bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting microbial redox dynamics and nutrient cycling in the subsurface considering spatio-temporal heterogeneities
Authors: Khurana Swamini , Heße Falk , Thullner Martin
Published: March 2020

Biogeochemical cycles are extensively studied as they control the flow of matter (carbon and nitrogen, specifically) up to the global scale, further impacting ecosystem functions and services. To be able to predict carbon and nitrogen budgets, it is necessary to study carbon and nitrogen cycles in all compartments of the biosphere, from forests to water, to soil and deep subsurface. Since the soil and deeper subsurface compartments store a high share of the global carbon and nitrogen budget, it is necessary to study the carbon and nitrogen cycles in the subsurface at a higher resolution. Given the spatial heterogeneity and temporal dynamics exhibited by the subsurface, coupled with lack of observational opportunities, the prediction of these cycles in the subsurface is a challenge. For this purpose, this study aims to resolve microbial mediated carbon and nitrogen dynamics in the subsurface with respect to spatial and temporal heterogeneity using a numerical modeling approach. The model considers the response of microbial growth and activity to varying environmental conditions such as access to nutrients and energy sources.

The obtained results show a linear relationship between the relative impact on carbon and nitrogen removal and relative difference in breakthrough times between homogeneous scenarios and the spatially heterogeneous scenarios. In contrast, the temporal dynamics of changing flow rates induces minimal aggregated impact on the carbon and nitrogen cycles in the subsurface. This implies that short term temporal dynamics do little to influence the long-term nutrient cycles, given the same average water flux through the entire simulation period. The findings of this study can assist in identification of drivers of microbial dynamics and nutrient cycling in the Critical Zone. This, in turn, can assist towards the regional scale modeling of biogeochemical cycles resulting from microbial dynamics.
High-resolution sea surface salinity and temperature in coastal areas from Sentinel-2 and Copernicus Marine in situ data
Authors: Medina-Lopez Encarni
Published: March 2020

The aim of this work is to obtain high-resolution values of sea surface salinity (SSS) and temperature (SST) in the global ocean by using raw satellite data (i.e., without any band data pre-processing or atmospheric correction). Sentinel-2 Level 1-C Top of Atmosphere (TOA) reflectance data is used to obtain accurate SSS and SST information. A deep neural network is built to link the band information with in situ data from different buoys, vessels, drifters, and other platforms around the world. The neural network used in this paper includes shortcuts, providing an improved performance compared with the equivalent feed-forward architecture. The in situ information used as input for the network has been obtained from the Copernicus Marine In situ Service. Sentinel-2 platform-centred band data has been processed using Google Earth Engine in areas of 100 m x 100 m. Accurate salinity values are estimated for the first time independently of temperature. Salinity results rely only on direct satellite observations, although it presented a clear dependency on temperature ranges. Results show the neural network has good interpolation and extrapolation capabilities. Test results present correlation coefficients of 82% and 84% for salinity and temperature, respectively. The most common error for both SST and SSS is 0.4 C and 0.4 PSU. The sensitivity analysis shows that outliers are present in areas where the number of observations is very low. The network is finally applied over a complete Sentinel-2 tile, presenting sensible patterns for river-sea interaction, as well as seasonal variations. The methodology presented here is relevant for detailed coastal and oceanographic applications, reducing the time for data pre-processing, and it is applicable to a wide range of satellites, as the information is directly obtained from TOA data.
Extended Range Arctic Sea Ice Forecast with Convolutional Long-Short Term Memory Networks
Authors: Liu Yang , Bogaardt Laurens , Attema Jisk , Hazeleger Wilco
Published: March 2020

Operational Arctic sea ice forecasts are of crucial importance to commercial and scientific activities in the Arctic region. Currently, numerical climate models, including General Circulation Models (GCMs) and regional climate models, are widely used to generate the Arctic sea ice predictions at weather time-scales. However, these numerical climate models require near real-time input of weather conditions to assure the quality of the predictions and these are hard to obtain and the simulations are computationally expensive. In this study, we propose a deep learning approach to forecasts of sea ice in the Barents sea at weather time scales. To work with such spatial-temporal sequence problems, Convolutional Long Short Term Memory Networks (ConvLSTM) are useful.  ConvLSTM are LSTM (Long-Short Term Memory) networks with convolutional cells embedded in the LSTM cells. This approach is unsupervised learning and it can make use of enormous amounts of historical records of weather and climate. With input fields from atmospheric (ERA-Interim) and oceanic (ORAS4) reanalysis data sets, we demonstrate that the ConvLSTM is able to learn the variability of the Arctic sea ice within historical records and effectively predict regional sea ice concentration patterns at weekly to monthly time scales. Based on the known sources of predictability, sensitivity tests with different climate fields were also performed. The influences of different predictors on the quality of predictions are evaluated. This method outperforms predictions with climatology and persistence and is promising to act as a fast and cost-efficient operational sea ice forecast system in the future.
Characterizing glacial processes applying classical beamforming and machine learning
Authors: Umlauft Josefine , Roux Philippe , Gimbert Florent , Lecointre Albanne , Rouet-LeDuc Bertrand , Trugman Daniel Taylor , Johnson Paul Allan
Published: March 2020

The cryosphere is a highly active and dynamic environment that rapidly responds to changing climatic conditions. processes behind are poorly understood they remain challenging to observe. Glacial dynamics are strongly intermittent in time and heterogeneous in space. Thus, monitoring with high spatio-temporal resolution is essential. In course of the RESOLVE project, continuous seismic observations were obtained using a dense seismic network (100 nodes, Ø 700 m) installed on the Argentière Glacier (French Alpes) during May in 2018. This unique data set offers the chance to study targeted processes and dynamics within the cryosphere on a local scale in detail.

We classical beamforming within the of the array (matched field processing) and unsupervised machine learning techniques to identify, cluster and locate seismic sources in 5D (x, y, z, velocity, time). Sources located with high resolution and accuracy related to processes and activity within the ice body, e.g. the geometry and dynamics of crevasses or the interaction at the glacier/bedrock interface, depending on the meteorological conditions such as daily temperature fluctuations or snow fall. Our preliminary results indicate strong potential in poorly resolved sources, which can be observed with statistical consistency reveal new insights into structural features/ physical properties of the glacier (e.g. analysis of scatterers).
Closing the global and regional sea level budgets by combining multi-mission altimetry and GRACE(-FO) data
Authors: Uebbing Bernd , Lück Christina , Rietbroek Roelof , Vielberg Kristin , Kusche Jürgen
Published: March 2020

Understanding present day sea level changes and their drivers requires the separation of the total sea level change into individual mass and steric related contributions. Total sea level rise has been observed continuously since 1993 providing a more than 25 year long time series of global and regional sea level variations. However, direct monitoring of ocean mass change has only been done since the start of the Gravity Recovery And Climate Experiment (GRACE) mission in 2002. It ended in 2017 and was succeeded by the follow-on mission (GRACE-FO) in 2018 leaving a gap of about 1 year. In the same time period of GRACE, since the early 2000s, a global array of freely drifting Argo floats samples temperature and salinity profiles of up to 2000m depth which can be converted to steric sea level change.

By combining altimetry, GRACE(-FO) and Argo data sets it is possible to derive global and regional sea level budgets. The conventional approach is to analyze at least two of the data sets and derive the residual, or compare with the third one. A more recent approach is the global joint inversion method (Rietbroek et al., 2016) which fits forward-modeled spatial fingerprints to a combination of GRACE gravity data and Jason-1/-2 satellite altimetry data. This enables us, additionally, to separate altimetric sea level change into mass contributions from terrestrial hydrology, the melting of land glaciers and the ice-sheets in Greenland and Antarctica as well as contributions from steric sea level changes due to variations in ocean temperature and salinity. It also allows to include a data weighting scheme in the analysis.

Here, we present global and regional sea level budget results from an updated inversion based on multi-mission altimetry (Jason-1/-2/-3, Envisat, Cryosat-2, Sentinel-3, …) providing better spatial coverage as well as new RL06 GRACE and GRACE-FO data which enables us to extend the time series of individual components of the sea level budget beyond the GRACE era from 2002-04 till 2019-06. The presented sea level budget is closed on global scale with a residual (unexplained) contribution of about 0.1 mm/yr, globally, originating in eddy-active regions. We provide consistent validation of our results against conventionally analyzed altimetry and GRACE data sets where we find agreement on global scales to be better than 0.1 mm/yr but a larger disagreement at regional scales as well as the implications of our results for deriving ocean heat content. We will also provide first results for filling the gap in the sea level budget estimates due to the gap between the GRACE and GRACE-FO missions by additionally incorporating time-variable gravity information from the Swarm mission as well as from Satellite Laser Ranging (SLR) to 5 satellites (Lageos-1/-2, Stella, Starlette, Ajisai).
Wind characteristics in 2019 on the Polish Baltic coast
Authors: Starosta Katarzyna , Wyszogrodzki Andrzej
Published: March 2020

 

 

Wind characteristics in 2019 on the Polish Baltic coast.

 

Katarzyna Starosta, Andrzej Wyszogrodzki

katarzyna.starosta@imgw.pl, andrzej.wyszogrodzki@imgw.pl

          Wind is one of the main complex elements that affects the climate and weather of our planet. The topic of our presentation is to show  characteristics of the wind for the  Polish coastal areas. In our presentation we show distribution  of wind speed and wind direction based on the COSMO (Consortium for Small-scale Modelling) model forecasts  at a mesh resolution of 2.8 km and their verification with 24 hour measurements for a five synoptic stations: Swinoujscie, Kolobrzeg, Ustka, Leba and Hel. The Polish Institute of Meteorology and Water Management – National Research Institute (IMWM-NRI) runs an operational model COSMO   using two nested domains at horizontal resolutions of 7 km and 2.8 km. The model produces 36 hour and 78 hour forecasts four times per day for 2.8 km and 7 km domain resolutions respectively. However, only the 00 UTC forecasts are  utilized in this study. We show wind analyzes at synoptic stations for different time scales (hours, days, months). We also analyze situations of extreme winds, such as for example passage of hurricane Alfrida in January 2019 on the Polish coast. The results show  characteristic distribution of wind speed and direction at the interface between sea and land . The wind is both destructive and conducive to human action. It causes local flooding, damage in ports, knocks down trees but also provides clean energy for wind farms or serves tourism activities as yachting or surfing.Poland plans recently to build an offshore wind farm in the Baltic Sea. Increasingly accurate wind forecasts are then one of the necessary elements for assessing the local climatology at the wind farm site and to further provide warnings and  decisive support to its operation. 

 

 

Presentation preference: POSTER

EGU/2020/session 35921

 

Institute of Meteorology and Water Management – National Research Institute

Podleśna 61

01-633 Warsaw

Poland
The history of Holocene atmospheric iodine over the North Atlantic
Authors: Cuevas Carlos Alberto , Corella Juan Pablo , Maffezzoli Niccolo , Vallelonga Paul , Spolaor Andrea , Cozzi Giulio , Müller Juliane , Vinther Bo , Barbante Carlo , Kjaer Helle Astrid , Edwards Ross , Saiz-Lopez Alfonso
Published: March 2020
Reach scale analysis of riparian vegetation interactions with fluvial morphology using UAV based laser scanning and multispectral imaging
Authors: Tomsett Chris , Leylan Julian
Published: March 2020

River corridors are greatly influenced by vegetation, whether it be through direct interactions with flow, influencing the stability of banks, or contributing to floodplain roughness. With vegetation present across many of the world’s river corridors in one form or another, it is a vital component of the active river corridor that receives relatively less attention than the flow and morphological components. This is partly because the routine monitoring of the very complex and temporally dynamic structure of vegetation is challenging.  Terrestrial Laser Scanning (TLS) and Airborne Laser Scanning (ALS) have been used to monitor fluvial vegetation across scales. However, whilst UAVs and Structure from Motion (SfM) techniques have recently bridged the gap between fine scale local surveys and coarse larger surveys for fluvial morphology, they are not well suited to characterising complex vegetation.

A UAV based laser scanning and imagery system has been developed which enables the collection of high resolution (> 300 points m2) point cloud data (first and last return) to analyse vegetation structure alongside simultaneous multispectral imagery data, including the red edge band. Such data can be collected on scales from metres to kilometres depending on the needs of the user, and is capable of picking out vegetation structure using metrics such as stand height, vertical distribution, canopy health, plant density etc. Moreover, the collection of this data through time will allow the evaluation of how these factors change across seasons, subsequently filling a void in data collection between spatially limited TLS and temporally limited ALS. Here we show some examples of how the data can be used to establish interactions between vegetation, flow and fluvial morphology from a series of flights over a 1 km reach of the River Teme, UK. These examples highlight how the data enables us to begin to establish a more detailed conceptual understanding of temporally evolving fluvial-vegetation interactions along river corridors.
Implementation of the wave boundary layer model in the OpenIFS model
Authors: Makrygianni Nefeli , Bidlot Jean R. , Bray Michaela , Pan Shunqi
Published: March 2020

For more than 30 years, many studies have been carried out to improve the understanding of the air-sea interaction and its impact on the predictions of atmospheric and the oceanic processes. It is well understood that the accuracy in predictions of the wind-driven waves is highly dependent on the source input and dissipation terms. The Wave Boundary Layer (WBL) approach for the estimation of surface stress has previously been used to improve the wind and wave simulations under extreme conditions. However, until recently the WBL was only used to determine the roughness length (z0) and drag coefficient (Cd), but not to alter the wind input source function in wave models. In this study, the wave boundary layer model (WBLM) was implemented in the OpenIFS coupled model as source functions as suggested by Du et al. (2017, 2019). The new wind input and dissipation terms are then tested using numerical model simulations, with a particular focus on the contribution of the high frequency tail in the source input function.  The comparison of the results of this study with published results hints at better performance of the model on the estimation of the roughness length and drag coefficient. This should improve predictions of the significant wave height and wind speeds, especially under extreme conditions.

Corresponding Author: Nefeli Makrygianni (makrygiannin@cardiff.ac.uk)
Tectonic controlled sedimentary features at the NE marigin of the Sorgenfrei-Tornquist Zone (STZ), southern Sweden
Authors: Pan Yaocen , Seidel Elisabeth , Hübscher Christian , Juhlin Christopher , Sopher Daniel
Published: March 2020

The Hanö Bay basin was formed during Late Cretaceous transgression as a sedimentary trough on the NE margin of the Sorgenfrei-Tornquist Zone (STZ), a narrow NW-SE striking intraplate inversion zone within the Fennoscandian Border Zone. Sedimentation within the basin was primarily controlled by inversion tectonics, resulting in a coarse-grained syn-inversion clastic wedge forming adjacent to the basin-bounding fault in the Santonian-Maastrichtian. Previous studies have highlighted the deposition of contourite sediments associated with topographic relief of the chalk sea created by such local inversion-induced uplift. Imaged upper Cretaceous clinforms in the marginal trough show a NE-ward progadational character, that is, away from the uplifted and eroded inversion zone. These extend along the inversion axis all the way to NE of the Mid-Polish trough.

To gain detailed stratigraphic constraints and to better understand the interaction of these syn-sedimentary features that developed during inversion tectonics, we use a combination of high-resolution multichannel seismic data (MCS) from the 2019 AL526 cruise and a number of key profiles from reprocessed 70-80’s legacy industry MCS. Preliminary results suggest a drift-moat system developed during a stepwise uplift of the SW shoulder of the STZ, with the uplift driven by transpressional reactivation of basement faults. The resultant aggradational wedge formed a shelf-margin extending fairly far into the basin. The overlying clinoform depositional successions clearly demonstrate several depositional stages; including highstand-progradation, highstand-aggradation and distinct transgression-retrogradation, during which an overall landward migration of the paleo-shoreline position is revealed. The results constrain relative sea-level changes in this area that were primarily related to tectonic events during the Santonian-Campanian.
Quantification of Nitrogen Dioxide and Sulfur Dioxide emissions from Bucharest using a mobile-DOAS setup
Authors: Iancu Sebastian
Published: March 2020

Atmospheric pollution has a well-known impact on the human life, thus observing the emissions of trace gases is an important part of monitoring the atmospheric composition. This paper aims to determine the vertical column densities (VCDs) of Nitrogen Dioxide (NO2) and Sulfur Dioxide (SO2). These quantities will be used to calculate emissions of these pollutants quantified using a ground based mobile remote sensing technique that relies on scattered light DOAS (Differential Optical Absorption Spectroscopy) measurements. This method will be implemented using the SWING (Small Whiskbroom Imager for atmospheric compositioN monitorinG). The instrument is designed to perform airborne measurements, but for the purpose of this paper it was adapted for ground-based use by the National Institute for Aerospace Research (INCAS) in Bucharest, Romania. The source aimed to be quantified is the city of Bucharest, specifically the total emissions generated by the traffic and industry within the city. The measurements will be performed during the Spring of 2020 between February and April. The experimental setup consists of the SWING that will be mounted on the roof of a car, which allows to perform measurements along the ring road of Bucharest. There will be presented results from several days of measurements from a total of 150 hours of driving in terms of differential slant column densities (DSCDs), vertical column densities (VCDs) and quantified emissions of NO­2 and SO2. This study will also be used for the fine tuning of the SWING operational parameters for use on UAV platforms in future measurement campaigns.
Patagonian Foreland burial and exhumation during Mesozoic revealed by low temperature thermochronology: a response to mantle processes?
Authors: Derycke Alexis , Gautheron Cécile , Genge Marie , Zattin Massimiliano , Mazzoli Stefano , Witt César , Marquez Marcelo
Published: March 2020

During the last decade, the study of the south Patagonian Andes and Antarctic area have demonstrated the occurrence of a complex mantle setup during the pre-Atlantic opening (200-140 Ma) with the formation and disappearance of an anomalous flat slab (~1000 km long), combined with the Karoo Plume development and western migration. In the Patagonian foreland, this period is characterized by plutons emplacement distant from the arc, flowed by a major volcanic income, the Chon Aike Large Igneous Province (~180 Ma to ~160 Ma). These markers are mostly seen in the Deseado Massif (~47 ° to ~48 ° S. Lat), a 350 x 200 km topographically high (between 500 and 1000 m elevation) area surrounded by Cretaceous and Cenozoic basins. The evolution of the Deseado Massif remains poorly constrained, although it is believed to be at this high topographic level since the end of the Chon Aike event.

In order to understand the pre-Atlantic opening evolution of the Deseado Massif and its potential long-term stability, we used a low temperature thermochronological approach. For this purpose, we sampled the Chon Aike deposits (rhyolite and ignimbrite) and basement rocks (~450 Ma to ~200 Ma plutons) across the Deseado Massif. The thermal history was reconstructed using new apatite (U-Th)/He data and published apatite fission tracks data. These thermochronometers are sensitive to temperature ranges from 120 ° and 40 °C, allowing to reconstitute rocks cooling and reheating history in the last kilometers of the crust. The thermal models reveal a significant Jurassic reheating event (post Chon Aike event) followed by a last cooling phase before ~100 Ma. The origin of this heating-cooling event will be discussed in relation with potential deposit accumulation/erosion, a change in the regional geothermal gradient, and finally, the eventual controls produced by the regional mantle setup.
Space-time machine learning for modelling soil organic carbon change
Authors: Heuvelink Gerard , Angelini Marcos , Poggio Laura , Bai Zhanguo , Batjes Niels , van den Bosch Rik , Bossio Deborah , Estella Sergio , Lehmann Johannes , Olmedo Guillermo , Sanderman Jonathan
Published: March 2020

Spatially resolved estimates of change in soil organic carbon (SOC) stocks are necessary for supporting national and international policies aimed at achieving land degradation neutrality and climate mitigation through better land management. In this work we report on the development, implementation and application of a data-driven, statistical space-time method for mapping SOC stocks, using Argentina as a pilot area. We used the Quantile Regression Forest machine-learning algorithm to predict SOC stock at 0-30 cm depth at 250 m resolution for Argentina between 1982 and 2017, on an annual basis. The model was calibrated using over 5,000 SOC stock values from the 36-year time period and 35 environmental covariates. Most covariates were static and could only explain the spatial SOC distribution. SOC change over time was modelled using time series maps of the AVHRR NDVI vegetation index. These NDVI time series maps were pre-processed using a temporal low-pass filter to allow the SOC stock for a given year to depend on the NDVI of the current as well as preceding years. Spatial patterns of SOC stock predictions were persistent over time and comparable to baseline SOC stock maps of Argentina. Predictions had modest temporal variation with an average decrease for the entire country from 2.55 kg C m‑2 to 2.48 kg C m‑2 over the 36-year period (equivalent to a decline of 210.7 Gg C, 3.0% of the total 0‑30 cm SOC stock in Argentina). The Pampa region had a larger estimated SOC stock decrease from 4.62 kg C m‑2 to 4.34 kg C m‑2 (5.9%) during the same period. For the 2001-2015 period, predicted temporal variation was 7-fold larger than that obtained using the Tier 1 approach of the Intergovernmental Panel on Climate Change and the United Nations Convention to Combat Desertification. Prediction uncertainties turned out to be substantial, mainly due to the limited number and poor spatial and temporal distribution of the calibration data, and the limited explanatory power of the covariates. Cross-validation confirmed that SOC stock prediction accuracy was limited, with a Mean Error of 0.03 kg C m-2 and a Root Mean Squared Error of 2.04 kg C m-2. The model explained 45% of the SOC stock variation. In spite of the large uncertainties, this work showed that machine learning methods can be used for space-time SOC mapping and may yield valuable information to land managers and policy makers, provided that SOC observation density in space and time is sufficiently large.
Beyond Plate Tectonics: The Northeast Atlantic Realm
Authors: Foulger Gillian
Published: March 2020

Conventional plate tectonics envisages simple continental breakup with clean splitting of supercontinents and subsequent orderly widening of oceans by seafloor spreading about a central ridge. No sooner was this paradigm proposed when the clear, first-order misfit of intraplate and large-volume volcanism was highlighted. That was quickly accommodated by adding an additional degree of freedom into the theory of Earth dynamics, i.e., ad hoc mantle plumes. Although this simple picture was adequate in the early years of plate tectonics, the subsequent rapid accumulation of vast datasets of ever-more-precise observations has rendered a theory of such simplicity no longer tenable. Simple plate tectonics can now serve only as a basic canvas on which the complexities of the real world must be painted. There is no better region for illustrating this than the Northeast Atlantic Realm which illustrates the full range of complexities. After a history of tectonic unrest spanning several 100 Myr true continental breakup, involving fracture of the entire lithosphere and ocean widening via sea-floor spreading, finally proceeded. However, geological complications are on at least an equal level to features arguably amenable to description by simple plate tectonics. Spreading ridges developed by propagation through continental lithosphere comprising a collage of cratons separated by orogenic belts. Where these propagators met insurmountable barriers the extension demanded by local kinematics could only be accommodated by diffuse continental extension. Continual changes occurred in the direction of regional extension and these resulted in local tectonic instabilities manifest in lateral ridge migrations, jumps, and parallel-ridge-pair extension. Extreme, magma-assisted continental extension, together with intense volcanism, formed lava-capped transitional crust. As a consequence the true extent of continental crust under the oceans is unclear. The geophysical characteristics of transitional crust are ambiguous in terms of physical properties. This presents a challenge to mapping continental material in the oceans, a problem that can be mitigated by joint interpretation with gravity, heatflow and geochemical data. Known continental blocks in the ocean include the array of blocks west of the British continental shelf (the Hatton-, George Bligh-, Lousy-, Bill Bailey’s- and Faroe Bank Highs, and Wyville-Thompson- and Fugløy Ridges), the Jan Mayen Microplate Complex, the Greenland-Iceland-Faroe Ridge and likely others that remain to be found. All of the above complexities in the solid Earth have profoundly affected the natural environment in the region, especially the oceans and the biosphere, and must be taken into account in predictions of future evolution of the natural environment.
Reconstruction of the Inshore Labrador Current using SWOT: from OI to DENKF
Authors: Han Guoqi , Ma Zhimin
Published: March 2020

Hourly sea surface height (SSH) from a coastal ocean model off eastern Newfoundland is used to generate simulated surface water and ocean topography (SWOT) data by a SWOT simulator. The simulated SWOT data are then used to reconstruct SSH by applying optimal interpolation (OI) in time and space. The reconstructed SSH is further used to calculate geostrophic currents associated with the inshore Labrador Current. The simulated SWOT data are also assimilated into the coastal ocean model by applying a deterministic ensemble Kalman filter (DEnKF). It is found that the inshore Labrador Current is fairly well reconstructed at the weekly scale, while the DEnKF assimilation reproduces well the  inshore Labrador Current at not only weekly but also daily scales.
Increasing compound warm spells and droughts during the growing season in the Mediterranean Basin
Authors: Vogel Johannes , Paton Eva
Published: March 2020

The Mediterranean Basin is known as a hot spot of climate change and therefore especially prone to increasing frequencies of warm spells and droughts. Investigating these events in isolation neglects their interactions, which illustrates the need to account for such compound events in a holistic manner. We analysed during which months the frequency of compound warm spells and droughts increased most over the 40-year period from 1979 – 2018. Warm spells and droughts were detected using daily maximum air temperature, precipitation and potential evaporation data from ERA 5. The two drought indices Standardised Precipitation Index (SPI) and Standardised Precipitation-Evapotranspiration Index (SPEI) were calculated.

Our results show the number of compound events increases substantially for almost the entire Mediterranean indicating that novel climatic conditions are occurring. The increases in compound events are predominantly driven by the rising number of warm spells, whereas SPI droughts remain almost constant. However, the rising temperatures lead to higher evapotranspiration, which alters the water balance in the Mediterranean. Therefore, the SPEI droughts shows significant increases in contrast to the SPI, indicating that even though the amount of precipitation does not decrease, the Mediterranean Basin is likely facing drier conditions due to increasing evapotranspiration. The highest changes in the number of compound warm spells and droughts occur in the time span from late winter to early summer. This finding is particularly relevant for Mediterranean ecosystems because this period encompasses the main growing season, and therefore ecosystem productivity and carbon sequestration might be reduced.
Applying Raman Spectroscopy to Modern and Palaeocharcoals Associated with Wildfire Activity
Authors: Theurer Thomas , Muirhead David , Jolley David
Published: March 2020

Evidence of wildfire activity in deep time is preserved in the rock record as fossilised charcoal. Modern wildfire temperature is often a function of fuel type, structure and availability. These three factors are reliant upon climatic conditions and offer a potential insight into palaeoenvironmental conditions through geothermometric analysis of preserved charcoals. Much like the analysis of vitrinite reflectance as an assessor of thermal maturity, similar methodology has been applied historically to charcoal in order to obtain palaeowildfire temperatures.  Raman spectroscopy has similarly been applied to organic material as an identifier of thermal maturity, via the analysis of carbon microstructure changes with increasing temperature – however very little palaeocharcoal has been analysed via Raman spectroscopy, with no apparent application to palaeowildfire geothermometry. Through the application of Raman spectroscopy, we present the first comparison of modern pyrolyzed plant material with spectra of early Danian palaeocharcoals, associated with wildfire activity. These results indicate that Raman spectroscopy of modern wildfire charcoal facilitates a correlation between charcoal microstructure change and temperature of formation. This in turn has enabled comparison with palaeocharcoal, and the generation of reliable wildfire geothermometry. With this new methodology, we intend to further the understanding of (1) changes in palaeowildfire regimes and intensity through time (2) the interaction between climate, plant community composition and structure, and palaeowildfires  (3) correlation and comparison with existing palaeowildfire interpretive approaches. Further analysis and experimentation is required to identify the impact of fire determining factors on observed spectra to target the new approach towards interpreting current and future wildfire behaviour under climatic stress. 
Tropical Cyclone Precipitation in the AMIP Experiments of the Primavera Project
Authors: Zhang Wei , Villarini Gabriele , Scoccimarro Enrico , Roberts Malcolm
Published: March 2020

This study examines the climatology and structure of precipitation associated with tropical cyclones based on the Atmospheric Model Intercomparison Project (AMIP) runs of the Process-based climate simulation: advances in high resolution modelling and European climate risk assessment (Primavera) Project during 1979-2014. We assess the role of spatial resolution in shaping tropical cyclone precipitation along with inter-model variability by evaluating climate models with a variety of dynamic cores and parameterization schemes. AMIP runs that prescribe historical sea surface temperatures and radiative forcings can well reproduce the observed spatial pattern of tropical cyclone precipitation climatology, with high-resolution performing better than low-resolution ones in the first order. Overall, the AMIP runs can also reproduce the fractional contribution of tropical cyclone precipitation to total precipitation in observations. Similar to tropical cyclone precipitation climatology, the factional contrition is better simulated by high-resolution models. All the models in the AMIP runs underestimate the observed composite tropical cyclone rainfall structure over both land and ocean, and we identify differences in this factor between high-resolution and low-resolution models. The underestimation of rainfall composites by the AMIP runs are also supported by the radial profile of tropical cyclone precipitation. This study shows that the high-resolution climate models can reproduce well the spatial pattern of tropical cyclone climatology and underestimate the composite rainfall structure, with increased spatial resolution that overall improves the performance of simulation.
Ground-ice stable-isotope paleoclimatology at the Batagay megaslump, East Siberia
Authors: Opel Thomas , Wetterich Sebastian , Meyer Hanno , Murton Julian
Published: March 2020

In recent years, permafrost ground ice (i.e. ice wedges and pore ice) has been frequently utilized as a paleoclimate archive for the Late Pleistocene and Holocene, mainly using stable isotopes from water as proxies for local air temperatures. Due to their formation processes (frost cracking in winter and crack infilling mainly with snowmelt in spring), ice wedges have a unique winter seasonality, whereas pore ice integrates summer or annual precipitation.

The world’s largest retrogressive thaw slump at Batagay in the Yana Upland, East Siberia (67.58 °N, 134.77 °E), provides unique access to Late and Middle Pleistocene permafrost formations usually deeply buried in the frozen ground. The Batagay megaslump exposes syngenetic ice wedges and composite wedges (ice–sand wedges) along with pore ice in four cryostratigraphic units: (1) the Lower Ice Complex, (2) the Lower Sand, (3) the Upper Ice Complex, and (4) the Upper Sand.

Here, we present ground-ice stable-isotope data from all four units. This dataset is accompanied by precipitation stable-isotope values from winter snowpack and summer rain as a first stable-isotope framework for this region.

The high continentality of the study region with – extremely low winter temperatures – is clearly reflected by the stable-isotope composition for ice wedges from the Upper Ice Complex (MIS 3) and nearby Holocene ice wedges. Both are much more depleted than for any other ice-wedge study site in East Siberia. The ice wedges from the Lower Ice Complex are likely the oldest ice wedges (>0.5 Ma) ever analyzed isotopically and also point to very cold winter climate during formation. Stable-isotope signatures of composite wedges and pore ice are less distinctive and require detailed studies of formation processes and seasonality.
Evaluation of Organized Convection Parameterization in Global Climate Models
Authors: Chen Chih-Chieh , Liu Changhai , Moncrieff Mitch , Richter Yaga
Published: March 2020

The importance of convective organization on the global circulation has been recognized for a long time, but parameterizations of the associated processes are missing in global climate models. Contemporary convective parameterizations commonly use a convective plume model (or a spectrum of plumes). This is perhaps appropriate for unorganized convection but the assumption of a gap between the small cumulus scale and the large-scale motion fails to recognize mesoscale dynamics manifested in mesoscale convective systems (MCSs) and multi-scale cloud systems associated with the MJO. Organized convection is abundant in environments featuring vertical wind shear, and significantly modulates the life cycle of moist convection, the transport of heat and momentum, and accounts for a large percentage of precipitation in the tropics. Mesoscale convective organization is typically associated with counter-gradient momentum transport, and distinct heating profiles between the convective and stratiform regions.

Moncrieff, Liu and Bogenschutz (2017) recently developed a dynamical based parameterization of organized moisture convection, referred to as multiscale coherent structure parameterization (MCSP), for global climate models. A prototype version of MCSP has been implemented in the NCAR Community Earth System Model (CESM) and the Energy Exascale Earth System Model (E3SM), positively affecting the distribution of tropical precipitation, convectively coupled tropical waves, and the Madden-Julian oscillation. We will show the further development of the MCSP and its impact on the simulation of mean precipitation and variability in the two global climate models.
Wave Climate of the Southern Ocean
Authors: Young Ian
Published: March 2020

Although the Southern Ocean is often viewed as a very remote area, it plays a critical role in global climate. Waves generated in intense Southern Ocean storms propagate across the Indian, Pacific and Atlantic Oceans and define the wave climate for many areas of these oceans. In addition, the wind and wave climate of the Southern Ocean plays an important role in determining the rate of decay of Antarctic glaciers which are an important element in global sea level change. Despite this important role, little is known about the wind and wave climate of this vast region. This paper will bring together a series of unique datasets to provide a comprehensive view of this wind and wave climate. These datasets include: the long duration model reanalysis dataset ERA-I, a 33-year calibrated and validated altimeter dataset and buoy data from four deployments. These buoys have been located at: Macquarie Island (540S), Campbell Island (520S), a site west of South America (550S) and the Southern Ocean Flux Buoy south of Tasmania (460S). Data from these buoy deployments spans a total of approximately 7 years and provides directional spectra in unique long fetch environments. In addition to providing valuable data for model validation, engineering design and Naval Architecture, these combined datasets provide new insights into air-sea interaction under extremely long fetch conditions. The paper will also use the satellite datasets to investigate changes in wave conditions in recent decades and the role that climate variability plays in such changes. This analysis will examine: long-term trends, annual variability and multi-year oscillations.
System of Multigrid NLS-4DVar Data Assimilation for Numerical Weather Prediction (SNAP)：System Formulation and Preliminary Evaluation
Authors: Zhang Hongqin , Tian Xiangjun
Published: March 2020

The system of multigrid NLS-4DVar data assimilation for Numerical Weather Prediction (SNAP) is established, building upon the multigrid NLS-4DVar assimilation scheme, the operational Gridpoint Statistical Interpolation (GSI)-based data-processing and observation operator and widely used numerical forecast model WRF (easily replaced by others global/regional model). The multigrid assimilation framework can adequately correct errors from large to small scales to achieve higher assimilation accuracy. Meanwhile, the multigrid strategy can accelerate iteration solution improving the computational efficiency. NLS-4DVar, as an advanced 4DEnVar method, employs the Gauss-Newton iterative method to handle the nonlinear of the 4DVar cost function and provides the flow-dependent background error covariance, which both contribute to the assimilation accuracy. The efficient local correlation matrix decomposition approach and its application in the fast localization scheme of NLS-4DVar and obviating the need of the tangent linear and adjoint model further improve the computational efficiency. The numerical forecast model of SNAP is any optional global/regional model, which makes the application of SNAP very flexible. The analysis variables of SNAP are rather the model state variables than the control variables adopted in the usual 4DVar system. The data-processing and observation operator modules are used from the National Centers for Environmental Prediction (NCEP) operational GSI analysis system, prominent in the various observation operators and the ability to assimilate multi-source observations. Currently, we have achieved the assimilation of conventional observations and we will continue to improve the assimilation of radar and satellite observations in the future. The performance of SNAP was investigated assimilating conventional observations used for the generation of the operational global atmospheric reanalysis product (CRA-40) by the National Meteorological Information Center of China Meteorological Administration. Cyclic assimilation experiments with two windows, which is 6-h for each window, are designed. The results of numerical experiments show that SNAP can absorb observations, improve initial field, and then improve precipitation forecast.
Habitat map plays an active role for coastal eco-DRR by multi-stakeholders
Authors: Kitazato Hiroshi , Oki Yuri , Yasukawa Soichiro
Published: March 2020

Coastal land- and sea-scapes are composed of diverse habitats such as reed bed, salt marsh, tidal-flats, sea grass fields, seaweed grounds, sandy and rocky-shores. Coastal habitats harbor both biodiversity and abundance of coastal lives. These complex coastal ecosystems are sustained by the function of land-sea linked material cycles. Coastal ecosystems provide wide ranges of ecosystem services and processes among natural environments, fisheries, and human livelihoods.  Protecting coastal ecosystems secure material cycle, which is fundamental for sustainable human livelihood in coastal communities prone to disasters. In addition, bio-diverse coastal species such as sea grasses, function as nursery areas for commercially important seafood species such as fishes, clams, shrimps, and others. On the other side, coastal ecosystems provide natural infrastructure for both prevention and reduction from hazardous events, known as ecosystem-based disaster risk reduction (eco-DRR).  For establishing concept of eco-DRR, we need to prepare precise coastal biological, geological and other data including human and social activities.  Habitat map projection is effective way to pile multi-disciplinary data on same GIS grid.  Habitat map, thus, provides common data sets to multiple stakeholders, such as scientists, fishermen, local fish markets and local and federal governments for planning coastal management systems.

    Earthquakes and Tsunamis should give heavy damages on coastal lives and ecosystems in global scale.  Because, more than half of world populations concentrate into vulnerable coastal areas.  Together with the conventional hard-infrastructure measures, we have witnessed in previous disasters, that eco-DRR is both affordable and sustainable solution.  Eco-DRR should be further promoted, not only in the preparedness and mitigation, but also for the better reconstruction from the disasters so to "Build Back Better". We plan to show a couple of best practices in terms of Eco-DRR activities from March 11, 2011 Earthquake and Tsunamis.
An extended transfer function model for the prediction of nonpoint-source pollutant travel times
Authors: Bancheri Marialaura , Coppola Antonio , Basile Angelo
Published: March 2020

Transfer functions are travel time probability density functions (TT pdfs), which describe the leaching behaviour in a given soil profile. Once they are defined, the output solute concentration at a given time and depth is simply the transfer function convolution with the input concentration signal to the system.

In this work we propose an extended version of Jury's transfer function model (TFM-ext). The proposed model allows to simulate the spatio-temporal distribution of nonpoint-source solutes along the unsaturated zone that: i) integrates a simplified statistical approach with the physically-based soil hydrological parameters; ii) is valid for wide range of applications, both in space and time; iii) is standard and easily replicable; iv) is easy to interpret.

With the assumptions of a) a gravity induced water flow, b) a conservative and nonreactive solute and c) a purely convective flow, ignoring the convective mixing of solute flowing at different velocities and the molecular diffusion, the TT pdf were calculated as functions of the unsaturated hydraulic conductivity k(θ). The strength of the model, despite its important assumptions, is that it derives the TT pdf from a physical quantity, i.e. the hydraulic conductivity function. Moreover, the model extends the transport process to the generic depth z, where information on the hydraulic properties could not be available, assuming a lognormal travel time pdf, whose parameters are scaled according to the generalized transfer function model.

A sensitivity analysis, based on Monte Carlo simulations, to evaluate to which parameters the TFM-ext is more sensitive, was performed. Results shown that θs and τ, of the van Genuchten-Mualem model, are the parameter affecting more the mean travel times.

Moreover, in order to validate TFM-ext, an application in the Telesina Valley, a hilly area of 200 km2 in Southern Italy, was performed. Forty-six soil profiles, completely characterized from the hydrological point of view, were used to evaluate the mean travel times and then compared with the results obtained with a notable physically based model, Hydrus 1D. Two distinct applications were performed: the first with constant upper boundary conditions equal to those applied to the TFM-ext exercise, and the second with real daily variable upper boundary conditions. Results of both cases gave very high correlation coefficients (above 0.8) and mean absolute errors of 30 and 40 days, respectively.

Eventually, the model was implemented as an operative tool for the groundwater vulnerability assessment within the geospatial Decision Support System developed for LANDSUPPORT H2020 project.