The 50 most-cited articles in Geophysical Research Letters, 2019

Abstract The Community Earth System Model Version 2 (CESM2) has an equilibrium climate sensitivity (ECS) of 5.3 K. ECS is an emergent property of both climate feedbacks and aerosol forcing. The increase in ECS over the previous version (CESM1) is the result of cloud feedbacks. Interim versions of CESM2 had a land model that damped ECS. Part of the ECS change results from evolving the model configuration to reproduce the long‐term trend of global and regional surface temperature over the twentieth century in response to climate forcings. Changes made to reduce sensitivity to aerosols also impacted cloud feedbacks, which significantly influence ECS. CESM2 simulations compare very well to observations of present climate. It is critical to understand whether the high ECS, outside the best estimate range of 1.5–4.5 K, is plausible.

Abstract In this study, we present a fast and reliable method for end‐to‐end estimation of earthquake magnitude from raw waveforms recorded at single stations. We design a regressor (MagNet) composed of convolutional and recurrent neural networks that is not sensitive to the data normalization, hence waveform amplitude information can be utilized during the training. The network can learn distance‐dependent and site‐dependent functions directly from the training data. Our model can predict local magnitudes with an average error close to zero and standard deviation of ~0.2 based on single‐station waveforms without instrument response correction. We test the network for both local and duration magnitude scales and show a station‐based learning can be an effective approach for improving the performance. The proposed approach has a variety of potential applications from routine earthquake monitoring to early warning systems.

Abstract Rapid identification of anomalous methane sources in oil/gas fields could enable corrective action to fight climate change. The GHGSat‐D satellite instrument measuring atmospheric methane with 50‐meter spatial resolution was launched in 2016 to demonstrate space‐based monitoring of methane point sources. Here we report the GHGSat‐D discovery of an anomalously large, persistent methane source (10–43 metric tons per hour, detected in over 50% of observations) at a gas compressor station in Central Asia, together with additional sources (4–32 metric tons per hour) nearby. The TROPOMI satellite instrument confirms the magnitude of these large emissions going back to at least November 2017. We estimate that these sources released 142 ± 34 metric kilotons of methane to the atmosphere from February 2018 through January 2019, comparable to the 4‐month total emission from the well‐documented Aliso Canyon blowout.

Abstract Pyrocumulonimbus (pyroCb) wildfires cause devastation in many regions globally. Given that fire‐atmosphere coupling is associated with pyroCbs, future changes in coincident high index values of atmospheric instability and dryness (C‐Haines) and near‐surface fire weather are assessed for southeastern Australia using a regional climate projection ensemble. We show that observed pyroCb events occur predominantly on forested, rugged landscapes during extreme C‐Haines conditions, but over a wide range of surface fire weather conditions. Statistically significant increases in the number of days where both C‐Haines and near‐surface fire weather values are conducive to pyroCb development are projected across southeastern Australia, predominantly for November (spring), and less strongly for December (summer) in 2060‐2079 versus 1990‐2009, with future C‐Haines increases linked to increased 850‐hPa dewpoint depression. The increased future occurrence of conditions conducive to pyroCb development and their extension into spring have implications for mitigating these dangerous wildfires…

Fluctuations in Antarctic Ice Sheet elevation and mass occur over a variety of time scales, owing to changes in snowfall and ice flow. Here we disentangle these signals by combining 25 years of satellite radar altimeter observations and a regional climate model. From these measurements, patterns of change that are strongly associated with glaciological events emerge. While the majority of the ice sheet has remained stable, 24% of West Antarctica is now in a state of dynamical imbalance. Thinning of the Pine Island and Thwaites glacier basins reaches 122 m in places, and their rates of ice loss are now five times greater than at the start of our survey. By partitioning elevation changes into areas of snow and ice variability, we estimate that East and West Antarctica have contributed -1.1 ± 0.4 and +5.7 ± 0.8 mm to global sea level between 1992 and 2017.

Abstract Here we evaluate five atmospheric reanalyses in an Arctic gateway during late summer. The reanalyses include ERA5, ERA‐Interim, Japanese 55 year Re‐Analysis (JRA‐55), Climate Forecasting System Reanalysis‐version 2 (CFSv2), and Modern Era Retrospective analysis for Research and Applications‐version 2 (MERRA‐2). We use observations from 50 radiosondes launched in the Fram Strait around 79‐80°N, between 25 August and 11 September 2017. Crucially, data from 27 radiosondes were not transmitted to the Global Telecommunications System and therefore not assimilated into any reanalysis. In most reanalyses, the magnitude of wind speed and humidity errors is similar for profiles with and without data assimilation. In cases without data assimilation, correlation coefficients (R) exceed 0.88 for temperature, wind speed, and specific humidity, in all reanalyses. Overall, the newly released ERA5 has higher correlation coefficients than any other reanalyses as well as smaller biases and root‐mean‐square errors, for all three variables. The largest improvements identified in ERA5 are in…

Abstract Climate warming in regions of ice‐rich permafrost can result in widespread thermokarst development, which reconfigures the landscape and damages infrastructure. We present multisite time series observations which couple ground temperature measurements with thermokarst development in a region of very cold permafrost. In the Canadian High Arctic between 2003 and 2016, a series of anomalously warm summers caused mean thawing indices to be 150–240% above the 1979–2000 normal resulting in up to 90 cm of subsidence over the 12‐year observation period. Our data illustrate that despite low mean annual ground temperatures, very cold permafrost (<−10 °C) with massive ground ice close to the surface is highly vulnerable to rapid permafrost degradation and thermokarst development. We suggest that this is due to little thermal buffering from soil organic layers and near‐surface vegetation, and the presence of near‐surface ground ice. Observed maximum thaw depths at our sites are already exceeding those projected to occur by 2090 under representative concentration pathway version 4.5.

Abstract Estimating ecosystem evapotranspiration (ET) is important to understanding the global water cycle and to study land‐atmosphere interactions. We developed a physics constrained machine learning (ML) model (hybrid model) to estimate latent heat flux (LE), which conserves the surface energy budget. By comparing model predictions with observations at 82 eddy covariance tower sites, our hybrid model shows similar performance to the pure ML model in terms of mean metrics (e.g., mean absolute percent errors) but, importantly, the hybrid model conserves the surface energy balance, while the pure ML model does not. A second key result is that the hybrid model extrapolates much better than the pure ML model, emphasizing the benefits of combining physics with ML for increased generalizations. The hybrid model allows inferring the structural dependence of ET and surface resistance ( r s ), and we find that vegetation height and soil moisture are the main regulators of ET and r s .

Abstract Recent observations show that the rate at which the Antarctic ice sheet (AIS) is contributing to sea level rise is increasing. Increases in ice‐ocean heat exchange have the potential to induce substantial mass loss through the melting of its ice shelves. Lack of data and limitations in modeling, however, has made it challenging to quantify the importance of ocean‐induced changes in ice shelf thickness as a driver for ongoing mass loss. Here, we use a numerical ice sheet model in combination with satellite observations of ice shelf thinning from 1994 to 2017 to quantify instantaneous changes in ice flow across all AIS grounding lines, resulting from changes in ice shelf buttressing alone. Our process‐based predictions are in good agreement with observed spatial patterns of ice loss, providing support for the notion that a significant portion of the current ice loss of the AIS is ocean driven and caused by a reduction in ice shelf buttressing.

Abstract Surface ice velocity is a fundamental characteristic of glaciers and ice sheets that quantifies the transport of ice. Changes in ice dynamics have a major impact on ice sheet mass balance and its contribution to sea level rise. Prior comprehensive mappings employed speckle and feature tracking techniques, optimized for fast‐flow areas, with precision of 2‐5 m/year, hence limiting our ability to describe ice flow in the slow interior. We present a vector map of ice velocity using the interferometric phase from multiple satellite synthetic aperture radars resulting in 10 times higher precision in speed (20 cm/year) and direction (5°) over 80% of Antarctica. Precision mapping over areas of slow motion (<1 m/year) improves from 20 to 93%, which helps better constrain drainage boundaries, improve mass balance assessment, evaluate regional atmospheric climate models, reconstruct ice thickness, and inform ice sheet numerical models.

Abstract In this study, Moderate Resolution Imaging Spectroradiometer land cover, land surface temperature (LST), and enhanced vegetation index (EVI) data were used to investigate the trends of surface urban heat island intensity (SUHII, urban LST minus rural LST) and their relations with vegetation in 397 global big cities during 2001–2017. Major findings include the following: (1) Annual daytime and nighttime SUHII increased significantly ( p < 0.05, Mann‐Kendall trend test) in 42.1% and 30.5% cities, respectively. (2) The daytime SUHII in the growing season was significantly and positively correlated with rural EVI in 58.9% cities. This is because high rural EVI can increase the EVI difference between urban and rural areas. (3) Rural greening contributed 22.5% of the increased daytime SUHII in the growing season at the global scale. This study highlights that the effect of greening in rural areas was a significant and widespread driver for the increased daytime SUHII.

The choice of the best basal friction law to use in ice-sheet models remains a source of uncertainty in projections of sea level. The parameters in commonly used friction laws can produce a broad range of behavior and are poorly constrained. Here we use a time series of elevation and speed data to examine the simulated transient response of Pine Island Glacier, Antarctica, to a loss of basal traction as its grounding line retreats. We evaluate a variety of friction laws, which produces a diversity of responses, to determine which best reproduces the observed speedup when forced with the observed thinning. Forms of the commonly used power law friction provide much larger model-data disagreement than less commonly used regularized Coulomb friction in which cavitation effects yield an upper bound on basal friction. Thus, adoption of such friction laws could substantially improve the fidelity of large-scale simulations to determine future sea level.

Abstract Antarctic snowfall consists of frequent clear‐sky precipitation and heavier falls from intrusions of maritime airmasses associated with amplified planetary waves. We investigate the importance of different precipitation events using the output of the RACMO2 model. Extreme precipitation events consisting of the largest 10% of daily totals are shown to contribute more than 40% of the total annual precipitation across much of the continent, with some areas receiving in excess of 60% of the total from these events. The greatest contribution of extreme precipitation events to the annual total is in the coastal areas and especially on the ice shelves, with the Amery Ice Shelf receiving 50% of its annual precipitation in less than the 10 days of heaviest precipitation. For the continent as a whole, 70% of the variance of the annual precipitation is explained by variability in precipitation from extreme precipitation events, with this figure rising to over 90% in some areas.

Abstract Retrospectively comparing future model projections to observations provides a robust and independent test of model skill. Here we analyze the performance of climate models published between 1970 and 2007 in projecting future global mean surface temperature (GMST) changes. Models are compared to observations based on both the change in GMST over time and the change in GMST over the change in external forcing. The latter approach accounts for mismatches in model forcings, a potential source of error in model projections independent of the accuracy of model physics. We find that climate models published over the past five decades were skillful in predicting subsequent GMST changes, with most models examined showing warming consistent with observations, particularly when mismatches between model‐projected and observationally estimated forcings were taken into account.

Abstract The lowest winter‐maximum areal sea‐ice coverage on record (1980–2019) in the Bering Sea occurred in the winter of 2017/2018. Sea ice arrived late due to warm southerly winds in November. More typical northerly winds (albeit warm) in December and January advanced the ice, but strong, warm southerlies in February and March forced the ice to retreat. The cold pool (shelf region with bottom water < 2 °C) was the smallest on record, because of two related mechanisms: (1) lack of direct cooling in winter by melting sea ice and (2) weaker vertical stratification (no ice melt reduced the vertical salinity gradient) allowing surface heating to penetrate into the near bottom water during summer. February 2019 exhibited another outbreak of warm southerly winds forcing ice to retreat. The number of >31‐day outbreaks of southerly winds in winter has increased since 2016.

Abstract We collected kinematic Global Navigation Satellite Systems (GNSS) surface height data, on a 750‐km ground‐based traverse of the flat interior of the Antarctic ice sheet, for comparison with Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) surface heights. Vertical errors in the GNSS data are estimated to be 5.6 cm, comparable to results from a previous traverse and with year‐to‐year comparisons. Comparisons of the GNSS heights and 6 months of ICESat‐2 ATL03 photon‐based heights and ATL06 segment‐based heights indicate that the accuracy and precision of ICESat‐2 data are comparable to that of results from the ICESat mission: ATL03 is currently accurate to better than 5 cm with better than 13 cm of surface measurement precision, while ATL06 is currently accurate to better than 3 cm with better than 9 cm of surface measurement precision.

Abstract Satellite laser ranging (SLR) observations are routinely applied toward the estimation of dynamic oblateness, C 20 , which is the largest globally integrated component of Earth's time‐variable gravity field. Since 2002, GRACE and GRACE Follow‐On have revolutionized the recovery of higher spatial resolution features of global time‐variable gravity, with SLR continuing to provide the most reliable estimates of C 20 . We quantify the effect of various SLR processing strategies on estimating C 20 and demonstrate better signal recovery with the inclusion of GRACE‐derived low‐degree gravity information in the forward model. This improved SLR product modifies the Antarctic and Greenland Ice Sheet mass trends by −15.4 and −3.5 Gt/year, respectively, as compared to CSR TN11, and improves global mean sea level budget closure by modifying sea level rise by +0.08 mm/year. We recommend that this new C 20 product be applied to RL06 GRACE data products for enhanced accuracy and scientific interpretation.

Abstract The knowledge regarding how the boundary layer height (BLH) changes over time is still poor. Here we analyze the spatial and temporal changes in radiosonde‐derived measurements of BLH over China from 1979 to 2016. A qualitatively robust and abrupt change of BLH occurred in 2004. Over the former period (from 1979 to 2003) a spatially uniform increase was found in the BLH, while over the latter period BLH decreased in a spatially nonuniform way. Second, the meteorological influence on the rising BLH was determined to have a negative association with soil moisture, lower tropospheric stability and relative humidity, and a positive association with the near‐surface temperature. Yet, there was a different influence of meteorology on the BLH over the latter period, where a negative association was revealed with Tsfc and relative humidity. These findings shed new light on the long‐term changes in air pollution across China.

Abstract Lake level change is an effective indicator of climate change, because it reflects the dynamic balance of water input and loss. Here we provide a first look of Ice, Cloud, and land Elevation Satellite‐2 (ICESat‐2) on the lakes of the Tibetan Plateau. ICESat‐2 doubles the number of lakes observed using predecessor ICESat data. The ICESat/ICESat‐2 altimetry data between 2003 and 2018 are in excellent agreement with in situ measurements from Qinghai Lake (R2 = 0.95, root‐mean‐square error = 0.10 m) and with gauge observations made on 3 December 2018 (< 2 cm). The 62 lakes examined show a mean rate of water level change of 0.28 ± 0.03 m/year in 2003–2018, with 58 lakes increasing (mean rate 0.30 ± 0.03 m/year), and 4 lakes decreasing (mean rate −0.12 ± 0.06 m/year). A total change of lake water storage of ~14 Gt/year is estimated. The results suggest that ICESat‐2 data will be an important tool for future lake level change studies.

Abstract Underestimation of the proportion of supercooled liquid in mixed‐phase clouds in climate models has called into question its impact on Arctic climate change. We show that correcting for this bias in the CESM model can either enhance or reduce Arctic amplification depending on the microphysical characteristics of the clouds as a corollary to the cloud phase feedback. Replacement of ice with liquid in the cloud phase feedback results in more downward longwave radiation, which is effectively trapped as heat at the surface in the Arctic due to its unique stable stratification conditions, and this ultimately leads to a more positive lapse rate feedback. The larger the ice particles are to begin with, the stronger Arctic amplification becomes due to the lower precipitation efficiency of liquid droplets compared to ice crystals. Our results emphasize the importance of realistic representations of microphysical processes in mixed‐phase clouds, particularly in the Arctic.

Abstract Millions of people died due to famines in India in the nineteenth and twentieth centuries; however, the relationship of historical famines with drought is complicated and not well understood. Using station‐based observations and simulations, we reconstruct soil moisture (agricultural) drought in India for the period 1870–2016. We show that over this century and a half period, India experienced seven major drought periods (1876–1882, 1895–1900, 1908–1924, 1937–1945, 1982–1990, 1997–2004, and 2011–2015) based on severity‐area‐duration analysis of reconstructed soil moisture. Out of six major famines (1873–74, 1876, 1877, 1896–97, 1899, and 1943) that occurred during 1870–2016, five are linked to soil moisture drought, and one (1943) was not. The three most deadly droughts (1877, 1896, and 1899) were linked with the positive phase of El Niño–Southern Oscillation. Five major droughts were not linked with famine, and three of those five nonfamine droughts occurred after Indian independence in 1947.

Abstract Seasonal water storage fluctuations are critical for evaluating water scarcity linked to climate forcing and human intervention. Here we compare seasonal changes in land total water storage anomalies using seven global hydrologic and land surface models (WGHM, PCR‐GLOBWB, and five GLDAS models) to GRACE satellite data in 183 river basins globally. This work builds on previous analysis that focused on total water storage anomaly trends. Results show that most models underestimate seasonal water storage amplitudes in tropical and (semi)arid basins and land surface models generally overestimate amplitudes in northern basins. Some models (CLM‐5.0 and PCR‐GLOBWB) agree better with GRACE than others. Causes of model‐GRACE discrepancies are attributed to missing storage compartments (e.g., surface water and/or groundwater) and underestimation of modeled storage capacities in tropical basins and to variations in modeled fluxes in northern basins. This study underscores the importance of considering water storage, in addition to water fluxes, to improve global models.

Abstract In the last two decades Europe experienced a series of high‐impact heat extremes. We here assess observed trends in temperature extremes at ECA&D stations in Europe. We demonstrate that on average across Europe the number of days with extreme heat and heat stress has more than tripled and hot extremes have warmed by 2.3 °C from 1950–2018. Over Central Europe, the warming exceeds the corresponding summer mean warming by 50%. Days with extreme cold temperatures have decreased by a factor of 2–3 and warmed by more than 3 °C, regionally substantially more than winter mean temperatures. Cold and hot extremes have warmed at about 94% of stations, a climate change signal that cannot be explained by internal variability. The clearest climate change signal can be detected in maximum heat stress. EURO‐CORDEX RCMs broadly capture observed trends but the majority underestimates the warming of hot extremes and overestimates the warming of cold extremes.

Abstract This study explores the early‐winter atmospheric response to Ural blocking anomalies in November, using a nudging technique to constrain the temperature and dynamics in a high‐top atmospheric model. Persistent Ural blocking anomalies in November are associated with a warm Arctic/cold Siberia pattern and increased upward planetary waves entering the stratosphere, leading to a warming of the polar vortex. This stratospheric response then propagates in the troposphere, leading to increased occurrence of the negative North Atlantic Oscillation in December and January. In contrast, simulations with perturbed Barents‐Kara sea ice and Siberian snow in November do not reproduce a significant atmospheric response. In simulations including a slab ocean, the Ural blocking induces Barents‐Kara sea ice and Siberia snow anomalies that resemble composite analyses from observations. These results highlight Ural blocking variability in November as a robust driver of early‐winter stratospheric warming while questioning causality between sea ice/snow and Ural blocking anomalies.

Abstract Using river centerlines created with Landsat images and the Shuttle Radar Topography Mission digital elevation model, we created spatially continuous maps of mean annual flow river width, slope, meander wavelength, sinuosity, and catchment area for all rivers wider than 90 m located between 60°N and 56°S. We analyzed the distributions of these properties, identified their typical ranges, and explored relationships between river planform and slope. We found width to be directly associated with the magnitude of meander wavelength and catchment area. Moreover, we found that narrower rivers show a larger range of slope and sinuosity values than wider rivers. Finally, by comparing simulated discharge from a water balance model with measured widths, we show that power laws between mean annual discharge and width can predict width typically to −35% to +81%, even when a single relationship is applied across all rivers with discharge ranging from 100 to 50,000 m 3 /s.

Abstract Many problems in climate science require extracting forced signals from a background of internal climate variability. We demonstrate that artificial neural networks (ANNs) are a useful addition to the climate science “toolbox” for this purpose. Specifically, forced patterns are detected by an ANN trained on climate model simulations under historical and future climate scenarios. By identifying spatial patterns that serve as indicators of change in surface temperature and precipitation, the ANN can determine the approximate year from which the simulations came without first explicitly separating the forced signal from the noise of both internal climate variability and model uncertainty. Thus, the ANN indicator patterns are complex, nonlinear combinations of signal and noise and are identified from the 1960s onward in simulated and observed surface temperature maps. This approach suggests that viewing climate patterns through an artificial intelligence (AI) lens has the power to uncover new insights into climate variability and change.

Abstract As Arctic temperatures rise at twice the global rate, sea ice is diminishing more quickly than models can predict. Processes that dictate Arctic cloud formation and impacts on the atmospheric energy budget are poorly understood, yet crucial for evaluating the rapidly changing Arctic. In parallel, warmer temperatures afford conditions favorable for productivity of microorganisms that can effectively serve as ice nucleating particles (INPs). Yet the sources of marine biologically derived INPs remain largely unknown due to limited observations. Here we show, for the first time, how biologically derived INPs were likely transported hundreds of kilometers from deep Bering Strait waters and upwelled to the Arctic Ocean surface to become airborne, a process dependent upon a summertime phytoplankton bloom, bacterial respiration, ocean dynamics, and wind‐driven mixing. Given projected enhancement in marine productivity, combined oceanic and atmospheric transport mechanisms may play a crucial role in provision of INPs from blooms to the Arctic atmosphere.

Abstract The El Niño–Southern Oscillation (ENSO) represents the largest source of year‐to‐year global climate variability. While Earth system models suggest a range of possible shifts in ENSO properties under continued greenhouse gas forcing, many centuries of preindustrial climate data are required to detect a potential shift in the properties of recent ENSO extremes. Here we reconstruct the strength of ENSO variations over the last 7,000 years with a new ensemble of fossil coral oxygen isotope records from the Line Islands, located in the central equatorial Pacific. The corals document a significant decrease in ENSO variance of ~20% from 3,000 to 5,000 years ago, coinciding with changes in spring/fall precessional insolation. We find that ENSO variability over the last five decades is ~25% stronger than during the preindustrial. Our results provide empirical support for recent climate model projections showing an intensification of ENSO extremes under greenhouse forcing.

Abstract Marine heatwaves (MHWs) are episodes of anomalous warming in the ocean, responsible for widespread impacts on marine ecosystems. For the first time summer MHW variability at surface and three ecosystem‐relevant depths of the upper Mediterranean Sea are assessed here for 1982–2017. We apply a MHW detection algorithm on a hindcast simulation, performed with a high‐resolution, fully coupled regional climate system model. Identified surface events last, on average, 15 days with a mean intensity of 0.6 °C above threshold and a maximum sea surface coverage of around 39%. Subsurface events are seasonally shifted and appear, on average, longer and more intense but less frequent and less extended in space than surface MHWs. We also find significant trends of increase in most MHW properties throughout the period, with severe surface MHWs detected for the first time in 2012, 2015, and 2017. However, MHW spatial ≪ hot spots ≫ are inhomogeneously distributed in surface and deeper layers.

Abstract Urban emissions remain an underexamined part of the methane budget. Here we present and interpret aircraft observations of six old and leak‐prone major cities along the East Coast of the United States. We use direct observations of methane (CH 4 ), carbon dioxide (CO 2 ), carbon monoxide (CO), ethane (C 2 H 6 ), and their correlations to quantify CH 4 emissions and attribute to natural gas. We find the five largest cities emit 0.85 (0.63, 1.12) Tg CH 4 /year, of which 0.75 (0.49, 1.10) Tg CH 4 /year is attributed to natural gas. Our estimates, which include all thermogenic methane sources including end use, are more than twice that reported in the most recent gridded EPA inventory, which does not include end‐use emissions. These results highlight that current urban inventory estimates of natural gas emissions are substantially low, either due to underestimates of leakage, lack of inclusion of end‐use emissions, or some combination thereof.

Abstract The dependence between extreme storm surges and wind waves is assessed statistically along the global coasts using the outputs of two numerical models consistently forced with the same atmospheric fields. We show that 55% of the world coastlines face compound storm surge wave extremes. Hence, for a given level of probability, neglecting these dependencies leads to underestimating extreme coastal water levels. Dependencies are dominant in midlatitudes and are likely underestimated in the tropics due to limited representation of tropical cyclones. Furthermore, we show that in half of the areas with dependence, the estimated probability of occurrence of coastal extreme water levels increases significantly when it is accounted for. Translated in terms of return periods, this means that along 30% of global coastlines, extreme water levels expected at most once in a century without considering dependence between storm surges and waves become a 1 in 50‐year event.

Abstract The methods to quantify equilibrium climate sensitivity are still debated. We collect millennial‐length simulations of coupled climate models and show that the global mean equilibrium warming is higher than those obtained using extrapolation methods from shorter simulations. Specifically, 27 simulations with 15 climate models forced with a range of CO 2 concentrations show a median 17% larger equilibrium warming than estimated from the first 150 years of the simulations. The spatial patterns of radiative feedbacks change continuously, in most regions reducing their tendency to stabilizing the climate. In the equatorial Pacific, however, feedbacks become more stabilizing with time. The global feedback evolution is initially dominated by the tropics, with eventual substantial contributions from the mid‐latitudes. Time‐dependent feedbacks underscore the need of a measure of climate sensitivity that accounts for the degree of equilibration, so that models, observations, and paleo proxies can be adequately compared and aggregated to estimate future warming.

Abstract We applied the chemical transport model GEOS‐Chem to examine the changes in aerosols and tropospheric O3 in China from 2012–2017 and the associated radiative forcing and health impact. Simulated surface layer concentrations and column burdens of aerosols and O3 were evaluated by comparing with ground‐based and satellite‐retrieved measurements. Between 2012 and 2017, simulated annual mean concentrations of PM2.5 decreased by 21.0%, while O3 increased by 11.9% over eastern China (20–45°N, 105–122.5°E). Changes in aerosols and O3 over 2012–2017 jointly exerted a positive radiative forcing of 1.26 W/m2 over eastern China, which was dominated by the less cooling from PM2.5 reductions (1.18 W/m2). The Global Exposure Mortality Model predicted 268.3 (247.3–291.6) thousand (9.6%) fewer deaths in eastern China in 2017 relative to 2012. These results suggest an appreciable health benefit and a potential warming as a consequence of clean air actions.

Abstract A probabilistic approach to describing El Niño–Southern Oscillation (ENSO), based on consideration of the signal‐to‐noise ratio for the coupled ocean‐atmosphere ENSO state, is presented. The ENSO signal is estimated using an ensemble of historical atmospheric model simulations forced by observed sea surface temperatures and sea ice during 1980–2016. The noise is estimated from departures of individual model realizations from their ensemble average when subjected to identical forcing. It is found that this atmospheric noise effect is substantial and yields considerable uncertainty in detecting the true coupled ENSO mode. This uncertainty exceeds analysis errors by an order of magnitude. Greater atmospheric noise is found to prevail during El Niño than La Niña, suggesting that the intensity of the monitored ENSO state during El Niño is prone to greater misattribution. Our results demonstrate that a deterministic state estimate of ENSO conditions may not be representative of the true real‐time coupled ENSO mode.

Abstract The July 2019 Ridgecrest, California, earthquake sequence produced cross‐fault ruptures from a Mw6.4 left‐lateral foreshock and a Mw7.1 right‐lateral mainshock. We use interferometric synthetic aperture radar and satellite optical imagery to characterize the surface displacements and subsurface fault slip characteristics of the sequence. We document ~46 km of surface rupture and peak slip values of ~5 m associated with the Mw7.1 and evidence that the two ruptures crossed each other. We additionally document evidence of triggered creep along 20–25 km of the central Garlock fault. Static stress change analysis shows that the foreshock sequence systematically promoted slip at the Mw7.1 hypocenter. Moreover, we find static stress changes promoted slip on the Garlock fault only in locations where we document surface creep, strongly indicating that the Garlock fault is sensitive to static stress changes. A potential rupture of the Garlock fault where slip was promoted could produce a Mw6.7–7.0 earthquake.

Abstract Urban land expansion is one of the most conspicuous aspects of urbanization and has profound impacts on regional climate change. Most studies, however, focus on its impacts on surface temperature, and possible effects on atmospheric humidity are less known. By examining the humidity changes in the Yangtze River Delta urban agglomeration of China during 1961–2014, we find a prominent urban dry island (UDI) effect in this urban agglomeration, as characterized by reduced humidity and increased vapor pressure deficit in the urban core area. In the past decades, the UDI effect has been significantly intensified by rapid urban land expansion. Urban expansion contributes to around half of the decrease in atmospheric humidity and the increase in vapor pressure deficit in urban areas. These effects are particularly stronger in wet hot summer and relatively weaker in cold dry winter. We suggest that the UDI effect should be considered in future urban planning, landscape design, and climate change assessment and mitigation.

Abstract Extreme precipitation often persists for multiple days with variable duration but has usually been examined at fixed duration. Here we show that considering extreme persistent precipitation by complete event with variable duration, rather than a fixed temporal period, is a necessary metric to account for the complexity of changing precipitation. Observed global mean annual‐maximum precipitation is significantly stronger (49.5%) for persistent extremes than daily extremes. However, both globally observed and modeled rates of relative increases are lower for persistent extremes compared to daily extremes, especially for Southern Hemisphere and large regions in the 0‐45°N latitude band. Climate models also show significant differences in the magnitude and partly even the sign of local mean changes between daily and persistent extremes in global warming projections. Changes in extreme precipitation therefore are more complex than previously reported, and extreme precipitation events with varying duration should be taken into account for future climate change assessments.

Abstract Climate sensitivity is a key metric used to assess the magnitude of global warming given increased CO2 concentrations. The geological past can provide insights into climate sensitivity; however, on timescales of millions of years, factors other than CO2 can drive climate, including paleogeographic forcing and solar luminosity. Here, through an ensemble of climate model simulations covering the period 150–35 million years ago, we show that climate sensitivity to CO2 doubling varies between ∼3.5 and 5.5 °C through this time. These variations can be explained as a nonlinear response to solar luminosity, evolving surface albedo due to changes in ocean area, and changes in ocean circulation. The work shows that the modern climate sensitivity is relatively low in the context of the geological record, as a result of relatively weak feedbacks due to a relatively low CO2 baseline, and the presence of ice and relatively small ocean area in the modern continental configuration.

Abstract Flowing stream networks extend and retract as their surrounding landscapes wet up and dry out, both seasonally and during rainstorms, with implications for aquatic ecosystems and greenhouse gas exchange. Some networks are much more dynamic than others, however, and the reasons for this difference are unknown. Here we show that the tendency of stream networks to extend and retract can be predicted from down‐valley changes in topographic attributes (slope, curvature, and contributing drainage area), without measuring subsurface hydrologic properties. Topography determines where water accumulates within valley networks, and we propose that it also modulates flow partitioning between the surface and subsurface. Measurements from 17 mountain stream networks support this hypothesis, showing that undissected valley heads have greater subsurface transport capacities than sharply incised valleys downstream. In catchments where broad valley heads rapidly transition to sharply incised valleys, subsurface transport capacity decreases abruptly, stabilizing stream length through wet and…

Abstract Long‐term seismic monitoring networks are well positioned to leverage advances in machine learning because of the abundance of labeled training data that curated event catalogs provide. We explore the use of convolutional and recurrent neural networks to accomplish discrimination of explosive and tectonic sources for local distances. Using a 5‐year event catalog generated by the University of Utah Seismograph Stations, we train models to produce automated event labels using 90‐s event spectrograms from three‐component and single‐channel sensors. Both network architectures are able to replicate analyst labels above 98%. Most commonly, model error is the result of label error (70% of cases). Accounting for mislabeled events (~1% of the catalog) model accuracy for both models increases to above 99%. Classification accuracy remains above 98% for shallow tectonic events, indicating that spectral characteristics controlled by event depth do not play a dominant role in event discrimination.

Abstract The assessment of return periods of extreme hydrological events often relies on statistical analysis using generalized extreme value (GEV) distributions. Here we compare the traditional GEV approach with a novel large ensemble approach to determine the added value of a direct, empirical distribution‐based estimate of extreme hydrological events. Using the global climate and hydrological models EC‐Earth and PCR‐GLOBWB, we simulate 2,000 years of global hydrology for a present‐day and 2 °C warmer climate. We show that the GEV method has inherent limitations in estimating changes in hydrological extremes, especially for compound hydrological events. The large ensemble method does not suffer from these limitations and quantifies the impacts of climate change with greater precision. The explicit simulation of extreme events enables better hydrological process understanding. We conclude that future studies focusing on the impact of climatic changes on hydrological extremes should use large ensemble techniques to properly account for these rare hydrological events.

Abstract The optical properties of atmospheric secondary brown carbon (BrC) aerosol are poorly understood because of its chemical complexity, and this has hampered quantitative assessments of the impacts of this light‐absorbing material on glaciers on the Tibetan Plateau. For this study, a statistical approach was developed to investigate BrC light absorption over the southeastern margin of the Tibetan Plateau. Secondary sources for BrC were more important for absorption than primary ones. A diurnal cycle in secondary BrC absorption was explained by the formation of light‐absorbing chromophores by photochemical oxidation after sunrise followed by photobleaching of the chromophores under the more oxidizing conditions as the day progressed. Multimethod analyses showed that biomass burning in northern Burma and along the Sino‐Burmese border was the most important source for the secondary BrC. The mean integrated simple forcing efficiency was 79 W/g, indicating that secondary BrC can cause substantial radiative effects.

Abstract Estimating thermal conductivity of snow, firn, and porous ice is key for modeling the thermal regime of alpine and polar glaciers. Whereas thermal conductivity of snow was widely investigated, studies on firn and porous ice are very scarce. This study presents the effective thermal conductivity tensor computed from 64 3‐D images of microstructures of snow, antarctic firn, and porous ice at −3, −20, and −60°C. We show that, in contrast with snow, conductivity of firn and porous ice correlates linearly with density, is approximately isotropic, and is largely impacted by temperature. We report that performances of commonly used estimates of thermal conductivity vary largely with density. In particular, formulas designed for snow lead to significant underestimations when applied to denser ice structures. We present a new formulation to accurately estimate the thermal conductivity throughout the whole density range, from fresh snow to bubbly ice, and for any temperature conditions encountered in glaciers.

Abstract Distributed acoustic sensing (DAS) is a recently developed technique that has demonstrated its utility in the oil and gas industry. Here we demonstrate the potential of DAS in teleseismic studies using the Goldstone OpticaL Fiber Seismic experiment in Goldstone, California. By analyzing teleseismic waveforms from the 10 January 2018 M7.5 Honduras earthquake recorded on ~5,000 DAS channels and the nearby broadband station GSC, we first compute receiver functions for DAS channels using the vertical‐component GSC velocity as an approximation for the incident source wavelet. The Moho P ‐to‐ s conversions are clearly visible on DAS receiver functions. We then derive meter‐scale arrival time measurements along the entire 20‐km‐long array. We are also able to measure path‐averaged Rayleigh wave group velocity and local Rayleigh wave phase velocity. The latter, however, has large uncertainties. Our study suggests that DAS will likely play an important role in many fields of passive seismology in the near future.

Abstract We use 2005–2016 observations of formaldehyde (HCHO) columns over China from the OMI, GOME‐2, and SCIAMACHY satellite instruments to evaluate long‐term trends in emission inventories of volatile organic compounds (VOCs) that affect air quality. The observations show large increases over 2005–2016 in the North China Plain (+1.1 ± 0.5% a−1 relative to 2005) and the Yangtze River Delta region (+1.5 ± 0.4% a−1 relative to 2005), consistent with the trend of anthropogenic VOC emissions in the Multi‐resolution Emission Inventory for China (MEIC). Unlike other pollutants, VOC emissions have not been decreasing in recent years. An exception is the Huai River Basin in rural eastern China where the satellite data show rapidly decreasing VOC emissions since the early 2010s that appear to reflect bans on agricultural fires.

Abstract Climate models project that extreme precipitation events will intensify in proportion to their intensity during the 21st century at large spatial scales. The identification of the causes of this phenomenon nevertheless remains tenuous. Using a large ensemble of North American regional climate simulations, we show that the more rapid intensification of more extreme events also appears as a robust feature at finer regional scales. The larger increases in more extreme events than in less extreme events are found to be primarily due to atmospheric circulation changes. Thermodynamically induced changes have relatively uniform effects across extreme events and regions. In contrast, circulation changes weaken moderate events over western interior regions of North America and enhance them elsewhere. The weakening effect decreases and even reverses for more extreme events, whereas there is further intensification over other parts of North America, creating an “intense gets intenser” pattern over most of the continent.

Abstract The National Aeronautics and Space Administration Global‐scale Observations of the Limb and Disk ultraviolet spectrograph has been imaging the equatorial ionization anomaly (EIA), regions of the ionosphere with enhanced electron density north and south of the magnetic equator, since October 2018. The initial 3 months of observations was during solar minimum conditions, and they included observations in December solstice of unanticipated variability and depleted regions. Depletions are seen on most nights, in contrast to expectations from previous space‐based observations. The variety of scales and morphologies also pose challenges to understanding of the EIA. Abrupt changes in the EIA location, which could be related to in situ measurements of large‐scale depletion regions, are observed on some nights. Such synoptic‐scale disruptions have not been previously identified.

Abstract Wintertime ammonium nitrate aerosol pollution is a severe air quality issue affecting both developed and rapidly urbanizing regions from Europe to East Asia. In the United States, it is acute in western basins subject to inversions that confine pollutants near the surface. Measurements and modeling of a wintertime pollution episode in Salt Lake Valley, Utah, demonstrate that ammonium nitrate is closely related to photochemical ozone through a common parameter, total odd oxygen, Ox,total. We show that the traditional nitrogen oxide and volatile organic compound (NOx‐VOC) framework for evaluating ozone mitigation strategies also applies to ammonium nitrate. Despite being nitrate‐limited, ammonium nitrate aerosol pollution in Salt Lake Valley is responsive to VOCs control and, counterintuitively, not initially responsive to NOx control. We demonstrate simultaneous nitrate limitation and NOx saturation and suggest this phenomenon may be general. This finding may identify an unrecognized control strategy to address a global public health issue in regions with severe winter…

Abstract Hurricane Maria was associated with record‐breaking rainfall over Puerto Rico and caused unprecedented flooding and landslides. Here we analyze the extreme rainfall produced by Hurricane Maria using 35 stations with daily precipitation data from 1956–2016. A covariate‐based extreme value analysis point process approach that accounts for natural climate variability and long‐term climate change influences on extreme rainfall is applied. Hurricane Maria produced the single largest maximum rainfall event since 1956 and had the highest total averaged precipitation of 129 storms that have impacted the island since 1956. Return periods for an event of Hurricane Maria's precipitation magnitude decreased in 48.6% of stations across Puerto Rico and at least halved when averaged across the island. Within the most affected areas it is likely that the probability of precipitation of Maria's magnitude has increased by a factor greater than 1 (best estimate 4.85) as a result of long‐term climate trends.

Abstract This study demonstrates the maturing ability of the half‐hourly precipitation estimates from the Integrated Multi‐satellitE Retrievals for GPM (IMERG) for use in global analyses of the diurnal cycle. The refined intercalibration and interpolation between the sensors in V06 leads to greater consistency in the precipitation retrievals over different hours of the day. Evaluation against ground measurements suggests a slight lag in the diurnal phase of only +0.59 hr. We demonstrate the diurnal cycle over different regions around the globe, including the Maritime Continent, where accurate representation of precipitation variability in global models remains a challenge. Using examples over Singapore, Bangladesh, and Lake Victoria, we reveal the intricate interplay between diurnal and seasonal variability. This study demonstrates the unprecedented capability of IMERG in capturing the diurnal cycle of precipitation globally, potentially advancing our understanding in regions of sparse ground measurements and supporting improvements in its representation in global models.