The 50 most-cited articles in Geophysical Research Letters, 2018

Abstract Higher evaporative demands and more frequent and persistent dry spells associated with rising temperatures suggest that drought conditions could worsen in many regions of the world. In this study, we assess how drought conditions may develop across the globe for 1.5, 2, and 3°C warming compared to preindustrial temperatures. Results show that two thirds of global population will experience a progressive increase in drought conditions with warming. For drying areas, drought durations are projected to rise at rapidly increasing rates with warming, averaged globally from 2.0 month/°C below 1.5°C to 4.2 month/°C when approaching 3°C. Drought magnitudes could double for 30% of global landmass under stringent mitigation. If contemporary warming rates continue, water supply‐demand deficits could become fivefold in size for most of Africa, Australia, southern Europe, southern and central states of the United States, Central America, the Caribbean, north‐west China, and parts of Southern America. In approximately 20% of the global land surface, drought magnitude will halve with…

Abstract Changes in global fire activity are influenced by a multitude of factors including land‐cover change, policies, and climatic conditions. This study uses 17 climate models to evaluate when changes in fire weather, as realized through the Fire Weather Index, emerge from the expected range of internal variability due to anthropogenic climate change using the time of emergence framework. Anthropogenic increases in extreme Fire Weather Index days emerge for 22% of burnable land area globally by 2019, including much of the Mediterranean and the Amazon. By the midtwenty‐first century, emergence among the different Fire Weather Index metrics occurs for 33–62% of burnable lands. Emergence of heightened fire weather becomes more widespread as a function of global temperature change. At 2 °C above preindustrial levels, the area of emergence is half that for 3 °C. These results highlight increases in fire weather conditions with human‐caused climate change and incentivize local adaptation efforts to limit detrimental fire impacts.

Abstract Representing unresolved moist convection in coarse‐scale climate models remains one of the main bottlenecks of current climate simulations. Many of the biases present with parameterized convection are strongly reduced when convection is explicitly resolved (i.e., in cloud resolving models at high spatial resolution approximately a kilometer or so). We here present a novel approach to convective parameterization based on machine learning, using an aquaplanet with prescribed sea surface temperatures as a proof of concept. A deep neural network is trained with a superparameterized version of a climate model in which convection is resolved by thousands of embedded 2‐D cloud resolving models. The machine learning representation of convection, which we call the Cloud Brain (CBRAIN), can skillfully predict many of the convective heating, moistening, and radiative features of superparameterization that are most important to climate simulation, although an unintended side effect is to reduce some of the superparameterization's inherent variance. Since as few as three months'…

In recent years, solar-induced chlorophyll fluorescence (SIF) retrieved from space borne spectrometers has been extensively used as a proxy for terrestrial photosynthesis at relatively sparse temporal and spatial scales. The near-infrared band of the recently launched TROPOspheric Monitoring Instrument (TROPOMI) features the required spectral resolution and signal-to-noise ratio to retrieve SIF in a spectral range devoid of atmospheric absorption features. We find that initial TROPOMI spectra meet high expectations for a substantially improved spatio-temporal resolution (up to 7 km × 3.5 km pixels with daily revisit), representing a step change in SIF remote sensing capabilities. However, interpretation requires caution, as the broad range of viewing-illumination geometries covered by TROPOMI's 2600 km wide swath needs to be taken into account. A first inter-sensor comparison with OCO-2 (Orbiting Carbon Observatory-2) SIF shows excellent agreement, underscoring the high quality of TROPOMI's SIF retrievals and the notable radiometric performance of the instrument. PLAIN LANGUAGE…

Abstract The Atlantic Meridional Overturning Circulation (AMOC) is responsible for a variable and climatically important northward transport of heat. Using data from an array of instruments that span the Atlantic at 26°N, we show that the AMOC has been in a state of reduced overturning since 2008 as compared to 2004–2008. This change of AMOC state is concurrent with other changes in the North Atlantic such as a northward shift and broadening of the Gulf Stream and altered patterns of heat content and sea surface temperature. These changes resemble the response to a declining AMOC predicted by coupled climate models. Concurrent changes in air‐sea fluxes close to the western boundary reveal that the changes in ocean heat transport and sea surface temperature have altered the pattern of ocean‐atmosphere heat exchange over the North Atlantic. These results provide strong observational evidence that the AMOC is a major factor in decadal‐scale variability of North Atlantic climate.

Abstract TROPOspheric Monitoring Instrument (TROPOMI), on‐board the Sentinel‐5 Precurser satellite, is a nadir‐viewing spectrometer measuring reflected sunlight in the ultraviolet, visible, near‐infrared, and shortwave infrared. From these spectra several important air quality and climate‐related atmospheric constituents are retrieved, including nitrogen dioxide (NO2) at unprecedented spatial resolution from a satellite platform. We present the first retrievals of TROPOMI NO2 over the Canadian Oil Sands, contrasting them with observations from the Ozone Monitoring Instrument satellite instrument, and demonstrate TROPOMI's ability to resolve individual plumes and highlight its potential for deriving emissions from individual mining facilities. Further, the first TROPOMI NO2 validation is presented, consisting of aircraft and surface in situ NO2 observations, and ground‐based remote‐sensing measurements between March and May 2018. Our comparisons show that the TROPOMI NO2 vertical column densities are highly correlated with the aircraft and surface in situ NO2 observations, and the…

Abstract This paper quantifies the relationship between forward scattered L‐band Global Navigation Satellite System (GNSS) signals, recorded by the Cyclone Global Navigation Satellite System (CYGNSS) constellation and Soil Moisture Active Passive (SMAP) soil moisture (SM). Although designed for tropical ocean surface wind sensing, the CYGNSS receivers also record GNSS reflections over land. The CYGNSS observations of reflection power are compared to SMAP SM between March 2017 and February 2018. A strong, positive linear relationship exists between changes in CYGNSS reflectivity and changes in SMAP SM, but not between the absolute magnitudes of the two observations. The sensitivity of CYGNSS reflectivity to SM varies spatially and can be used to convert reflectivity to estimates of SM. The unbiased root‐mean‐square difference between daily averaged CYGNSS‐derived SM and SMAP SM is 0.045 cm 3 /cm 3 and is similarly low between CYGNSS and in situ SM. These results show that CYGNSS, and future GNSS reflection missions, could provide global SM observations.

Abstract Changing climate in northern regions is causing permafrost to thaw with major implications for the global mercury (Hg) cycle. We estimated Hg in permafrost regions based on in situ measurements of sediment total mercury (STHg), soil organic carbon (SOC), and the Hg to carbon ratio (R HgC ) combined with maps of soil carbon. We measured a median STHg of 43 ± 30 ng Hg g soil −1 and a median R HgC of 1.6 ± 0.9 μg Hg g C −1 , consistent with published results of STHg for tundra soils and 11,000 measurements from 4,926 temperate, nonpermafrost sites in North America and Eurasia. We estimate that the Northern Hemisphere permafrost regions contain 1,656 ± 962 Gg Hg, of which 793 ± 461 Gg Hg is frozen in permafrost. Permafrost soils store nearly twice as much Hg as all other soils, the ocean, and the atmosphere combined, and this Hg is vulnerable to release as permafrost thaws over the next century. Existing estimates greatly underestimate Hg in permafrost soils, indicating a need to reevaluate the role of the Arctic regions in the global Hg cycle.

Abstract A spherical harmonic model of the magnetic field of Jupiter is obtained from vector magnetic field observations acquired by the Juno spacecraft during its first nine polar orbits about the planet. Observations acquired during eight of these orbits provide the first truly global coverage of Jupiter's magnetic field with a coarse longitudinal separation of ~45° between perijoves. The magnetic field is represented with a degree 20 spherical harmonic model for the planetary (“internal”) field, combined with a simple model of the magnetodisc for the field (“external”) due to distributed magnetospheric currents. Partial solution of the underdetermined inverse problem using generalized inverse techniques yields a model (“Juno Reference Model through Perijove 9”) of the planetary magnetic field with spherical harmonic coefficients well determined through degree and order 10, providing the first detailed view of a planetary dynamo beyond Earth.

Abstract Weather and climate models approximate diabatic and sub‐grid‐scale processes in terms of grid‐scale variables using parameterizations. Current parameterizations are designed by humans based on physical understanding, observations, and process modeling. As a result, they are numerically efficient and interpretable, but potentially oversimplified. However, the advent of global high‐resolution simulations and observations enables a more robust approach based on machine learning. In this letter, a neural network‐based parameterization is trained using a near‐global aqua‐planet simulation with a 4‐km resolution (NG‐Aqua). The neural network predicts the apparent sources of heat and moisture averaged onto (160 km)2 grid boxes. A numerically stable scheme is obtained by minimizing the prediction error over multiple time steps rather than single one. In prognostic single‐column model tests, this scheme matches both the fluctuations and equilibrium of NG‐Aqua simulation better than the Community Atmosphere Model does.

Abstract The TROPOspheric Monitoring Instrument (TROPOMI), launched on 13 October 2017, aboard the Sentinel‐5 Precursor satellite, measures reflected sunlight in the ultraviolet, visible, near‐infrared, and shortwave infrared spectral range. It enables daily global mapping of key atmospheric species for monitoring air quality and climate. We present the first methane observations from November and December 2017, using TROPOMI radiance measurements in the shortwave infrared band around 2.3 μm. We compare our results with the methane product obtained from the Greenhouse gases Observing SATellite (GOSAT). Although different spectral ranges and retrieval methods are used, we find excellent agreement between the methane products acquired from the two satellites with a mean difference of 13.6 ppb, standard deviation of 19.6 ppb, and Pearson's correlation coefficient of 0.95. Our preliminary results capture the latitudinal gradient and show expected regional enhancements, for example, in the African Sudd wetlands, with much more detail than has been observed before.

Abstract We provide a new analysis of glacial isostatic adjustment (GIA) with the goal of assembling the model uncertainty statistics required for rigorously extracting trends in surface mass from the Gravity Recovery and Climate Experiment (GRACE) mission. Such statistics are essential for deciphering sea level, ocean mass, and hydrological changes because the latter signals can be relatively small (≤2 mm/yr water height equivalent) over very large regions, such as major ocean basins and watersheds. With abundant new >7 year continuous measurements of vertical land motion (VLM) reported by Global Positioning System stations on bedrock and new relative sea level records, our new statistical evaluation of GIA uncertainties incorporates Bayesian methodologies. A unique aspect of the method is that both the ice history and 1‐D Earth structure vary through a total of 128,000 forward models. We find that best fit models poorly capture the statistical inferences needed to correctly invert for lower mantle viscosity and that GIA uncertainty exceeds the uncertainty ascribed to trends from…

Abstract Performance of earthquake early warning systems suffers from false alerts caused by local impulsive noise from natural or anthropogenic sources. To mitigate this problem, we train a generative adversarial network (GAN) to learn the characteristics of first‐arrival earthquake P waves, using 300,000 waveforms recorded in southern California and Japan. We apply the GAN critic as an automatic feature extractor and train a Random Forest classifier with about 700,000 earthquake and noise waveforms. We show that the discriminator can recognize 99.2% of the earthquake P waves and 98.4% of the noise signals. This state‐of‐the‐art performance is expected to reduce significantly the number of false triggers from local impulsive noise. Our study demonstrates that GANs can discover a compact and effective representation of seismic waves, which has the potential for wide applications in seismology.

Abstract It is shown that it is possible to emulate the dynamics of a simple general circulation model with a deep neural network. After being trained on the model, the network can predict the complete model state several time steps ahead—which conceptually is making weather forecasts in the model world. Additionally, after being initialized with an arbitrary model state, the network can through repeatedly feeding back its predictions into its inputs create a climate run, which has similar climate statistics to the climate of the general circulation model. This network climate run shows no long‐term drift, even though no conservation properties were explicitly designed into the network.

Abstract Atmospheric aerosols have been found to influence the development of planetary boundary layer (PBL) and hence to enhance haze pollution in megacities. Previous works on aerosol‐PBL interaction were mainly based on model simulation for short‐term cases; so far, there is a lack of long‐term observational evidences. In this study, based on multiyear measurements and reanalysis meteorological data, we give observational evidences on aerosol‐PBL interaction and its impact on pollution aggravation. We found a significant heating in upper PBL with maximum temperature change about 0.7 °C on average and a substantial dimming near surface with a mean temperature drop of −2.2 °C under polluted condition. By integrating Eulerian forward simulation and Lagrangian backward trajectory calculation, we demonstrated that the atmospheric heating was mainly induced by light‐absorbing aerosols like black carbon. Then an index representing such effect was proposed, which could well characterize aerosol‐PBL interaction and its impact on air pollution.

Abstract Rocky debris on glacier surfaces influences ice melt rates and the response of glaciers to climate change. However, scarce data on the extent and evolution of supraglacial debris cover have so far limited its inclusion in regional to global glacier models. Here we present global data sets of supraglacial debris‐cover extents, based on Landsat 8 and Sentinel‐2 optical satellite imagery. We find that about 4.4% (~26,000 km 2 ) of all glacier areas (excluding the Greenland ice sheet and Antarctica) are covered with debris, but that the distribution is heterogeneous. The largest debris‐covered areas are located in high‐mountain ranges, away from the poles. At a global scale, we find a negative scaling relationship between glacier size and percentage of debris. Therefore, the influence of debris cover on glacier mass balances is expected to increase in the future, as glaciers continue to shrink.

Limiting global warming to 1.5 or 2.0°C requires strong mitigation of anthropogenic greenhouse gas (GHG) emissions. Concurrently, emissions of anthropogenic aerosols will decline, due to coemission with GHG, and measures to improve air quality. However, the combined climate effect of GHG and aerosol emissions over the industrial era is poorly constrained. Here we show the climate impacts from removing present-day anthropogenic aerosol emissions and compare them to the impacts from moderate GHG-dominated global warming. Removing aerosols induces a global mean surface heating of 0.5-1.1°C, and precipitation increase of 2.0-4.6%. Extreme weather indices also increase. We find a higher sensitivity of extreme events to aerosol reductions, per degree of surface warming, in particular over the major aerosol emission regions. Under near-term warming, we find that regional climate change will depend strongly on the balance between aerosol and GHG forcing.

Abstract Climate change has exacerbated the occurrence of large‐scale sea surface temperature anomalies, or marine heatwaves (MHWs)—extreme phenomena often associated with mass mortality events of marine organisms. Using a combination of citizen science and federal data sets, we investigated the causal mechanisms of the 2014/2015 die‐off of Cassin's Auklets (Ptychoramphus aleuticus), a small zooplanktivorous seabird, during the NE Pacific MHW of 2013–2015. Carcass deposition followed an effective reduction in the energy content of mesozooplankton, coincident with the loss of cold‐water foraging habitat caused by the intrusion of the NE Pacific MHW into the nearshore environment. Models examining interannual variability in effort‐controlled carcass abundance (2001–2014) identified the biomass of lipid‐poor zooplankton as the dominant predictor of increased carcass abundance. In 2014, Cassin's Auklets dispersing from colonies in British Columbia likely congregated into a nearshore band of cooler upwelled water and ultimately died from starvation following the shift in zooplankton…

Abstract A uniform, global approach is used to quantify how atmospheric rivers (ARs) change between Coupled Model Intercomparison Project Phase 5 historical simulations and future projections under the Representative Concentration Pathway (RCP) 4.5 and RCP8.5 warming scenarios. The projections indicate that while there will be ~10% fewer ARs in the future, the ARs will be ~25% longer, ~25% wider, and exhibit stronger integrated water vapor transports (IVTs) under RCP8.5. These changes result in pronounced increases in the frequency (IVT strength) of AR conditions under RCP8.5: ~50% (25%) globally, ~50% (20%) in the northern midlatitudes, and ~60% (20%) in the southern midlatitudes. The models exhibit systematic low biases across the midlatitudes in replicating historical AR frequency (~10%), zonal IVT (~15%), and meridional IVT (~25%), with sizable intermodel differences. A more detailed examination of six regions strongly impacted by ARs suggests that the western United States, northwestern Europe, and southwestern South America exhibit considerable intermodel differences in…

Abstract Compound extremes correspond to events with multiple concurrent or consecutive drivers (e.g., ocean and fluvial flooding, drought, and heat waves) leading to substantial impacts such as infrastructure failure. In many risk assessment and design applications, however, multihazard scenarios of extremes and compound events are ignored. In this paper, we review the existing multivariate design and hazard scenario concepts and introduce a novel copula‐based weighted average threshold scenario for an expected event with multiple drivers. The model can be used for obtaining multihazard design and risk assessment scenarios and their corresponding likelihoods. The proposed model offers uncertainty ranges of most likely compound hazards using Bayesian inference. We show that the uncertainty ranges of design quantiles might be large and may differ significantly from one copula model to the other. We also demonstrate that the choice of marginal and copula functions may profoundly impact the multihazard design values. A robust analysis should account for these uncertainties within and…

Abstract A likely important feature of the poorly understood aerosol‐cloud interactions over the Southern Ocean (SO) is the dominant role of sea spray aerosol, versus terrestrial aerosol. Ice nucleating particles (INPs), or particles required for heterogeneous ice nucleation, present over the SO have not been studied in several decades. In this study, boundary layer aerosol properties and immersion freezing INP number concentrations (nINPs) were measured during a ship campaign that occurred south of Australia (down to 53°S) in March–April 2016. Ocean surface chlorophyll a concentrations ranged from 0.11 to 1.77 mg/m3, and nINPs were a factor of 100 lower than historical surveys, ranging from 0.38 to 4.6 m−3 at −20 °C. The INP population included organic heat‐stable material, with contributions from heat‐labile material. Lower INP source potentials of SO seawater samples compared to Arctic seawater were consistent with lower ice nucleating site densities in this study compared to north Atlantic air masses.

Abstract Clouds have an enormous influence on the Earth's energy balance, climate, and weather. Cloud types have different cloud radiative effects, which is an essential indicator of the cloud effect on radiation. Therefore, identifying the cloud type is important in meteorology. In this letter, we propose a new convolutional neural network model, called CloudNet, for accurate ground‐based meteorological cloud classification. We build a ground‐based cloud data set, called Cirrus Cumulus Stratus Nimbus, which consists of 11 categories under meteorological standards. The total number of cloud images is three times that of the previous database. In particular, it is the first time that contrails, a type of cloud generated by human activity, have been taken into account in the ground‐based cloud classification, making the Cirrus Cumulus Stratus Nimbus data set more discriminative and comprehensive than existing ground‐based cloud databases. The evaluation of a large number of experiments demonstrates that the proposed CloudNet model could achieve good performance in meteorological cloud…

Abstract A few days with heavy rain contribute disproportionately to total precipitation, while many days with light drizzle contribute much less. What is not appreciated is just how asymmetric this distribution is in time, and the even more asymmetric nature of trends due to climate change. We diagnose the temporal asymmetry in models and observations. Half of annual precipitation falls in the wettest 12 days each year in the median across observing stations worldwide. Climate models project changes in precipitation that are more uneven than present‐day precipitation. In a scenario with high greenhouse‐gas emissions, one fifth of the projected increase in rain falls in the wettest 2 days of the year and 70% in the wettest 2 weeks. Adjusting modeled unevenness to match present‐day unevenness at stations, half of precipitation increase occurs in the wettest 6 days each year.

Abstract Pronounced warming occurring on the Tibetan Plateau is expected to stimulate alpine grassland growth but could also increase atmospheric aridity that limits photosynthesis. But there lacks a systematic assessment of the impact of atmospheric aridity on alpine grassland productivity. Here we combine satellite observations, flux‐tower‐based productivity, and model simulations to quantify the effect of atmospheric aridity on grassland productivity and its temporal change between 1982 and 2011. We found a negative impact of atmospheric vapor pressure deficit on grassland productivity. This negative effect becomes increasingly intensified in terms of the impact severity and extent, suggesting an increasingly important role of atmospheric aridity on productivity. We further demonstrated that this negative effect is mitigated but cannot be overcompensated by the positive effect of rising CO 2 . Given that vapor pressure deficit is projected to further increase by ~10–38% in the future, Tibetan alpine grasslands will face an increasing stress of atmospheric drought.

Abstract Rapid adjustments are responses to forcing agents that cause a perturbation to the top of atmosphere energy budget but are uncoupled to changes in surface warming. Different mechanisms are responsible for these adjustments for a variety of climate drivers. These remain to be quantified in detail. It is shown that rapid adjustments reduce the effective radiative forcing (ERF) of black carbon by half of the instantaneous forcing, but for CO 2 forcing, rapid adjustments increase ERF. Competing tropospheric adjustments for CO 2 forcing are individually significant but sum to zero, such that the ERF equals the stratospherically adjusted radiative forcing, but this is not true for other forcing agents. Additional experiments of increase in the solar constant and increase in CH 4 are used to show that a key factor of the rapid adjustment for an individual climate driver is changes in temperature in the upper troposphere and lower stratosphere.

Abstract Although the Southern Ocean is thought to account for a significant portion of the contemporary oceanic uptake of carbon dioxide (CO 2 ), flux estimates in this region are based on sparse observations that are strongly biased toward summer. Here we present new estimates of Southern Ocean air‐sea CO 2 fluxes calculated with measurements from biogeochemical profiling floats deployed by the Southern Ocean Carbon and Climate Observations and Modeling project during 2014–2017. Compared to ship‐based CO 2 flux estimates, the float‐based fluxes find significantly stronger outgassing in the zone around Antarctica where carbon‐rich deep waters upwell to the surface ocean. Although interannual variability contributes, this difference principally stems from the lack of autumn and winter ship‐based observations in this high‐latitude region. These results suggest that our current understanding of the distribution of oceanic CO 2 sources and sinks may need revision and underscore the need for sustained year‐round biogeochemical observations in the Southern Ocean.

Abstract This study investigates global changes in indicators of mean and extreme streamflow. The assessment is based on the Global Streamflow Indices and Metadata archive and focuses on time series of the annual minimum, the 10th, 50th, and 90th percentiles, the annual mean, and the annual maximum of daily streamflow. Trends are estimated using the Sen‐Theil slope, and the significance of mean regional trends is established through bootstrapping. Changes in the indices are often regionally consistent, showing that the entire flow distribution is moving either upward or downward. In addition, the analysis confirms the complex nature of hydrological change where drying in some regions (e.g., in the Mediterranean) is contrasted by wetting in other regions (e.g., North Asia). Observed changes are discussed in the context of previous results and with respect to model estimates of the impacts of anthropogenic climate change and human water management.

Abstract Using the first full annual cycle of Cyclone Global Navigation Satellite System (CyGNSS) observations, we investigated the limitations and capabilities of CyGNSS observations for soil moisture (SM) estimates (0–5 cm). A relative signal‐to‐noise ratio (rSNR) value from a CyGNSS‐derived delay‐Doppler map is introduced to improve the temporal resolution of SM derived from Soil Moisture Active Passive (SMAP) data. We then evaluated the CyGNSS‐derived rSNR using ground‐based SM measurements and the triple collocation method with SMAP and modeled SM products. We found that CyGNSS can provide useful SM estimates over moderately vegetated regions (correlation coefficient of the individual data: 0.77) but shows degraded performance over arid and densely vegetated regions (correlation coefficient of the individual data: 0.68 and 0.67). However, when rSNR data is combined with SM data from SMAP, daily SM estimates can be achieved. These results show that synergistic use of CyGNSS observations can improve on SM estimates from current satellite systems.

Abstract Future projections suggest an increase in drought globally with climate change. Current vegetation models typically regulate the plant photosynthetic response to soil moisture stress through an empirical function, rather than a mechanistic response where plant water potentials respond to changes in soil water. This representation of soil moisture stress may introduce significant uncertainty into projections for the terrestrial carbon cycle. We examined the use of the soil moisture limitation function in historical and future emissions scenarios in nine Earth system models. We found that soil moisture‐limited productivity across models represented a large and uncertain component of the simulated carbon cycle, comparable to 3–286% of current global productivity. Approximately 40–80% of the intermodel variability was due to the functional form of the limitation equation alone. Our results highlight the importance of implementing mechanistic water limitation schemes in models and illuminate several avenues for improving projections of the land carbon sink.

Abstract Although the flux of dissolved organic carbon (DOC) through freshwaters is nearly equivalent to the net carbon uptake of all terrestrial ecosystems, uncertainty remains about how source processes (carbon production and location) and transport processes (hydrologic connectivity and routing) interact to determine DOC flux across flow conditions and ecoregions. This limits our ability to predict the fluvial carbon flux responses to changes in climate and land use. We used DOC concentration and discharge patterns with ensemble modeling techniques to quantify DOC flux behavior for 1,006 U.S. watersheds spanning diverse climate and land cover conditions. We found that DOC flux was transport‐limited (concentration increased with discharge) in 80% of watersheds and that this flux behavior spanned ecoregions and watershed sizes. The generality of transport limitation demonstrates how coupling discharge models with widely available watershed properties could allow DOC flux to be efficiently integrated into landscape and Earth system models.

Abstract Eight atmospheric general circulation models (AGCMs) are forced with observed historical (1871–2010) monthly sea surface temperature and sea ice variations using the Atmospheric Model Intercomparison Project II data set. The AGCMs therefore have a similar temperature pattern and trend to that of observed historical climate change. The AGCMs simulate a spread in climate feedback similar to that seen in coupled simulations of the response to CO 2 quadrupling. However, the feedbacks are robustly more stabilizing and the effective climate sensitivity (EffCS) smaller. This is due to a pattern effect , whereby the pattern of observed historical sea surface temperature change gives rise to more negative cloud and longwave clear‐sky feedbacks. Assuming the patterns of long‐term temperature change simulated by models, and the radiative response to them, are credible; this implies that existing constraints on EffCS from historical energy budget variations give values that are too low and overly constrained, particularly at the upper end. For example, the pattern effect increases the…

Abstract A combination of hot temperature and high humidity (high heat stress) has severe impacts on environment, society, and public health, especially in urban areas where the majority of the world's population lives. This study investigates the changes of heat stress in urban areas of eastern China and urbanization effects. Data for 242 urban areas and records from a dense network of nearly 2,000 stations are examined. All urban areas have experienced substantial increases in mean heat stress and the frequencies of extreme heat stress days and events during 1971–2014. The increases in human‐perceived heat stress are even stronger than air temperature. Urban areas experience more intense heat stress than the surrounding rural areas. We estimate that urbanization accounts for nearly 30% of the increase in mean and extreme heat stress. Urbanization effects are more prominent in the major urban conglomerates such as Beijing‐Tianjin‐Hebei and the Yangtze and Pearl river deltas.

Abstract Wide disagreement among individual modeling studies has contributed to a debate on the role of recent sea ice loss in the Arctic amplification of global warming and the Siberian wintertime cooling trend. We perform coordinated experiments with six atmospheric general circulation models forced by the observed and climatological daily sea ice concentration and sea surface temperature. The results indicate that the impact of the recent sea ice decline is rather limited to the high‐latitude lower troposphere in winter, and the sea ice changes do not significantly lead to colder winters over Siberia. The observed wintertime Siberian temperature and corresponding circulation trends are reproduced in a small number of ensemble members but not by the multimodel ensemble mean, suggesting that atmospheric internal dynamics could have played a major role in the observed trends.

Abstract Extratropical cyclones (ECs) and atmospheric rivers (ARs) impact precipitation over the U.S. West Coast and other analogous regions globally. This study investigates the relationship between ECs and ARs by exploring the connections between EC strength and AR intensity and position using a new AR intensity scale. While 82% of ARs are associated with an EC, only 45% of ECs have a paired AR and the distance between the AR and EC varies greatly. Roughly 20% of ARs (defined by vertically integrated water vapor transport) occur without a nearby EC. These are usually close to a subtropical/tropical moisture source and include an anticyclone. AR intensity is only moderately proportional to EC strength. Neither the location nor intensity of an AR can be simply determined by an EC. Greater EC intensification occurs with stronger ARs, suggesting that ARs enhance EC deepening by providing more water vapor for latent heat release.

Abstract Worldwide, coastal, and deltaic communities are susceptible to flooding from the individual and combined effects of rainfall excess and astronomic tide and storm surge inundation. Such flood events are a present (and future) cause of concern as observed from recent storms such as the 2016 Louisiana flood and Hurricanes Harvey, Irma, and Maria. To assess flood risk across coastal landscapes, it is advantageous to first delineate flood transition zones, which we define as areas susceptible to hydrologic and coastal flooding and their collective interaction. We utilize numerical simulations combining rainfall excess and storm surge for the 2016 Louisiana flood to describe a flood transition zone for southeastern Louisiana. We show that the interaction of rainfall excess with coastal surge is nonlinear and less than the superposition of their individual components. Our analysis provides a foundation to define flooding zones across coastal landscapes throughout the world to support flood risk assessments.

Abstract The Paris Agreement aims to keep global warming well below 2°C above preindustrial levels with a preferred ambitious 1.5°C target. Developing countries, especially small island nations, pressed for the 1.5°C target to be adopted, but who will suffer the largest changes in climate if we miss this target? Here we show that exceeding the 1.5°C global warming target would lead to the poorest experiencing the greatest local climate changes. Under these circumstances greater support for climate adaptation to prevent poverty growth would be required.

Abstract Aquifers are vital groundwater reservoirs for residential, agricultural, and industrial activities worldwide. Tracking their state with high temporal and spatial resolution is critical for water resource management at the regional scale yet is rarely achieved from a single type of groundwater data. Here we show that variations in groundwater levels can be mapped using perturbations in seismic velocity (dv/v). We measure dv/v in the San Gabriel Valley, California, from cross correlation of the ambient seismic field. dv/v reproduces the groundwater level changes that are marked by the multiyear depletions and rapid recharges, typical of California's cycles of droughts and floods. dv/v correlates spatially with vertical surface displacements and deformation measured with the Global Positioning System (GPS). Our results successfully predict the volume of water lost in the San Gabriel Valley during the 2012–2016 drought and thus provide a new, complementary approach to monitor groundwater storage.

Abstract The sensitivity of the Greenland ice sheet to climate forcing is of key importance in assessing its contribution to past and future sea level rise. Surface mass loss occurs during summer, and accounting for temperature seasonality is critical in simulating ice sheet evolution and in interpreting glacial landforms and chronologies. Ice core records constrain the timing and magnitude of climate change but are largely limited to annual mean estimates from the ice sheet interior. Here we merge ice core reconstructions with transient climate model simulations to generate Greenland‐wide and seasonally resolved surface air temperature fields during the last deglaciation. Greenland summer temperatures peak in the early Holocene, consistent with records of ice core melt layers. We perform deglacial Greenland ice sheet model simulations to demonstrate that accounting for realistic temperature seasonality decreases simulated glacial ice volume, expedites the deglacial margin retreat, mutes the impact of abrupt climate warming, and gives rise to a clear Holocene ice volume minimum.

Abstract The Geostationary Lightning Mapper (GLM) continuously observes lightning throughout a near‐hemispheric field of view, capturing spatiotemporal variability on unprecedented scales. This study documents GLM lightning distributions during the initial 9 months in the operational Geostationary Operational Environmental Satellite‐East position (December 2017 to August 2018). Spatial maps, summary statistics, and time series illustrate seasonal, regional, and diurnal lightning patterns. Lightning activity shifts from south to north during the study period with most lightning over land (83%). The average GLM flash extends over a 454‐km2 area, lasts 301 ms, produces 262 fJ of optical energy, and consists of 16.4 (42.2) groups (events). On average, GLM flashes over the oceans are larger (570 km2), of longer duration (345 ms), and brighter (420 fJ) than flashes over land (431 km2, 293 ms, and 230 fJ). The baseline values and early insights reported herein aim to guide the early development and application of GLM observations.

Abstract We use height‐resolved and total column satellite observations and 3‐D chemical transport model simulations to study stratospheric ozone variations during 1998–2017 as ozone‐depleting substances decline. In 2017 extrapolar lower stratospheric ozone displayed a strong positive anomaly following much lower values in 2016. This points to large interannual variability rather than an ongoing downward trend, as reported recently by Ball et al. (2018, https://doi.org/10.5194/acp‐18‐1379‐2018 ). The observed ozone variations are well captured by the chemical transport model throughout the stratosphere and are largely driven by meteorology. Model sensitivity experiments show that the contribution of past trends in short‐lived chlorine species to the ozone changes is small. Similarly, the potential impact of modest trends in natural brominated short‐lived species is small. These results confirm the important role that atmospheric dynamics plays in controlling ozone in the extrapolar lower stratosphere on multiannual time scales and the continued importance of monitoring ozone…

Abstract On interannual to decadal time scales, the climate mode with many of the strongest societal impacts is the El Niño–Southern Oscillation (ENSO). However, quantifying ENSO's changes in a warming climate remains a formidable challenge, due to both the noise arising from internal variability and the complexity of air‐sea feedbacks in the tropical Pacific Ocean. In this work, we use large (≥30‐member) ensembles of climate simulations to show that anthropogenic climate change can produce systematic increases in ENSO teleconnection strength over many land regions, driving increased interannual variability in regional temperature extremes and wildfire frequency. As the spatial character of this intensification exhibits strong land‐ocean contrasts, a causal role for land‐atmosphere feedbacks is suggested. The identified increase in variance occurs in multiple model ensembles, independent of changes in sea surface temperature variance. This suggests that in addition to changes in the overall likelihoods of heat and wildfire extremes, the variability in these events may also be a…

Abstract The spatial distribution of subsurface parameters such as permeability are increasingly relevant for regional to global climate, land surface, and hydrologic models that are integrating groundwater dynamics and interactions. Despite the large fraction of unconsolidated sediments on Earth's surface with a wide range of permeability values, current global, high‐resolution permeability maps distinguish solely fine‐grained and coarse‐grained unconsolidated sediments. Representative permeability values are derived for a wide variety of unconsolidated sediments and applied to a new global map of unconsolidated sediments to produce the first geologically constrained, two‐layer global map of shallower and deeper permeability. The new mean logarithmic permeability of the Earth's surface is −12.7 ± 1.7 m2 being 1 order of magnitude higher than that derived from previous maps, which is consistent with the dominance of the coarser sediments. The new data set will benefit a variety of scientific applications including the next generation of climate, land surface, and hydrology models at…

Abstract Mars Science Laboratory Curiosity rover observations of the 2018/Mars year 34 global/planet‐encircling dust storm represent the first in situ measurements of a global dust storm with dedicated meteorological sensors since the Viking Landers. The Mars Science Laboratory team planned and executed a science campaign lasting approximately 100 Martian sols to study the storm involving an enhanced cadence of environmental monitoring using the rover's meteorological sensors, cameras, and spectrometers. Mast Camera 880‐nm optical depth reached 8.5, and Rover Environmental Monitoring Station measurements indicated a 97% reduction in incident total ultraviolet solar radiation at the surface, 30K reduction in diurnal range of air temperature, and an increase in the semidiurnal pressure tide amplitude to 40 Pa. No active dust‐lifting sites were detected within Gale Crater, and global and local atmospheric dynamics were drastically altered during the storm. This work presents an overview of the mission's storm observations and initial results.

Abstract The Tropospheric Monitoring Instrument (TROPOMI) was launched onboard of the European Space Agency's (ESA) Sentinel‐5P satellite. One of the mission's key products is the total column density of carbon monoxide, inferred from TROPOMI's 2.3 μm measurements. Using the operational processing algorithm, we analyze six subsequent days of measurements during the commissioning phase. The TROPOMI product is compared with CO fields from the European Centre for Medium‐Range Weather Forecasts (ECMWF) assimilation system. Globally, a small mean difference between the data sets of 3.2 ± 5.5% with a correlation coefficient of 0.97 is found. The daily global coverage of TROPOMI enables it to capture day‐to‐day evolution of the atmospheric composition. As an example, we discuss the air pollution event of India in November 2017 with high carbon monoxide (CO) concentrations, which partly dispersed when the CO polluted air was transported north alongside the Himalaya to China. The striking agreement and also regional differences with ECMWF indicate new exciting applications for the TROPOMI CO…

Abstract Snow water equivalent (SWE) variability and its drivers over different regions remain uncertain due to lack of representativeness of point measurements and deficiencies of existing coarse‐resolution SWE products. Here, for the first time, we quantify and understand the snowpack change from 1982 to 2016 over conterminous United States at 4‐km pixels. Annual maximum SWE decreased significantly ( p < 0.05) by 41% on average for 13% of snowy pixels over western United States. Snow season was shortened significantly by 34 days on average for 9% of snowy pixels over the United States, primarily caused by earlier ending and later arrival of the season over western and eastern United States, respectively. October–March mean temperature and accumulated precipitation largely explain the temporal variability of 1 April SWE over western United States, and considering temperature alone would exaggerate the warming effect on SWE decrease. In contrast, temperature plays the primary role in the 1 April SWE variability over eastern United States.

Abstract When a more viscous fluid displaces a less viscous one in porous media, viscous pressure drop stabilizes the displacement front against capillary pressure fluctuation. For this favorable viscous ratio conditions, previous studies focused on the front instability under slow flow conditions but did not address competing effects of wettability and flow rate. Here we study how this competition controls displacement patterns. We propose a theoretical model that describes the crossover from fingering to stable flow as a function of invading fluid contact angle θ and capillary number Ca. The phase diagram predicted by the model shows that decreasing θ stabilizes the displacement for θ≥45° and the critical contact angle θc increases with Ca. The boundary between corner flow and cooperative filling for θ < 45° is also described. This work extends the classic phase diagram and has potential applications in predicting CO2 capillary trapping and manipulating wettability to enhance gas/oil displacement efficiency.

Abstract It is well known that urban areas are typically hotter than the surrounding (vegetated) rural areas. However, the contribution of urbanization to the trends of extreme temperature events such as heat waves (HWs) is less understood. Using a homogenized meteorological dataset drawn from nearly 2,000 stations in China, we find that urban and rural areas have different HW trends and the urban‐rural contrast of HW trends varies across climate regimes. In wet climates, the increasing trends of HWs in urban areas are greater than those in rural areas, suggesting a positive contribution of urbanization to HW trends. In arid regions, the urbanization contribution to HW trends is smaller and even negative. The stronger urbanization contribution to HW trends in wet climates is linked to the smaller variability of urban heat island intensity. This study highlights the important role of local hydroclimate in modulating the urbanization contribution to extreme temperatures.

Abstract In recent years, global weather forecast models and global climate models have begun to depict intense tropical cyclones, even up to category 5 on the Saffir‐Simpson scale. In light of the limitation of horizontal resolution in such models, the author performs calculations, using the extended Best Track data for Atlantic tropical cyclones, to estimate the ability of models with differing grid spacing to represent Atlantic tropical cyclone intensity statistically. Results indicate that, under optimistic assumptions, models with horizontal grid spacing of one fourth degree or coarser should not produce a realistic number of category 4 and 5 storms unless there are errors in spatial attributes of the wind field. Furthermore, the case of Irma (2017) is used to demonstrate the importance of a realistic depiction of angular momentum and to motivate the use of angular momentum in model evaluation.

Abstract Sudden stratospheric warmings (SSWs) are significant source of enhanced subseasonal predictability, but whether this source is untapped in operational models remains an open question. Here we report on the prediction of the SSW on 12 February 2018, its dynamical precursors, and surface climate impacts by an ensemble of dynamical forecast models. The ensemble forecast from 1 February predicted 3 times increased odds of an SSW compared to climatology, although the lead time for SSW prediction varied among individual models. Errors in the forecast location of a Ural high and underestimated magnitude of upward wave activity flux reduced SSW forecast skill. Although the SSW's downward influence was not well forecasted, the observed northern Eurasia cold anomaly following SSW was predicted, albeit with a weaker magnitude, due to persistent tropospheric anomalies. The ensemble forecast from 8 February predicted the SSW, its subsequent downward influence, and a long‐lasting cold anomaly at the surface.

Abstract Two large ensembles are used to quantify the extent to which internal variability can contribute to long‐term changes in El Niño‐Southern Oscillation (ENSO) characteristics. We diagnose changes that are externally forced and distinguish between multi‐model simulation results that differ by chance and those that differ due to different model physics. The range of simulated ENSO amplitude changes in the large ensemble historical simulations encompasses 90% of the Coupled Model Intercomparison Project 5 historical simulations and 80% of moderate (RCP4.5) and strong (RCP8.5) warming scenarios. When considering projected ENSO pattern changes, model differences are also important. We find that ENSO has high internal variability and that single realizations of a model can produce very different results to the ensemble mean response. Due to this variability, 30–40 ensemble members of a single model are needed to robustly compute absolute ENSO variance to a 10% error when 30‐year analysis periods are used.