐derived values are suitable for replacing any problematic GRACE/GRACE‐FO estimates, enabling the accurate recovery of Antarctic Ice Sheet mass changes, among others.

Future changes in tropical cyclone properties are an important component of climate change impacts and risk for many tropical and midlatitude countries. In this study we assess the performance of a multimodel ensemble of climate models, at resolutions ranging from 250 to 25 km. We use a common experimental design including both atmosphere-only and coupled simulations run over the period 1950-2050, with two tracking algorithms applied uniformly across the models. There are overall improvements in tropical cyclone frequency, spatial distribution, and intensity in models at 25 km resolution, with several of them able to represent very intense storms. Projected tropical cyclone activity by 2050 generally declines in the South Indian Ocean, while changes in other ocean basins are more uncertain and sensitive to both tracking algorithm and imposed forcings. Coupled models with smaller biases suggest a slight increase in average TC 10 m wind speeds by 2050.

Abstract TROPOMI satellite data show substantial drops in nitrogen dioxide (NO 2 ) during COVID‐19 physical distancing. To attribute NO 2 changes to NO x emissions changes over short timescales, one must account for meteorology. We find that meteorological patterns were especially favorable for low NO 2 in much of the United States in spring 2020, complicating comparisons with spring 2019. Meteorological variations between years can cause column NO 2 differences of ~15% over monthly timescales. After accounting for solar angle and meteorological considerations, we calculate that NO 2 drops ranged between 9.2% and 43.4% among 20 cities in North America, with a median of 21.6%. Of the studied cities, largest NO 2 drops (>30%) were in San Jose, Los Angeles, and Toronto, and smallest drops (<12%) were in Miami, Minneapolis, and Dallas. These normalized NO 2 changes can be used to highlight locations with greater activity changes and better understand the sources contributing to adverse air quality in each city.

Abstract Measurements of present‐day surface deformation are essential for the assessment of long‐term seismic hazard. The European Space Agency's Sentinel‐1 satellites enable global, high‐resolution observation of crustal motion from Interferometric Synthetic Aperture Radar (InSAR). We have developed automated InSAR processing systems that exploit the first ~5 years of Sentinel‐1 data to measure surface motions for the ~800,000‐km 2 Anatolian region. Our new 3‐D velocity and strain rate fields illuminate deformation patterns dominated by westward motion of Anatolia relative to Eurasia, localized strain accumulation along the North and East Anatolian Faults, and rapid vertical signals associated with anthropogenic activities and to a lesser extent extension across the grabens of western Anatolia. We show that automatically processed Sentinel‐1 InSAR data can characterize details of the velocity and strain rate fields with high resolution and accuracy over large regions. These results are important for assessing the relationship between strain accumulation and release in earthquakes.

Abstract New particle formation in the Arctic atmosphere is an important source of aerosol particles. Understanding the processes of Arctic secondary aerosol formation is crucial due to their significant impact on cloud properties and therefore Arctic amplification. We observed the molecular formation of new particles from low‐volatility vapors at two Arctic sites with differing surroundings. In Svalbard, sulfuric acid (SA) and methane sulfonic acid (MSA) contribute to the formation of secondary aerosol and to some extent to cloud condensation nuclei (CCN). This occurs via ion‐induced nucleation of SA and NH3 and subsequent growth by mainly SA and MSA condensation during springtime and highly oxygenated organic molecules during summertime. By contrast, in an ice‐covered region around Villum, we observed new particle formation driven by iodic acid but its concentration was insufficient to grow nucleated particles to CCN sizes. Our results provide new insight about sources and precursors of Arctic secondary aerosol particles.

Abstract Changes in climate are usually considered in terms of trends or differences over time. However, for many impacts requiring adaptation, it is the amplitude of the change relative to the local amplitude of climate variability which is more relevant. Here, we develop the concept of “signal‐to‐noise” in observations of local temperature, highlighting that many regions are already experiencing a climate which would be “unknown” by late 19th century standards. The emergence of observed temperature changes over both land and ocean is clearest in tropical regions, in contrast to the regions of largest change which are in the northern extratropics—broadly consistent with climate model simulations. Significant increases and decreases in rainfall have also already emerged in different regions with the United Kingdom experiencing a shift toward more extreme rainfall events, a signal which is emerging more clearly in some places than the changes in mean rainfall.

Abstract High Mountain Asia is impacted by extreme monsoonal rainfall that triggers landslides in large proportions relative to global distributions, resulting in substantial human impacts and damage to infrastructure each year. Previous landslide research has qualitatively estimated how patterns in landslide activity may change based on climate change scenarios. We present the first quantitative view of potential modulation in future landslide activity over the High Mountain Asia region leveraging a new landslide hazard model and precipitation data from satellite and Global Climate Model sources. In doing so, we find that the rate of increase in landslide activity at the end of the century is expected to be greatest over areas covered by current glaciers and glacial lakes, potentially exacerbating the impacts of cascading hazards on populations downstream. This work demonstrates the potential of Global Climate Models and satellite‐based precipitation estimates to characterize landslide hazards at time scales affected by climate change.

Abstract The resolution of climate models is limited by computational cost. Therefore, we must rely on parameterizations to represent processes occurring below the scale resolved by the models. Here, we focus on parameterizations of ocean mesoscale eddies and employ machine learning (ML), namely, relevance vector machines (RVMs) and convolutional neural networks (CNNs), to derive computationally efficient parameterizations from data, which are interpretable and/or encapsulate physics. In particular, we demonstrate the usefulness of the RVM algorithm to reveal closed‐form equations for eddy parameterizations with embedded conservation laws. When implemented in an idealized ocean model, all parameterizations improve the statistics of the coarse‐resolution simulation. The CNN is more stable than the RVM such that its skill in reproducing the high‐resolution simulation is higher than the other schemes; however, the RVM scheme is interpretable. This work shows the potential for new physics‐aware interpretable ML turbulence parameterizations for use in ocean climate models.

Abstract Recent evidence shows that wind‐driven ocean currents, like the western boundary currents, are strongly affected by global warming. However, due to insufficient observations both on temporal and spatial scales, the impact of climate change on large‐scale ocean gyres is still not clear. Here, based on satellite observations of sea surface height and sea surface temperature, we find a consistent poleward shift of the major ocean gyres. Due to strong natural variability, most of the observed ocean gyre shifts are not statistically significant, implying that natural variations may contribute to the observed trends. However, climate model simulations forced with increasing greenhouse gases suggest that the observed shift is most likely to be a response of global warming. The displacement of ocean gyres, which is coupled with the poleward shift of extratropical atmospheric circulation, has broad impacts on ocean heat transport, regional sea level rise, and coastal ocean circulation.

Abstract The drought‐pluvial seesaw—defined as the phenomenon of pluvials (wet spells) following droughts (dry spells)—magnifies the impact of individual pluvial and drought events yet has not been systematically evaluated, especially at the global scale. We apply an event coincidence analysis to explore the aggregated seesaw behavior based on land surface model simulations for the past seven decades (1950–2016). We find that globally, about 5.9% and 7.6% of the land surface have experienced statistically significant ( p <0.10) drought‐pluvial seesaw behavior during the boreal spring‐summer and fall‐winter, with an average 11.1% and 11.4% of all droughts being followed by pluvials in the following season, respectively. Although this global frequency pattern is modest and coherent changes cannot be detected at the subcontinental scale, local hot spots of drought‐pluvial seesaw have become more frequent than either droughts or pluvials alone in the last three decades, albeit with a small percentage of area coverage.

Abstract It is a puzzle as to why more severe haze formed during the New Year Holiday in 2020 (NYH‐20), when China was in an unprecedented state of shutdown to contain the coronavirus (COVID‐19) outbreak, than in 2019 (NYH‐19). We performed a comprehensive measurement and modeling analysis of the aerosol chemistry and physics at multiple sites in China (mainly in Shanghai) before, during, and after NYH‐19 and NYH‐20. Much higher secondary aerosol fraction in PM2.5 were observed during NYH‐20 (73%) than during NYH‐19 (59%). During NYH‐20, PM2.5 levels correlated significantly with the oxidation ratio of nitrogen (r2 = 0.77, p < 0.01), and aged particles from northern China were found to impede atmospheric new particle formation and growth in Shanghai. A markedly enhanced efficiency of nitrate aerosol formation was observed along the transport pathways during NYH‐20, despite the overall low atmospheric NO2 levels.

Abstract Changes in global land monsoon (GLM) precipitation determine the local water resource, affecting two thirds of global population. The future changes in GLM summer precipitation and the sources of projection uncertainty under four scenarios are investigated using the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The GLM summer precipitation is projected to increase by 1.76 ± 1.57% (2.54 ± 2.22%), 1.33 ± 1.97% (3.52 ± 3.05%), 0.96 ± 2.04% (3.51 ± 4.97%), and 1.71 ± 2.38% (5.75 ± 5.92%) in the near (long) term under Shared Socioeconomic Pathway (SSP) 1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5, respectively. The enhancement is caused by thermodynamic responses due to increased moisture, which is partly offset by dynamic responses due to weakened circulation. The uncertainty in GLM precipitation projection is the largest in SSP5–8.5 long‐term projection. The uncertainty of submonsoon precipitation projections is larger than that in GLM precipitation. The uncertainty of monsoon precipitation projection arises from the circulation changes, which can be partly…

Abstract In 2020, the Yangtze River (YR) suffered a long‐persisting Meiyu season. The accumulated rainfall broke its record since 1961 and caused severe flooding and death in China. Our results show the sequential warm and cold Meiyu front regulated by the North Atlantic Oscillation (NAO) was responsible for this unexpected extreme Meiyu event. From 11 to 25 June with the positive NAO, the interaction between the South Asian High (SAH) and the western Pacific subtropical high maintained a warm front to strengthen the rainband north of the YR. Afterward, the coupling between SAH and midlatitude Mongolian Cyclone induced a cold front, which retreated the rainband to the south of YR from 30 June to 13 July with the negative NAO. Although the ECMWF S2S model successfully predicted the warm‐front‐related Meiyu rainband, it failed to forecast the Meiyu rainband in the cold‐front period, suggesting a great challenge of S2S forecasting on Meiyu rainfall.

Abstract Recent advances in remote sensing of solar‐induced chlorophyll fluorescence (SIF) have garnered wide interest from the biogeoscience and Earth system science communities, due to the observed linearity between SIF and gross primary productivity (GPP) at increasing spatiotemporal scales. Three recent studies, Maguire et al., (2020, https://doi.org/10.1029/2020GL087858 ), He et al. (2020, https://doi.org/10.1029/2020GL087474 ), and Marrs et al. (2020, https://doi.org/10.1029/2020GL087956 ) highlight a nonlinear relationship between fluorescence and photochemical yields and show empirical evidence for the decoupling of SIF, stomata, and the carbon reactions of photosynthesis. Such mechanistic studies help advance our understanding of what SIF is and what it is not. We argue that these findings are not necessarily contradictory to the linear SIF‐GPP relationship observed at the satellite scale and provide context for where, when, and why fluorescence and photosynthesis diverge at smaller spatiotemporal scales. Understanding scale dependencies of remote sensing data is crucial…

Abstract Aura Microwave Limb Sounder (MLS) measurements show that chemical processing was critical to the observed record‐low Arctic stratospheric ozone in spring 2020. The 16‐year MLS record indicates more polar denitrification and dehydration in 2019/2020 than in any Arctic winter except 2015/2016. Chlorine activation and ozone depletion began earlier than in any previously observed winter, with evidence of chemical ozone loss starting in November. Active chlorine then persisted as late into spring as it did in 2011. Empirical estimates suggest maximum chemical ozone losses near 2.8 ppmv by late March in both 2011 and 2020. However, peak chlorine activation, and thus peak ozone loss, occurred at lower altitudes in 2020 than in 2011, leading to the lowest Arctic ozone values ever observed at potential temperature levels from ∼400–480 K, with similar ozone values to those in 2011 at higher levels.

Abstract Both the Arctic and Antarctic sea ice extents (SIEs) from 44 coupled models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) are evaluated by comparing them with observations and CMIP5 results. The CMIP6 multimodel mean can adequately reproduce the seasonal cycles of both the Arctic and Antarctic SIE. The observed Arctic September SIE declining trend (−0.82 ± 0.18 million km 2 per decade) between 1979 and 2014 is slightly underestimated in CMIP6 models (−0.70 ± 0.06 million km 2 per decade). The observed weak but significant upward trend of the Antarctic SIE is not captured, which was an issue already in the CMIP5 phase. Compared with CMIP5 models, CMIP6 models have lower intermodel spreads in SIE mean values and trends, although their SIE biases are relatively larger. The CMIP6 models did not reproduce the new summer tendencies after 2000, including the faster decline of Arctic SIE and the larger interannual variability in Antarctic SIE.

Abstract Fires in southeastern Australia produced at least 18 pyrocumulonimbus (pyroCb) between 29 December 2019 and 4 January 2020. The largest plumes from this event exhibited several previously undocumented phenomena in the stratosphere. These include (i) the generation of potential vorticity and anticyclonic circulations from absorptive aerosol heating, (ii) the formation of a vertical temperature anomaly dipole, (iii) the rapid ascent from the lowermost stratosphere (15–16 km) to altitudes above 31 km in less than 2 months, (iv) an unprecedented abundance of H2O and CO in the stratosphere, and (v) the displacement of background O3 and N2O from rapid ascent of air from the troposphere and lower stratosphere. Each of these phenomena is traced back to a 5‐day‐old stratospheric plume composed of a massive amount of aerosol and biomass burning gases from a pyroCb outbreak. Until now, there has been no documented evidence that pyroCb plumes can affect stratospheric winds.

Abstract In early summer 2020, the Meiyu‐Baiu rainfall was markedly enhanced, triggering devastating floods in Japan and central China. We examined the underlying processes using a climate model and analysis. The enhanced Meiyu‐Baiu rainfall was reasonably predicted by the climate model initialized at the end of April. The sensitivity experiment indicated that Indian Ocean (IO) warming enhanced the Meiyu‐Baiu rainfall. Moreover, we found that the warm IO condition can be traced back to the super Indian Ocean Dipole (IOD) in 2019. The IO warmth was influenced by successive processes: record strong downwelling Rossby waves excited by the IOD and tripole sea surface temperature anomalies in the tropical IO‐western Pacific, their arrival to the southwestern IO in spring, and associated modulation of monsoon flow. The results suggest that the seasonal predictability of the Meiyu‐Baiu rainfall in 2020 originated from the super IOD.

Abstract The GRACE‐FO satellites launched in May 2018 are able to quantify the water mass deficit in Central Europe during the two consecutive summer droughts of 2018 and 2019. Relative to the long‐term climatology, the water mass deficits were −112 ± 10.5 Gt in 2018 and −145 ± 12 Gt in 2019. These deficits are 73% and 94% of the mean amplitude of seasonal water storage variations, which is so severe that a recovery cannot be expected within 1 year. The water deficits in 2018 and 2019 are the largest in the whole GRACE and GRACE‐FO time span. Globally, the data do not show an offset between the two missions, which proves the successful continuation of GRACE by GRACE‐FO and thus the reliability of the observed extreme events in Central Europe. This allows for a joint assessment of the four Central European droughts in 2003, 2015, 2018, and 2019 in terms of total water storage deficits.

Abstract During the COVID‐19 lockdown (24 January–20 March) in China low air pollution levels were reported in the media as a consequence of reduced economic and social activities. Quantification of the pollution reduction is not straightforward due to effects of transport, meteorology, and chemistry. We have analyzed the NO x emission reductions calculated with an inverse algorithm applied to daily NO 2 observations from TROPOMI onboard the Copernicus Sentinel‐5P satellite. This method allows the quantification of emission reductions per city and the analysis of emissions of maritime transport and of the energy sector separately. The reductions we found are 20–50% for cities, about 40% for power plants, and 15–40% for maritime transport depending on the region. The reduction in both emissions and concentrations shows a similar timeline consisting of a sharp reduction (34–50%) around the Spring festival and a slow recovery from mid‐February to mid‐March.

Abstract The steepness of the beach face is a fundamental parameter for coastal morphodynamic research. Despite its importance, it remains extremely difficult to obtain reliable estimates of the beach‐face slope over large spatial scales (thousands of km of coastline). In this letter, a novel approach to estimate this slope from time series of satellite‐derived shoreline positions is presented. This new technique uses a frequency domain analysis to find the optimum slope that minimizes high‐frequency tidal fluctuations relative to lower‐frequency erosion/accretion signals. A detailed assessment of this new approach at eight locations spanning a range of tidal regimes, wave climates, and sediment grain sizes shows strong agreement ( R 2 = 0.93) with field measurements. The automated technique is then applied across thousands of beaches in eastern Australia and California, USA, revealing similar regional‐scale distributions along these two contrasting coastlines and highlights the potential for new global‐scale insight to beach‐face slope spatial distribution, variability, and trends.

Abstract The Atlantic Meridional Overturning Circulation (AMOC) has been, and will continue to be, a key factor in the modulation of climate change both locally and globally. However, there remains considerable uncertainty in recent AMOC evolution. Here, we show that the multimodel mean AMOC strengthened by approximately 10% from 1850–1985 in new simulations from the 6th Coupled Model Intercomparison Project (CMIP6), a larger change than was seen in CMIP5. Across the models, the strength of the AMOC trend up to 1985 is related to a proxy for the strength of the aerosol forcing. Therefore, the multimodel difference is a result of stronger anthropogenic aerosol forcing on average in CMIP6 than CMIP5, which is primarily due to more models including aerosol‐cloud interactions. However, observational constraints—including a historical sea surface temperature fingerprint and shortwave radiative forcing in recent decades—suggest that anthropogenic forcing and/or the AMOC response may be overestimated.

Abstract Many climate models struggle with a poor simulation of the Madden‐Julian Oscillation (MJO), especially its propagation across the Maritime Continent (MC). This study quantitatively evaluates the robustness of MJO propagation over the MC in climate models that participated in Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6) with a newly developed MC propagation metric. The results show that the CMIP6 models simulate MJO propagation over the MC more realistically than the CMIP5 models. Lower free‐tropospheric moisture budget analysis highlights that the greater horizontal moisture advection is responsible for the enhanced MJO propagation over the MC. The increase in horizontal moisture advection in the CMIP6 models is mainly attributed to the steeper horizontal mean state moisture gradient around the MC, which is associated with the reduction of the equatorial dry bias.

Abstract An exceptionally strong stationary planetary wave with Zonal Wavenumber 1 led to a sudden stratospheric warming (SSW) in the Southern Hemisphere in September 2019. Ionospheric data from European Space Agency's Swarm satellite constellation mission show prominent 6‐day variations in the dayside low‐latitude region at this time, which can be attributed to forcing from the middle atmosphere by the Rossby normal mode “quasi‐6‐day wave” (Q6DW). Geopotential height measurements by the Microwave Limb Sounder aboard National Aeronautics and Space Administration's Aura satellite reveal a burst of global Q6DW activity in the mesosphere and lower thermosphere during the SSW, which is one of the strongest in the record. The Q6DW is apparently generated in the polar stratosphere at 30–40 km, where the atmosphere is unstable due to strong vertical wind shear connected with planetary wave breaking. These results suggest that an Antarctic SSW can lead to ionospheric variability through wave forcing from the middle atmosphere.

Trade-wind clouds exhibit a large diversity of spatial organizations at the mesoscale. Over the tropical western Atlantic, a recent study has visually identified four prominent mesoscale patterns of shallow convection, referred to as flowers, fish, gravel, and sugar. We show that these four patterns can be identified objectively from satellite observations by analyzing the spatial distribution of infrared brightness temperatures. By applying this analysis to 19 years of data, we examine relationships between cloud patterns and large-scale environmental conditions. This investigation reveals that on daily and interannual timescales, the near-surface wind speed and the strength of the lower-tropospheric stability discriminate the occurrence of the different organization patterns. These results, combined with the tight relationship between cloud patterns, low-level cloud amount, and cloud-radiative effects, suggest that the mesoscale organization of shallow clouds might change under global warming. The role of shallow convective organization in determining low-cloud feedback should…

Abstract In the Antarctic ozone hole, ozone mixing ratios have been decreasing to extremely low values of 0.01–0.1 ppm in nearly all spring seasons since the late 1980s, corresponding to 95–99% local chemical loss. In contrast, Arctic ozone loss has been much more limited and mixing ratios have never before fallen below 0.5 ppm. In Arctic spring 2020, however, ozonesonde measurements in the most depleted parts of the polar vortex show a highly depleted layer, with ozone loss averaged over sondes peaking at 93% at 18 km. Typical minimum mixing ratios of 0.2 ppm were observed, with individual profiles showing values as low as 0.13 ppm (96% loss). The reason for the unprecedented chemical loss was an unusually strong, long‐lasting, and cold polar vortex, showing that for individual winters the effect of the slow decline of ozone‐depleting substances on ozone depletion may be counteracted by low temperatures.

Abstract We use time series of time‐variable gravity from the Gravitational Recovery and Climate Experiment (GRACE) and GRACE Follow‐On (GRACE‐FO) missions to evaluate the mass balance of the world's glaciers and ice caps (GIC) for the time period April 2002 to September 2019, excluding Antarctica and Greenland peripheral glaciers. We demonstrate continuity of the mass balance record across the GRACE/GRACE‐FO data gap using independent data from the GMAO Modern‐Era Retrospective Analysis for Research and Applications, Version 2 (MERRA‐2) reanalysis. We report an average mass loss of 281.5 ± 30 Gt/yr, an acceleration of 50 ± 20 Gt/yr per decade, and a 13‐mm cumulative sea level rise for the analyzed period. Seven regions dominate the mass loss, with the largest share from the Arctic: Alaska (72.5 ± 8 Gt/yr), Canadian Arctic Archipelago (73.0 ± 9 Gt/yr), Southern Andes (30.4 ± 13 Gt/yr), High Mountain Asia (HMA) (28.8 ± 11 Gt/yr), Russian Arctic (20.2 ± 6 Gt/yr), Iceland (15.9 ± 4 Gt/yr), and Svalbard (12.1 ± 4 Gt/yr). At the regional level, the analysis of acceleration is complicated…

Abstract Ice nucleating particles (INPs) affect the radiative properties of cold clouds. Knowledge concerning their concentration above ground level and their potential sources is scarce. Here we present the first highly temperature resolved ice nucleation spectra of airborne samples from an aircraft campaign during late winter in 2018. Most INP spectra featured low concentration levels (<3 · 10−4 L−1 at −15°C). However, we also found INP concentrations of up to 1.8·10−2 L−1 at −15°C and freezing onsets as high as −7.5°C for samples mainly from the marine boundary layer. Shape and onset temperature of the ice nucleation spectra of those samples as well as heat sensitivity hint at biogenic INP. Colocated measurements additionally indicate a local marine influence rather than long‐range transport. Our results suggest that even in late winter above 80°N a local marine source for biogenic INP, which can efficiently nucleate ice at high temperatures, is present.

Abstract Governments restricted mobility and effectively shuttered much of the global economy in response to the COVID‐19 pandemic. Six San Francisco Bay Area counties were the first region in the United States to issue a “shelter‐in‐place” order asking non‐essential workers to stay home. Here we use CO 2 observations from 35 Berkeley Environment, Air‐quality and CO 2 Network (BEACO 2 N) nodes and an atmospheric transport model to quantify changes in urban CO 2 emissions due to the order. We infer hourly emissions at 900‐m spatial resolution for 6 weeks before and 6 weeks during the order. We observe a 30% decrease in anthropogenic CO 2 emissions during the order and show that this decrease is primarily due to changes in traffic (–48%) with pronounced changes to daily and weekly cycles; non‐traffic emissions show small changes (–8%). These findings provide a glimpse into a future with reduced CO 2 emissions through electrification of vehicles.

Brown carbon (BrC) is an organic aerosol material that preferentially absorbs light of shorter wavelengths. Global-scale radiative impacts of BrC have been difficult to assess due to the lack of BrC observational data. To address this, aerosol filters were continuously collected with near pole-to-pole latitudinal coverage over the Pacific and Atlantic basins in three seasons as part of the Atmospheric Tomography Mission. BrC chromophores in filter extracts were measured. We find that globally, BrC was highly spatially heterogeneous, mostly detected in air masses that had been transported from regions of extensive biomass burning. We calculate the average direct radiative effect due to BrC absorption accounted for approximately 7% to 48% of the top of the atmosphere clear-sky instantaneous forcing by all absorbing carbonaceous aerosols in the remote atmosphere, indicating that BrC from biomass burning is an important component of the global radiative balance.

Abstract Future greenhouse warming is expected to influence the characteristics of global monsoon systems. However, large regional uncertainties still remain. Here we use 16 Coupled Model Intercomparison Project Phase 6 (CMIP6) models to determine how the length of the summer rainy season and precipitation extremes over the Asian summer monsoon domain will change in response to greenhouse warming. Over East Asia the models simulate on average on the earlier onset and later retreat; whereas over India, the retreat will occur later. The model simulations also show an intensification of extreme rainfall events, as well as an increase of seasonal drought conditions. These results demonstrate the high volatility of the Asian summer monsoon systems and further highlight the need for improved water management strategies in this densely populated part of the world.

Abstract We revise the direct radiative effect (DRE) of mineral dust aerosols in the shortwave (SW) and longwave (LW) based on global model simulations that include coarse dust particles (>20 μm) and a new LW complex refractive index data set representative of major global sources. Simulations are constrained against observed dust size distributions and optical depth. Scattering of LW radiation is accounted for in the analysis. The extension of the dust size beyond 20 μm causes a reduction in the SW DRE compared to current model estimates, while the LW DRE remains within published values due to compensating effects between changing size distribution, complex refractive index, and accounting for dust scattering. The dust direct radiative effect efficiency from model simulations reproduces well field observations close to sources and after transport. The global mean net effect of dust is −0.03 Wm −2 as a result of cooling over oceans and warming over land.

Abstract Compound events have the potential to cause high socioeconomic and environmental losses. We examine the ability of the sixth phase of the Coupled Model Intercomparison Project (CMIP6) models to capture two bivariate compound events: the co‐occurrence of heavy rain and strong wind, and heat waves and meteorological drought. We evaluate the models over North America, Europe, Eurasia, and Australia using observations and reanalysis data set spanning 1980–2014. Some of the CMIP6 models capture the return periods of both bivariate compound events over North America, Europe, and Eurasia surprisingly well but perform less well over Australia. For heavy rain and strong wind, this poor performance was particularly clear in northern Australia which suggests limits in simulating tropical and extratropical cyclones, local convection, and mesoscale convective systems. We did not find higher model resolution improved performance in any region. Overall, our results show some CMIP6 models can be used to examine compound events, particularly over North America, Europe, and Eurasia.

Abstract Urban subsurface monitoring requires high temporal‐spatial resolution, low maintenance cost, and minimal intrusion to nearby life. Distributed acoustic sensing (DAS), in contrast to conventional station‐based sensing technology, has the potential to provide a passive seismic solution to urban monitoring requirements. Based on data recorded by the Stanford Fiber Optic Seismic Observatory, we demonstrate that near‐surface velocity changes induced by the excavation of a basement construction can be monitored using existing fiber optic infrastructure in a noisy urban environment. To achieve satisfactory results, careful signal processing comprising of noise removal and source signature normalization are applied to raw DAS recordings. Repeated blast signals from quarry sites provide free, unidirectional, and near‐impulsive sources for periodic urban seismic monitoring, which are essential for increasing the temporal resolution of passive seismic methods. Our study suggests that DAS will likely play an important role in urban subsurface monitoring.

Abstract Timely and accurate monitoring of crops is essential for food security. Here, we examine how well solar‐induced chlorophyll fluorescence (SIF) can inform crop productivity across the United States. Based on tower‐level observations and process‐based modeling, we find highly linear gross primary production (GPP):SIF relationships for C4 crops, while C3 crops show some saturation of GPP at high light when SIF continues to increase. C4 crops yield higher GPP:SIF ratios (30–50%) primarily because SIF is most sensitive to the light reactions (does not account for photorespiration). Scaling to the satellite, we compare SIF from the TROPOspheric Monitoring Instrument (TROPOMI) against tower‐derived GPP and county‐level crop statistics. Temporally, TROPOMI SIF strongly agrees with GPP observations upscaled across a corn and soybean dominated cropland ( R 2 = 0.89). Spatially, county‐level TROPOMI SIF correlates with crop productivity ( R 2 = 0.72; 0.86 when accounting for planted area and C3/C4 contributions), highlighting the potential of SIF for reliable crop monitoring.