A number of insitu and passive microwave satellite sensors have observed Arctic sea ice and Greenland Ice Sheet (GrIS) mass loss trends over recent decades. Along with sea and land ice declines, above-freezing, near-surface air temperatures are observed earlier in boreal spring and later in autumn thus extending periods of melt beyond the core of summer (JJA). Little is known about whether lengthening periods of open ocean proximate to the ice sheet, for instance, demonstrably effect unseasonal GrIS melt events. Here, a new Baffin Bay sea ice advance dataset is utilized to determine dates of sea ice growth along Greenland’s west coast for the 2011-2015 period. Preceding, multi-scale ocean-atmospheric conditions, including at the Baffin-GrIS interface, are analyzed and linked to unseasonal melt events observed at a series of on-ice automatic weather stations (AWS) along the K-transect in southwest Greenland. The local marine versus synoptic influence on the above and below freezing surface air temperature events is assessed through analyses involving AWS winds, pressure, and humidity observations. These surface observations are further compared against Modele Atmospherique Regional (MAR), Regional Atmospheric Climate Model (RACMO), and ERA-Interim reanalysis fields to understand the airmass origins and (thermo)dynamic drivers of the melt events. Results suggest that the K-transect transition season melt events, primarily in the ablation zone, are strongly affected by ridging atmospheric circulation patterns that transport warm, moist air from lower latitude land-ocean areas toward west Greenland. While local conduction of oceanic surface heat appears to impact coastal air temperatures, consistent with previous studies, marine air incursions from Baffin waters onto the ice sheet are likely obstructed by barrier flows and the pressure gradient-driven katabatic regime off of central Greenland.

The University of Colorado at Boulder’s Laboratory for Atmospheric and Space Physics (LASP) has a long history of providing state of the art solar instrumentation and datasets to the community. LISIRD has played an integral part in this history by providing a simple web interface for the plotting of and access to a number of solar datasets (irradiance, sunspots, proxies, etc.). Since introducing LISIRD version 3 last year at AGU, LASP has nearly doubled the number of datasets that are being served via LISIRD and has drastically increased LISIRD’s usage both within LASP and around the world. This talk will discuss many aspects of LISIRD including: Interface updates to enhance dataset search and analysis capabilities. User insights through usage statistics and usability testing. Infrastructure to easily manage datasets being served on LISIRD.

The International Satellite Cloud Climatology Project (ISCCP)’s Convection Tracking (CT) database was designed to track the evolution of deep convective cloud systems throughout their life cycle. The database is produced in 3 steps. The first step determines whether a particular image pixel is cloudy and determines the cloud top temperature and optical thickness. The second step clusters up all adjacent cold IR pixels with brightness temperature (TBIR)< 245 K and stores the summary information about cloud structural and radiative properties. Such clusters are referred to as Convective Systems (CSs). A further test identifies Convective Clusters (CCs) as adjacent cloud pixels with TBIR < 220 K. The third step tracks each individual CS over time to form families and produces the CT database. Previous version of the CT data covered the period from 1983-2008 and treated one geostationary satellite at a time. Recently, we started producing a new version of CT data that are built upon the new, H-version ISCCP data (HXG). Improvements from this new CT data include: 1) globally uniform coverage, 2) higher spatial sampling/resolution (from 30 km down to 10 km), and 3) longer data record (1983-2015). This presentation will introduce the new ISCCP CT database and show some preliminary results including comparison with the old CT data and some essential global statistics of deep convective cloud systems.

Climate change affects the global water cycle and has the potential to alter water availability for food-energy-water production and the ecosystems services on regional and local scales. In southeastern Brazil, the Cantareira Water Supply System reached unprecedented low levels in January 2015 compromising the water supply for the Metropolitan Region of São Paulo (MRSP). However, there is still few studies investigating the effects of climate change on water availability in this region. Here, we assess the influence of climate change on water availability in the Jaguari Basin, Southeastern Brazil using a modeling approach. This basin covers and area of about 1200 km2 and it is the main source of the Cantareira Water Supply System, responsible for providing water for about 7 million people in the MRSP. To evaluate climate change scenarios, we use the lumped conceptual HYMOD model on daily time step. This model was calibrated and evaluated using daily observed data of precipitation, evapotranspiration, and discharge for the period of 1990 to 2009. To evaluated climate change scenarios, we used data of an ensemble of 17 General Circulation Models (GCMs), downscaled by MarkSim GCM working off a 30 arc-second climate surface spatial resolution forced by two Representative Concentration Pathways (RCP): RCP 4.5 and RCP 8.5. These data were integrated into the HYMOD to projected scenarios (up to 2095) of water discharge. We find values of Nash-Sutcliffe Efficiency Coefficient (NSE) and Coefficient of Determination (R2) greater than 0.80 for the calibration and evaluation period. We also noticed an increase in the peak of runoff and a decrease and baseflow for both scenarios. Such changes reflect in a higher interannual variability, therefore, increasing the risk of drought and flood. In terms of Environmental Flow Requirement, the probability of exceedance Q90, reveal a clear pattern of decreasing, about 23% from 2010 to 2040, and reaching 28% by the end of the century. Our findings indicate that the water discharge could not be enough for the current and future water demand. Our results expose the fragility of the studied basin, presenting a technical and scientific information focusing on guiding the plans and strategies to deal with situations of water scarcity.

Water managers face the daunting task of managing freshwater resources in the face of industrialization and population growth. As surface water resources become fully allocated, increased groundwater use can fill the void, particularly during periods of drought. Improper groundwater management can result in reduced water quality, land subsidence, increased pumping costs, and in some cases, the complete exhaustion of an aquifer and the loss of groundwater as a buffer during times of drought. Assessing the long-term impact of various groundwater management decisions can be difficult and costly, and therefore many decisions are made without sufficient analysis. Advancements in the acquisition and dissemination of Earth observations, coupled with advances in cloud computing, web apps, online mapping, and visualization provide a unique opportunity to deliver tools and actionable information to groundwater managers to assist them in addressing global and regional challenges and opportunities. We have developed a web-based tool that ingests in situ groundwater level measurements for specific aquifers and generates time series plots, maps, and raster animations showing groundwater depletion over time and short-term projections into the future. This process involves both temporal and spatial interpolation algorithms. In some aquifers, the observation wells are sparse and/or the historical observations have large gaps, leading to greater uncertainty in the interpolation and the resulting groundwater depletion estimates. To address this, we utilize Earth observations (GRACE, SMAP, etc.) and a co-kriging algorithm to enhance the interpolation process. The utility of the Earth observations in improving the estimates is evaluated using a jackknifing process. We present case studies for application of the system in the states of Utah and Texas.

The ocean floor broadband seismology has been established based on several practical observations by using broadband ocean bottom seismometer (BBOBS) and its new generation system (BBOBS-NX) in Japan since 1999. The data obtained by our BBOBS and BBOBS-NX is adequate for broadband seismic analyses, especially the BBOBS-NX enables the quality of the horizontal data comparable to land sites in longer periods (10 s –). And, the BBOBS-NX with tilt measurement function, BBOBST-NX, is in practical evaluation for the mobile tilt observation that may realize a dense seafloor geodetic monitoring with low cost. The weak point of the BBOBS-NX system lies in the intrinsic limitation of the submersible in its operation. If this system can be operated alone like as the BBOBS, it should be a true breakthrough of ocean bottom seismology. We call this new autonomous BBOBS-NX as the NX-2G in short. Several problems to realize the NX-2G have been almost cleared through test observations since 2012. The function of the NX-2G system is based on 3 stage operations as shown in the image. The glass float is added to obtain enough buoyancy to extract the sensor unit from the seafloor and also to suppress the oscillating tilt of the system in descending, not to exceed the tilt allowance of the broadband seismic sensor. In Oct. 2016, the first in-situ test of the NX-2G system was performed. The landing of the NX-2G looked well and the maximum tilt in descending was about ±2.5°, that ensured the effective suppression for the oscillating tilt by the glass float. As the final step test of the NX-2G, the one-year-long observation has been started in April 2017 with the BBOBS deployed nearby, to obtain simultaneous data for the noise level evaluation. The free-fall deployment and the transition from the landing stage to the observation stage were completed, those were monitored through the acoustic communication from the ship. This NX-2G was recovered in Oct. 2018 with the ROV, KAIKO Mk-IV, to watch the transition from the observation stage to the recovery stage at the seafloor. All function of the NX-2G at the seafloor was perfect with immediate extraction of the sensor unit. Noise level comparison with the BBOBS shows about 10 dB improvement that is not enough as expected, which may lie in a small tension of the cable between the sensor unit and the recording unit. And, scenes of the landing and the first transition were selfied by the Deep-Sea CAM.

We present approach based on physically substantiated short-term precursor’s selection to provide the real-time multiparameter monitoring having as a purpose the short-term forecast of earthquakes. Three main principles should be fulfilled: 1. We register natural phenomena for which we have multi-year experience demonstrating their connection with the earthquake preparation process 2. All these phenomena have very high statistical confidence in relation to post-phenomena earthquake occurrence 3. We have the physical explanation of these anomalous phenomena generation and their interrelation within the framework of earthquake preparation process. It is important to note that precursors are registered in different geospheres (lithosphere, atmosphere, ionosphere and magnetosphere) what confirms the fact of geospheres coupling during the earthquake preparation period. For the first time we included in consideration the role of triggers and their relationship with precursors. One of the well confirmed triggers is the Space weather evens changing the global atmospheric circulation. The arising large-scale irregularities of atmospheric pressure may serve as earthquake triggers while their linear borders coincide with the active tectonic fault. Another recently revealed effect is existence of earthquake retarders when earthquake happens later (up to month) in comparison with our procedure of earthquake time determination. Complications created by triggers and retarders in developed procedure of short-term earthquake forecast should be resolved in future development of our research. All these ideas are presented in the book which just published by Institute of Physics (IOP) and has the same title as abstract. This work was supported by RSF (project No 18-12-00441)

Coastal wetlands provide a wealth of ecosystem services, including improved water quality, protection from storm surges, and wildlife habitat. Louisiana’s wetlands, however, are threatened by development, pollution, and relative sea level rise (RSLR)—the combination of sea level rise and subsidence rates. Despite widespread wetland loss, areas such as the Wax Lake and Atchafalaya river deltas are in fact growing due to their sediment loads, resulting in a complex of both degradation and aggradation along the Louisiana coast. In order to understand and model how coastal wetlands are responding to RSLR, there is a need for improved vegetation mapping, biomass estimation, and landscape-scale study of accretionary processes. AVIRIS-NG offers high spatial and spectral resolution data that can be integrated with external datasets—including from in situ measurements, monitoring stations, and other remote sensing platforms—to study these distributions and processes. Spectra derived from AVIRIS-NG imagery were used to parameterize Multiple Endmember Spectral Mixture Analysis (MESMA) for mapping vegetation functional types in addition to partial least squares regression (PLSR) models for plant aboveground biomass (AGB). The historical Landsat record complemented this analysis by deriving maps of change in wetland health and sediment availability through time. Each of these remotely sensed parameters were investigated to determine their combined relationship to Louisiana’s coastal accretion rates. In quantifying landscape-scale processes that impact wetland accretion, this research aids the assessment of coastal resiliency in the face of sea level rise. Further, the investigated imaging spectroscopy methods pertaining to vegetation mapping, biomass estimation, and accretionary modeling will inform future studies under the global Surface Biology and Geology mission.

Due to its inherent ability to estimate the background error covariances, an ensemble Kalman filter (EnKF) is thought to be a practical approach to the strongly coupled data assimilation problems, where an entire coupled model state is estimated as if it was a single integrated system. However, increased complexity and the multiple time scale of the coupled system aggravate the rank-deficiency and spurious correlation problems caused by limited ensemble size available for the analysis. To alleviate these problems, a distance-independent localization method to systematically select the observations to be assimilated into each model variable has been developed and successfully tested with a nine-variable coupled model with slow and fast modes. This method, called correlation-cutoff method, utilizes the mean squared ensemble error correlation between each observable and model variable to identify where the cross-update should be used, and we cut off the assimilation of observations when the squared error correlation becomes small. To implement the method on a more realistic model, we thoroughly investigate inter-fluid background covariances in an atmosphere-ocean coupled general circulation model where the spatiotemporal scales of coupled dynamics significantly vary by latitudes and driving processes.

The Mw 7.2 Sarez strike-slip earthquake occurred on Dec 7, 2015 in the Pamir region at the North-West of the Tibetan Plateau. We used Sentinel-1A/B Interferometric Synthetic Aperture Radar (InSAR) data to investigate postseismic deformation due to the Mw 7.2 Sarez earthquake. We analyzed 2.5 years of post-earthquake acquisitions from the ascending track 100 and the descending track 005. Despite challenging surface conditions (that include rugged topography and snow cover), we were able to derive time series of line of sight (LOS) displacements within 150 km from the earthquake rupture. We used stacks of interferograms covering snow-free months, as well as persistent scatterers to detect possible deformation transients. Preliminary results indicate no postseismic relaxation signals above the noise level (10-20 mm/yr for average LOS velocities). We do observe coseismic deformation due to two M>6 earthquakes that occurred ~100 km to the North-East from the epicenter of the Sarez earthquake. We use constraints on the maximum amplitude of surface displacements provided by the InSAR data to provide bounds on the effective rheologic structure of the lower crust and upper mantle beneath Pamir.

Irrigation parameterizations in land surface models have been advanced over the past decade, but the newly available data from the Soil Moisture Active Passive (SMAP) satellite has seldom been used to improve irrigation modeling. Here, we investigate the potential of assimilating SMAP soil moisture (SM) data into the Community Land Model (CLM) to improve irrigation representation. Simulations are conducted at 3 arc-minute resolution over the highly irrigated region in the central US, fully enclosing the upstream areas of the river basins draining over the High Plains Aquifer (i.e., the Missouri and Arkansas), and Colorado River basins. We test the original CLM4.5 irrigation scheme and two new irrigation parameterizations using SMAP data assimilation by: (1) directly integrating raw SMAP data, and (2) integrating SMAP data using 1-D Kalman Filter (KF) smoother. An a priori scaling approach is also used to account for bias correction of the shortly-recorded SMAP data based on the ground observations, enabling us to use SMAP for out-of-sample tests (i.e., assessment of the new parameterizations during a non-SMAP period). The ground-based SM observations from three monitoring networks, namely Soil Climate Analysis Network (SCAN), US Climate Reference Network (USCRN), and SNOwpack TELemetry (SNOTEL) are employed for bias correcting SMAP data and validating SM simulations. Results show that SMAP data assimilation using 1-D KF significantly improves irrigation simulations. Bias correction of SMAP data further improves results from KF assimilation in some regions. However, the improvements are small compared to those achieved from 1-D KF application alone, indicating the robustness of using SMAP data and KF globally even for the regions where ground-based data are not available for bias correction. The data assimilation also improves the accuracy of the temporal dynamics and vertical profile of simulated SM. These results are expected to provide a basis for improved modeling of irrigation water use and land-atmosphere interactions.

Addressing research problems in Earth and environmental science usually requires combining data from multiple sources. This is facilitated by the use of common practices, vocabularies, interfaces and standards and recently it has been accelerated through connected communities of practice. This abstract will focus on the Earth Science Information Partners (ESIP) and the Australian Earth and Environment Science Information Partners (E2SIP) Over the last 20 years ESIP has built a community of practice in USA, supported by NASA, NOAA & USGS, through regular meetings and online forums to examine and develop emerging technologies. ESIP has become a braintrust and professional home for the Earth science data and informatics community where both peer-led education & training and the codevelopment of conventions, practices and guidelines have helped make Earth science data more interoperable. Through connections in the ESIP network and these boundary objects, ESIP has influenced the international community. The Australian Earth and Environment Science Information Partners (E2SIP) was recently established through liaison with ESIP to support similar functions in Australia. E2SIP is working with the National Earth and Environmental Sciences Facilities Forum which provides a common voice to government on behalf of long term science infrastructure. In addition, E2SIP, supported by programs from the National Research Infrastructure Strategy (NCRIS) such as the newly formed Australian Research Data Commons (ARDC), will convene workshops, courses, hackathons, and develop guidance and best practices tailored for the Australian community. This talk will explore how ESIP and E2SIP will work together, utilizing the collective impact framework orienting around a common shared agenda and leveraging a shared backbone structure in the U.S. and Australia. We will highlight our current understanding through a few case studies.

Arctic plants are small in stature and spectrally diverse, which presents challenges to current NASA missions to visualize effects of disturbance or directional vegetation change via mapping. Remotely sensed data having fine spatial (ca. 10 cm pixels) and spectral grain (eg. “hyperspectral”) will therefore help resolve patches of many arctic plant groups, such as dwarf shrubs, bryophytes and lichens and separate them from litter, wood or rock/soil. To address these challenges, in summer 2018 we sampled vegetation at 15 different sites around Fairbanks, Alaska using ground-based and airborne hyperspectral sensors under eight different AVIRIS ng flight lines next gen flight lines (circa 2017-2018). At each AVIRIS flight line, we estimated percent cover of plant functional types in eleven 1m2 quadrats every 10 m along a 100m transect. We then flew our UAV and imaging spectrometer (Headwall Micro A-series VNIR, 400-1000 nm, 330 bands, 10 cm pixels). Spectral signatures of any surfaces were sampled using a field spectroradiometer (PSR+ Spectral Evolution, 400-2500 nm, 1nm bands). We collected 600+ georeferenced scans from 70+ species/plant functional types at 25+ different sites around Alaska. Spectral profiles showed many different plant species have similar to indistinguishable signatures (eg. Paper birch and Alder) while many plant functional types that have been grouped together (eg. Moss) were very spectrally heterogenous. UAV-based hyperspectral imagery (ca. 4-10 cm pixels) resolved pure pixels of many artic plants. Our approach resolves fine grained ecological features, such as networks of circular patches (mostly lichens, brophytes and mineral soil) over very large areas (ca. 10,000 m2), created by small cryoturbation features (frost boils). We explore spectral unmixing and other statistical approaches to compare mapping results using our spectral library with AVIRIS ng (4 m pixels) and our UAV-based VNIR hyperspectral imagery.

The influence of clouds on photochemistry remains a significant uncertainty in global chemistry models. Variability in cloud fraction, morphology, phase and optical properties provides significant challenges to models with horizontal resolutions that far exceed the scale of most clouds. Measured photolysis frequencies derived from the Charged-coupled device Actinic Flux Spectroradiometers (CAFS) on board the NASA DC-8 during the Atmospheric Tomography (ATom) mission in 2016 provide an extensive set of statistics on how clouds alter the photolytic rates throughout remote ocean basins. Here we focus on north and tropical pacific transects during the first deployment (ATom-1) in August 2016 including regular profiles through cloudy, partly cloudy and clear conditions. Nine global chemistry–climate or –transport models provide similar statistics on J-values for regional domains encompassing the measured flight path. The statistical picture of the impact of clouds on J-values emerges through the distribution of the ratio of the cloud influenced models and measurement to corresponding cloud free model runs (J-cloudy/J-clear). The models all reproduce general patterns of enhancement above and shading below cloud, but diverge in distribution patterns and clear sky prevalence.

In long-established cities such as Detroit, MI, stormwater runoff from impervious surfaces (roads, roofs, etc.) is combined with sanitary waste and piped beneath the city to a wastewater treatment plant. These engineered methods of water management, termed gray infrastructure, currently dominate management practices but have drawbacks due to issues of cost, capacity, reliability, and maintenance requirements. In addition, combined sewer systems in cities like Detroit can become overwhelmed during extreme storm events, requiring the diversion of untreated sewage into local bodies of water. In a world of growing urbanization and intensifying storm events, the development of innovative approaches to stormwater management is expected to play a large role in mitigating negative environmental impacts from polluted urban runoff and flooding. The eco-friendly counterpart of gray infrastructure, known as green infrastructure (green roofs, rain gardens, bioswales, etc.), is an integrated approach to stormwater management that utilizes decentralized infiltration systems to mimic the natural processes of water filtration and deceleration. Correspondingly, our research focuses on a bioswale that was retrofitted into the center island of a previously designed parking lot in the post-industrial urban ecosystem of Detroit. The main goals of our work are to: 1) quantify potential pollutant removal, 2) quantify runoff infiltration capacity, and 3) provide qualitative insight into best management practices for future bioswale retrofits. We collected soil samples from 2 depths (30 and 45 cm) at 9 points from the bioswale for characterization (pH, organic matter, electric conductivity, and texture). We also collected and analyzed undisturbed soil cores with and without added metal contaminants common to Detroit and with a surface addition of biochar to test infiltration and determine the potential of increased contaminant sorption. The results will allow us to advance with an improved design and methodology and convey a strong argument for the expansion of bioswales and other forms of green infrastructure across the greater Detroit area, potentially leading to a more robust system of controlling stormwater that brings aesthetics, health, and a wide array of ecosystem services to a redeveloping concrete jungle.

High concentration of fluoride in the groundwater is observed to be associated with granitic aquifers as well as near phosphate mines around the globe. The present work is a hydrogeological study of the ground water of Beldih phosphate mines in India. Being located in the Singhbhum shear zone the area has a complex tectonic history and is dominated by phosphate, alkali granites, amphibolites, and granitic gneiss with higer abundance of fluoride bearing minerals like apatite and biotite. Total of 12 water samples were collected for a preliminary study to assess the spatial variation of fluoride in ground water and surface water with an aim to understand the effect of phosphate mines in elevating fluorosis in adjoining areas. The groundwater chemistry shows a trend that the concentration of fluoride and nitrate gets elevated as we approach towards the open cast phosphate mines. From the spatial observation combined with the water chemistry and geology it is evident that the apatite dissolution is the prime cause of the elevation in fluoride concentration. However presence of iron in the lithology controls the fluoride level to some extent. Since the area is effected with high fluorosis its can be concluded that the groundwater geochemistry along with the air borne fluoride present in the phosphate dust are the major cause of the fluorosis. The exploration of phosphate must be carried out with out most environmental care and the mitigation of post mining effect should be planned before mining operation. Fluorosis is an irreparable health hazard and a major geohealth concern that has already affected a large amount of population.

In 2013, the Office of Science and Technology Policy (OSTP) issued a memorandum directing Federal agencies with over $100 million in annual research and development expenditures to develop a plan to support increased access to federally funded research results. In response, the US Geological Survey developed a Public Access Plan and published four new data management policies. The policies focus on review and approval of scientific data supporting scholarly conclusions, requirements for metadata, preservation, and data management planning. The new policies, in conjunction with the Public Access Plan, represent a shift in culture in how the USGS manages and provides access to its science data. The USGS recognizes that successful implementation of these new policies requires multiple pillars of support, from USGS leadership and staff buy-in, to effective tools. Active community engagement in the Bureau is stimulated through the Community for Data Integration (CDI), an open forum for community discussion and engagement, and an important component creating buy-in and contributing to the success of the new policies. Also critical are a suite of tools available to scientists to ensure their ability to implement the policies. Finally, support from leadership that manifests in the Fundamental Science Practices Advisory Council (FSPAC), a committee of representatives from across the Bureau who preside over policies and guidance is a critical component. While far from complete, the USGS has shifted its approach to science data management by engaging the community, offering tools to support policy, and providing leadership support for the quality and scientific integrity of USGS science data.

Our presentation represents a brief overview of recent climatic and environmental changes over the Dry Lands of Northern Eurasia. The Dry Land Belt (DLB) in Northern Eurasia is the largest contiguous dryland on Earth. During the last century, changes here have included land use change (e.g., rapid virgin land development in the mid of the 1950s; cf. Figure 1), resource extraction, rapid institutional shifts (e.g., collapse of the Soviet Union), climatic changes, and natural disturbances. These factors intertwine, overlap, sometimes mitigate but sometimes feedback upon each other to exacerbate their synergistic and cumulative effects. Thus, it is important to document properly each of these external and internal factors and to characterize structural relationships among them in order to develop better approaches to alleviating negative consequences of these regional environmental changes. This paper addresses the climatic changes observed over the DLB in recent decades and outlines possible links of these changes (both impacts and feedbacks) with other external and internal factors of contemporary regional environmental change and human activities within the DLB.