bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of winter mean precipitation over North India in CMIP6 models
Authors: Sharma Nischal
Published: March 2022

Evaluation of winter mean precipitation over North India in CMIP6 models

Nischal Sharma1, Raju Attada1*, A. R. Dandi2, R. K. Kunchala3, Anant Parekh2, J. S. Chowdary2

1Department of Earth and Environmental Sciences - Indian Institute of Science Education and Research Mohali, Punjab – 140306

2 Indian Institute of Tropical Meteorology, Pune, India

3Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, India

*E-mail of corresponding author: rajuattada@iisermohali.ac.in

 

Abstract

North India receives a significant proportion of annual precipitation during winter (December to February) through mid-latitudinal cyclonic perturbations (Western Disturbances) embedded in subtropical westerly jet stream. This region accounts for a paucity of available in-situ observations owing to complex topography which underpins the necessity of other non-conventional tools for precipitation estimation. Global Climate Models are an effective tool to investigate global monsoon systems and are being extensively used to better understand spatio-temporal characteristics of precipitation. In the present study, north Indian winter precipitation (NIWP) and its variability has been characterized in 30 CMIP6 historical simulations (1979-2014) and compared with IMD gridded data observations. Normalized biases in different models relative to observations have been used to categorize models as wet (11), dry (8) and normal (11) models and further composite analysis has been conducted for these model categories. Our findings suggest that all the models show highest precipitation orientation along the western Himalayan belt, with the normal model category showcasing quite similar results to observations. Wet models show highest variability, errors and positive bias over the region while dry models exhibit least variability and negative bias. Majority of the models show an overall good correlation with observations. The representation of winter mean dynamical and circulation patterns has been carried out using composite analysis of three model categories relative to observations. The composite analysis reveals an intensified jet in both wet and dry model categories, with a southward shift of the jet position in wet models.  Detailed results will be discussed.

Keywords: Global climate models, CMIP6, winter precipitation
Assessing the impact of climate change on three decades of soil salinity dynamics in the Bajestan Playa, Northeast Iran
Authors: Khosravichenar Azra , Aalijahan Mehdi , Moaazeni-Noghondar Saeidreza , Ulrich Mathias , Parvian Naser , Sadeghi Abouzar , Von.Suchodoletz Hans
Published: March 2022

Playas are endorheic sediment basins in drylands that are temporally filled with water. During dry seasons, their surfaces are generally covered with a thick crust of clay-rich clastic material and soluble salts. Strong winds can mobilize that fine-grained material, including the salts, from the playa surfaces as aeolian dust that strongly affects the surrounding ecosystems and human livelihood. During recent decades, climate change strongly altered the salinity regimes of many playas, leading to an increase of surface salinity. During this study we investigated the impact of climate change on soil salinity dynamics in the Bajestan Playa, Northeast Iran, over a period of three decades (1992-2021). The studied region is particularly exposed to the "Sistan winds of 120-Days" during the dry season in summer. Therefore, it is one of the main dust source areas in eastern Iran.

In order to better understand and predict the geochemical composition of aeolian dust, it is necessary to monitor and map regional salinization processes. Thus, we applied a multi-disciplinary approach that encompased remote sensing, field-based ground truthing, and climatic data analysis. Remote sensing analysis on Landsat data (first week of July of all studied years) were carried out on three generations of sensors (TM, ETM+, OLI 8) that were uniformly corrected for atmospheric and geometrical conditions. During a field campaign in July 2021, a total number of 130 soil sampleswere collected from the upper 20 cm of soil of areas that represent seven soil salinity classes that were preliminary identified based on multispectral remote sensing analysis and regional geological maps. In addition, the electrical conductivity (EC) was subsequently measured on the soil surface samples in the laboratory. Based on these field measurements and the remote sensing analyzes, we were finally able to derive twelve soil salt indices. Two among all indices (S12 and S13) showed the most satisfactory calibration accuracies between the field and remote sensing-based EC values. Finally, the index SI2 was applied to the Landsat images for temporal and spatial quantitative soil salinity mapping. Furthermore, to validate the impact of climate change on the salinity changes, the Standardized Precipitation Index (SPI) and the Mann-Kendal Index were calculated based on temperature and precipitation data at different time scales of the last 60 years.
The WOD framework for weather forecasting
Authors: Rögnvaldsson Ólafur , Ragnarsson Logi , Stanisławska Karolina
Published: March 2022

Belgingur Ltd. has created a novel weather forecasting framework, called Weather On Demand – WOD, that can be deployed in the cloud and customised for any location world-wide at a very short notice.

The WOD framework is a distributed system for:

gathering upstream weather forecasts and observations from a wide variety of sources

triggering scheduled or on-demand jobs

running the WRF weather model for data-assimilation and forecasts

processing data for long to medium-term storage

making results available through APIs

making data files available to custom post-processors

Much effort is put into starting processing as soon as the required data becomes available and in parallel when possible. The software is maintained in Git and can be installed on suitable hardware in a matter of hours, bringing the full flexibility and power of the WRF modelling system at your fingertips.
Flooding Effect on Rhizosphere Processes in Salt Marsh Plants: Visualizing Spatio-temporal Dynamics of O2 and CO2 using Planar Optodes
Authors: Wilson Monica , Jensen Kai , Mueller Peter
Published: March 2022

Tidal marshes are vegetated coastal ecosystems that are heavily influenced by estuarine gradients such as tidal inundation and salinity. The sequestration potential of these blue carbon ecosystems relies on the balance between the input and degradation of soil organic matter. At the root-soil interface, plant activity greatly impacts the physicochemical and biological properties of the surrounding soil through interactions with soil microbiota. The transport of oxygen into the anoxic sediments and exudation of metabolic substrates by wetland species demonstrate two key mechanisms by which plants can prime the microbial decomposition of organic matter. Previous studies have observed markedly distinct modulation of rhizosphere processes even amongst closely related species. Using planar optodes, these biogeochemical processes can be visualized and quantified as 2D images via dynamic quenching of O2 and CO2-sensitive fluorophores. This technique enables real-time spatial and temporal mapping of these analytes with minimal disturbance to the belowground biomass. Characterizing these profiles for marsh vegetation under hydrological stress may inform future predictions about species performance under the ongoing threat of accelerated sea level rise. In a microcosm experiment, three salt marsh species will be used in a transplant study to investigate the effect of inundation stress on O2 and CO2 dynamics in the rhizosphere over alternating light-dark cycles. By combining physiological measurements with morphological attributes, we aim to catalogue plant trait information that can used in scaled-up projections of long-term ecosystem functioning in wetlands.
Shear strength of unsaturated soils artificially vegetated in a field test site
Authors: Cuomo Sabatino , Moscariello Mariagiovanna , Foresta Vito
Published: March 2022

The effect of a long-root grass on the shear strength response of a partially saturated pyroclastic soil was investigated through a field and laboratory experimental program. Field measurements of soil water content, suction, temperature, and laboratory tests aimed to estimate the shear strength of differently rooted soils were performed. The experimental investigation was carried out on a test site located in Nocera Inferiore, (Campania region, Italy), a few kilometers far from sites of past catastrophic flow-like landslides. The experimental program was carried out on three species of Perennial graminae grass species, characterized by fine and fasciculate long roots.  

In the field, soil temperature, pH, humidity, and suction were monitored from seeding. The trends were compared with those of air temperature and humidity. Moreover, soil suction and water content trends were related to daily rainfall.

Undisturbed pyroclastic soil specimens containing roots of perennial graminae grass species were collected after 5 months from seeding and tested at natural water content in standard and suction controlled direct shear equipment. The specimens exhibited different Root Volume ratio (RV) and suction. The shear envelopes were extrapolated using Bishop formulation of effective stress, which allows to consistently consider the partially saturated condition of the soils. The experimental results outlined that the shear strength envelope of vegetated specimens moves upwards in the τ-σ’ space, but also rotates counterclockwise. In general, the cohesion intercept increases, while the effective frictional angle reduces. Moreover, the RV influence on the magnitude of friction angle and cohesion has been assessed. Densely vegetated soils undergo larger modifications of the shear strength envelop than poorly vegetate specimens.   

The authors would like to acknowledge Prati Armati S.r.l. that provided the grass species used for the tests.
Fragile earth history ­– geological, societal and ethical perspectives on the planetary memory
Authors: Hildebrandt Dominic
Published: March 2022

The geological record of earth history is a fragile document, which enables us to extract information on past planetary processes, e.g. natural hazard events or fluctuations of the earth's climate, which are increasingly used as the basis for future regulatory frameworks in modern societies. However, due to an intense interference of humans with the earth surface in the Anthropocene, this unique document of earth history is endangered. It is crucial to consider that the geological record is not continuous and primarily incomplete, although the exact extent is still elusive. Human activities such as mining and construction works heavily alter, disturb or even entirely destroy parts of the earth history. Also, inadequate sampling strategies of earth scientists can contribute to a loss of earth-historical information at key sites for understanding the earth's past. Most societies are well aware of the conservation of the human history indicated by standardized archaeological surveys. At the same time, such procedures are hardly formalized for earth history archives, revealing an anthropocentric narrowing of the perception of pasts. Humans are seen as a major geological agent during the Anthropocene – but how does the destructive facet of anthropogenic activities compare to natural destructive processes throughout the earth history and what are implications for the protection of geo-archives? I argue that anthropogenic disturbance is distinctively different from natural processes regarding the rates and the final fate of manipulated earth materials. Pushing the spatio-temporal assessment of the completeness of the geological record, e.g. by hiatus mapping, would help to identify a baseline for the protection of earth history records during the Anthropocene. Promoting Geoethics, in particular the sustainable knowledge exchange with society to create awareness for planetary history as a basis for a responsible handling of nature, is a key for an effective protection of earth history records. In particular, understanding psychological aspects of landscapes and the environment plays a vital role. Therefore, post-normal science approaches and the consideration of extended spheres of knowledge bear a great potential for future perspectives.
Crack healing in salt: time-resolved 3D microtomography
Authors: Ji Yuntao , Spiers Christopher , Hangx Suzanne , de Bresser Hans , Drury Martyn
Published: March 2022

Rocksalt caverns are considered or already used as storage for nuclear waste, petroleum, hydrogen, CO2, and compressed air energy because of the low permeability and potential of fracture healing of salt. An important concern is the sealing capacity. Undisturbed rocksalt deposits in nature generally have very low permeability. However, as a result of excavation stress, a network of fractures will be induced within the rocksalt formation, increasing the permeability. At low deviatoric stresses and/or at low effective stresses, a fracture network filled with brine is expected to heal, and the connectivity of the brine-filled network, consisting of grain boundaries, pores, and microcracks, is expected to decrease over time. The driving force for such a healing process is the tendency to reduce the interfacial energy by reducing the total interfacial area. In order to assess the rate of pore reconfiguration and permeability evolution in damaged salt and to capture the key process of crack network evolution during healing, we employ time-resolved 3D microtomography to study the long-term evolution of the fracture network of small-scale polycrystalline rocksalt samples. We found that precipitation prefers to occur in open spaces in the early stage of healing, such as new cracks. As a result, flat cracks evolve into zigzag cracks, which create narrow throats, thereby reducing the permeability of the crack network. Our study also offers a way to testify the thermodynamic models quantitatively.
Agroclimatological Classification for Iran Land for Earth Observation Purposes
Authors: Asadi Oskouei Ebrahim , Delsouz Khaki Bahareh , Lopez-Baeza Ernesto
Published: March 2022

Modeling climatic conditions and knowing about them helps us to improve ecosystem management. Climate classifications generally have been produced using stations' data, and because satellite data did not have a proper temporal period, they could not be applied as a tool for climate classification. The aim of this study was a qualitative assessment of the fitness of satellite data as covariates of an agro-climate classification. To define agroclimate classes in Iran land, temperature and precipitation were selected as the main climatological parameters in agriculture. Using data collected from 3825 synoptic, climatological, rain gauge, and evaporation stations from 2002 to 2016, an agroclimatic map was produced with a resolution of 5 km which is divided into 24 agroclimatic classes. Comparison between resulted agroclimatic classes and some remote sensed agricultural related variables including mean_yearly_NDVI-TVDI, average actual evapotranspiration (m/yr), evapotranspiration (m/yr) and average soil moisture (m3/m3), showed a very sharp visual accordance. The accordance was very clear specially in the case of TVDI which had a greater resolution of 1 km x 1 km. The results showed that satellite data can be a useful candidate (as meaningful auxiliary variables) for agroclimate classifiers. moreover, in situ based classifications can be beneficial as a tool of satellite data classification and interpretation. Another point is that, the greater the similarity between satellite data and agroclimate classified raster resolutions, the better the conditions for comparing and evaluating performance.
Finding Riverine Plastics in Floating Plant Patches using Worldview-3 Satellite Imagery
Authors: Biermann Lauren , Schreyers Louise , van Emmerik Tim , Bui Thanh-Khiet , Ling Yangrong , Streett Davida
Published: March 2022

Water hyacinths appear to play an important role in gathering and transporting macroplastic litter in riverine ecosystems. These fast-growing and free-floating invasive freshwater plants tend to form large patches at the water surface, which makes it possible to detect and map them in freely available imagery collected by the European Space Agency (ESA) satellites. In polluted rivers, hyacinth may thus serve as a viable proxy for macroplastics. However, at the ~10m spatial resolution offered by the Sentinel-1 and Sentinel-2 satellites, it’s not possible to discriminate smaller items of plastic caught up within large plant patches.

We present a case study from the Saigon River around Ho Chi Minh City, Vietnam. Here, we were able to successfully discriminate plastic debris within hyacinth patches using MAXAR Worldview-3 multispectral optical data (1.24m) and panchromatic imagery (0.31m). For the optical data, we selected the ACOLITE atmospheric correction and applied a novel detection index that leveraged the panchromatic band and the red band (band 5) to highlight differences between vegetation and debris. This approach allowed for the detection of riverine plastics within hyacinth patches floating downstream from Ho Chi Minh City towards the coast. Initial results from the Han River and coastal waters of Da Nang in Vietnam suggest that our plastic litter discrimination method is transferable to other aquatic environments. This research is preparatory for further remote sensing monitoring of 'plastic plants' in riverine ecosystems, and will be supporting clean-up operations being trialled in 2022.
Inferring permafrost thermal properties from freeze-thaw column experiments and numerical modelling
Authors: de Bruin Jelte , Bense Victor , van der Ploeg Martine
Published: March 2022

Cold-regions contain a vast pool of organic carbon in permafrost, which is currently immobilized. As the global air temperatures rise, permafrost active layer depths are increasing. The deepening of the active layer reactivates groundwater transport processes, leading to the release of solutes such as dissolved carbon to streams and the atmosphere. In order to make predictions of the rates of permafrost thaw based upon numerical modeling, we need accurate data on active layer thermal properties.

Active layer thermal properties, thermal conductivity and heat capacity, are strongly coupled to geological properties such as water content, and organic matter content and are therefore highly heterogenous in natural systems. Furthermore, the effective thermal properties vary as a function of temperature through ice-content, especially across the freeze-thaw interval near 0 oC. Direct in-situ observations of active-layer thermal properties are rare because in-situ measurements involves sampling of frozen samples and analysis in a laboratory.

This study uses soil column (1 m high x 0.31 m diameter) experiments to investigate the relation between soil physical properties and thermal properties. A total of nine samples were synthesized using a range of grain sizes and organic matter contents, and were fully saturated with water. The columns were insulated on the sides and top, aiming to create a fully 1D thermal system allowing only vertical heat transport. The columns are subjected to one freeze-thaw cycle, lasting about 20 weeks. Resulting temperature observations were analyzed using a numerical heat transfer model. By fitting the temperature observations to the heat transfer model, thermal properties can be inferred. Initial data shows differences in heat propagation through the soil column, indicating differences in thermal conductivity and heat capacity as a result of varying soil grain size and organic matter content. This research will help to link permafrost soil physical properties to thermal properties, and increase understanding at the dynamic freeze-thaw interval.
Late Cenozoic faulting deformation of the Fanshi Basin (Northern Shanxi rift, China), inferred from paleostress analysis of mesoscale fault-slip data
Authors: Tranos Markos D. , Assie Konan Roger , Wang Yu , Ma Huimin , Kouamelan Kouamelan Serge , Thompson Brantson Eric , Zhou Liyun , Blaise Ketchaya Yanick
Published: March 2022

The Fanshi Basin is one of the NE-SW-striking depocenters formed along the northern segment of the fault-bounded Shanxi rift. In order to understand the crustal driving stresses that led to the basin formation and development, a paleostress analysis of a large number of fault-slip data collected mainly at the boundaries of the basin was accomplished. The stress inversion of these data revealed three stress regimes. The oldest SR1 was a Neogene stress regime giving rise to a strike-slip deformation with NE-SW contraction and NW-SE extension. SR1 activated the large faults trending NNE-NE, i.e., (sub) parallel to the main strike of the Shanxi rift, as right-lateral strike-slip faults. It was subjected to the Shanxi rift before the activation of the Fansi Basin boundary fault, i.e., the Fanshi (or Wutai) fault, as a normal fault. The next is a short-lived NE-SW extensional stress regime SR2 in the Early Pleistocene, which shows the inception of the basin's extension. A strong NW-SE to NNW-SSE extensional stress regime SR3 governed the northern segment of the Shanxi rift since the Late Pleistocene and is the present-day extension. It gives rise to the current half-graben geometry of the Fanshi Basin by activating the Fanshi (or Wutai) fault as a normal fault in the southern part of the graben. Because of the dominance of the NW-SE to NNW-SSE extension, which is perpendicular to the NE-SW extension, mutual permutations between σ3 and σ2 due to inherited fault patterns might occur while the stress regime changed from SR1 to SR3.
A Web Based Open Source Deformation Analysis Platform for identifying Crustal Movements
Authors: Bak Mehmet , Celik Rahmi Nurhan
Published: March 2022

Deformation measurements and deformation analysis are important fields of study in geodesy. Investigating the results obtained from the deformation analysis is very important for human safety. By monitoring the movements of the earth's crust or engineering structures, many measures can be taken to protect human life against potential disasters. For this reason, geodetic measurement techniques have been used since the beginning of the 20th century. Important studies have been carried out, especially with the development of GNSS measurement techniques for monitoring displacement movements and deformations. Both academic and commercial software are available for deformation analysis for the determination of earth crust movements. However, the increasing interest in studying crustal movements has revealed new demands. Today, developing technology has allowed the development of new platforms for deformation analysis.

In this study, an open source web-based deformation analysis platform named Web-NDefA (Web-'N'etwork 'Def'ormation 'A'nalysis), which was developed for 3D static deformation analysis using geodetic methods, is introduced. In addition, the analysis of a data group obtained from Continuously Operating Reference Stations in the Marmara Region with this platform is also explained. After the processing of the base vectors obtained from univariant GNSS networks with the LGO (Leica Geo Office) software, Web-NDefA is used to load the ASCII file of the base solutions to the platform, to adjust the measurements according to the free adjustment method, to obtain the confidence criteria and to analyse the networks compared according to the static deformation model and S-Transformation method. It is a static deformation analysis platform that performs 3-Dimensional statistical analysis that provides visualization, computation of coordinate differences, and drawing velocity vectors. This platform is written with client-side programming languages. HTML (HyperText Markup Language), CSS (Cascading Style Sheets), JavaScript applications were made.

As a result, in this study, information about the design of the have developed open source web platform is given and GNSS data obtained from certain days in 2016, 2019 and 2020 in the Marmara Region are analysed. In this way, a new vision is put forward to the applications used in GNSS-based static deformation analysis and experts who are interested in monitoring and analysing deformations can access such platforms more easily.
Differences between surface and air urban heat island for clear sky conditions in Iasi city (Romania) and their relation with atmospheric circulation
Authors: Sfica Lucian , Cretu Claudiu , Ichim Pavel , Breaban Iuliana-Gabriela , Hritac Robert
Published: March 2022

The increasing accessibility to high resolution land surface temperature (LST) data unbalances recently the investigation of the urban heat island (UHI) towards approaches based on these remote sensing tools. However, for a holistic assessment of UHI, a need of comparison of the resulted surface urban heat island (SUHI) with the air urban heat island(AUHI) remains of great interest. In our study we respond to this demand by taking to account all the MODIS LST images and their corresponding synchronous air temperature observations from 9 in-situ monitoring points evenly distributed over the city of Iași for 2013-2020. This way, using a total of 2901 satellite images, the main diurnal and seasonal characteristics of clear-sky SUHI have been outlined for Iași city.

The results obtained describe accurately the intensity of the SUHI, but also its relation with the urban land use categories. During summer season in daytime the spatial extent of SUHI reaches its maximum, SUHI being bounded by the 35°C isotherm in direct relation with the highest imperviousness ratio. In the winter season instead, SUHI is almost absent during the day especially due to the high frequency of temperature inversions in this area. Also, the geometry of SUHI tends to be compact and regular during the nighttime and more irregular during the daytime, as a result of the higher and more complex energy input.

The comparison with the in-situ observations indicates that the differences between SUHI and AUHI are highest during the daytime in spring and summer, when LST is 5 to 7°C higher than the air temperature in classical sheltered conditions, while during winter no major difference can be observed. For the nighttime the LST is 1 to 3°C lower than air conditions regardles of the seasons. The analysis is detailed with the influence of land use categories and imperviousness ratio on SUHI, but also on the difference between SUHI and AUHI. As well, using a k-means atmospheric circulation classification we identified the weather patterns that are capable to increase both the SUHI intensity, and the difference between SUHI and AUHI.
Direct evidence for a 20th Century decline in Southern Ocean sea ice
Authors: Ferreira David , Day Jonathan
Published: March 2022

Since satellite records began in the 1970s, a small expansion of sea ice area around Antarctica has been observed, in stark contrast with the large decrease seen in the Arctic region. This expansion is difficult to reconcile with the observed rise in global temperatures and appears at odds with the ice loss simulated by climate models over the same period. Efforts to elucidate the driving mechanism are hampered by a short observational record, with little information available prior to the advent of satellite observations. Here we use direct observations recovered from logbooks of early explorers and routine shipping reports (1900 to 1953) to shed new light on the position of the ice edge. The data reveals that the early 20th century sea ice extended 3.1$^\circ$ (2.6$^\circ$-3.3$^\circ$ for 5-95\% confidence interval) further north ($\sim$100\% more extensive) than the present day. This finding re-frames the 20th century as a period of overall long-term sea ice loss in the Antarctic. The extensive sea ice cover, compared to present, goes hand-in-hand with cooler sea surface temperatures and reduced zonal wind speed in the region, consistent with reduced concentrations of anthropogenic forcing agents (greenhouse gas, ozone depletion) in the early 20th century, and may reflect the unperturbed state of Antarctic sea ice.

 
Exploring satellite-derived relationships between cloud droplet number concentration and liquid water path using large-domain large-eddy simulation
Authors: Dipu Sudhakar , Schwarz Matthias , Ekman Annica M. L , Gryspeerdt Edward , Goren Tom , Sourdeval Odran , Mülmenstädt Johannes , Quaas Johannes
Published: March 2022

Important aspects of the adjustments to aerosol-cloud interactions can be examined using the relationship between cloud droplet number concentration (Nd) and liquid water path (LWP). Specifically, this relation can constrain the role of aerosols in leading to thicker or thinner clouds in response to adjustment mechanisms. This study investigates the satellite retrieved relationship between Nd and LWP for a selected case of mid-latitude continental clouds using high-resolution Large-eddy simulations (LES) over a large domain in weather prediction mode. Since the satellite retrieval uses the adiabatic assumption to derive the Nd (NAd), we have also considered NAd from the LES model for comparison. The joint histogram analysis shows that the NAd-LWP relationship in the LES model and the satellite is in approximate agreement. In both cases, the peak conditional probability (CP) is confined to lower NAd and LWP, and the corresponding mean LWP shows a weak relation with NAd. In contrast, at higher NAd (> 50 cm−3 ), the CP shows a larger spread; consequently, the mean LWP increases non-monotonically with increasing NAd in both cases. However, the NAd-LWP relation lacks, in particular, the negative sensitivity at higher NAd. This case over continent thus behaves differently compared to previously-published analysis of Oceanic clouds using satellite retrievals. Additionally, our analysis illustrates a regime dependency (marine and continental) in the NAd-LWP relation from the satellite retrievals. When considering the relationship of the simulated cloud-top Nd, rather than NAd, with LWP, the result shows a much more nonlinear (positive and negative) relationship and is inconsistent with the satellite retrievals. However, the difference is much less pronounced when the sensitivity (Nd-LWP) is considered for shallow stratiform (adiabatic) than convective (sub-adiabatic) clouds. Comparing local vs large-scale statistics from satellite data shows that continental clouds exhibit only a weak nonlinear Nd-LWP relationship. Hence a regime-based Nd-LWP analysis is even more relevant when it comes to continental clouds and its comparison to satellite retrievals. 
Space-time simulation of storms and beyond!
Authors: Papalexiou Simon Michael , Serinaldi Francesco , Porcu Emilio
Published: March 2022

Simulating storms, or hydro-environmental fluxes in general, in space and time is challenging and crucial to inform environmental risk analysis and decision making under variability and uncertainty. Here, we advance space-time modelling by enabling simulation of random fields (RF) described by general velocity fields and anisotropy. This advances the skills of the Complete Stochastic Modeling Solution (CoSMoS) framework in space and time and enables RF's simulations that reproduce desired: (a) non-Gaussian marginal distribution, (b) spatiotemporal correlation structure (STCS), (c) velocity fields with locally varying speed and direction that describe advection, and (d) locally varying anisotropy. We demonstrate applications of CoSMoS by simulating storms at fine spatiotemporal scales that move across an area, spiraling fields such weather cyclones, air masses converging to (or diverging from) a point and more. The methods are implemented in the CoSMoS R package freely available in CRAN.

Reference: Papalexiou, S. M., Serinaldi, F., & Porcu, E. (2021). Advancing Space-Time Simulation of Random Fields: From Storms to Cyclones and Beyond. Water Resources Research, 57(8), e2020WR029466. https://doi.org/10.1029/2020WR029466
On the Similarity and Repeatability of Fast Magnetopause Shadowing Loss
Authors: Olifer Leonid , Mann Ian , Ozeke Louis , Claudepierre Seth , Baker Daniel , Spence Harlan
Published: March 2022

Properly characterizing fast relativistic electron losses in the terrestrial Van Allen belts remains a significant challenge for accurately simulating their dynamics. In particular, magnetopause shadowing losses can deplete the radiation belt within hours or even minutes but can have long-lasting impacts on the subsequent belt dynamics. By statistically analyzing seven years of data from the entire Van Allen Probes mission in the context of the last closed drift shell, here we show how these losses are much more organized and predictable than previously thought. Once magnetic storm electron dynamics are properly analyzed in terms of the location of the last closed drift shell, not only is the loss shown to be repeatable but its energy-dependent spatio-temporal evolution is also revealed to follow a very similar pattern from storm to storm. Employing an energy-dependent ULF wave radial diffusion model, we further show for the first time how the similar and repeatable fractional loss of the pre-storm electron population in each storm can be reproduced and explained. Empirical characterization of this loss may open a pathway toward improved radiation belt specification and forecast models. This is especially important since underestimates of loss can also create unrealistic sources in models, creating phantom electron radiation and leading to the prediction of an overly harsh radiation environment.
Transfer learning for estimating dynamic precipitation across different climate models
Authors: Kuettel Joel , Sippel Sebastian , Heinze-Deml Christina , Knutti Reto , Meinshausen Nicolai
Published: March 2022

Variations in the global water cycle are among the most impact-relevant consequences of climate change to human society. However, large uncertainties exist in regional precipitation trends due to the presence of internal variability, limited coverage of observational data, and model deficiencies. Dynamical adjustment methods have been developed to quantify the role of circulation-induced variability in relevant climate variables such as precipitation and temperature. By subtracting the latter, the thermodynamic signals are expected to remain in the residuals, therefore increasing the signal-to-noise (S/N) ratio of trend estimates. However, dynamical adjustment for high-resolution spatial and temporal data remains challenging, especially over heterogeneous terrain such as the Alps.

In this study, we build upon the Latent Linear Adjustment Autoencoder (LLAAE), a new statistical model introduced by Heinze-Deml et al., (2021, Geoscientific Model Development 14(8), pp. 4977-4999, doi:10.5194/gmd-2020-275.) that combines dynamical adjustment techniques with elements of deep learning. By combining a linear model with a nonlinear deep neural network, the method has shown great promise in extracting the forced thermodynamic components of high-resolution winter precipitation over Europe. So far, this model has only been trained and tested on different members of the Canadian Regional Climate Model (CanESM2). Here, we illustrate and evaluate the LLAAE in the context of transfer learning. The LLAAE, trained on 9 members of the CanESM2, is evaluated on 10 different high-resolution (EUR-11) Regional Climate Models of the EURO-CORDEX ensemble. We show, despite large climatological model differences, that the LLAAE is capable of reconstructing up to 50 % of the daily precipitation variance across the spatial domain of the CORDEX-data. Furthermore, trend estimates can be improved when retraining the linear model with relatively few additional data points from the target distribution: Retraining the model with 4000 individual days further increases the explained variance by about 30%, improving the S/N ratio of long-term and spatial trend estimates. This could be particularly useful for future real-world applications such as the detection and attribution of anthropogenic forced regional changes in precipitation and the contribution of the circulation-induced variability.
CME-learn: An interactive playground to benchmark CME databases for the time of arrival (ToA) prediction for using machine learning methods.
Authors: Tiwari Ajay , Camporeale Enrico , Del Moro Dario , Foldes Raffaello , Napoletano Gianluca , de Gasperis Giancarlo , Teunissen Jannis
Published: March 2022

Coronal mass ejections are one of the most significant drivers of space weather. The ToA predictions along with the Arrival speed of the CMEs are one of the crucial pieces of information for preparing for the possible geomagnetic storms. Geomagnetic storms can have adverse effects on several key components of modern society e.g. communications and electrical grids. The development of many machine learning methods provides us with the opportunity to use these tools in space weather applications. There have been several studies using machine learning methods for ToA predictions. In this study, we present an interactive dashboard to apply several machine learning methods (regression models) to test on the several CME databases used in the community. We also use this opportunity to benchmark various CME databases for TOA and CME arrival speed predictions. We also welcome the community to use this interactive dashboard as a tool to learn about machine learning.
Early greenup impact on seasonal streamflow and soil moisture dynamics
Authors: Hwang Taehee , Band Lawrence , Oishi A. Christopher , Scaife Charles , Kang Hojeong
Published: March 2022

Ongoing warming under climate change generally brought lengthened growing season and subsequent changes in evapotranspiration (ET) seasonality, but its implication in future freshwater regimes is not fully understood. In this study, we investigate how remotely sensed vegetation phenology information has correlated with seasonal flow patterns in the southern Appalachians over the last three decades. We characterize low-frequency seasonal peaks using cumulative 50 percentiles of daily precipitation, streamflow and soil moisture measurements, further related to long-term greenup anomalies in the study site. After removing a dominant precipitation control, the greenup anomalies show a significant correlation with spring flow peak timing at a low-elevation deciduous catchment. This indicates strong dependency of seasonal flow regimes on precipitation was mediated by warming-induced extended growing season, especially by early greenup. At a plot scale, similar correlations were found only at an upslope topographic position, which occupies most of forest landscapes within the catchment. Meanwhile, we found less significant correlations of the greenup anomalies on the flow percentiles at an adjacent evergreen and a high-elevation deciduous catchments. This suggests that early greenup in deciduous forests leading to early ET increases, in turn result in early soil moisture dry-down patterned by hillslope positions, and early seasonal streamflow declines given precipitation. Our study suggests that it is likely that spring flow peak timing in this region continue to be shifted earlier with time by warming-induced early greenup, which would have great implications for understanding future freshwater availability in the southeastern US. 
Aquifer Response Lag to Meteorological Droughts from GRACE Satellites
Authors: Paladino Brielle , El Kadiri Racha , Momm Henrique
Published: March 2022

Climate change increases the probability of drought occurrence in many parts of the United States and worldwide. Aquifer response to these drought events vary in space and time. This project seeks to understand the response of aquifers to drought events by quantifying the lag time between meteorological droughts and groundwater droughts using the Standardized Precipitation and Evapotranspiration Index (SPEI) and Gravity Recovery and Climate Experiment (GRACE) derived groundwater storage anomalies. Ten major aquifer systems in the continental United States were selected for analysis: Columbia Plateau, Arizona Alluvial, Snake River Basin, Upper Colorado, Pennsylvanian, Mississippi Embayment, Texas Gulf Coast, Edwards-Trinity Plateau, Floridian, Central California, and the High Plains Aquifer Systems. Groundwater storage anomaly data was derived from GRACE total water storage anomaly data by removing all other hydrologic components using the Global Land Data Assimilation System’s (GLDAS) Community Land Surface Model (CLM) of 1.0-degree spatial resolution monthly datasets. Timeseries on monthly intervals for both the derived groundwater storage and SPEI were created for the period of April 2002 to June 2021. Each selected aquifer system had a meteorological drought occur at least three times during the study period, with a maximum occurrence of fifteen in central California. There is a temporal gap in between the original GRACE mission and the launch of GRACE-Follow on (GRACE-FO) from June 2017 to June 2018, five of the ten selected aquifers had meteorological droughts occur in this gap, which have been excluded. Preliminary results indicate that the lag time between the start of the two types of droughts for these aquifer systems is between zero and one month, while the lag time between the end of these types of droughts is more widely varied, between zero and eight months. As these results are varied, contextualizing them with more in-depth looks at the aquifer system characteristics is important and is the next step in furthering our understanding of aquifer responses to the increasing number of probable drought events.
EMIC Waves Induced by the Enhancement of Solar Wind Dynamic Pressure and Subsequent Relativistic Electron Precipitation
Authors: Yan Yun , Yue Chao
Published: March 2022

Electromagnetic ion cyclotron (EMIC) wave plays an important role in precipitating relativistic electrons. In this study, we analyze an EMIC wave event on 6 November 2015 that extended over 6 hours in local time and the amplitude of this EMIC wave is about 3nT. Solar wind dynamic pressure enhancement excites EMIC waves, and whistler mode chorus waves are observed at the same time. When the EMIC wave occurs, the flux of relativistic electrons with pitch angle around 90° increases and the flux of small-pitch-angle relativistic electrons decreases. We calculate the electron PSD, which proves that EMIC wave leads to relativistic electron precipitation. Our result indicates that the large-amplitude EMIC wave will lead to nonlinear wave-particle interaction, thus leading to relativistic electron precipitation. When the wave amplitude is larger, the nonlinear wave-particle interaction becomes stronger.
Prediction of future sea-level rise in land suitability for mangrove rehabilitation and restoration in Indonesia
Authors: Syahid Luri Nurlaila , Ward Raymond D. , Sakti Anjar D. , Rosleine Dian , Wikantika Ketut , Windupranata Wiwin
Published: March 2022

Mangroves have many benefits, both for humans and for the surrounding ecosystem. One of the most benefits from mangroves is that mangroves have coastal blue carbon reserves up to five times greater than the total carbon storage of temperate, taiga, and tropical forests. But recently, mangroves have decreased in extent by 20-35% due to both anthropogenic and naturogenic factors. One of the naturogenic factors that impact mangroves is sea-level rise. Mangroves cannot survive if sediment accumulation cannot keep pace with sea-level rise. This can result in mangrove death or zonal shifts in plant communities.

The decline in mangrove areas has resulted in increases in carbon emissions. This increase in carbon costs $US6-24 billion in economic damage annually. Indonesia experienced the highest increase in carbon dioxide emissions in the world in 1990-2010. Whereas in the Paris agreement, 2015, countries in the world including Indonesia have committed to reducing emissions by 29-41% by 2030. Therefore, rehabilitation and restoration of mangroves need to be undertaken, as well as identification of those mangroves most under threat.

The aim of this study is to model future sea-level rise and the impact of its exposure on land suitability for mangrove rehabilitation and restoration in Indonesia. This study uses the integration of remote sensing, statistical, and future climate model data combined with GIS methods to produce a sea-level rise model. This study also uses several scenarios both climate and temporal to predict sea-level rise.

The results of this study indicate that there are several areas that have high exposure caused by sea-level rise. This is exacerbated by low rates of sedimentation or land subsidence in some areas. In contrast, several other areas experienced high rates of accretion and thus are at less risk. Changes in rates of inundation caused by sea-level rise have caused some areas suitable for planting mangroves to become unsuitable. Therefore, if planting is carried out in the area now, it is very likely that the mangrove will be submerged by excessive tidal inundation and any rehabilitation and restoration carried out will fail.

This study is expected to be taken into consideration in driving new policy based on the results of the model. This study can also be used as a guide to consider which areas are suitable for mangrove rehabilitation and restoration without the threat of a sea-level rise in the future.
Factors that control the isotopic composition of precipitation in northern Chile
Authors: Vázque-Suñe Enric , Valdivielso Sonia , Hassanzadeh Ashkan , Custodio Emilio , Criollo Rotman
Published: March 2022

The determination of aquifer recharge zones is necessary for optimal and sustainable management of water resources. Stable isotopes (δ18O and δ2H) are an effective tool to better understand the relationship between precipitation and groundwater. However, there are areas in the world such as northern Chile, where there is a lot of available isotopic information on groundwater but very heterogeneous isotopic information on precipitation. This study contributes to a better understanding of the spatial and meteorological variables that control the isotopic composition in precipitation in Northern Chile and to estimate these meteorological and stable isotopes in precipitation. Results show that in summer, the significant features for temperature, relative humidity and precipitation are altitude-latitude, latitude and altitude-latitude respectively. The stable isotopes of precipitation are controlled by temperature, altitude, latitude, longitude, and precipitation. The monthly estimation models of temperature, relative humidity and precipitation and three isotopic models (summer, winter and annual) are created based on the controlling features.