The 50 most-cited articles in Geophysical Research Letters, 2017

Abstract Spaceborne digital elevation models (DEMs) are a fundamental input for many geoscience studies, but they still include nonnegligible height errors. Here we introduce a high‐accuracy global DEM at 3″ resolution (~90 m at the equator) by eliminating major error components from existing DEMs. We separated absolute bias, stripe noise, speckle noise, and tree height bias using multiple satellite data sets and filtering techniques. After the error removal, land areas mapped with ±2 m or better vertical accuracy were increased from 39% to 58%. Significant improvements were found in flat regions where height errors larger than topography variability, and landscapes such as river networks and hill‐valley structures, became clearly represented. We found the topography slope of previous DEMs was largely distorted in most of world major floodplains (e.g., Ganges, Nile, Niger, and Mekong) and swamp forests (e.g., Amazon, Congo, and Vasyugan). The newly developed DEM will enhance many geoscience applications which are terrain dependent.

Greenland's bed topography is a primary control on ice flow, grounding line migration, calving dynamics, and subglacial drainage. Moreover, fjord bathymetry regulates the penetration of warm Atlantic water (AW) that rapidly melts and undercuts Greenland's marine-terminating glaciers. Here we present a new compilation of Greenland bed topography that assimilates seafloor bathymetry and ice thickness data through a mass conservation approach. A new 150 m horizontal resolution bed topography/bathymetric map of Greenland is constructed with seamless transitions at the ice/ocean interface, yielding major improvements over previous data sets, particularly in the marine-terminating sectors of northwest and southeast Greenland. Our map reveals that the total sea level potential of the Greenland ice sheet is 7.42 ± 0.05 m, which is 7 cm greater than previous estimates. Furthermore, it explains recent calving front response of numerous outlet glaciers and reveals new pathways by which AW can access glaciers with marine-based basins, thereby highlighting sectors of Greenland that are most…

Abstract Even though knowing the contributions of transpiration (T), soil and open water evaporation (E), and interception (I) to terrestrial evapotranspiration (ET = T + E + I) is crucial for understanding the hydrological cycle and its connection to ecological processes, the fraction of T is unattainable by traditional measurement techniques over large scales. Previously reported global mean T/(E + T + I) from multiple independent sources, including satellite‐based estimations, reanalysis, land surface models, and isotopic measurements, varies substantially from 24% to 90%. Here we develop a new ET partitioning algorithm, which combines global evapotranspiration estimates and relationships between leaf area index (LAI) and T/(E + T) for different vegetation types, to upscale a wide range of published site‐scale measurements. We show that transpiration accounts for about 57.2% (with standard deviation ± 6.8%) of global terrestrial ET. Our approach bridges the scale gap between site measurements and global model simulations,and can be simply implemented into current global climate…

Abstract In the western United States, the seasonal phase of snow storage bridges between winter‐dominant precipitation and summer‐dominant water demand. The critical role of snow in water supply has been frequently quantified using the ratio of snowmelt‐derived runoff to total runoff. However, current estimates of the fraction of annual runoff generated by snowmelt are not based on systematic analyses. Here based on hydrological model simulations and a new snowmelt tracking algorithm, we show that 53% of the total runoff in the western United States originates as snowmelt, despite only 37% of the precipitation falling as snow. In mountainous areas, snowmelt is responsible for 70% of the total runoff. By 2100, the contribution of snowmelt to runoff will decrease by one third for the western U.S. in the Intergovernmental Panel on Climate Change Representative Concentration Pathway 8.5 scenario. Snowmelt‐derived runoff currently makes up two thirds of the inflow to the region's major reservoirs. We argue that substantial impacts on water supply are likely in a warmer climate.

Abstract Uncertainties of climate projections are routinely assessed by considering simulations from different models. Observations are used to evaluate models, yet there is a debate about whether and how to explicitly weight model projections by agreement with observations. Here we present a straightforward weighting scheme that accounts both for the large differences in model performance and for model interdependencies, and we test reliability in a perfect model setup. We provide weighted multimodel projections of Arctic sea ice and temperature as a case study to demonstrate that, for some questions at least, it is meaningless to treat all models equally. The constrained ensemble shows reduced spread and a more rapid sea ice decline than the unweighted ensemble. We argue that the growing number of models with different characteristics and considerable interdependence finally justifies abandoning strict model democracy, and we provide guidance on when and how this can be achieved robustly.

Abstract Our understanding of subsurface processes suffers from a profound observation bias: seismometers are sparse and clustered on continents. A new seismic recording approach, distributed acoustic sensing (DAS), transforms telecommunication fiber‐optic cables into sensor arrays enabling meter‐scale recording over tens of kilometers of linear fiber length. We analyze cataloged earthquake observations from three DAS arrays with different horizontal geometries to demonstrate some possibilities using this technology. In Fairbanks, Alaska, we find that stacking ground motion records along 20 m of fiber yield a waveform that shows a high degree of correlation in amplitude and phase with a colocated inertial seismometer record at 0.8–1.6 Hz. Using an L‐shaped DAS array in Northern California, we record the nearly vertically incident arrival of an earthquake from The Geysers Geothermal Field and estimate its backazimuth and slowness via beamforming for different phases of the seismic wavefield. Lastly, we install a fiber in existing telecommunications conduits below Stanford University…

Abstract We apply machine learning to data sets from shear laboratory experiments, with the goal of identifying hidden signals that precede earthquakes. Here we show that by listening to the acoustic signal emitted by a laboratory fault, machine learning can predict the time remaining before it fails with great accuracy. These predictions are based solely on the instantaneous physical characteristics of the acoustical signal and do not make use of its history. Surprisingly, machine learning identifies a signal emitted from the fault zone previously thought to be low‐amplitude noise that enables failure forecasting throughout the laboratory quake cycle. We infer that this signal originates from continuous grain motions of the fault gouge as the fault blocks displace. We posit that applying this approach to continuous seismic data may lead to significant advances in identifying currently unknown signals, in providing new insights into fault physics, and in placing bounds on fault failure times.

Abstract The Tibetan Plateau (TP), the highest and largest plateau in the world, with complex and competing cryospheric‐hydrologic‐geodynamic processes, is particularly sensitive to anthropogenic warming. The quantitative water mass budget in the TP is poorly known. Here we examine annual changes in lake area, level, and volume during 1970s–2015. We find that a complex pattern of lake volume changes during 1970s–2015: a slight decrease of −2.78 Gt yr −1 during 1970s–1995, followed by a rapid increase of 12.53 Gt yr −1 during 1996–2010, and then a recent deceleration (1.46 Gt yr −1 ) during 2011–2015. We then estimated the recent water mass budget for the Inner TP, 2003–2009, including changes in terrestrial water storage, lake volume, glacier mass, snow water equivalent (SWE), soil moisture, and permafrost. The dominant components of water mass budget, namely, changes in lake volume (7.72 ± 0.63 Gt yr −1 ) and groundwater storage (5.01 ± 1.59 Gt yr −1 ), increased at similar rates. We find that increased net precipitation contributes the majority of water supply (74%) for the lake…

Abstract Fusing satellite observations and station measurements to estimate ground‐level PM 2.5 is promising for monitoring PM 2.5 pollution. A geo‐intelligent approach, which incorporates geographical correlation into an intelligent deep learning architecture, is developed to estimate PM 2.5 . Specifically, it considers geographical distance and spatiotemporally correlated PM 2.5 in a deep belief network (denoted as Geoi‐DBN). Geoi‐DBN can capture the essential features associated with PM 2.5 from latent factors. It was trained and tested with data from China in 2015. The results show that Geoi‐DBN performs significantly better than the traditional neural network. The out‐of‐sample cross‐validation R 2 increases from 0.42 to 0.88, and RMSE decreases from 29.96 to 13.03 μg/m 3 . On the basis of the derived PM 2.5 distribution, it is predicted that over 80% of the Chinese population live in areas with an annual mean PM 2.5 of greater than 35 μg/m 3 . This study provides a new perspective for air pollution monitoring in large geographic regions.

Abstract This study provides evidence of substantial increases in atmospheric ammonia (NH3) concentrations (14 year) over several of the worlds major agricultural regions, using recently available retrievals from the Atmospheric Infrared Sounder (AIRS) aboard NASA's Aqua satellite. The main sources of atmospheric NH3 are farming and animal husbandry involving reactive nitrogen ultimately derived from fertilizer use; rates of emission are also sensitive to climate change. Significant increasing trends are seen over the U.S. (2.61% yr−1), the European Union (EU) (1.83% yr−1), and China (2.27% yr−1). Over the EU, the trend results from decreased scavenging by acid aerosols. Over the U.S., the increase results from a combination of decreased chemical loss and increased soil temperatures. Over China, decreased chemical loss, increasing temperatures, and increased fertilizer use all play a role. Over South Asia, increased NH3 emissions are masked by increased SO2 and NOx emissions, leading to increased aerosol loading and adverse health effects.

The Juno spacecraft has measured Jupiter's low‐order, even gravitational moments, J 2 – J 8 , to an unprecedented precision, providing important constraints on the density profile and core mass of the planet. Here we report on a selection of interior models based on ab initio computer simulations of hydrogen‐helium mixtures. We demonstrate that a dilute core, expanded to a significant fraction of the planet's radius, is helpful in reconciling the calculated J n with Juno 's observations. Although model predictions are strongly affected by the chosen equation of state, the prediction of an enrichment of Z in the deep, metallic envelope over that in the shallow, molecular envelope holds. We estimate Jupiter's core to contain a 7–25 Earth mass of heavy elements. We discuss the current difficulties in reconciling measured J n with the equations of state and with theory for formation and evolution of the planet.

Abstract Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high‐resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high‐resolution simulations, for example, of clouds and convection, through matching low‐order statistics between ESMs, observations, and high‐resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.

Abstract Record rainfall amounts were recorded during Hurricane Harvey in the Houston, Texas, area, leading to widespread flooding. We analyze observed precipitation from the Global Historical Climatology Network with a covariate‐based extreme value statistical analysis, accounting for both the external influence of global warming and the internal influence of El Niño–Southern Oscillation. We find that human‐induced climate change likely increased the chances of the observed precipitation accumulations during Hurricane Harvey in the most affected areas of Houston by a factor of at least 3.5. Further, precipitation accumulations in these areas were likely increased by at least 18.8% (best estimate of 37.7%), which is larger than the 6–7% associated with an attributable warming of 1°C in the Gulf of Mexico and Clausius‐Clapeyron scaling. In a Granger causality sense, these statements provide lower bounds on the impact of climate change and motivate further attribution studies using dynamical climate models.

Abstract A global climatology and database of mixed layer properties are computed from nearly 1,250,000 Argo profiles. The climatology is calculated with both a hybrid algorithm for detecting the mixed layer depth (MLD) and a standard threshold method. The climatology provides accurate information about the depth, properties, extent, and seasonal patterns of global mixed layers. The individual profile results in the database can be used to construct time series of mixed layer properties in specific regions of interest. The climatology and database are available online at http://mixedlayer.ucsd.edu . The MLDs calculated by the hybrid algorithm are shallower and generally more accurate than those of the threshold method, particularly in regions of deep winter mixed layers; the new climatology differs the most from existing mixed layer climatologies in these regions. Examples are presented from the Labrador and Irminger Seas, the Southern Ocean, and the North Atlantic Ocean near the Gulf Stream. In these regions the threshold method tends to overestimate winter MLDs by approximately…

Abstract The Soil Moisture Active Passive (SMAP) mission has delivered valuable sensing of surface soil moisture since 2015. However, it has a short time span and irregular revisit schedules. Utilizing a state‐of‐the‐art time series deep learning neural network, Long Short‐Term Memory (LSTM), we created a system that predicts SMAP level‐3 moisture product with atmospheric forcings, model‐simulated moisture, and static physiographic attributes as inputs. The system removes most of the bias with model simulations and improves predicted moisture climatology, achieving small test root‐mean‐square errors (<0.035) and high‐correlation coefficients >0.87 for over 75% of Continental United States, including the forested southeast. As the first application of LSTM in hydrology, we show the proposed network avoids overfitting and is robust for both temporal and spatial extrapolation tests. LSTM generalizes well across regions with distinct climates and environmental settings. With high fidelity to SMAP, LSTM shows great potential for hindcasting, data assimilation, and weather forecasting.

Abstract Regional hot extremes are projected to increase more strongly than global mean temperature, with substantially larger changes than 2°C even if global warming is limited to this level. We investigate the role of soil moisture‐temperature feedbacks for this response based on multimodel experiments for the 21st century with either interactive or fixed (late 20th century mean seasonal cycle) soil moisture. We analyze changes in the hottest days in each year in both sets of experiments, relate them to the global mean temperature increase, and investigate processes leading to these changes. We find that soil moisture‐temperature feedbacks significantly contribute to the amplified warming of the hottest days compared to that of global mean temperature. This contribution reaches more than 70% in Central Europe and Central North America. Soil moisture trends are more important for this response than short‐term soil moisture variability. These results are relevant for reducing uncertainties in regional temperature projections.

Abstract During austral spring 2016 Antarctic sea ice extent (SIE) decreased at a record rate of 75 × 10 3 km 2 d −1 , which was 46% faster than the mean rate and 18% faster than in any previous spring season during the satellite era. The decrease of sea ice area was also exceptional and 28% greater than the mean. Anomalous negative retreat occurred in all sectors of the Antarctic but was greatest in the Weddell and Ross Seas. Record negative SIE anomalies for the day of year were recorded from 3 November 2016 to 9 April 2017. Rapid ice retreat in the Weddell Sea took place in strong northerly flow after an early maximum ice extent in late August. Rapid ice retreat occurred in November in the Ross Sea when surface pressure was at a record high level, with the Southern Annular Mode at its most negative for that month since 1968.

Abstract In order to better manage anthropogenic CO2 emissions, improved methods of quantifying emissions are needed at all spatial scales from the national level down to the facility level. Although the Orbiting Carbon Observatory 2 (OCO‐2) satellite was not designed for monitoring power plant emissions, we show that in some cases, CO2 observations from OCO‐2 can be used to quantify daily CO2 emissions from individual middle‐ to large‐sized coal power plants by fitting the data to plume model simulations. Emission estimates for U.S. power plants are within 1–17% of reported daily emission values, enabling application of the approach to international sites that lack detailed emission information. This affirms that a constellation of future CO2 imaging satellites, optimized for point sources, could monitor emissions from individual power plants to support the implementation of climate policies.

Abstract Here we show that the characteristics of the Indian Ocean Dipole (IOD), such as its power spectrum and phase relationship with the El Niño–Southern Oscillation (ENSO), can be succinctly explained by ENSO combination mode (C‐mode) wind and heat flux forcing together with a seasonal modulation of the air/sea coupled Indian Ocean (IO) Bjerknes feedback. This model explains the observed high‐frequency near‐annual IOD variability in terms of deterministic ENSO/annual cycle interactions. ENSO‐independent IOD events can be understood as a seasonally modulated ocean response to white noise atmospheric forcing. Under this new physical null hypothesis framework, IOD predictability is determined by both ENSO predictability and the ENSO signal‐to‐noise ratio. We further emphasize that lead/lag correlations between different climate variables are easily misinterpreted when not accounting properly for the seasonal modulation of the underlying climate phenomena.

Abstract Aerosol acidity plays an important role in atmospheric chemistry. China emits large amounts of SO 2 , NO x , and NH 3 into the atmosphere, but aerosol acidity is poorly characterized. In this study, simultaneous 1 h measurements of particulate and gaseous compositions along with the ISORROPIA‐II thermodynamic equilibrium model were used to study aerosol acidity during severe haze episodes in northern China. The summed concentration of sulfate, nitrate, and ammonium was 135 ± 51 μg/m 3 with a maximum of 250 μg/m 3 , and the gas‐phase NH 3 mixing ratio was 22 ± 9 ppb. Fine particles were moderately acidic, with a pH range of 3.0–4.9 and an average of 4.2, which was higher than those in the United States and Europe. Excess NH 3 and high aerosol water content are responsible for the relatively lower aerosol acidity. These results suggest that the new pathways for sulfate production in China proposed by recent studies should be revisited.

Abstract The large socioeconomic costs of droughts make them a crucial target for impact assessments of climate change scenarios. Using multiple drought metrics and a set of simulations with the Community Earth System Model targeting 1.5°C and 2°C above preindustrial global mean temperatures, we investigate changes in aridity and the risk of consecutive drought years. If warming is limited to 2°C, these simulations suggest little change in drought risk for the U.S. Southwest and Central Plains compared to present day. In the Mediterranean and central Europe, however, drought risk increases significantly for both 1.5°C and 2°C warming targets, and the additional 0.5°C of the 2°C climate leads to significantly higher drought risk. Our study suggests that limiting anthropogenic warming to 1.5°C rather than 2°C, as aspired to by the Paris Climate Agreement, may have benefits for future drought risk but that such benefits may be regional and in some cases highly uncertain.

Abstract A new method for automatic detection of atmospheric rivers (ARs) is developed and applied to an atmospheric reanalysis, yielding an extensive catalog of ARs land‐falling along the west coast of North America during 1948–2017. This catalog provides a large array of variables that can be used to examine AR cases and their climate‐scale variability in exceptional detail. The new record of AR activity, as presented, validated and examined here, provides a perspective on the seasonal cycle and the interannual‐interdecadal variability of AR activity affecting the hydroclimate of western North America. Importantly, AR intensity does not exactly follow the climatological pattern of AR frequency. Strong links to hydroclimate are demonstrated using a high‐resolution precipitation data set. We describe the seasonal progression of AR activity and diagnose linkages with climate variability expressed in Pacific sea surface temperatures, revealing links to Pacific decadal variability, recent regional anomalies, as well as a generally rising trend in land‐falling AR activity. The latter…

Abstract Subtle but important differences are identified between the 1997/1998 and 2015/2016 extreme El Niños that reflect fundamental differences in their underlying dynamics. The 1997/1998 event is found to evolve following the eastern Pacific El Niño dynamics that relies on basin‐wide thermocline variations, whereas the 2015/2016 event involves additionally the central Pacific (CP) El Niño dynamics that depends on subtropical forcing. The stronger CP dynamics during the 2015/2016 event resulted in its sea surface temperature (SST) anomalies lingering around the International Date Line during the decaying phase, which is in contrast to the retreat of the anomalies toward the South American Coast during the decaying phase of the 1997/1998 event. The different SST evolution excited different wave trains resulting in the western U.S. not receiving the same above‐normal rainfall during the 2015/2016 El Niño as it did during the 1997/1998 El Niño. Ensemble model experiments are conducted to confirm the different climate impacts of the two El Niños.

Abstract The Amundsen Sea sector is experiencing the largest mass loss, glacier acceleration, and grounding line retreat in Antarctica. Enhanced intrusion of Circumpolar Deep Water onto the continental shelf has been proposed as the primary forcing mechanism for the retreat. Here we investigate the dynamics and evolution of Thwaites Glacier with a novel, fully coupled, ice‐ocean numerical model. We obtain a significantly improved agreement with the observed pattern of glacial retreat using the coupled model. Coupled simulations over the coming decades indicate a continued mass loss at a sustained rate. Uncoupled simulations using a depth‐dependent parameterization of sub‐ice‐shelf melt significantly overestimate the rate of grounding line retreat compared to the coupled model, as the parameterization does not capture the complexity of the ocean circulation associated with the formation of confined cavities during the retreat. Bed topography controls the pattern of grounding line retreat, while oceanic thermal forcing impacts the rate of grounding line retreat. The importance of…

Abstract Climate models have consistently projected a drying trend in the southwestern United States, aiding speculation of increasing dust storms in this region. Long‐term climatology is essential to documenting the dust trend and its response to climate variability. We have reconstructed long‐term dust climatology in the western United States, based on a comprehensive dust identification method and continuous aerosol observations from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network. We report here direct evidence of rapid intensification of dust storm activity over American deserts in the past decades (1988–2011), in contrast to reported decreasing trends in Asia and Africa. The frequency of windblown dust storms has increased 240% from 1990s to 2000s. This dust trend is associated with large‐scale variations of sea surface temperature in the Pacific Ocean, with the strongest correlation with the Pacific Decadal Oscillation. We further investigate the relationship between dust and Valley fever, a fast‐rising infectious disease caused by inhaling…

Abstract The evidence for abundant liquid water on early Mars despite the faint young Sun is a long‐standing problem in planetary research. Here we present new ab initio spectroscopic and line‐by‐line climate calculations of the warming potential of reduced atmospheres on early Mars. We show that the strength of both CO2–H2 and CO2–CH4 collision‐induced absorption (CIA) has previously been significantly underestimated. Contrary to previous expectations, methane could have acted as a powerful greenhouse gas on early Mars due to CO2–CH4 CIA in the critical 250–500 cm−1 spectral window region. In atmospheres of 0.5 bar CO2 or more, percent levels of H2 or CH4 raise annual mean surface temperatures by tens of degrees, with temperatures reaching 273 K for pressures of 1.25–2 bars and 2–10% of H2 and CH4. Methane and hydrogen produced following aqueous alteration of Mars' crust could have combined with volcanically outgassed CO2 to form transient atmospheres of this composition 4.5–3.5 Ga. Our results also suggest that inhabited exoplanets could retain surface liquid water at significant…

Abstract Historic observations of dissolved oxygen (O 2 ) in the ocean are analyzed to quantify multidecadal trends and variability from 1958 to 2015. Additional quality control is applied, and the resultant oxygen anomaly field is used to quantify upper ocean O 2 trends at global and hemispheric scales. A widespread negative O 2 trend is beginning to emerge from the envelope of interannual variability. Ocean reanalysis data are used to evaluate relationships with changes in ocean heat content (OHC) and oxygen solubility (O 2,sat ). Global O 2 decline is evident after the 1980s, accompanied by an increase in global OHC. The global upper ocean O 2 inventory (0–1000 m) changed at the rate of −243 ± 124 T mol O 2 per decade. Further, the O 2 inventory is negatively correlated with the OHC ( r = −0.86; 0–1000 m) and the regression coefficient of O 2 to OHC is approximately −8.2 ± 0.66 nmol O 2 J −1 , on the same order of magnitude as the simulated O 2 ‐heat relationship typically found in ocean climate models. Variability and trends in the observed upper ocean O 2 concentration are…

Abstract Increases in the severity and frequency of drought in a warming climate may negatively impact agricultural production and food security. Unlike previous studies that have estimated agricultural impacts of climate condition using single‐crop yield distributions, we develop a multivariate probabilistic model that uses projected climatic conditions (e.g., precipitation amount or soil moisture) throughout a growing season to estimate the probability distribution of crop yields. We demonstrate the model by an analysis of the historical period 1980–2012, including the Millennium Drought in Australia (2001–2009). We find that precipitation and soil moisture deficit in dry growing seasons reduced the average annual yield of the five largest crops in Australia (wheat, broad beans, canola, lupine, and barley) by 25–45% relative to the wet growing seasons. Our model can thus produce region‐ and crop‐specific agricultural sensitivities to climate conditions and variability. Probabilistic estimates of yield may help decision‐makers in government and business to quantitatively assess the…

Abstract Understanding the evolution and physical drivers of drought is critical to informing forecasting efforts. One aspect that has seldom been explored is the joint evolution of droughts in space and time. Most studies fix the reference area and focus on their temporal variability or study their spatial heterogeneity over fixed durations. This work implements a Lagrangian approach by aggregating contiguous areas under drought into clusters. These clusters become the frame of reference and are tracked as they evolve through space and time. Clusters were identified from soil moisture data from the Climate Forecast System Reanalysis (1979–2009). Evapotranspiration, moisture fluxes, and precipitation were used to explore the relevance of possible mechanisms of drought propagation. While most droughts remain near their origin, the centroid of 10% of clusters traveled at least 1400–3100 km, depending on the continent. This approach also revealed that large‐scale droughts often lock into further growth and intensification.

Abstract Projected future changes in global tropical cyclone (TC) activity are assessed using 5,000 year scale ensemble simulations for both current and 4 K surface warming climates with a 60 km global atmospheric model. The global number of TCs decreases by 33% in the future projection. Although geographical TC occurrences decrease generally, they increase in the central and eastern parts of the extra tropical North Pacific. Meanwhile, very intense (category 4 and 5) TC occurrences increase over a broader area including the south of Japan and south of Madagascar. The global number of category 4 and 5 TCs significantly decreases, contrary to the increase seen in several previous studies. Lifetime maximum surface wind speeds and precipitation rate are amplified globally. Regional TC activity changes have large uncertainty corresponding to sea surface temperature warming patterns. TC‐resolving large‐ensemble simulations provide useful information, especially for policy making related to future climate change.

Abstract We revisit the global mean sea level (GMSL) budget during the whole altimetry era (January 1993 to December 2015) using a large number of data sets. The budget approach allows quantifying the TOPEX A altimeter drift (amounting 1.5 ± 0.5 mm/yr over 1993–1998). Accounting for this correction and using ensemble means for the GMSL and components lead to closure of the sea level budget (trend of the residual time series being 0.0 ± 0.22 mm/yr). The new GMSL rate over January 1993 to December 2015 is now close to 3.0 mm/yr. An important increase of the GMSL rate, of 0.8 mm/yr, is found during the second half of the altimetry era (2004–2015) compared to the 1993–2004 time span, mostly due to Greenland mass loss increase and also to slight increase of all other components of the budget.

Abstract The urban agglomeration of Yangtze River Delta (YRD) is emblematic of China's rapid urbanization during the past decades. Based on homogenized daily maximum and minimum temperature data, the contributions of urbanization to trends of summer extreme temperature indices (ETIs) in YRD are evaluated. Dynamically classifying the observational stations into urban and rural, this study presents unexplored changes in temperature extremes during the past four decades in YRD and quantifies the amplification of the positive trends in ETIs by the urban heat island effect. Overall, urbanization contributes to more than one third of the increase of intensity of extreme heat events in the region, which is comparable to the contribution of greenhouse gases. Compared to rural stations, more notable shifts to the right in the probability distribution of temperature and ETIs are found in urban stations. The rapid urbanization in YRD has resulted in large increases in the risk of heat extremes.

Abstract Antarctica is the largest reservoir of ice on Earth. Understanding its ice sheet dynamics is crucial to unraveling past global climate change and making robust climatic and sea level predictions. Of the basic parameters that shape and control ice flow, the most poorly known is geothermal heat flux. Direct observations of heat flux are difficult to obtain in Antarctica, and until now continent‐wide heat flux maps have only been derived from low‐resolution satellite magnetic and seismological data. We present a high‐resolution heat flux map and associated uncertainty derived from spectral analysis of the most advanced continental compilation of airborne magnetic data. Small‐scale spatial variability and features consistent with known geology are better reproduced than in previous models, between 36% and 50%. Our high‐resolution heat flux map and its uncertainty distribution provide an important new boundary condition to be used in studies on future subglacial hydrology, ice sheet dynamics, and sea level change.

Abstract Irrigation can influence weather and climate, but the magnitude, timing, and spatial extent of irrigation are poorly represented in models, as are the resulting impacts of irrigation on the coupled land‐atmosphere system. One way to improve irrigation representation in models is to assimilate soil moisture observations that reflect an irrigation signal to improve model states. Satellite remote sensing is a promising avenue for obtaining these needed observations on a routine basis, but to date, irrigation detection in passive microwave satellites has proven difficult. In this study, results show that the new enhanced soil moisture product from the Soil Moisture Active Passive satellite is able to capture irrigation signals over three semiarid regions in the western United States. This marks an advancement in Earth‐observing satellite skill and the ability to monitor human impacts on the water cycle.

Abstract Near‐surface air temperatures close to 0°C were observed in situ over sea ice in the central Arctic during the last three winter seasons. Here we use in situ winter (December–March) temperature observations, such as those from Soviet North Pole drifting stations and ocean buoys, to determine how common Arctic winter warming events are. Observations of winter warming events exist over most of the Arctic Basin. Temperatures exceeding −5°C were observed during >30% of winters from 1954 to 2010 by North Pole drifting stations or ocean buoys. Using the ERA‐Interim record (1979–2016), we show that the North Pole (NP) region typically experiences 10 warming events (T2m > −10°C) per winter, compared with only five in the Pacific Central Arctic (PCA). There is a positive trend in the overall duration of winter warming events for both the NP region (4.25 days/decade) and PCA (1.16 days/decade), due to an increased number of events of longer duration.

Abstract Although it has been documented that daily precipitation extremes are increasing worldwide, faster increases may be expected for subdaily extremes. Here after a careful quality control procedure, we compared trends in hourly and daily precipitation extremes using a large network of stations across the United States (U.S.) within the 1950–2011 period. A greater number of significant increasing trends in annual and seasonal maximum precipitation were detected from daily extremes, with the primary exception of wintertime. Our results also show that the mean percentage change in annual maximum daily precipitation across the U.S. per global warming degree is ~6.9% °C−1 (in agreement with the Clausius‐Clapeyron rate) while lower sensitivities were observed for hourly extremes, suggesting that changes in the magnitude of subdaily extremes in response to global warming emerge more slowly than those for daily extremes in the climate record.

Abstract The mechanisms leading to large earthquakes are poorly understood and documented. Here we characterize the long‐term precursory phase of the 1 April 2014 M w 8.1 North Chile megathrust. We show that a group of coastal GPS stations accelerated westward 8 months before the main shock, corresponding to a M w 6.5 slow slip event on the subduction interface, 80% of which was aseismic. Concurrent interface foreshocks underwent a diminution of their radiation at high frequency, as shown by the temporal evolution of Fourier spectra and residuals with respect to ground motions predicted by recent subduction models. Such ground motions change suggests that in response to the slow sliding of the subduction interface, seismic ruptures are progressively becoming smoother and/or slower. The gradual propagation of seismic ruptures beyond seismic asperities into surrounding metastable areas could explain these observations and might be the precursory mechanism eventually leading to the main shock.

Abstract The 2016 austral spring was characterized by the lowest Southern Hemisphere (SH) sea ice extent seen in the satellite record (1979 to present) and coincided with anomalously warm surface waters surrounding most of Antarctica. We show that two distinct processes contributed to this event: First, the extreme El Niño event peaking in December–February 2015/2016 contributed to pronounced extratropical SH sea surface temperature and sea ice extent anomalies in the eastern Ross, Amundsen, and Bellingshausen Seas that persisted in part until the following 2016 austral spring. Second, internal unforced atmospheric variability of the Southern Annular Mode promoted the exceptional low sea ice extent in November–December 2016. These results suggest that a combination of tropically forced and internal SH atmospheric variability contributed to the unprecedented sea ice decline during the 2016 austral spring, on top of a background of slow changes expected from greenhouse gas and ozone forcing.

Abstract In this study we conducted a comprehensive modeling analysis to identify global trends in extreme wave energy flux (WEF) along coastlines in the 21st century under a high emission pathway (Representative Concentration Pathways 8.5). For the end of the century, results show a significant increase up to 30% in 100 year return level WEF for the majority of the coastal areas of the southern temperate zone, while in the Northern Hemisphere large coastal areas are characterized by a significant negative trend. We show that the most significant long‐term trends of extreme WEF can be explained by intensification of teleconnection patterns such as the Antarctic Oscillation, El Niño–Southern Oscillation, and North Atlantic Oscillation. The projected changes will have broad implications for ocean engineering applications and disaster risk management. Especially low‐lying coastal countries in the Southern Hemisphere will be particularly vulnerable due to the combined effects of projected relative sea level rise and more extreme wave activities.

Abstract Observations of coincident high relative humidity and low surface ozone are common in air quality data sets, but models underpredict the strength of this correlation. We perform a statistical analysis of 28 years of ozone and meteorology observations taken as part of the Clean Air Status and Trends Network across the United States and find that vapor pressure deficit (VPD) is the strongest predictor of midday ozone in the spring, summer, and fall, and this correlation is strongest at sites with the largest leaf area index. We argue that stomatal regulation of dry deposition, which is known to have a VPD dependence that is not typically included in model parameterizations, can explain this relationship. Using a box model of ozone production and loss, we show that a negative ozone‐humidity slope is only achieved by the inclusion of VPD‐dependent dry deposition, suggesting that this mechanism may explain the observed ozone‐humidity correlation.

Abstract Urban areas are usually warmer than their surrounding natural areas, an effect known as the urban heat island effect. As such, they are particularly vulnerable to global warming and associated increases in extreme temperatures. Yet ensemble climate‐model projections are generally performed on a scale that is too coarse to represent the evolution of temperatures in cities. Here, for the first time, we combine unprecedented long‐term (35 years) urban climate model integrations at the convection‐permitting scale (2.8 km resolution) with information from an ensemble of general circulation models to assess temperature‐based heat stress for Belgium, a densely populated midlatitude maritime region. We discover that the heat stress increase toward the mid‐21st century is twice as large in cities compared to their surrounding rural areas. The exacerbation is driven by the urban heat island itself, its concurrence with heat waves, and urban expansion. Cities experience a heat stress multiplication by a factor 1.4 and 15 depending on the scenario. Remarkably, the future heat stress…

Abstract A track of sea ice reflected Global Navigation Satellite System (GNSS) signal collected by the TechDemoSat‐1 mission is processed to perform phase altimetry over sea ice. High‐precision carrier phase measurements are extracted from coherent GNSS reflections at a high angle of elevation (>57°). The altimetric results show good consistency with a mean sea surface (MSS) model, and the root‐mean‐square difference is 4.7 cm with an along‐track sampling distance of ∼140 m and a spatial resolution of ∼400 m. The difference observed between the altimetric results and the MSS shows good correlation with the colocated sea ice thickness data from Soil Moisture and Ocean Salinity. This is consistent with the reflecting surface aligned with the bottom of the ice‐water interface, due to the penetration of the GNSS signal into the sea ice. Therefore, these high‐precision altimetric results have potential to be used for determination of sea ice thickness.

Abstract Slower rates of increase in global mean surface temperature (GMST) after 2000, dubbed “global warming hiatus,” recently gave way to a rapid temperature rise. This rise coincided with persistent warm conditions in the equatorial Pacific between March 2014 and May 2016, which peaked as the 2015 extreme El Niño. Here we show that the El Niño–Southern Oscillation (ENSO) tightly controls interannual variations in atmospheric heating rate in the tropics ( r > 0.9), allowing us to construct a simple, physically based model of GMST variations that incorporates greenhouse gas emissions, ENSO forcing, and stratospheric sulfate aerosols produced by volcanoes. The model closely reproduces GMST changes since 1880, including the global warming hiatus and the subsequent temperature rise. Our results confirm that weak El Niño activity, rather than volcanic eruptions, was the cause of the hiatus, while the rapid temperature rise is due to atmospheric heat release during 2014–2016 El Niño conditions concurrent with the continuing global warming trend.

Abstract The Arctic has been warming faster than elsewhere, especially during the cold season. According to the leading theory, ice‐albedo feedback warms the Arctic Ocean during the summer, and the heat gained by the ocean is released during the winter, causing the cold‐season warming. Screen and Simmonds (2010; SS10) concluded that the theory is correct by comparing trend patterns in surface air temperature (SAT), surface turbulence heat flux (HF), and net surface infrared radiation (IR). However, in this comparison, downward IR is more appropriate to use. By analyzing the same data used in SS10 using the surface energy budget, it is shown here that over most of the Arctic the skin temperature trend, which closely resembles the SAT trend, is largely accounted for by the downward IR, not the HF, trend.

Abstract Summertime hot extremes in China are categorized into three distinct types, i.e., independent hot days, independent hot nights, and compound events, based on differing configurations between daily maximum and minimum temperature. Linear trends for multiple indictors of these subtypes and traditionally defined hot days/nights exhibited remarkable differences in significance, magnitude, and even sign, especially for events involving daytime extremes. Thus, some significant changes masked in conventional analyses are successfully uncovered. Particularly, the dominance of independent hot days has decayed significantly, accompanied by a rapid boom of compound events and/or independent hot nights in different regions. These nighttime‐accentuated hot extremes have exhibited significant increases in duration, intensity, and spatial extent, with much stronger trends detected in severest events.

Abstract We investigate a large geodetic data set of interferometric synthetic aperture radar (InSAR) and GPS measurements to determine the source parameters for the three main shocks of the 2016 Central Italy earthquake sequence on 24 August and 26 and 30 October ( M w 6.1, 5.9, and 6.5, respectively). Our preferred model is consistent with the activation of four main coseismic asperities belonging to the SW dipping normal fault system associated with the Mount Gorzano‐Mount Vettore‐Mount Bove alignment. Additional slip, equivalent to a M w ~ 6.1–6.2 earthquake, on a secondary (1) NE dipping antithetic fault and/or (2) on a WNW dipping low‐angle fault in the hanging wall of the main system is required to better reproduce the complex deformation pattern associated with the greatest seismic event (the M w 6.5 earthquake). The recognition of ancillary faults involved in the sequence suggests a complex interaction in the activated crustal volume between the main normal faults and the secondary structures and a partitioning of strain release.

Abstract Multitemporal interferometric synthetic aperture radar (InSAR) observations are used to characterize spatial variations of the permafrost active layer and its temporal evolution in Northwestern Tibet. We develop a method to enhance InSAR performances for such difficult terrain conditions and construct an 8 year timeline of the surface deformation over a 60,000 km 2 area. The ground movement induced by the active layer's response to climate forcing is limited to Cenozoic sedimentary basins and is spatially variable in both its seasonal amplitude (2.5–12 mm) and multiannual trend (−2 to 3 mm/yr). A degree‐day integrated model adjusted to the data indicates that subsidence occurs when the surface temperature exceeds zero (May to October) over areas where seasonal movements are large (>8 mm). The period of subsidence is delayed by 1–2 months over areas where smaller seasonal movements are observed, suggesting an unsaturated soil where water occurs in the deeper part of the active layer.

Abstract Using 12 years of high‐resolution global lightning stroke data from the World Wide Lightning Location Network (WWLLN), we show that lightning density is enhanced by up to a factor of 2 directly over shipping lanes in the northeastern Indian Ocean and the South China Sea as compared to adjacent areas with similar climatological characteristics. The lightning enhancement is most prominent during the convectively active season, November–April for the Indian Ocean and April–December in the South China Sea, and has been detectable from at least 2005 to the present. We hypothesize that emissions of aerosol particles and precursors by maritime vessel traffic lead to a microphysical enhancement of convection and storm electrification in the region of the shipping lanes. These persistent localized anthropogenic perturbations to otherwise clean regions are a unique opportunity to more thoroughly understand the sensitivity of maritime deep convection and lightning to aerosol particles.

Abstract Arctic winter sea ice loss is most pronounced in the Barents Sea. Here we combine observations since 1850 with climate model simulations to examine the recent record low winter Barents Sea ice extent. We find that the present observed winter Barents Sea ice extent has been reduced to less than one third of the pre‐satellite mean and is lower than the minimum sea ice extent in all multicentury climate model control simulations assessed here. The current observed sea ice loss is furthermore unprecedented in the observational record and appears as an uncommon trend in the long control simulations. In a warming climate, projections from the large ensemble simulation with the Community Earth System Model show a winter ice‐free Barents Sea for the first time within the time period 2061–2088. The large spread in projections of ice‐free conditions highlights the importance of internal variability in driving recent and future sea ice loss.

This study investigates some of the benefits and drawbacks of assimilating Terrestrial Water Storage (TWS) observations from the Gravity Recovery and Climate Experiment (GRACE) into a land surface model over India. GRACE observes TWS depletion associated with anthropogenic groundwater extraction in northwest India. The model, however, does not represent anthropogenic groundwater withdrawals and is not skillful in reproducing the interannual variability of groundwater. Assimilation of GRACE TWS introduces long-term trends and improves the interannual variability in groundwater. But the assimilation also introduces a negative trend in simulated evapotranspiration whereas in reality evapotranspiration is likely enhanced by irrigation, which is also unmodeled. Moreover, in situ measurements of shallow groundwater show no trend, suggesting that the trends are erroneously introduced by the assimilation into the modeled shallow groundwater, when in reality the groundwater is depleted in deeper aquifers. The results emphasize the importance of representing anthropogenic processes in land…