bluuebunny/crossref_metadata_2025 huggingface dataset:
The role of water content in wildfire ash mobilization by wind erosion under laboratory conditions
Authors: Keizer Jan , Martins Ricardo , Xavier Adriana , Vieira Diana , Miranda Ana , Sorte Sandra , Borrego Carlos , Correia Luís , Morgado Fábio , Rafael Sandra , Rebelo Micael
Published: March 2020

The Portuguese ASHMOB project (CENTRO-01-0145-FEDER-029351) is addressing the overall lack of knowledge on the mobilization of wildfire ash with time since fire. More specifically, ASHMOB is looking into the lateral transport of wildfire ash by water as well as wind erosion. ASHMOB involves a combined measurement-modeling approach comprising five phases: (i) wildfire ash collection and characterization; (ii) wind tunnel experiments of ash mobilization by wind erosion; (iii) hydraulic laboratory experiments of ash mobilization by rainfall splash, run-on and their combination; (iv) adjusting selected wind and water erosion models to accommodate erosion of wildfire ash; (v) validating the adjusted models by field measurements in a recently burnt area.  The current presentation concerns the second phase and, in particular, wind tunnel experiments aiming to assess the influence of water content on the post-fire ash mobilization. The experiments were performed in the wind tunnel of the Atmosphere Aerodynamics Laboratory of Aveiro University’s Department of Environment and Planning, which is an open-circuit wind tunnel with 13 m long and a test section of 6.5x1.5x1.0 m (LxWxH), often used for physical modelling of urban flows and air quality. For these experiments, wildfire ash was used from three different land cover types, i.e. Maritime Pine and Eucalypt forest plantations and Strawberry tree woodlands (or, more concretely, woodland patches). These ashes were collected as soon as possible after three wildfires that occurred during the summer of 2019 in central Portugal, typically within 2 weeks. The pine, strawberry tree and eucalypt ashes were collected following wildfires in july in Vila de Rei, august in Fátima and september in Albergaria-a-Velha, respectively. The experiments involved one specific ash load of 10 mm, based on findings of earlier experiment with varying ash loads, and ash-to-water ratio of 1:0, 1:0.25, 1:0.5, 1:0.75, 1:1, 1:1.5 and 1:2 (wash/wwater) at the start of the experiments. Ash mobilization with stepwise increasing wind speeds up till 9 m.s-1 was measured continuously using a measurement scale linked to a computer and was also filmed from above using a Go-Pro video camera. For each combination of ash type and ash-to-water ratio, 5 replicate experiments were run. Preliminary analysis of the obtained results revealed a clear role of water content in the mobilization by wind of all three types of wildfire ash, with marked increased shear velocity with increasing ash-to-water ratio. At the same time, shear velocity also differed markedly between the woodland types, with consistently lower shear velocity for pine ash than for eucalypt as well as strawberry tree ash at the different ash-to-water ratios.
Last interglacial speleothem records from the western and southeastern side of the Alps
Authors: Honiat Charlotte , Spötl Christoph , Jaillet Stéphane , Wilcox Paul , Racine Tanguy , Edwards R.Larry , Cheng Hai
Published: March 2020

The Last Interglacial (LIG, ~130–116 ka) was one of the warmest interglacials of the past 800,000 years. Although the orbital configuration was different, the LIG is a useful test bed for the future of the Holocene, because LIG archives have a higher preservation potential and can be dated at much higher precision than older interglacials, e.g. Marine Isotope Stage 11. Speleothems are among the most important terrestrial archives to study the climate of the LIG. Only few well-dated such studies, however, have been published for Europe and there are significant uncertainties regarding the timing of the onset and the magnitude of the peak warmth between some of these reconstructions.

The European Alps have shown to be a climatically highly sensitive region with a warming trend twice the average of the Northern Hemisphere. We therefore examined Alpine caves and studied stalagmite records of the LIG to gain insights into how this mountain range was affected by a warmer climate than today. We present a new, replicated and precisely dated speleothem stable isotope stack from two caves in the Western Alps and two caves in the southeastern Alps. Modern and paleodata show that the O isotopic composition of meteoric precipitation is a function of the mean air temperature in most parts of the Alps. Western stalagmites record an initial warming at 129.6 ± 0.4 ka and reach a first O isotope plateau at 129.0 ± 0.4 ka. An early optimum is identified after the first warming until 127.4 ± 0.5 ka, followed by a cooling until 126.6 ± 0.5 ka. The warming continued but the growth rate slowed down from 126.2 ±0.4 ka to 123.7 ±0.8 ka. Toward the end of the record (123.7 ±0.8 ka) the carbon isotopes slightly rise toward less negative values, possibly indicating climate cooling. The southeastern Alpine stalagmites started growing after Termination II (between 129.1±1.1 ka and 128.5±0.5 ka) and the oxygen isotope values slightly increase from 129 to 120 ka. At the onset of the LIG the carbon isotope values show a stepwise decrease as the oxygen isotope values become less negative, documenting the expansion of vegetation and the gradual soil development during the early part of the LIG. Vegetation and soil bioproductivity peaked around 126 ka in the west and at 125 ka in the southeast. Growth in the west was interrupted soon after 125 ka while in the southeast the carbon isotope signal stayed stable until 123 ka. The final decrease in vegetation density towards the end of the LIG was less synchronous among the southeastern speleothems and was characterized by abrupt shifts. Most stalagmites stopped growing after 119 ka when the carbon isotope values reached their highest values indicating a decrease in soil activity and/or vegetation density, possibly associated with deforestation. 
Observation-constrained Radiative Forcing from historical land-cover changes in CMIP5 models
Authors: Lejeune Quentin , Davin Edouard , Duveiller Grégory , Crezee Bas , Meier Ronny , Cescatti Alessandro , Seneviratne Sonia
Published: March 2020

The albedo of trees is lower than the one of crops and grasses, especially in the presence of snow. It is therefore understood that the replacement of forests by croplands and grasslands used for agricultural purposes that has occurred since pre-industrial times led to large-scale albedo increases. This is reflected by the estimate of the Radiative Forcing (RF) from historical Land-Cover Changes (LCC) of the Fifth Assessment Report (AR5) of the IPCC, which amounts to -0.15 +/- 0.10 W/m2. However, this expert judgment was intended to both account for a few studies using single climate models which put forward values close to 0.2W/m2, and the finding that climate models usually overestimate the albedo difference between natural vegetation and croplands in comparison to satellite-derived observational evidence. Further uncertainties around this number have also been suggested by studies revealing a substantial model spread in the albedo response to historical LCC. This points at the need to revisit the IPCC AR5 conclusions in light of recent model intercomparison efforts and observational data.

In this study, we reconstructed the local albedo changes induced by conversions between trees and crops/grasses since 1860 for 15 CMIP5 models. We evaluated the employed methodology using factorial experiments isolating the historical LCC forcing in four models for which the required simulations are available, and obtained very similar results. Using an empirical parameterisation of the radiative kernel, we then derived estimates of the associated RF ranging between 0 and -0.22 W/m2, with a multi-model mean value of -0.07 W/m2.

Furthermore, we constrained the RF estimates with observations by replacing the albedo response to the transition between trees and crops/grasses from the models by that provided by satellite-derived data. This led to an unexpected increase in the range between the models, due to two models having unrealistic conversion rates from trees to crops/grasses. Excluding these two models, we obtain a revised multi-model mean estimate of -0.11 W/m2 (with individual model results between -0.04 and -0.16 W/m2). We were also able to link the differences between the unconstrained and constrained RF estimates to some of the model biases in the albedo sensitivity to deforestation.

Since the conversions between trees and crops/grasses are responsible for almost the totality of historical albedo changes in CMIP5 models, our findings are comparable to previous estimates of the RF from all LCC. They point at values that are at the lower end of the range provided by the IPCC AR5. The approach described in this study can be applied on other model simulations, such as those from CMIP6.
An overview of the EUCP project – towards improved European Climate Predictions and Projections
Authors: Lowe Jason A. , McSweeney Carol , Hewitt Chris
Published: March 2020

There is clear evidence that, even with the most favourable emission pathways over coming decades, there will be a need for society to adapt to the impacts of climate variability and change. To do this regional, national and local actors need up-to-date information on the changing climate with clear accompanying detail on the robustness of the information. This needs to be communicated to both public and private sector organisations, ideally as part of a process of co-developing solutions.

EUCP is an H2020 programme that began in December 2017 with the aim of researching and testing the provision of improved climate predictions and projections for Europe for the next 40+ years, and drawing on the expertise of researchers from a number of major climate research institutes across Europe. It is also engaging with users of climate change information through a multiuser forum (MUF) to ensure that what we learn will match the needs of the people who need if for decision making and planning.

The first big issue that EUCP seeks to address is how better to use ensembles of climate model projections, moving beyond the one-model-one-vote philosophy. Here, the aim is to better understand how model ensembles might be constrained or sub-selected, and how multiple strands of information might be combined into improved climate change narratives or storylines. The second area where EUCP is making progress is in the use of very high-resolution regional climate simulations that are capable of resolving aspects of atmospheric convection. Present day and future simulations from a new generation of regional models ae being analysed in EUCP and will be used in a number of relevant case studies. The third issue that EUCP will consider is how to make future simulations more seamless across those time scales that are most relevant user decision making. This includes generating a better understanding of predictability over time and its sources in initialised forecasts, and also how to transition from the initialised forecasts to longer term boundary forced climate projections.

This presentation will provide an overview of the challenges being addressed by EUCP and the approaches the project is using.

 
Scattering of lightning optical radiation by complex, inhomogeneous clouds
Authors: Luque Estepa Alejandro , Gordillo-Vázquez Francisco José , Li Dongshuai , Malagón-Romero Alejandro , Soler Sergio , Pérez-Invernón Francisco Javier , Chanrion Olivier , Heumesser Matthias , Neubert Torsten
Published: March 2020

Lightning flashes emit intense optical radiation that can be detected from space. Several space missions work by observing this light in order to investigate lightning, thunderstorms, and other phenomena closely associated to them such as Transient Luminous Events (TLEs) and Terrestrial Gamma-ray Flashes (TGFs).

In its path towards a satellite-borne observing device, the optical radiation emitted by a flash is scattered many times by the droplets and ice crystals in the cloud. The detected signal is thus shaped by and contains information about the cloud geometry and composition. This is particularly relevant for instruments with a high spatial resolution such as the cameras in the Modular Multispectral Imaging Array (MMIA), which is part of the Atmosphere-Space Interactions Monitor (ASIM) currently onboard the International Space Station. These cameras provide images of lightning-illuminated cloud tops with a resolution of about 400 m.

We present a numerical code that can simulate light scattering in clouds with complex geometries and location-dependent droplet density and effective radius. The cloud geometry is specified by a number of elementary shapes (e.g. spheres and cylinders) that can be linearly deformed as well as combined by set operations such as unions, intersections and subtractions. The cloud composition can be specified by arbitrary functions. Designed to aid in the interpretation of satellite images, the code simulates spatially resolved observations from an arbitrary viewpoint. Some examples and applications of this tool will be discussed.
Machine Learning: potential for local and regional deep-seated landslide nowcasting
Authors: van Natijne Adriaan , Lindenbergh Roderik , Bogaard Thom
Published: March 2020

Where landslide hazard mitigation is impossible, Early Warning Systems are a valuable alternative to reduce landslide risk. To this extent nowcasting and Early Warning Systems for landslide hazard have been implemented mostly at local scale. Unfortunately, such systems are often difficult to implement at regional scale or in remote areas due to dependency on local sensors. However, in recent years various studies have demonstrated the effective application of Machine Learning for deformation forecasting of slow-moving, deep-seated landslides. Machine Learning, combined with satellite Remote Sensing products offers new opportunities for both local and regional monitoring of deep-seated landslides and associated processes.

Working from the key variables of the landslide process we selected the available satellite Remote Sensing products, the necessary assumptions for a satellite only application and evaluated the potential benefit of local information. In the absence of continuous, satellite deformation measurements, nowcasting of the system state will provide a short term deformation prediction. We demonstrate the opportunities of Machine Learning on multi-sensor monitored Austrian landslide and anticipate on the integration in an Early Warning System. Furthermore, we highlight the risks and opportunities arising from the limited physics constraints in Machine Learning.
Simplifying Instrument Pools: The Next Generation Family of Smart Instrumentation.
Authors: Mohr Sally , Balon Marie , Filippi Sofia , Watkiss Neil , Hill Phil
Published: March 2020

As the community further expands their scope of study, pushing into different sub-disciplines and evermore challenging environments, the need for dynamic and highly adaptable systems grows. One of the challenges for instrument pool managers is finding a system that can cater for a wide range of possible use scenarios.

This is where traditional broadband, force-feedback sensors meet their limitations: with constrained frequency responses and sensitivities, they tend to target very narrow applications offering limited flexibility. When managing a pool of instruments, this translates into increasing pressure to acquire multiple units within different instrument ranges to meet the requirements for each specific application. This in turn leads to complex pool maintenance and may require operators to use unfamiliar instruments if their first choice is being used owing to a reduced number of instruments for each application within the pool.

Güralp’s 35 years’ experience in working with major national instrument pools revealed the necessity to develop flexible, easy-to use systems that could fit a wider scope of applications. This has led to a new, highly versatile smart sensor that supports extensive user configuration and ultra-wide tilt ranges.

The new sensor has a configurable long period corner allowing for rapid deployment in a range of environments: the 1s mode ensures the sensor settles quickly for rapid response purposes, and the 120s mode is ideally suited for long period observation.

The group of products that use this technology deliver high sensor reliability, sophisticated tools for ease of instrument and data management as well as industry standard data formats. The sensors have been integrated into various instruments: the Certimus for surface and shallow burial, the Radian for deeper postholes and boreholes, and the Fortimus for strong-motion applications.  The same philosophy also brought about Aquarius, an Ocean Bottom Seismometer that utilises the same sensor technology for the benefit of OBS pools.

This family of just four instruments covers the vast majority of seismic monitoring requirements. They represent Güralp’s solution to make instrument pool management easier and more affordable.

 

 
Geophysical basin characterization using seismic noise H/V spectral ratio and gravity data (Vallès Basin NE-Spain).
Authors: Gabàs Anna , Macau Albert , Bellmunt Fabián , Benjumea Beatriz , Sedano Jose , Figueras Sara
Published: March 2020

Vallès Basin (NE-Spain) is a neogene basin with mainly granitic bedrock and delimited at NW by one normal fault (Vallès fault). This basin presents significant geothermal anomalies reflected with surficial hot thermal waters. Previous studies carried out in the 70s, to define its energy resource potential using one single geophysical technique, were not enough to clearly interpret the subsoil structure and many uncertainties remain still unsolved.

The aim of this work is to combine two different geophysical techniques for collaborative interpretation of the Vallès Basin structure in order to reduce the uncertainties: 2D gravity profiles and seismic noise H/V spectral ratio measurements distributed in the whole basin area. 2D gravity profiles provide subsurface structural information and basement depth from density models obtained after modelling and inversion processes; whereas the seismic noise H/V spectral ratio technique determines the soil fundamental frequency, which helps to locate the boundary between soft sediments and hard rock materials using empirical equations. Therefore, bedrock geometry and infill sediments structure can be estimated, which is crucial to understand ongoing processes related to the surface geothermal evidences.

The work methodology consists of combining both geophysical methods comparing the density models obtained from Bouguer anomaly in the 2D gravity profiles with the soft soil-hard rock contact surface obtained from the seismic noise H/V spectral measurement. The co-validation between them is carried out overlapping these two individual geophysical results and complementing models between them to obtain the best fit. Despite using different geophysical techniques to reduce ambiguities, a final discussion about lithology of sediments, geometry of basement and location of main faults is always needed. In this case, two equally probable models are proposed to interpret the Vallès Basin structure. One of them presents a shallow basin with granitic basement below. The other one presents a deeper basin, the granitic bedrock is located at 2000 m depth, with conglomerate deposits near the main fault. In both cases, the obtained models detect the Vallès fault as a sub-vertical fault which slightly diminishes its slope from 1200-1400 m in depth.

These new results in the Vallès Basin provide valuable information for geothermal purposes, but should be completed with more geophysical data to assure the geological model. As a future work, the gravity data will be extended at the whole basin in order to create a 3D geological model. To accomplish this objective, it will be fundamental to construct a very dense mesh of gravity points (good resolution) which affords a plausible hypothesis about the basin geological structure.
Spatial Patterns and Spatial Modeling of Primary Organic Aerosol Concentrations in Three North American Cities
Authors: Saha Provat , Robinson Ellis , Zhang Wenwen , Hankey Steven , Robinson Allen , Presto Albert
Published: March 2020

We measure highly spatially resolved primary organic aerosol (POA) concentrations in three North American cities (Oakland, Pittsburgh, and Baltimore) using an aerosol mass spectrometer deployed on a mobile laboratory. We conduct between 10 and 20 days of repeated mobile sampling in each city, covering a wide range of urban land use attributes. We derive two POA factors using positive matrix factorization of the measured organic mass spectra: cooking OA (COA) and traffic-related OA (hydrocarbon-like OA; HOA). Both the COA and HOA concentrations vary substantially within and between cities. The COA and HOA concentrations in Oakland are about a factor of 2-4 higher than Pittsburgh and Baltimore. Within a city, the concentrations vary by a factor of 2-5. The COA concentrations are higher than the HOA in each city, indicating that cooking is an important POA source in the US. In each city, the concentrations are higher in the downtown and near large sources, showing the linkage between land-use activities and POA concentrations. We develop land-use regression (LUR) models for COA and HOA using the measured concentrations and available land-use covariates. We find that a similar set of land-use covariates explain the variability of measured POA in each city. The LUR models are moderately transferable between sampling cities. An external validation effort using literature data shows that our models predict the previous point measurements in six North American cities reasonably well. We are applying our LUR models for a national prediction of the concentration surfaces of COA and HOA. We plan to apply the national estimates for the epidemiologic and environmental justice analysis of POA in the United States.
Molecular characterization and volatility of organonitrates: Latest observations from field and laboratory
Authors: Mohr Claudia , Wu Cheng , Huang Wei , Graham Emelie , Bianchi Federico , Andrade Marcos , Bell David
Published: March 2020

Here we show recent results from different field and laboratory campaigns focusing on organonitrate (ON) formation, mass concentration, and physicochemical properties such as volatility. ONs are formed via volatile organic compounds (VOC) and NOx. They are therefore key species for our understanding of the interaction between the biosphere and anthropogenic activities, and the effects of altering both VOC and NOx emissions due to climate change and/or air quality mitigation measures. Recently, we were able to show that ONs from different precursor VOC can also contribute significantly to the growth of newly formed particles in the atmosphere to sizes where they can become active and cloud condensation nuclei (Huang et al., 2019).

We present direct, real-time observations of ONs in the gas and particle phase at the highest atmospheric research station in the world, Chacaltaya (5240 m a. s. l) in Bolivia. This southern hemisphere station is often located in the free troposphere during night time, and influenced by the emissions from the nearby El Alto-La Paz metropolitan area, and biogenic emissions from surrounding forests as well as from the Amazon through long-range transport. ONs were measured using a Chemical Ionization Mass Spectrometer with a Filter Inlet for Gases and Aerosols. We observed hundreds of highly functionalized ONs with different molecular composition during day- and nighttime, indicating different sources and formation processes. A large contribution of the highly functionalized ONs was found especially during new particle formation events regularly observed at this location (Rose et al., 2015). Observations from the field will be compared to results from the Nitrate Aerosol and Volatility Experiment (NArVE) at the EUROCHAMP 2020 PACS-C3 smog chamber (PSI, Switzerland), where we investigated the ON fraction, chemical composition, and volatility of secondary organic aerosol (SOA) formed via nitrate radical initiated oxidation reactions of biogenic and anthropogenic VOC.
New insight on the sedimentary record related to the late-Quaternary tectonics of the western segment of the “Livorno-Sillaro” (Northern Tuscany, Italy).
Authors: Sarti Giovanni , Giannico Vito Gerardo , Pittaro Daniele , Porta Lorenzo
Published: March 2020

The “Livorno-Sillaro” line represents one of the most important transversal structure of the inner Northern Apennines.  It has been described in the literature as a major strike-slip fault (e.g., Bortolotti, 1966; Carmignani et al., 1994; Pascucci, 2005; Pascucci et al., 2007), and it is divided into two segments, eastern and western. 

A stratigraphic-sequence frame for the late-Quaternary deposits has been developed by using the different facies associations defined through a large subsurface database analysis. Moreover, a correlation has been done between subsoil deposits and the outcropping sediments on the hilly areas (Livorno, Pisa and Cerbaie hills) surrounding the Arno valley.

Additionally, a morphotectonic analysis of the hydrographic networks and relief distribution has been done the Lidar data (DTM), supplied by the Tuscany Region, at the 2 m and 10 m of resolution. Specifically, the river system is particularly sensitive to deformation processes. The fluvial streams are in fact characterized by low geomorphological inertia and, therefore, by response times of a few hundred thousand years to the tectonic processes in progress.

As a result of the integrated multidisciplinary analysis, it was possible to highlight a tectonic activity in the middle Pleistocene -Holocene interval of the western portion of the "Livorno-Sillaro" lineament neglected in the geological literature until now.

References

Bortolotti V. (1966) – La tettonica trasversale dell’Appennino – La linea Livorno-Sillaro. Bollettino della Società Geologica Italiana, Vol.85, pp. 529-540, 3 ff., 1 tav.

Carmignani L., Decandia F.A., Fantozzi P.L., Lazzarotto A., Liotta D. & Meccheri M. (1994) – Tertiary extensional tectonics in Tuscany (Northern Apennines, Italy). Tectonophysics. Vol. 238, pp. 295-315.

Pascucci V. (2005) – Neogene evolution of the Viareggio Basin, Northern Tuscany (Italy). GeoActa. Vol. 4, pp. 123-128.

Pascucci V., Martini I.P., Sagri M. & Sandrelli F. (2007) – Effects of transverse structural lineaments on the Neogene-Quaternary basins of Tuscany (inner Northern Apennines, Italy). Sedimentary Processes, Environments, and Basins: A Tribute to Peter Friend.

 
A new space-borne perspective of crop productivity variations over the US Corn Belt
Authors: Somkuti Peter , Boesch Hartmut , Parker Robert , Webb Alex , Feng Liang , Palmer Paul , Quaife Tristan
Published: March 2020

We analyse inter-annual variations of SIF over the US Corn Belt using a seven-year time series (2010–2016) retrieved from measurements of short-wave IR radiation collected by the Japanese Greenhouse gases Observing SATellite (GOSAT). Using survey data and annual reports from the US Department of Agriculture (USDA) National Agricultural Statistics Service (NASS), we relate anomalies in the GOSAT SIF time series to meteorological and climatic events that affected planting or growing seasons. The events described in the USDA annual reports are confirmed using remote sensing-based data such as land surface temperature, precipitation, water storage anomalies and soil moisture. These datasets were carefully collocated with the GOSAT footprints on a sub-pixel basis to remove any effect that could occur due to different sampling. We find that cumulative SIF, integrated from April to June, tracks the planting progress established in the first half of the planting season (Pearson correlation r > 0.89). Similarly, we show that crop yields for corn (maize) and soybeans are equally well correlated to the integrated SIF from July to October (r > 0.86). Our results for SIF are consistent with reflectance-based vegetation indices, that have a longer established history of crop monitoring. Despite GOSAT’s sparse sampling, we were able to show the potential for using satellite-based SIF to study agriculturally-managed vegetation.

[1] Somkuti et al., "A new space-borne perspective of crop productivity variations over the US Corn Belt." Agricultural and Forest Meteorology 281 (2020): 107826.

 
The relationship between the bulk density, the apparent porosity and ultrasonic pulse velocity of highly porous limestone, examples from Hungary
Authors: Papay Zita , Rozgonyi-Boissinot Nikoletta , Török Ákos
Published: March 2020

Different stone qualities in masonry walls cause considerable problems on masonry walls during restoration works. The properties of limestone show significant variations due to differences in sedimentary structures which are might not be visible at the scale of laboratory test specimens. Even at one quarry level, there could be major differences in properties due to the cross-bedding or tilted rock beds. Physical parameters of 3 typical types of porous limestone (fine-, medium-, coarse-grained) were studied under laboratory conditions in order to assess an explanation for variations in weathering forms on masonries of historical buildings. Laboratory experiments were performed to determine the bulk density, water absorption, apparent porosity, ultrasonic pulse velocity under dry and water-saturated conditions. Aim of this research is to find correlations between physical parameters of limestones and show considerable diversity in properties. Our results indicate that there is a relationship between dry and water-saturated bulk density vs. ultrasonic pulse velocity and dry and water-saturated bulk density vs. apparent porosity, respectively. It is well known that microstructure influences the damage mechanism of stones. Our research demonstrates that variations exist in the stone fabric even at quarry level, based on the samples of Sóskút quarry. The different limestone lithologies were used side by side in historical buildings; therefore our results help experts during restoration works in decay mapping of monuments.
Impact of improved Ocean initial condition in Climate Forecast System (CFSv2) Hindcast run
Authors: Pokhrel Samir , Rahaman Hasibur , Chaudhari Hemantkumar , Saha Subodh Kumar , Hazra Anupam
Published: March 2020

IITM provides seasonal monsoon rainfall forecast using modified CGCM CFSv2. The present operational CFSv2 initilized with the INCOIS-GODAS ocean analysis based on MOM4p0d and 3DVar assimilation schemes. Recently new Ocean analysis GODAS-Mom4p1 using Moduler Ocean Model (MOM) upgraded physical model MOM4p1 is generated. This analysis has shown improvement in terms of subsurface temperature, salinity , current as well as sea surface temperature (SST), sea surface salinity (SSS) and surface currents over the Indian Ocean domain with respect to present operational INCOIS-GODAS analysis (Rahaman et al. 2017;Rahman et al. 2019). This newly generated ocean analysis is used to initialize NCEP Climate Forecast System (CFSv2) for the retrospective run from 2011 to 2018. The simulated coupled run has shown improvement in both oceanic as well atmospheric parameters. The more realistic nature of coupled simulations across the atmosphere and ocean may be promising to get better forecast skill.
The effects of trees on outdoor thermal comfort in cities
Authors: Cravero Julien , Versini Pierre-Antoine , Feraille Adélaïde , Caron Jean-François , Tchiguirinskaia Ioulia
Published: March 2020

Nature-based solutions appear to be an interesting option for enhancing the thermal comfort of the urban population during summer, while providing multiple services (e.g. biodiversity enhancement, the reduction in buildings energy consumption, stormwater management, acoustic insulation or air purification). However, the effects of green infrastructures on thermal comfort are not properly characterized, which prevents urban planning policies to be consistent.

The impacts of a single idealized tree on its microclimate are studied. The sensible heat flux emitted by the soil to the air is computed by solving the heat equation in a semi-infinite domain with a Robin boundary condition representing the energy balance of the soil. The sensible heat flux emitted by the vegetation is computed in two ways: with Newton’s law and with an energy-balance approach. This model is applicated to a tree-shaped structure supporting climbing plants and compared with the experimental data collected. The prototype has been built to assess the cooling performance of this type of vegetation, and particularly the part played by soil shading, evapotranspiration (i.e. the latent heat flux emitted to the air by the plants and the soil) and absorbed solar radiation. These results may permit to estimate the contribution of vegetation for mitigating urban heat island effects on a larger scale.
Linking thermal UAS-based imagery and Cosmic-Ray Neutron Sensing data
Authors: Döpper Veronika , Gränzig Tobias , Förster Michael , Kleinschmit Birgit
Published: March 2020

Soil moisture content (SMC) is of fundamental importance to many hydrological, biological, biochemical and atmospheric processes. Common soil moisture measurements range from local point measurements to global remote sensing-based SMC datasets. Nevertheless, they always compromise between temporal and spatial resolution. Thus, it is still challenging to quantify spatially and temporally distributed SMC at a regional scale which is extremely relevant for hydrological modeling or agricultural management. The innovative technology Cosmic-Ray Neutron Sensing (CRNS) shows significant potential to fill this gap by quantifying the present hydrogen pools within footprints larger than 0.1 ha.

Owing to the difference in scale between the ground resolution of satellites used to retrieve soil moisture and the common point scale of ground-based soil moisture instruments, the large footprint of the CRNS poses a high potential for the validation of SMC remote sensing products. When linking the CRNS measurements with remote sensing data, the vertical and horizontal characteristics of its footprint need to be considered.

To examine the influence of the CRNS footprint characteristics on the linkage of CRNS and remote sensing data, we couple CRNS measurements with high-resolution UAS-based thermal imagery acquired at two sites in Bavaria and Brandenburg (Germany) using a radiometrically calibrated FLIR Tau 2 336 (FLIR Systems, Inc., Wilsonville, OR, USA) with a focal length of 9 mm. Within this context, we evaluate the added value of applying a horizontal weighting function to the spatially distributed thermal data in comparison to an unweighted mean when statistically representing the corrected neutron counting rates.

The project is part of the DFG-funded research group Cosmic Sense, which aims to provide interdisciplinary new representative insights into hydrological changes at the land surface.
Modernizing Canadian Geodetic Survey’s precise GNSS orbit and clock system
Authors: Goudarzi Mohammad Ali
Published: March 2020

In order to enable our new PPP processing engine and online service to work in full multi-GNSS mode, and provide high quality precise GNSS orbit and clock (POD) products to IGS and international geodetic community, Canadian Geodetic Survey (known as EMR) has started to modernize his POD system. The new system is based on GipsyX and in-house software development and will replace our current POD system in near future. When become operational, the new POD system will produce multi-GNSS precise orbit and clock corrections with ambiguity resolution along with wide-lane and phase biases using zero-differenced, dual-frequency, ionosphere-free phase and code observations in RINEX 2 and 3 formats estimated in combined solution. The new system also benefits from advanced features such as removing observations affected by ionospheric scintillation and ground stations affected by earthquake as well as real-time monitoring of estimated position time-series of ground stations, among others.
Evaluating the potential of Sentinel-1 images for the estimation of soil moisture on an alluvial Fan
Authors: Singh Abhilash , Gaurav Kumar , Kumar Shashi
Published: March 2020

We evaluate the potential of Sentinel-1A & 1B satellite images to estimate the volumetric soil moisture content over an alluvial fan of the Kosi River in the North Bihar, India. Over this region, only dual polarised images (VH and VV) are available. However, the existing backscattering models (i.e., Dubois, Oh and IEM models) uses quad polarised (VV, VH, HH and HV) images for the estimation of soil permittivity and surface roughness over the bareland. To overcome the constraint of dual polarised data, we eliminated one of the unknown (i.e. surface roughness) by developing a regression model between the in-situ measured surface roughness and the ratio of backscatter values (VH/VV) in dB.  In a field campaign in the Kosi Fan from December 10-21, 2019, we have measured surface roughness, soil temperature, soil pH and soil moisture at 78 different location using the pin-meter, soil survey instrument (soil temperature and pH), and Time Domain Reflectometer (TDR) respectively. The average surface roughness and soil moisture varies between (0.61 - 5.45) cm and (0.12-0.53) m3/m3 respectively in the study area.

Further, using the surface roughness we modify the Dubois, Oh and IEM models. This reduces the number of unknowns in the models from two to one; the soil permittivity. We compute the soil permittivity from the inversion of the existing backscattering models. Finally, we use the permittivity values in the Top’s model to estimate the volumetric soil moisture in the study area. Our initial results exhibit a good correlation (R2 = 0.85) to the in-situ measured soil moisture.
Down-scaling MODIS operational vegetation products with machine learning and fused gap-free high resolution reflectance data in Google Earth Engine
Authors: Moreno Martínez Álvaro , Izquierdo Verdiguier Emma , Camps Valls Gustau , Maneta Marco , Muñoz Marí Jordi , Robinson Nathaniel , Adsuara José E. , Campos Taberner Manuel , García Haro Francisco J. , Pérez Suay Adrián , Running Steven W.
Published: March 2020

Among Essential Climate Variables (ECVs) for global climate observation, the Leaf Area Index (LAI) and the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) are the most widely used to study land vegetated surfaces. The NASA’s Moderate  Resolution Imaging Spectro-radiometer (MODIS) is a key instrument aboard the Terra and Aqua platforms and allows to estimate both biophysical variables at coarse resolution (500 m) and global scales. The MODIS operational algorithm to retrieve LAI and FAPAR (MOD15/MYD15/MCD15) uses a physically-based radiative transfer model (RTM) to compute their estimates with corrected surface spectral information content. This algorithm has been heavily validated and compared with field measurements and other sensors but, so far, no equivalent products at high spatial resolution and continental or global scales are routinely produced. 

Here, we introduce and validate a methodology to create a set of high spatial resolution LAI/FAPAR products by learning the MODIS RTM using advanced machine learning approaches and gap filled Landsat surface reflectances. The latter are smoothed and gap-filled by the HIghly Scalable Temporal Adaptive Reflectance Fusion Model (HISTARFM). HISTARTFM has a great potential to improve the original Landsat reflectances by reducing their noise and recovering missing data due to cloud contamination. In addition, HISTARFM runs very fast in cloud computing platforms such as Google Earth Engine (GEE) and provides uncertainty estimates which can be propagated through the models. These estimates allow to compute numerical uncertainties beyond the typical and qualitative control information layers provided in operational products such as the MODIS LAI/FAPAR. The introduced high spatial resolution biophysical products here could be of interest to the users to achieve the needed levels of spatial detail to adequately monitor croplands and heterogeneously vegetated landscapes.

 
The effects of fluvial and basal sediment properties on the morphodynamics of deltas undergoing sediment supply reduction
Authors: Johnson Joshua , Parsons Daniel , Hackney Christopher , Edmonds Douglas , Best James
Published: March 2020

Deltas are home to hundreds of millions of people worldwide and form a key part of many coastal environments. Due to their low elevation, many deltas are threatened by sea level rise as well as direct human influences on flow and subsidence. Added to this, the volume of sediment exported by rivers to the coast has been reduced by around 1.4 billion tons per year, starving deltas of the building material needed to construct and maintain their valuable subaerial land in the face of these challenges. The calibre and cohesivity of sediment have both been shown to be important factors in determining the erosion, deposition and stability regimes within a delta system. However, it has not yet been shown how the qualities of river and substrate sediment affect how resilient deltas are to sediment reduction.

This study uses numerical modelling to investigate how the cohesivity of incoming river sediment and the erosion resistance of the delta’s substrate affect how deltas respond to a reduction in supplied sediment. Delft3D was used to create a series of stable deltas with varying fluvial and basal sediments, that where then exposed to sediment reduction. The loss of land area, change in channel geometry and other metrics where extracted from model output using Matlab to assess the effects of this sediment reduction, and how these effects varies between deltas.
Learning ordinary differential equations from remote sensing data
Authors: Adsuara Jose E. , Pérez-Suay Adrián , Moreno-Martínez Alvaro , Mateo-Sanchis Anna , Piles Maria , Kraemer Guido , Reichstein Markus , Mahecha Miguel D. , Camps-Valls Gustau
Published: March 2020

Modeling and understanding the Earth system is of paramount relevance. Modeling the complex interactions among variables in both space and time is a constant and challenging endevour. When a clear mechanistic model of variable interaction and evolution is not available or uncertain, learning from data can be an alternative. 

Currently, Earth observation (EO) remote sensing data provides almost continuous space and time sampling of the Earth system which has been used to monitor our planet with advanced, semiautomatic algorithms able to classify and detect changes, and to retrieve relevant biogeophysical parameters of interest. Despite great advances in classification and regression, learning from data seems an ilusive problem in machine learning for the Earth sciences. The hardest part turns out to be the extraction of their relevant information and figuring out reliable models for summarizing, modeling, and understanding variables and parameters of interest.

 

We introduce the use of machine learning techniques to bring systems of ordinary differential equations (ODEs) to light purely from data. Learning ODEs from stochastic variables is a challenging problem, and hence studied scarcely in the literature. Sparse regression algorithms allow us to explore the space of solutions of ODEs from data. Owing to the Occam's razor, and exploiting extra physics-aware regularization, the presented method identifies the most expressive and simplest ODEs explaining the data. From the learned ODE, one not only learns the underlying dynamical equation governing the system, but standard analysis allows us to also infer collapse, turning points, and stability regions of the system. We illustrate the methodology using some particular remote sensing datasets quantifying biosphere and vegetation status. These analytical equations come to be self-explanatory models which may provide insight into these particular Earth Subsystems.
Setup and first testing of Laser Ablation - ICP-MS measurements for high resolution chemical ice core analyses at University of Cambridge
Authors: Hoffmann Helene , Wolff Eric , Day Jason , Grieman Mackenzie , Humby Jack , Gibson Sally
Published: March 2020

The ice in the deepest and therefore oldest parts of polar ice cores is highly compressed and therefore annual layers, although potentially preserved, can be thinned to a millimeter level or even below. However, for many palaeoclimate studies these are the most interesting sections. Within the WACSWAIN project we aim to investigate the basal part of an ice core recently drilled to bedrock at the Skytrain ice rise in West Antarctica to obtain unique information on the state of the Filchner-Ronne ice shelf during the last interglacial. To achieve this we have set up a system to perform high resolution laser-ablation ICP-MS measurements using a cryocell stage on selected segments of the deepest parts of the ice cores.

Here we present first results of system performance including assessment of measurement sensitivity and precision with respect to analyses of the most relevant components, namely sodium, calcium and aluminium. We also report on the development and the performance of a matrix matched calibration method using flash-freezed water samples of known composition to convert relative signal intensities into concentrations. This especially focuses on homogeneity and reproducibility of the in-house produced standard. Finally, the results of laser ablation ICP-MS results are compared to parallel low resolution data from continuous flow analysis of the Skytrain core to evaluate the capabilities of the method in terms of improving depth resolution.
Adsorption of Dimethylmercury onto Natural Particles
Authors: Jonsson Sofi , West Johannes , Nguyen Van Liem
Published: March 2020

Dimethylmercury (DMeHg), a highly toxic form of mercury (Hg), appears as a dissolved gas in marine waters as well as some terrestrial environments. Although DMeHg does not reach concentrations in natural environments that are of direct concern for human and wildlife health, it has been suggested that DMeHg could play a role in controlling the amount of monomethylmercury (MMeHg) available. As MMeHg bioaccumulates in aquatic food webs to concentrations of concern, it links the occurrence of DMeHg in marine systems with the negative consequences of Hg pollution for human and wildlife health. Our understanding of the biogeochemical cycle of DMeHg is however scant. The potential for adsorption of DMeHg onto natural particles has so far not been addressed. This, despite the fact that adsorption is recognised to be an important process controlling the distribution of other chemical forms of Hg in the environment, including ionic forms of inorganic divalent Hg and monomethylmercury as well as gaseous elemental Hg.  

Here, we will present the data from the first adsorption experiments with dimethylmercury using model compounds (including FeS-minerals) as well as natural sediments and soils. For FeS(s), DMeHg readily adsorbed onto the mineral surface reaching equilibrium within 1-2 h. Observed partitioning between the solid and aqueous phase for FeS were also close to observed partitioning of e.g. MMeHg. Preliminary data also suggests DMeHg to readily adsorb onto natural particles, including sediments and soils.