Showing papers in "Geophysical Research Letters in 2017"

A high-accuracy map of global terrain elevations

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 (eg, Ganges, Nile, Niger, and Mekong) and swamp forests (eg, Amazon, Congo, and Vasyugan) The newly developed DEM will enhance many geoscience applications which are terrain dependent

BedMachine v3: Complete Bed Topography and Ocean Bathymetry Mapping of Greenland From Multibeam Echo Sounding Combined With Mass Conservation.

Abstract: 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 vulnerable to future oceanic forcing.

Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach

Abstract: Fusing satellite observations and station measurements to estimate ground-level PM2.5 is promising for monitoring PM2.5 pollution. A geo-intelligent approach, which incorporates geographical correlation into an intelligent deep learning architecture, is developed to estimate PM2.5. Specifically, it considers geographical distance and spatiotemporally correlated PM2.5 in a deep belief network (denoted as Geoi-DBN). Geoi-DBN can capture the essential features associated with PM2.5 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 R2 increases from 0.42 to 0.88, and RMSE decreases from 29.96 to 13.03 μg/m3. On the basis of the derived PM2.5 distribution, it is predicted that over 80% of the Chinese population live in areas with an annual mean PM2.5 of greater than 35 μg/m3. This study provides a new perspective for air pollution monitoring in large geographic regions.

Lake volume and groundwater storage variations in Tibetan Plateau's endorheic basin

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 volume increase, followed by glacier mass loss (13%), and ground ice melt due to permafrost degradation (12%). Other term such as SWE (1%) makes a relatively small contribution. These results suggest that the hydrologic cycle in the TP has intensified remarkably during recent decades.

Fiber‐Optic Network Observations of Earthquake Wavefields

Abstract: Author(s): Lindsey, NJ; Martin, ER; Dreger, DS; Freifeld, B; Cole, S; James, SR; Biondi, BL; Ajo-Franklin, JB | 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 20nm of fiber yield a waveform that shows a high degree of correlation in amplitude and phase with a colocated inertial seismometer record at 0.8–1.6nHz. 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 and show that little cable-to-soil coupling is required for teleseismic P and S phase arrival detection.

Comparing Jupiter interior structure models to Juno gravity measurements and the role of a dilute core

Abstract: The Juno spacecraft has measured Jupiter's low-order, even gravitational moments, J2–J8, 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 Jn 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 Jn with the equations of state and with theory for formation and evolution of the planet.

Revisiting the contribution of transpiration to global terrestrial evapotranspiration

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 models to improve biological CO2 flux simulations.

Attributable Human-Induced Changes in the Likelihood and Magnitude of the Observed Extreme Precipitation during Hurricane Harvey

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 Nino–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.

A climate model projection weighting scheme accounting for performance and interdependence

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.

Increased atmospheric ammonia over the world's major agricultural areas detected from space.

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 US (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 US, 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.

Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High‐Resolution Simulations

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.

How much runoff originates as snow in the western United States, and how will that change in the future?

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.

Extensive and drastically different alpine lake changes on Asia's high plateaus during the past four decades

Abstract: Asia's high plateaus are sensitive to climate change and have been experiencing rapid warming over the past few decades. We found 99 new lakes and extensive lake expansion on the Tibetan Plateau during the last four decades, 1970–2013, due to increased precipitation and cryospheric contributions to its water balance. This contrasts with disappearing lakes and drastic shrinkage of lake areas on the adjacent Mongolian Plateau: 208 lakes disappeared and 75% of the remaining lakes have shrunk. We detected a statistically significant coincidental timing of lake area changes in both plateaus, associated with the climate regime shift that occurred during 1997/1998. This distinct change in 1997/1998 is thought to be driven by large-scale atmospheric circulation changes in response to climate warming. Our findings reveal that these two adjacent plateaus have been changing in opposite directions in response to climate change. These findings shed light on the complex role of the regional climate and water cycles, and provide useful information for ecological and water resource planning in these fragile landscapes.

Machine Learning Predicts Laboratory Earthquakes

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.

An Argo mixed layer climatology and database

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://mixedlayerucsdedu 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 10% compared to the algorithm

Why were the 2015/2016 and 1997/1998 extreme El Niños different?

Abstract: Subtle but important differences are identified between the 1997/1998 and 2015/2016 extreme El Ninos that reflect fundamental differences in their underlying dynamics. The 1997/1998 event is found to evolve following the eastern Pacific El Nino dynamics that relies on basin-wide thermocline variations, whereas the 2015/2016 event involves additionally the central Pacific (CP) El Nino 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 Nino as it did during the 1997/1998 El Nino. Ensemble model experiments are conducted to confirm the different climate impacts of the two El Ninos.

Projected drought risk in 1.5°C and 2°C warmer climates

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.

Transient reducing greenhouse warming on early Mars

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 CO_2–H_2 and CO_2–CH_4 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 CO_2–CH_4 CIA in the critical 250–500 cm^(−1) spectral window region In atmospheres of 05 bar CO_2 or more, percent levels of H_2 or CH_4 raise annual mean surface temperatures by tens of degrees, with temperatures reaching 273 K for pressures of 125–2 bars and 2–10% of H_2 and CH_4 Methane and hydrogen produced following aqueous alteration of Mars' crust could have combined with volcanically outgassed CO_2 to form transient atmospheres of this composition 45–35 Ga Our results also suggest that inhabited exoplanets could retain surface liquid water at significant distances from their host stars

Unprecedented springtime retreat of Antarctic sea ice in 2016

Abstract: During Austral spring 2016 Antarctic sea ice extent (SIE) decreased at a record rate of 75 × 103 km2 day-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 until 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.

Assessing the climate-scale variability of atmospheric rivers affecting western North America

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 trend is consistent with a long-term increase in vapor transport from the warming North Pacific onto the North American continent. The new catalog provides unprecedented opportunities to study the climate-scale behavior and predictability of ARs affecting western North America.

Fine particle pH during severe haze episodes in northern China

Abstract: Aerosol acidity plays an important role in atmospheric chemistry. China emits large amounts of SO2, NOx, and NH3 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/m3 with a maximum of 250 μg/m3, and the gas-phase NH3 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 NH3 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.

Divergent surface and total soil moisture projections under global warming

Abstract: Land aridity has been projected to increase with global warming. Such projections are mostly based on off-line aridity and drought metrics applied to climate model outputs but also are supported by climate-model projections of decreased surface soil moisture. Here we comprehensively analyze soil moisture projections from the Coupled Model Intercomparison Project phase 5, including surface, total, and layer-by-layer soil moisture. We identify a robust vertical gradient of projected mean soil moisture changes, with more negative changes near the surface. Some regions of the northern middle to high latitudes exhibit negative annual surface changes but positive total changes. We interpret this behavior in the context of seasonal changes in the surface water budget. This vertical pattern implies that the extensive drying predicted by off-line drought metrics, while consistent with the projected decline in surface soil moisture, will tend to overestimate (negatively) changes in total soil water availability.

Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture-temperature feedbacks

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 multi-model 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 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.

Satellite sea surface temperatures along the West Coast of the United States during the 2014–2016 northeast Pacific marine heat wave

Abstract: From January 2014 to August 2016, sea-surface temperatures (SSTs) along the Washington, Oregon, and California coasts were significantly warmer than usual, reaching a maximum SST anomaly of 6.2 °C off southern California. This marine heat wave occurred alongside the Gulf of Alaska marine heat wave, and resulted in major disturbances in the California Current ecosystem and massive economic impacts. Here, we use satellite and blended reanalysis products to report the magnitude, extent, duration, and evolution of SSTs and wind stress anomalies along the west coast of the continental United States during this event. Nearshore SST anomalies along the entire coast were persistent during the marine heat wave, and only abated seasonally, during spring upwelling-favorable wind stress. The coastal marine heat wave weakened in July 2016 and disappeared by September 2016.

New estimate of the current rate of sea level rise from a sea level budget approach

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.

Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network

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 ( 0.87 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.

Intensified dust storm activity and Valley fever infection in the southwestern United States

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 soil-dwelling fungus (Coccidioides immitis and C. posadasii) in the southwestern United States. The frequency of dust storms is found to be correlated with Valley fever incidences, with a coefficient (r) comparable to or stronger than that with other factors believed to control the disease in two endemic centers (Maricopa and Pima County, Arizona).

Continued retreat of Thwaites Glacier, West Antarctica, controlled by bed topography and ocean circulation

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 oceanic forcing increases with time as Thwaites grounding line retreats farther inland.

Quantifying CO2 Emissions From Individual Power Plants From Space

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.

Intermittent energy dissipation by turbulent reconnection

Abstract: Magnetic reconnection—the process responsible for many explosive phenomena in both nature and laboratory—is efficient at dissipating magnetic energy into particle energy. To date, exactly how this dissipation happens remains unclear, owing to the scarcity of multipoint measurements of the “diffusion region” at the sub-ion scale. Here we report such a measurement by Cluster—four spacecraft with separation of 1/5 ion scale. We discover numerous current filaments and magnetic nulls inside the diffusion region of magnetic reconnection, with the strongest currents appearing at spiral nulls (O-lines) and the separatrices. Inside each current filament, kinetic-scale turbulence is significantly increased and the energy dissipation, E′ ⋅ j, is 100 times larger than the typical value. At the jet reversal point, where radial nulls (X-lines) are detected, the current, turbulence, and energy dissipations are surprisingly small. All these features clearly demonstrate that energy dissipation in magnetic reconnection occurs at O-lines but not X-lines.