bluuebunny/crossref_metadata_2025 huggingface dataset:
The Coda Calibration and Processing Tool: Java-Based Freeware for the Geophysical Community
Authors: Mayeda Kevin , Gok Rengin , Barno Justin , Walter William , Roman-Nieves Jorge
Published: March 2020

The coda magnitude method of Mayeda and Walter (1996) provides stable source spectra and moment magnitudes (Mw) for local to regional events from as few as one station that are virtually insensitive to source and path heterogeneity. The method allows for a consistent measure of Mw over a broad range of event sizes rather than relying on empirical magnitude relationships that attempt to tie various narrowband relative magnitudes (e.g., ML, MD, mb, etc.) to absolute Mw derived from long-period waveform modeling. The use of S-coda and P-coda envelopes has been well documented over the past several decades for stable source spectra, apparent stress scaling, and hazard studies. However, up until recently, the method requires extensive calibration effort and routine operational use was limited only to proprietary US NDC software. The Coda Calibration Tool (CCT) stems from a multi-year collaboration between the US NDC and LLNL scientists with the goal of developing a fast and easy Java-based, platform independent coda envelope calibration and processing tool. We present an overview of the tool and advantages of the method along with several calibration examples, all of which are freely available to the public via GitHub (https://github.com/LLNL/coda-calibration-tool). Once a region is calibrated, the tool can then be used in routine processing to obtain stable source spectra and associated source information (e.g., Mw, radiated seismic energy, apparent stress, corner frequency, source discrimination on event type and/or depth). As more events are recorded or new stations added, simple updates to the calibration can be performed. All calibration and measurement information (e.g., site and path correction terms, raw & measured amplitudes, errors, etc.) is stored within an internal database that can be queried for future use. We welcome future collaboration, testing and suggestions by the geophysical community.  
Composite distribution of North Atlantic extreme wind waves inferred from satellite altimetry data
Authors: Ponce de León Sonia , Bettencourt Joao
Published: March 2020

The north Atlantic Ocean is regularly traversed by extratropical cyclones and winter low pressure systems originated in the Western part of the basin that can potentially generate dangerous extreme sea states. The region where these extreme sea states occur is linked to the tracks of the low-pressure systems in the north Atlantic basin.

Extreme sea states are usually generated by storms that can traverse whole ocean basins and generate high-energy swells that can propagate for thousands of kilometers. Additionally, rogue waves are a recognized source of extreme waves that needs to be considered when designing for operation at sea.

This study aims at the spatial distribution of the mean and extreme wave significant wave height inside the extratropical cyclones. We studied the significant wave height distribution of extratropical cyclones using merged satellite altimetry data to produce composite maps of this sea state variable. Although there are large variations among individual cyclones, the compositing method allows obtaining general features. We find that the higher waves are in the south-eastern quadrant of the cyclone, due to the extended fetch mechanism. The highest wave heights are found during the 48h period when the cyclone’s strength is maximum.

 
Dynamics of atmospheric oxygen under anthropogenic stresses
Authors: Livina Valerie
Published: March 2020

We analyse proxy and observed data of atmospheric oxygen (ten contemporary records over the globe) and demonstrate its nonlinear decline, which is small but of uncertain decline rate. This decline was previously thought to be linear and caused mainly by use of fossil fuels (combustion), but by reviewing anthropogenic interventions we list more than a dozen smaller-scale processes that utilise oxygen in various forms. We have identified and quantified a previously unaccounted sink of atmospheric oxygen that serves multiple industries. This sink grows nonlinearly and has already exceeded the natural weathering deoxygenation. It has also been confirmed by means of comparison of the projection of oxygen decline with carbon emissions in the IPCC scenarios. We discuss the updated oxygen budget, possible solutions for the mitigation of the oxygen sink, and future dynamics of atmospheric oxygen.

[1] Livina et al, Tipping point analysis of atmospheric oxygen concentration, Chaos 25, 036403 (2015).

[2] Livina & Vaz Martins, The future of atmospheric oxygen, Springer Nature, in press.

 
Precipitation structure during the life cycle of cloud systems over Peru using satellite based observations
Authors: Kumar Shailenda , Silva Yamina , Del Castillo Carlos , Flores Rojas Jose Luis , S. Alveraz Aldo Moya , Castro Daniel Martinez
Published: March 2020

In the present study, a unique approach is applied to investigate the life cycle properties of the precipitation combining the satellite-based information. Data from Global Precipitation Measurement Dual Precipitation Radar (GPM-DPR) and brightness temperature (BT) form the GOES satellite. First, we used the GPM-DPR data to identify the precipitating cloud systems (PCSs) and then 9 (± 4 hours) hours of GOES BT data to identify the life phases for a particular PCSs e.g., a developing stage, a mature stage, or a dissipating stage. The case study of PCS related to different phases of the PCSs shows that PCSs consist of different systematic properties including the area of convective-stratiform precipitation, the convective rain rate and the storm-top height. The developing stage PCSs have the highest convective precipitation fraction (~26%) with highest near surface rain rate (RR, 4.97 mm h-1), whereas the dissipating stage PCSs have the largest precipitation area (11489 km2) with least near surface convective RR (~4.11 mm h-1). The vertical structure of precipitation and raindrop size distribution (DSD parameters) show the different characteristics above and below the freezing level and related with the different microphysical processes during different stages and related with the convective to stratiform area fraction and water vapour. The developing stage PCSs have the largest but sparse, droplets in convective precipitation, whereas the mature stage has the largest droplets below in the freezing level for all the vertical rainy profiles. The developing stage PCSs have the highest concentration of least sized of hydrometeors. Also, north-eastern continent of SA has higher near surface RR with higher sized of hydrometeors and even higher in developing stage PCSs. Our analysis indicates that the different microphysical properties for the PCSs in different phases are related to cloud and ice water path upward motion and related to the orographic influence.
Laboratory calibration of different soil moisture sensors in various soil types
Authors: Pečan Urša , Kastelec Damijana , Pintar Marina
Published: March 2020

Measurements of soil water content are particularly useful for irrigation scheduling. In optimal conditions, field data are obtained through a dense grid of soil moisture sensors. Most of the currently used sensors for soil water content measurements, measure relative permittivity, a variable which is mostly dependant on water content in the soil. Spatial variability of soil characteristics, such as soil texture and mineralogy, organic matter content, dry soil bulk density and electric conductivity can also alter measurements with dielectric sensors. So the question arises, whether there is a need for a soil specific calibration of such sensors and is it dependant on the type of sensor? This study evaluated the performance of three soil water content sensors (SM150T, Delta-T Devices Ltd, UK; TRIME-Pico 32, IMKO micromodultechnik GmbH, DE; MVZ 100, Eltratec trade, production and services d.o.o., SI) in nine different soil types in laboratory conditions. Our calibration approach was based on calibration procedure developed for undisturbed soil samples (Holzman et al., 2017). Due to possible micro location variability of soil properties, we used disturbed and homogenized soil samples, which were packed to its original dry soil bulk density. We developed soil specific calibration functions for each sensor and soil type. They ranged from linear to 5th order polynomial. We calculated relative and actual differences in sensor derived and gravimetrically determined volumetric soil water content, to evaluate the errors of soil water content measured by sensors which were not calibrated for soil specific characteristics. We observed differences in performance of different sensor types in various soil types. Our results showed measurements conducted with SM150T sensors were within the range of manufacturer specified measuring error in three soil types for which calibration is not necessary but still advisable for improving data quality. In all other cases, soil specific calibration is required to obtain relevant soil moisture data in the field.
A Survey of Interplanetary Small Flux Ropes at Mercury
Authors: Winslow Réka , Murphy Amy , Schwadron Nathan , Lugaz Noé , Yu Wenyuan , Farrugia Charles , Niehof Jonathan
Published: March 2020

Small flux ropes (SFRs) are interplanetary magnetic flux ropes with durations from a few minutes to a few hours. We have built a comprehensive catalog of SFRs at Mercury using magnetometer data from the orbital phase of the MESSENGER mission (2011-2015). In the absence of solar wind plasma measurements, we developed strict identification criteria for SFRs in the magnetometer observations, including conducting force-free field fits for each flux rope. We identified a total of 48 events that met our strict criteria, with events ranging in duration from 2.5 minutes to 4 hours. Using superposed epoch analysis, we obtained the generic SFR magnetic field profile at Mercury. Due to the large variation in Mercury's heliocentric distance (0.31-0.47 AU), we split the data into two distance bins. We found that the average SFR profile is more symmetric "farther from the Sun", in line with the idea that SFRs form closer to the Sun and undergo a relaxation process in the solar wind. Based on this result, as well as the SFR durations and the magnetic field strength fall-off with heliocentric distance, we infer that the SFRs observed at Mercury are expanding as they propagate with the solar wind. We also determined that the SFR occurrence frequency is nearly four times as high at Mercury as for similarly detected events at 1 AU. Most interestingly, we found two SFR populations in our dataset, one likely generated in a quasi-periodic formation process near the heliospheric current sheet, and the other formed away from the current sheet in isolated events.
Triple isotopic composition of oxygen in water and dioxygen during deglaciations recorded in the EPICA Dome C ice core to link climate, biosphere productivity and water cycle
Authors: Landais Amaelle , Yang Ji-Woong , Pasquier Nicolas , Grisart Antoine , Brandon Margaux , Extier Thomas , Prié Frédéric , Minster Bénédicte , Piel Clément , Sauze Joana , Milcu Alexandru , Stenni Barbara , Blunier Thomas
Published: March 2020

High precision measurements of triple isotopic composition of oxygen in water is a useful tool to infer the dynamic of past hydrological cycle when measured in ice core together with δ18O and δD. In particular, the triple isotopic composition of oxygen in water provides information on the climatic conditions of the evaporative sources. In parallel, it has been shown that the triple isotopic composition of oxygen in the atmospheric dioxygen can be a useful tracer of the global biosphere productivity and hence reconstruct the dynamic of the global biosphere productivity in the past from measurements performed in the air bubbles. Measuring triple isotopic composition of oxygen both in the water and in the atmospheric dioxygen trapped in bubbles in ice cores is thus a strong added value to study the past variability of water cycle and biosphere productivity in parallel to climate change.

Here, we first present new laboratory experiments performed in closed biological chambers to show how the triple isotopic composition of oxygen in atmospheric dioxygen can be used for quantification of the biosphere productivity with determination of fractionation coefficients. Then, we present new records of triple isotopic composition of oxygen in water and O2 trapped in bubbles from the EPICA Dome C ice core over the deglaciations of the last 800 ka.
Climatology and variability of jets in the upper troposphere
Authors: Spensberger Clemens , Spengler Thomas
Published: March 2020

Jets in the upper troposphere constitute a cornerstone of both synoptic meteorology and climate dynamics, thus providing a direct link between weather and mid-latitude climate variability. Conventionally, jet variability is mostly inferred indirectly through the variability of geopotential or sea-level pressure. Here we use a feature-based jet detection and present a global climatology of upper tropospheric jets as well as their variability for ocean sectors in both Hemispheres. The jet streams on both hemispheres are found to spiral poleward, featuring a continuous transition from subtropical to eddy-driven jets. Most intrinsic patterns of jet variability represent a changeover from a meridional shifting type variability to a pulsing-type variability, or vice-versa, across each ocean basin.

For the Southern Hemisphere, we find considerable discrepancies between geopotential and jet-based variability. Specifically, we show that SAM cannot be interpreted in terms of mid-latitude variability, as SAM merely modulates the most poleward part of the cyclone tracks and only marginally influences the distribution of other weather-related features of the storm track (e.g., position of jet axes and Rossby wave breaking). Instead, SAM emerges as the leading pattern of geopotential variability due to strong correlations of sea-level pressure around the Antarctic continent. Considering sector-specific variability pattern, we identify modes of consistent geopotential and jet variability in the South Pacific, and, to a lesser extent, the South Indian Ocean. In the South Pacific the leading mode of variability points towards NAO-like variability.
A new solar radiation pressure model for BDS-3 satellites
Authors: Chen Xinghan , Ge Maorong , Schuh Harald
Published: March 2020

Currently, with the rapid development of the third generation of BeiDou satellite system (BDS-3), the corresponding solar radiation pressure (SRP) forces should be well and soon modeled in order to enhance the performance of precise orbit determination (POD) and precise clock estimation (PCE) for high-precision applications. In this contribution, the BDS-3 post-processed and ultra-rapid PODs have been realized by fully exploiting data provided by the International GNSS Service (IGS). We firstly test the Center for Orbit Determination in Europe (CODE) SRP model (ECOM1) and ECOM2 models and notice a large disagreement of overlapping orbits at the boundary of two adjacent days within an eclipse period. The reason for this could be that the ECOM2 model is over-parameterized or an extra periodic SRP term should be considered. Furthermore, our numerical analyses confirm that the cosinus terms must be excluded and the fourth- and sixth-order SRP sinus terms are significant in the Sun direction for the SRP model of BDS-3 satellites. Therefore, a new SRP model is developed herein to improve BDS-3 orbits, especially for eclipse season. Using the new SRP model, the large fluctuations of 20 cm can be reduced to below 10 cm for the radial-track component of overlapping orbits over eclipse seasons and SLR residuals are improved by a factor of 2 compared to that of ECOM1 and ECOM2. For the predicted orbits, the improvement due to the new SRP model is also demonstrated and the mean offsets of overlapping orbit differences over the eclipse periods can be reduced from -9.3 cm, -18.9 cm, and 39.9 cm to -5.5 cm, 8.3 cm, and 12.7 cm in the radial, cross, and along directions, respectively.
The cooling, deformation and exhumation history of the late Miocene syn-tectonic Porto Azzurro pluton in a regional transfer zone (Elba Island, Italy)
Authors: Brogi Andrea , Spiess Richard , Caggianelli Alfredo , Langone Antonio , Stuart Fin , Zucchi Martina , Bianco Caterina , Liotta Domenico
Published: March 2020

In extensional tectonic settings, stretched terrains are often associated to lithosphere partial melting and widespread magmatism with plutons emplaced in the thinned crust. Emplacement of felsic magmas, at upper crustal levels, represents the final stage of the magma transfer from profound to shallow depth. In this framework, a mostly vertical permeability controls the magma uprising migration, as induced by dominant transcurrent crustal structures. Nevertheless, the interplay between extension and prolonged heat transfer favors uplift and progressive exhumation of the magmatic bodies, during their cooling.

In this presentation, we show an example of a felsic magmatic intrusion, the Porto Azzurro pluton (inner northern Apennines), emplaced in an extensional tectonic setting and mainly controlled by a regional transfer zone related to the opening of the Tyrrhenian Basin. This is exposed in the eastern Elba Island (Tuscan Archipelago). The hosting rocks of the Porto Azzurro pluton are mainly represented by micaschist, paragneiss and quartzite, affected by contact metamorphism and intense fluid circulation. We have analysed the structures that assisted the pluton emplacement and the ones that deformed the pluton itself during its cooling, from melt-present to brittle conditions, based on the integration among fieldwork, micro-structural, petrological and EBSD analyses. Furthermore, new U/Pb geochronological data on zircons and (U-Th)/He on apatite fission track refined the age of the pluton emplacement and its cooling, adding new data about the pluton history. Existing petrological analyses of the hosting rocks allowed us to better constrain the time-evolution of the thermal perturbation, permitting to frame the deformation and exhumation history of the Porto Azzurro monzogranite in the context of the Neogene extensional tectonics affecting the inner Northern Apennines.
Analysis of seismicity caused by fluid injection
Authors: Riga Vasily , Turuntaev Sergey
Published: March 2020

Induced seismicity associated with fluid injection into the subsurface is an important issue worldwide. Sometimes the fluid injection into a fault leads to aseismic creep of the fault or to microseismic events, but other times it results in more significant seismicity. In our work, we analyze the influence of various parameters of the fault and the rock, as well as the geometry of the model on induced seismicity. A case of well injecting water near a single fault was considered. To describe the slip process, several versions of the rate-and-state friction law was used. It was analyzed, how the model parameters, such as the position of the well relative to the fault, the permeability of the rock, the frictional properties of the fault affect the fault displacements. The problem of the poroelastic effect influence on the fault motion was also considered. Conditions that are favorable for the occurrence of noticeable seismicity were obtained. Difference in the fault behavior with one-parameter and two-parameter rate-and-state friction law were also considered.
Fires can overwinter in boreal forests of North America
Authors: Scholten Rebecca , Veraverbeke Sander
Published: March 2020

The boreal forest stores 35 % of the world’s soil carbon reserves. Wildfires burn frequently in the boreal forest of North America and drive the boreal forest carbon balance. Previously, lightning strikes and human activities were identified as the sole ignition sources for wildfires in the boreal regions of North America. In recent years however, fire managers in Alaska, USA and Northwest Territories, Canada have started reporting the occurrence of overwintering fires. Overwintering fires are fires, that survive the cold and wet boreal winter by smouldering in deep, carbon-rich soils and re-emerge early in the subsequent spring, when fire weather favours fire spread.

Using the location and ignition dates of 42 overwintering fires reported by fire managers in Alaska and Northwest Territories between 2002 and 2017, we developed an algorithm to identify these new ignition sources. Our algorithm detected 8 out of 9 additional reported fires we used for validation, and further identified 15 unreported overwintering fires. Even though overwintering fires make up only 0.5 % of the burned area in total, they can amount to up to more than 10 % of the annual burned area after exceptionally large fire years.

We found that overwintering of fires is facilitated by deep burning into the organic soils. Overwintering fires occur more frequently after large fire years in combination with subsequent mild winters and springs leading to an early snowmelt.

In a warming climate, the boreal forest is burning more frequently and more intensely. As a consequence, the burned area and burn depth are predicted to increase. Our results suggest that overwintering fires are closely tied to these conditions and will therefore occur more often in the future.
What changes when we use ambient noise recorded by fiber optics?
Authors: Martin Eileen , Lindsey Nate , Biondi Biondo , Ajo-Franklin Jonathan , Zhu Tieyuan
Published: March 2020

Ambient noise seismology has greatly reduced the cost of acquiring data for seismic monitoring and imaging by reducing the need for active sources. For applications requiring time-lapse imaging or continuous monitoring, we desire sensor arrays that require little effort, money, and power to maintain over long periods of time. Distributed Acoustic Sensing repurposes a standard fiber optic cable as a series of single-component strain rate sensors with spacing at the scale of meters over distances of kilometers. With a single location providing the power source and recording all data, along with the ability to use existing underground fiber optic networks, a small team is now able to easily establish a monitoring network and acquire massive amounts of strain rate data continuously.

This talk will explore two conceptual changes when using DAS data for ambient noise interferometry: greatly increased data volumes, and the difference between velocity and distributed strain-rate data. These two challenges will be illustrated in the context of experiments with applications in near-surface Vs imaging with applications in earthquake hazard analysis, permafrost thaw monitoring, and urban geohazard and hydrology monitoring.

On the issue of data volumes: Orders of magnitude more sensors and high sample rates (often in the kilohertz range) quickly result in data quantities that exceed the limits of computational infrastructure and algorithms available to many seismologists, potentially at the petabyte/year scale for modern acquisition instruments. New algorithms focused on reduced data movement are improving our ability to analyze more data with existing resources. This talk will include a brief overview of some recent algorithmic improvements for both ambient noise interferometry for imaging, and interferometry-based event detection.

On the issue of changing from velocity to distributed strain rate data: Because strain rate is a tensor quantity and velocities are a vector quantity, the sensitivity of DAS to seismic sources at different orientations is quite different from typical seismometers. This difference can be clear both in polarity and amplitude of the signal, and is particularly significant in shear and Love wave recordings. We will describe simple models to describe expected changes in how seismometers and DAS record the same noises, and the corresponding changes expected in noise correlation functions. These sensitivity differences are more pronounced in ambient noise correlation functions than they are in raw signal recordings, effectively emphasizing a different distribution of ambient noise sources. Modeling these sensitivities helps determine which sensor orientations are reliable for use in ambient noise interferometry imaging.
Hydrology of plants: Modeling the interaction between infiltration and evapotranspiration.
Authors: D'Amato Concetta , Tubini Niccolò , Bottazzi Michele , Noto Leonardo , Rigon Riccardo
Published: March 2020

It is known that measuring and modeling of water and solute fluxes across soil-plant-atmosphere is nowadays a very important challenge because of the complexity of both soil and plants. In particular evapotranspiration (Schymanski and Or, 2017) is related with radiation, temperature, relative humidity, wind but it depends also by the water content in soil. Specifically, the water content varies with precipitation and with the water properties of soil, soil water retention curves and soil hydraulic conductivity.  
To consider the effects of water content on the rate of evapotranspiration it is necessary to study infiltration and evapotranspiration processes and find a physical, but also, a modelling point of view to coupled these processes.  

Considering the 1D problem we implement a virtual lysimeter model in which we coupled infiltration and evapotranspiration by using stress factor (Collatz at all, 1991), with which we can compute effective evapotranspiration and remove it from Richards’ equation balance (Casulli and Zanolli, 2010). In addition, the modeling of water and solute fluxes across soil-plant-atmosphere is made possible by implementation of travel times of waters within vegetation, the growing of the roots and in general the growing of the plants. 

Casulli e Zanolli, 2010. A Nested Newton-type algorithm for finite volume methods solving Richards’ equation in mixed form. SIAM J. SCI. COMPUT. Vol. 32, No. 4, pp. 2255–2273.

G. James Collatz, J. Timothy Ball, Cyril Grivet and Joseph A. Berry, 1991. Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer. Agricultural and Forest Meteorology, Vol. 54, pp. 107-136.

P.M. Cox, C. Huntingford, R.J. Harding, 1998. A canopy conductance and photosynthesis model for use in a GCM land surface scheme. Journal of Hydrology 212–213, 79–94.

Jarvis, P.G., 1976. The interpretation of the variances in leaf water potential and stomatal conductance found in canopies in the field. Phil. Trans. Roy. Soc. Lond. B273, 593–610.

Stanislaus J. Schymanski and Dani Or, 2017. Leaf-scale experiments reveal an important omission in the Penman–Monteith equation. Hydrol. Earth Syst. Sci., 21, 685–706.
Artemisia halodendron litters have strong negative allelopathic effects on earlier successional plants during vegetation restoration in a semi-arid sandy dune region in China
Authors: Du Zhong , Luo Yongqing , Yan Zhiqiang , Zhao Xueyong , Li Yuqiang , Yang Yue , Li Mai-He
Published: March 2020

Artemisia halodendron Turcz. ex Besser occurs following the appearance of a pioneer species, Agriophyllum squarrosum (L.) Moq., and the former “killed” and replaced the latter during the naturally vegetation succession in sandy dune regions in China. A previous study revealed that the foliage litter of A. halodendron had strong negative allelopathic effects on germination of the soil seed bank and on the seedling growth. It is unclear whether an allelopathic effect of A. halodendron litters positively or negatively affects the seed germination, leading to a progressively replacement of the plant species in sandy dune regions.

We, therefore, carried out a seed germination experiment to determine the allelopathic effects of three litter types of A. halodendron (roots, foliage, and stems) on seed germination of six plant species that progressively occur along a successional gradient in the semi-arid grasslands of northeastern China.

In line with our expectation, we found that the early-successional species rather than the late-successional species were negatively affected by the allelopathic effects of A. halodendron, and that the allelopathic effects on seed germination increase with increasing concentration of litter extracts, irrespective of litter types.

Our study evidenced the negative allelopathic effects of A. halodendron on the species replacement and on the community composition during dune stabilization. Further studies are needed to better understand the successional process and thus to promote the vegetation restoration, as A. halodendron itself disappeared also during the process.
Multi-spacecraft Observations of interacting CME flux ropes
Authors: Kilpua Emilia , Good Simon , Palmerio Erika , Asvestari Eleanna , Pomoell Jens , Lumme Erkka , Ala-Lahti Matti , Kalliokoski Milla , Morosan Diana , Price Daniel , Magdalenic Jasmina , Poedts Stefaan , Futaana Yoshimi
Published: March 2020

Interactions between coronal mass ejections (CMEs) in interplanetary space are a highly important aspect for understanding their physical dynamics and evolution as well as their space weather consequences. Here we present an analysis of three CMEs that erupted from the Sun on June 12-14, 2012 using almost radially aligned spacecraft at Venus and Earth, complemented by heliospheric imaging and modelling with EUHFORIA. These multi-spacecraft observations were critical for interpreting the event correctly, in particular regarding the last two CMEs in the series (June 13 and June 14). At the orbit of Venus these CMEs were mostly separate with the June 14 CME just about to reach the previous CME. A significant interaction occurred before the CMEs reached the Earth. The shock of the June 14 CME had propagated through the June 13 CME and the two CMEs had coalesced into a single large flux rope structure before they reached the Earth. This merged flux rope had one of the largest magnetic field magnitudes observed in the near-Earth solar wind during Solar Cycle 24. We discuss also the general importance of multi-spacecraft observations and modelling using them in analyzing solar eruptions.
Seasonal partitioning of precipitation between streamflow and evapotranspiration, inferred from end-member splitting analysis
Authors: Kirchner James , Allen Scott
Published: March 2020

The terrestrial water cycle partitions precipitation between its two ultimate fates: "green water" that is evaporated or transpired back to the atmosphere, and "blue water" that is discharged to stream channels.  Measuring this partitioning is difficult, particularly on seasonal timescales.  End-member mixing analysis has been widely used to quantify streamflow as a mixture of isotopically distinct sources, but knowing where streamwater comes from is not the same as knowing where precipitation goes, and this latter question is the one we seek to answer.  Here we introduce "end-member splitting analysis", which uses isotopic tracers and water flux measurements to quantify how isotopically distinct inputs (such as summer vs. winter precipitation) are partitioned into different ultimate outputs (such as evapotranspiration and summer vs. winter streamflow).  End-member splitting analysis has modest data requirements and can potentially be applied in many different catchment settings.  We illustrate this data-driven, model-independent approach with publicly available biweekly isotope time series from Hubbard Brook Watershed 3.  A marked seasonal shift in isotopic composition allows us to distinguish rainy-season (April-November) and snowy-season (December-March) precipitation, and to trace their respective fates.  End-member splitting shows that about one-sixth (18±2%) of rainy-season precipitation is discharged during the snowy season, but this accounts for over half (60±9%) of snowy-season streamflow.  By contrast, most (55±13%) snowy-season precipitation becomes streamflow during the rainy season, where it accounts for 38±9% of rainy-season streamflow.  Our analysis thus shows that significant fractions of each season's streamflow originated as the other season's precipitation, implying significant inter-seasonal water storage within the catchment, as both groundwater and snowpack.  End-member splitting can also quantify how much of each season's precipitation is eventually evapotranspired.  At Watershed 3, we find that only about half (44±8%) of rainy-season precipitation evapotranspires, but almost all (85±15%) evapotranspiration originates as rainy-season precipitation, implying that there is relatively little inter-seasonal water storage supplying evapotranspiration.  This proof-of-concept study demonstrates that end-member mixing and splitting yield different, but complementary, insights into catchment-scale partitioning of precipitation into blue water and green water.  It could thus help in gauging the vulnerability of both water resources and terrestrial ecosystems to changes in seasonal precipitation.
Surveying the Machine Learning Landscape in Earth Sciences
Authors: Ramasubramanian Muthukumaran , Virts Katrina , Shirey Ashlyn , Kumar Ankur , Hassan Muhammad , Acharya Ashish , Ramachandran Rahul , Manil Maskey
Published: March 2020

Several recent papers have investigated different challenges in applying machine learning (ML) techniques to Earth science problems. The challenges listed range from interpretability of the results to computational demand to data issues. In this paper, we focus on specific challenges listed in the review papers that are centered around training data, as the size of training data is important in applying deep learning (DL) techniques.  We are in the process of conducting a literature survey to better understand these challenges as well as to understand any trends. As part of this survey, our review has encompassed Earth science papers from AGU, AMS, IEEE and SPIE journals covering the last ten years and focused on papers that utilize supervised ML techniques.

Our initial survey results show some interesting findings. The use of supervised machine learning techniques in Earth science research has increased significantly in the last decade. The number of atmospheric science papers (i.e., from AMS journals) using ML approaches has increased by over 40%. Across all of Earth science even larger changes have occurred, including a >90% increase in AGU papers and a >10-fold increase in IEEE papers using ML.

We also conducted a deep dive into all the papers from AGU journals and uncovered interesting findings. There is a prevalence of the use of supervised ML in certain sub-disciplines within Earth science. The biogeoscience and land surface research communities lead in this area: over 20% of papers published in Global Biogeochemical Cycles, JGR Biogeosciences, JGR Earth Surface, and Water Resources Research use supervised ML techniques, including over 35% of the papers in JGR Biogeosciences. The availability of labeled training data in Earth science is reflected in the number of training samples used in supervised analysis. In the papers we surveyed, most ML algorithms were trained using small (i.e. hundreds of labeled) samples. However, for some applications using model output or large, established datasets, the number of training data ranged several orders of magnitude greater.

In this presentation, we will describe our findings from the literature survey. We will also list recommendations for the science community to address the existing challenges around training data.
Which climate models capture the variability and forced response in observed temperatures: a large ensemble comparison
Authors: Maher Nicola , Suarez-Gutierrez Laura , Milinski Sebastian
Published: March 2020

We evaluate how large ensembles of ten coupled climate models represent the observed internal variability and response to external forcings in historical surface temperatures based on a novel methodological framework. This framework allows us to directly attribute whether discrepancies between models and observations arise due to biases in the simulated internal variability or rather in the forced response, without relying on assumptions to separate both signals in the observations. The largest discrepancies occur due to overestimated forced warming in some models during recent decades. The areas where most models, a maximum of nine, adequately simulate observed temperatures are the North Atlantic, Tropical Eastern Pacific, and the Northern Hemisphere land areas. In contrast, none of the models considered offers an adequate representation over the Southern Ocean. Our evaluation shows that CESM-LE, GFDL-ESM2M, and MPI-GE perform best at representing the internal variability and forced response in observed surface temperatures both globally and regionally. 
Machine Learning is Central to the Future of Hydrological Modeling
Authors: Nearing Grey , Kratzert Frederik , Pelissier Craig , Klotz Daniel , Frame Jonathan , Gupta Hoshin
Published: March 2020

This talk addresses aspects of three of the seven UPH themes: (i) time variability and change, (ii) space variability and scaling, and (iii) modeling methods. 

During the community contribution phase of the 23 Unsolved Problems effort, one of the suggested questions was “Does Machine Learning have a real role in hydrological modeling?” The final UPH paper claimed that “Most hydrologists would probably agree that [extrapolating to changing conditions] will require a more process-based rather than calibration-based approach as calibrated conceptual models do not usually extrapolate well.” In this talk we will present a collection of recent experiments that demonstrate how catchment models based on deep learning can account for both temporal nonstationarity and spatial information transfer (e.g., from gauged to ungauged catchments), often achieving significantly superior predictive performance compared to other state-of-the-art (process-based) modeling strategies, while also providing interpretable results. This is due to the fact that deep learning can learn, exploit, and explain catchment and hydrologic similarity in ways and with accuracies that the community has not been able to achieve using traditional methods. 

We argue that the results we have obtained motivate a path forward for hydrological modeling that centers around ‘physics-informed machine learning.’ Future model development might focus on building hybrid (AI + process-informed) models with three objectives: (i) integrating known catchment behaviors into models that are also able to learn directly from data, (ii)  building explainable deep learning models that allow us to extract scientific insights, and (iii) building hybrid models that are also able to simulate unobserved or sparsely observed variables. We argue further that while the sentiments expressed in the UPH paper about process-based modeling are common, the community currently lacks an evidence-based understanding of where and when process-based understanding is important for future predictions, and that addressing this question in a meaningful way will require true hybrids between different modeling approaches.

We will conclude by providing two fundamentally novel examples of physics-informed machine learning applied to catchment-scale and point-scale modeling: (i) conservation-constrained neural network architectures applied to rainfall-runoff processes, and (ii) integrating machine learning into existing process-based models to learn unmodeled hydrologic behaviors. We will show results from applying these strategies to the CAMELS dataset in a rainfall-runoff context, and also to FluxNet soil moisture data sets.
Evaluating CMIP6 Model Fidelity at Simulating Non-Gaussian Temperature Distribution Tails
Authors: Catalano Arielle , Loikith Paul , Neelin J. David
Published: March 2020

Under global warming, changes in extreme temperatures will manifest in more complex ways in locations where temperature distribution tails deviate from Gaussian. For example, uniform warming applied to a temperature distribution with a shorter-than-Gaussian warm tail would lead to greater exceedances in warm-side temperature extremes compared with a Gaussian distribution. Confidence in projections of future temperature extremes and associated impacts under global warming therefore relies on the ability of global climate models (GCMs) to realistically simulate observed temperature distribution tail behavior. This presentation examines the ability of the latest state-of-the-art ensemble of GCMs from the Coupled Model Intercomparison Project phase six (CMIP6) to capture historical global surface temperature distribution tail shape in hemispheric winter and summer seasons. Comparisons between the multi-model ensemble mean and a reanalysis product reveal strong agreement on coherent spatial patterns of longer- and shorter-than-Gaussian tails for the cold and warm sides of the temperature distribution, suggesting that CMIP6 is broadly capturing tail behavior for plausible physical and dynamical reasons. Most individual GCMs are also reasonably skilled at capturing historical tail shape on a global scale, but a division of the domain into sub-regions reveals considerable model and spatial variability. To explore potential mechanisms driving these differences, a back trajectory analysis examining patterns in the origin of air masses on days experiencing extreme temperatures is also discussed.
Towards operational quantification of GHG exchange in heterogeneous agricultural landscapes and experimental plots
Authors: Kruijt Bart , Nouta Reinder , Jacobs Cor , van den Berg Merit , Fritz Christian , Klumpp Katja , Hutjes Ronald , Franssen Wietse , Osborne Bruce
Published: March 2020

With the increasing  need to mitigate rising atmospheric greenhouse gas (GHG) concentrations more attention is being directed at the quantification  of the GHG exchange characteristics of heterogenous landscape assemblages that vary in land cover and land use.   Whilst emission-limiting or uptake-enhancing management actions are often being proposed for specific land use most remain to be experimentally tested and  validated at the landscape scale. This is a challenge because the typical size of different landscape elements  (fields, afforested areas and unmanaged land at hectare scale) or experimental fields where emission reduction measures are being tested, is at the lower limit of what micrometeorological techniques such as eddy covariance measurements can deal with. With large heterogeneity the use  of chamber measurements is also limited. The investments to be made in equipment are a challenge for operational monitoring of GHG budgets.

To address this we assess the feasibility of several options to acquire appropriate data in a way that is achievable for stakeholders, such as land managers and regional authorities. We use existing and new flux data from an agricultural landscape in the North of the Netherlands  to: 1) compare paired eddy covariance (EC) data and automatic chamber (AC) data to test the representativity of small footprints. Results from a test site on drained meadows show almost identical CO2 fluxes. Future research should compare grass length and soil moisture of EC- and AC footprints; 2) test simplified alternatives to EC, such as those relying on concentration variances. Data from the peat meadow site suggest that time-averaged fluxes can be estimated in an empirical way with reasonable accuracy from concentration variances; 3) analyze the value of information gathered with mobile, roving/temporary EC approaches interpolated with gap filling models. The indications are  that the values and variability of fluxes is largely  conserved and predictable within seasons In all these analyses, we will consider the tradeoffs between the need for accuracy and pragmatism in operational practice.
Can Continental Models Convey Useful Seasonal Hydrologic Information at the Catchment Scale?
Authors: Crochemore Louise , Ramos Maria-Helena , Pechlivanidis Ilias
Published: March 2020

Climatic variations can have a significant impact on a number of water-related sectors. Managing such variations through accurate predictions is thus crucial. Continental hydro-climate services have recently received attention to address various user needs. However, predictions for months ahead can be limited at catchment scale, highlighting the need for data tailoring. Here, we address how seasonal forecasts from continental services can be used to address user needs at the catchment scale. We compare a continentally-calibrated process-based model (E-HYPE) and a catchment-specific parsimonious model (GR6J) to forecast streamflow in a set of French catchments.

This work provides insights into UPH 20 (How can we disentangle and reduce model structural/parameter/input uncertainty in hydrological prediction?) by proposing a skill assessment framework that isolates gains from hydrological model forcings and forecast initialisation. Our results show that a good estimation of the hydrologic states, such as soil moisture or lake levels, prior to the prediction is the most important factor in obtaining accurate streamflow predictions in both setups. We also show that the spread in internal model states varies largely between the two systems, reflecting the differences in their setups and calibration strategies, and highlighting that caution is needed before extracting hydrologic variables other than streamflow.

This work also provides insights into UPH 21 (How can the (un)certainty in hydrological predictions be communicated to decision makers and the general public?). Despite the expected high performance from the catchment setup against observed streamflow, the continental setup can, in some catchments, match the catchment-specific setup for 3-month aggregations and when looking at statistics relative to model climatology, such as anomalies. Nevertheless, differences in the setups can result in different uncertainties for variables such as soil water content.
Probabilistic damage scenarios from uncertain macroseismic data
Authors: Varini Elisa , Rotondi Renata
Published: March 2020

Nowaday, macroseismic data are still essential for the seismic hazard assessment in several regions because they provide important knowledge on preinstrumental earthquakes, nedeed to compile historical earthquake catalogs. This is especially true for Italy, which boasts a large and accurate macroseismic database, DBMI15, composed by 122701 macroseismic records related to 3212 earthquakes occurred from 1000 up to 2014. It should be noted that some records are incomplete or the available information is insufficient for the assignment of the intensity at a given site (e.g. intensity IX-X denotes that the level of damage at that site is uncertain and evaluated IX or X with a probability of 50% each). In order to respect both the ordinal nature of macroseismic intensity and its tendency to decrease with distance from the epicentre, we consider the beta-binomial model by Rotondi and Zonno (Ann. Geophys., 2004; Rotondi et al., Bull. Earthq. Eng., 2016) which describes the probability distribution of the intensity at a site, conditioned on the epicentral intensity and on the epicentre-to-site distance. The application of the beta-binomial model typically requires rounding-up or -down the observed intensities to the nearest integer values. We propose an extension of the beta-binomial model in order to include in the stochastic modelling the uncertainty in the assignment of the intensities. Then we exploit the advantages of the Bayesian approach for uncertainty quantification both in the estimation procedure and in the forecast of damage scenarios.