bluuebunny/crossref_metadata_2025 huggingface dataset:
Changing spatial patterns of convective rainfall across urban areas
Authors: Torelló-Sentelles Herminia , Marra Francesco , Peleg Nadav
Published: February 2023

Observations using remote sensing data reveal that urban areas affect the intensities and spatial structure of rainfall fields on small scales (i.e., at sub-hourly and sub-kilometer resolutions). However, there is currently disagreement regarding the precise pattern of change and the driving dynamic and thermodynamic forces behind it. As the hydrological response in urban areas is fast and highly sensitive to space-time rainfall variability, it is crucial to understand how urban areas change the intensity and spatial structure of rainfall to improve our abilities to nowcast rainfall and urban floods. We used high-resolution weather radar data to analyze the intensity, spatial structure, and motion of convective rainfall events that crossed several urban areas with diverse characteristics (e.g., Milan, Italy; Phoenix, US). We present an automatic methodology  (i.e., does not require an expert’s interpretation of rainfall fields) that can be applied to different urban areas worldwide. We first tracked convective rainfall events using a storm-tracking algorithm (from a Lagrangian perspective) and investigated changes to the properties of the rainfall fields (e.g., mean intensity, area, and intensity distribution profile) at varying upwind and downwind distances relative to each urban center. We also investigated changes to storms’ trajectories and to the frequency of storm initiations, terminations, splitting and merging events. We validated our results by repeating the analyses in control regions, that were adjacent to each study region and did not contain large urban areas within them. Our results show a general intensification of rainfall over cities, conserved spatial structures (instead of an expected weakening), as well as, increased storm initiations downwind of urban areas. Our findings also suggest that urban areas might be acting as barriers, by increasing storm terminations upwind of urban areas and deflecting incoming storms leftwards; possibly as a result of roughness-induced frictional turning.
CloudRoots-Amazonia22: Integrating clouds with photosynthesis by crossing scales
Authors: Vila-Guerau de Arellano Jordi , Hartogensis Oscar ,   CloudRoots and collaborators from Brasil and Germany
Published: February 2023

How are carbon dioxide assimilation by photosynthesis and (shallow) cumulus clouds connected? What is the local interaction between rainforest evapotranspiration and cloud formation modulated by incoming regional air masses? These interrelated questions were the main drivers of the experimental campaign CloudRoots-Amazonia22 that took place at the ATTO/Campina supersites in the pristine Amazon rainforest during August 2022 (dry season). CloudRoots-Amazonia22 collected observational data to derive relationships between leaf level processes to canopy scales and connected them to the diurnal evolution of the clear to cloudy atmospheric boundary layer. At leaf level, first results indicate a diurnal asymmetry of the leaf conductance with maximum openings before midday. These observations are related to radiative energy fluxes to study the partitioning into sensible and latent heating and of plant-soil carbon dioxide exchnages. By coupling measurements of carbon and water stable isotopologues by fast laser instruments to turbulence measurements we aim to quantify flux variations related to the radiation fluctuations driven by clouds. These observations are integrated with 75 soundings of state variables and greenhouse gas profiles taken by flights below, through and above the cloud layers. We investigate what controls the transition from shallow to deep convection and the causality between the surface-cloud shear and the moisture transport at the interface between the different atmospheric layers. The observational analysis is completed with conceptual modelling and systematic large-eddy simulation experiments, which include dynamic vegetation models to advance our understanding of the diurnal energy, water and carbon cycles over the Amazon rainforest.
Reassessing proposed paleo-tsunami deposits in Sweden
Authors: Smith Colby A. , Öhrling Christian
Published: February 2023

Claims of paleo-tsunami deposits in Sweden have existed for more than twenty-five years and often rely on sediments deposited at outer-shelf water depths during deglaciation.  The claims pre-date any significant knowledge of the effects of tsunamis in the offshore environment.  Given the large knowledge gains in this field in the past decade, a reassessment of the peer-reviewed claims of paleo-tsunami deposits in Sweden has been undertaken.

Deglaciation was undoubtably a period of higher-magnitude seismicity in Fennoscandia.  During this time, numerous pre-existing faults ruptured to the surface as a result of the combination of tectonic and glacio-isostatic stresses. The dimensions of the surface ruptures of these so-called glacially influenced faults (GIF) suggest earthquake magnitudes on the order of 6-8. Despite the increased seismicity associated with the rupture of GIFs, there are no known fault ruptures of sufficient dimensions to produce a high-intensity tsunami in the Baltic basin.

Given the bathymetry and tectonic setting of the Baltic, a significant tsunami is extremely unlikely.  Nevertheless, the peer-reviewed claims of paleo-tsunami deposits are considered in the context of the local Quaternary stratigraphy.  Three proposed events in Stockholm, Iggesund, and Forsmark are subjected to the same test.  Do the claims of paleo-tsunami deposits present a well-dated event stratigraphy that rules out alternate explanations of the same stratigraphy?  The dating is critical because it demonstrates that the deposits are the same age and thus widespread.

None of the proposed tsunami deposits meet this standard.  In Stockholm, the event layer consists of distorted varves and liquefaction features. The layer is undated and consistent with slumping, perhaps seismically induced. In Iggesund, the event layer includes liquefaction features, laminated sand, and distorted varves, overlain by an unconformity.  Again, the stratigraphy is undated and consistent with slumping.  Additionally, the geologic setting and unconformity are not adequately described. In Forsmark, the event stratigraphy is a regional unconformity in the post-glacial stratigraphy.  Previous workers have dated this unconformity at different elevations and determined that it is time transgressive and was formed during shoreline regression.  Thus, there is currently no credible evidence of paleo-tsunami deposits in Sweden.
Adapting Transfer Learning for Multiple Channels in Satellite Data Applications
Authors: Simumba Naomi , Tatsubori Michiaki
Published: February 2023

Transfer learning is a technique wherein information learned by previously trained models is applied to new learning tasks. Typically, weights learned by a network pretrained on other datasets are copied or transferred to new networks. These new networks, or downstream models, are then are then used for assorted tasks. Foundation models extend this concept by training models on large datasets. Such models gain a contextual understanding which can then be used to improve performance of downstream tasks in different domains. Common examples include GPT-3 in the field on natural language processing and ImageNet trained models in the field of computer vision.Beyond its high rate of data collection, satellite data also has a wide range of meaningful applications including climate impact modelling and sustainable energy. This makes foundation models trained on satellite data very beneficial as they would reduce the time, data, and computational resources required to obtain useful downstream models for these applications.However, satellite data models differ from typical computer vision models in a crucial way. Because several types of satellite data exist, each with its own benefits, a typical use case for satellite data involves combining multiple data inputs in configurations that are not readily apparent during pretraining of the foundation model. Essentially, this means that the downstream application may have a different number of input channels from the pretrained model, which raises the question of how to successfully transfer information learned by the pretrained model to the downstream application.This research proposes and examines several architectures for the downstream model that allow for pretrained weights to be incorporated when a different number of input channels is required. For evaluation, models pretrained with self-supervised learning on precipitation data are applied to a downstream model which conducts temporal interpolation of precipitation data and requires two inputs. The effect of including perceptual loss to enhance model performance is also evaluated. These findings can be used to guide adaptation for applications ranging from flood modeling, land use detection, and more.
Evaluation of Hargreaves method for calculation of reference evapotranspiration in selected stations of Slovakia
Authors: Rattayová Viera , Garaj Marcel , Kandera Mirowslav , Hlavčová Kamila
Published: February 2023

Evapotranspiration has an essential role in the hydrological cycle by affecting the volume of surface runoff and the amount of available water on the land. It is an input parameter for many hydrological models based on water balance; it is an important parameter for calculating agricultural land irrigation and water management. In the current hydrology, the role of evapotranspiration is increasingly important because of global warming and the increasing occurrence of drought. Many methods for evaluating drought are based on the value of Actual evapotranspiration, which is not directly measured, and data about this variable are not available from a national database. For this reason, the Reference evapotranspiration, which can be calculated from more frequently measured meteorological variables, is gaining in importance. FAO Penman-Monteith (P-M) method is a method for the calculation of Reference Evapotranspiration recommended by many international organizations and worldwide used by researchers like reference method in research. However, the high demand for required P-M method input meteorological parameters caused its difficult usability in the case of research covering large regions. For this reason, the methods less demanding on inputs for reference evapotranspiration calculation were derived. The accuracy of this method is necessary to verify in local conditions.This research aims to describe the spatial and temporal distribution of reference evapotranspiration and evaluate the Hargreaves method accuracy in the selected stations of Slovakia. The punctuality of the Hargreaves method showed a positive correlation with the increasing altitude of the Climatological station. The correlation coefficient of P-M and Hargreaves reaches more accuracy in comparing monthly values for all Climatological stations. The results bring information about the usability of the Hargreaves method in different conditions, which is mainly essential for hydrological modelling.This publication is the result of the project implementation: „Scientific support of climate change adaptation in agriculture and mitigation of soil degradation” (ITMS2014+ 313011W580) supported bythe Integrated Infrastructure Operational Programme funded by the ERDF; and was supported by the Slovak Research and Development Agency under Contract No. APVV-18-0347; and grant number VEGA 1/0782/21.
How to derive regional/global averages from sparsely sampled data
Authors: Schutgens Nick ,   AEROCOM modellers & AEROSAT retrieval specialists
Published: February 2023

Aerosol observations always suffer from limited sampling, be they in-situ or remote sensing measurements. This introduces representation errors when using these observations to derive regional estimates, or when using them to evaluate models. In the latter case, one can collocate the model data with the observations to alleviate the problem. The downside is that only part of the model data (the collocated part) can be compared to observations).We present a technique to homogenize observations (i.e. "remove" their limited sampling). In essence, this is possible because aerosol exhibits spatial and temporal correlations. In practice, we use models to provide this information. Here the technique is applied to satellite data.First we use synthetic observations to show that remaining representation errors due to this homogenization technique are below 10%. Next, we show that after applying this homogenization technique, estimates of regional AOD (or AAOD) from 14 (or 5) different observational datasets are far better in agreement than without homogenziation. Lastly, we present evidence that remaining differences in homogenzied (A)AOD in these daatsets is dominated by retrieval error.We also discuss the evaluation of AEROCOM models with these homogenized data. In particular, we highlight existing biases in modelled AAOD.Although we have not tried it yet, the technique should also be applicable to in-situ data.
Expression of Millennial Climate Events in the Central United States during the Last Glacial Period
Authors: Denniston Rhawn , Ummenhofer Caroline , Cresswell-Clay Nathaniel , Amber Gabriel , Asmerom Yemane , Polyak Victor , Wanamaker Alan , Thatcher Diana , Oeste Ryan
Published: February 2023

The nature of Late Glacial millennial-scale climate variability in the central United States is not well understood owing to a paucity of high-resolution, precisely-dated records in this region. Here we present a discontinuous, composite stalagmite record from Cosmic Cavern (36.4˚N, 93.5˚W), located on the southwestern margin of the Ozark Plateau in northwestern Arkansas, that preserves evidence of environmental change coincident with Greenland (inter)stadials and Heinrich stadials from 54-14 ka (marine isotope stages 3-2). Among the four stalagmites that comprise this record, carbon isotopes replicate well. Oxygen isotope ratios in three of the four stalagmites also exhibit robust replication, but in the fourth, oxygen isotope ratios are offset from coeval stalagmites by 1.5 permil, and thus this stalagmite was excluded from the composite record. Variability in stalagmite carbon and oxygen isotopes are broadly coincident with, and characterized by the same asymmetry as, the Greenland Ice Sheet Project Two (GISP2) oxygen isotope record; pronounced positive carbon and oxygen isotope anomalies also mark Heinrich stadials. Elevated carbon isotope values likely reflect reductions in soil respiration rates and increased CO2 out-gassing in voids above the cave during colder, and perhaps drier, stadials. Shifts in stalagmite oxygen isotope ratios are interpreted as reflecting variations in air temperature, consistent with modern temperature effects on precipitation oxygen isotope values documented over the course of a multi-year (and still on-going) precipitation monitoring program. We investigate the impacts of precipitation seasonality and moisture source on oxygen isotopic variability using Coupled Model Intercomparison Project phase 5 (CMIP5) simulations, namely the historical, pre-industrial, and Last Glacial Maximum simulations of the MIROC Earth System Model. Particular focus is placed on quantifying changes in moisture source and transport in the model simulations and the roles played by the North Atlantic subtropical high pressure system to the south and east, and precipitation derived from a Pacific moisture source to the west.
Subglacial drainage across Kamb Ice Stream’s Grounding Zone, West Antarctica.
Authors: Horgan Huw , Dunbar Gavin , Hulbe Christine , Schmidt Britney , Stevens Craig , Stewart Craig , Werder Mauro ,   KIS2 Science Team
Published: February 2023

Kamb Ice Stream in West Antarctica is a poster child for the natural variability of ice sheet flow. This major ice stream ceased flowing approximately 160 years ago and mass gain in its catchment currently offsets a significant portion of the mass loss occurring elsewhere in West Antarctica. Hypotheses explaining why Kamb shut down include changes in water routing at the ice stream bed. Here I report on our exploration of the main subglacial drainage channel crossing Kamb’s grounding zone and entering the ocean cavity beneath the Ross Ice Shelf. We find that the subglacial channel transitions into a large sub ice shelf channel. Oceanographic observations detect subglacial discharge within the channel, although the channel shape and surface elevation change suggest greater discharge rates in the past. Sediment coring of the channel substrate shows evidence of repeated high-velocity discharge events. The provenance of these sediments, combined with subglacial routing constraints indicate the subglacial catchment varies in time. Together with observations of surface change, these findings indicate that the subglacial hydrologic network beneath Kamb Ice Stream varies temporally, with background flow punctuated by fast flow events, and also changes spatially, spanning catchments of variable size.   
Greening the cities – Improving micro-scale thermal conditions and enhancing sustainable urban environments
Authors: Savić Stevan , Milošević Dragan , Dunjić Jelena , Krstić Hrvoje , Šećerov Ivan
Published: February 2023

To improve the urban environment in general and contribute to the greening of urban areas in the cities of Central and Southeastern Europe, an international project was implemented in the period 2019-2022. The GReENERGY project is an international/cross-border project that is implemented in Europe, with the aim to improve the environmental conditions in cities, i.e., in this case, the urban areas of Novi Sad (Serbia) and Osijek (Croatia). Therefore, the activities of the GReENERGY project aim to: a) encourage the production and consumption of green energy through the installation of new solar power plants in public buildings, and reduce the energy consumption from conventional sources that are the major emitters of CO2; b) highlight the installation of vertical and horizontal greenery (green roofs and walls) on public facilities as one of the nature-based solutions (NBS) that ensure increased energy efficiency of buildings; and c) help preserve the urban ecosystem and improve outdoor thermal comfort conditions on a microscale.The microclimate monitoring during the summer period and on hot days around a public building in Novi Sad (School for primary and secondary education “Milan Petrović”) showed that the thermal conditions are mainly driven by a combination of direct sunlight exposure or the presence of tree/building shadows. In our case, the differences in globe temperature (Tg) range from 6 °C to 10 °C during daytime at the micro-scale. A noticeable cooling effect caused by horizontal/vertical green areas is present during the night and based on datasets from our network this cooling effect is about 2 °C in Tg values.Finally, thanks to the GReENERGY project the AWS network was installed around the public building in Novi Sad, and further monitoring, analysis and research of datasets from the network and current microclimate conditions in Novi Sad is supported by a new regional project financed by Autonomous Province of Vojvodina (regional government).Finally, thanks to the GReENERGY project, an AWS network was installed around a public building in Novi Sad, and further monitoring, analysis and research of datasets from the network and current microclimate conditions in Novi Sad is supported by a new regional project financed by the Autonomous Province of Vojvodina (regional government).Acknowledgement: The research was supported by the project entitled: "Improving the environment in Vojvodina in order to adapt to climate change and reduce the risk of natural disasters" (no. 142-451-3161/2022-01) financed by the Autonomous Province of Vojvodina.
Soil properties and vegetation patterns four years after a wildfire and post-fire salvage logging treatment in a Mediterranean environment
Authors: Francos Marcos , Úbeda Xavier , Pereira Paulo
Published: February 2023

High-severity wildfires have a major impact on vegetation and soil properties. Moreover, recently burned areas are susceptible to extreme rainfall events and post-fire management. However, little is known about the impact of extreme rainfall and salvage logging on the relationship between soil properties and vegetal recovery and their spatial distribution. This study examines the effects of intense rainfall and post-fire management on soil properties and vegetal recovery and their spatial distribution in a small area using principal component analysis (PCA) medium-term after the fire. The vegetal recovery was measured using the index as Richness (S), Evenness (It), Density (D) and Diversity (H'). The soil variables studied were aggregate stability (AS), total nitrogen (TN), soil organic matter (SOM), inorganic carbon (IC), C/N ratio, calcium carbonates (CaCO3), pH, electrical conductivity (EC), available phosphorus (P), extractable calcium (Ca), extractable magnesium (Mg), extractable sodium (Na) and extractable potassium (K). Each PCA for vegetation and soil (one year after fire and four years after fire) allowed us to extract five factors and carry out the variograms with each factor for each moment. The preliminary results showed an increase in factors that mainly explain the results at the time four years after the fire compared to one year after. The PCA score maps illustrated a marked change in the spatial distribution of the variables one year and four years after the wildfire.
On the climatic influence of CO2 forcing in the Pliocene
Authors: Burton Lauren , Haywood Alan , Tindall Julia , Dolan Aisling , Hill Daniel ,   PlioMIP2 participants
Published: February 2023

The Pliocene (~3 million years ago) is of great interest to the palaeoclimate community as a potential palaeoclimate analogue for future climate change. It was the most recent period of sustained warmth above pre-industrial levels, was recent enough to have similar-to-modern continental configuration, and had similar-to-modern atmospheric CO2 concentrations around 400 ppm. If we are to use the Pliocene as a palaeoclimate analogue for our warmer future, it is important to consider the drivers of Pliocene climate change as well as its comparable large-scale climate features.  We implement a novel, simple linear factorisation method to assess the relative influence of CO2 forcing in Pliocene climate change compared to non-CO2 forcings such as changes to ice sheets, orography and vegetation. Outputs of this method are termed “FCO2” and reflect the relative influence of CO2, where 1 represents wholly dominant CO2 forcing and 0 represents wholly dominant non-CO2 forcing.The accuracy of the FCO2 method is evidenced by comparison to an energy balance analysis using a method previous used in Pliocene climate research, and the energy balance analysis also adds nuance to the FCO2 results and highlights feedbacks that arise from CO2 forcing.We apply the FCO2 method to seven models from the PlioMIP2 ensemble (CCSM4-UoT, CESM2, COSMOS, HadCM3, IPSLCM5A2, MIROC4m and NorESM1-F) which are found to be representative of the ensemble in terms of the modelled climate sensitivity and global mean surface air temperature anomaly.CO2 forcing is found to be the most important driver of surface air temperature change in six of the seven models (global mean FCO2 of ensemble = 0.56), and five of the seven models for sea surface temperature (global mean FCO2 of ensemble = 0.56). CO2 forcing is also the most important driver for precipitation change (global mean FCO2 of ensemble = 0.51), but spatial patterns in precipitation change are predominantly driven by non-CO2 forcings and the effects of these must not be overlooked.CO2 forcing being the most important driver of change in the climate variables considered here suggests that the Pliocene is a relevant analogue for our warmer future, but attention must also be paid to the significant effects of non-CO2 forcing in the Pliocene which may be less analogous to the present and near-term future.Our results also have implications for the interpretation of Pliocene proxy data and data-model comparison. For example, by assessing FCO2 in regions with large data-model discord it could become possible to highlight where the implementation of boundary conditions is largely responsible for the discord and, hence, where model boundary conditions should be modified. Given the spatial and latitudinal patterns seen in the FCO2 results, it may also be possible to suggest new sites from which additional proxy data would be most useful.
An integrated assessment framework for exploring resilience to climate extremes and nutrition security in Zambia
Authors: Jennings Stewart , Challinor Andrew , Smith Pete , Macdiarmid Jennie , Pope Edward , Bradshaw Catherine , Crocker Thomas , King Richard , Vetter Sylvia , Whitfield Stephen , Sarku Rebecca
Published: February 2023

Achieving climate-smart nutrition security in sub-Saharan Africa is an urgent challenge due to increasing climate risks to agricultural production, population growth and food price volatility This necessitates an integrated evidence base that takes into account not only future food system modelling but stakeholder knowledge and the plausible and desirable transformations that these information streams can provide. Accordingly, we use the integrated Future Estimator for Emissions and Diets (iFEED) to explore scenarios of food system transformation towards nutrition security in Zambia. iFEED integrates climate, crop and land use modelling to explore scenarios of relevance to the Zambian policy landscape, as informed by stakeholders. Four scenarios were defined by stakeholders, based on the extent of market connectivity and technological development, and the level of climate risk. Analysis of cross-scenario implications shows that diversification of agricultural production away from maize and towards more nutrient-dense foods is necessary to achieve nutrition security by mid-century, and that agricultural areas must expand unless yield improvements are faster than seen historically. These transformative changes could result in increased greenhouse gas emissions, which may be a necessary trade-off given the need to ensure nutrition security. We also present results from further analysis that shows how crop diversification and irrigation – both identified as key policy topic areas for Zambia – can contribute to building resilience in the face of increasing climate extremes. Results show that irrigation can help to reduce the interannual variability of food production by mid-century – and hence improve nutrition security in an increasingly volatile future climate. Crop diversification also helps to build resilience through crop risk-spreading, and also increases average production. Whilst these transformations are challenging to achieve, the alternative for a nutrition-secure future is to rely increasingly on imports, which would be economically and politically challenging given the large import increases required.
A comparative analysis of Holocene monsoon precipitation in the central highlands of Vietnam using hydrogen isotopic analyses of leaf wax n-alkanes
Authors: Pineda Linda , Doiron Kelsey , Stevens Lora , Brassell Simon
Published: February 2023

Understanding the effects of current climate change on water resources is of critical importance particularly in tropical regions where water availability is reliant on both the timing and intensity of monsoon precipitation.  Summer rainfall in Southeast Asia is directly influenced by the Bay of Bengal arm of the Indian Summer Monsoon. Based on numerous speleothem records, prevailing theory argues that compared with the late Holocene, the early Holocene experienced enhanced monsoon strength and thus greater rainfall due to greater summer insolation. However, recent modeling work and one preliminary multi-proxy record from Ia M’He, Vietnam suggest that monsoon rainfall in parts of mainland southeast Asia may be out of phase with monsoon trends in eastern Asia. The results of the modeling work and multi-proxy record suggest that unlike eastern Asia, monsoon precipitation in Vietnam is greater in the late Holocene relative to the early Holocene. To confirm the results of these data, a lake sediment core from the Central Highlands of Vietnam was used to reconstruct a record of precipitation using the hydrogen-isotopic values of n-alkanes in terrestrial leaf waxes. The objective of this research is to provide the first well-dated hydroclimate record for Vietnam and to test the proposed model of an out-of-phase relationship between SE Asia and surrounding monsoon trends.
Understanding the added value of the new generation of aerosol instruments for regional emissions estimations using Observing System Simulation Experiments (OSSE)
Authors: Lopez-Restrepo Santiago , Schutgens Nick , Houweling Sander , Segers Arjo , Tokaya Janot , Henzing Bas
Published: February 2023

The current generation of satellite sensors (such as AISI, CrIS, MOPITT, OMI, and POLDER) has a spatial resolution that is still too coarse for urban scale air quality monitoring or is not sensitive enough to the ground level. The Dutch S5p TROPOMI instrument has advanced significantly in studying reactive gases with daily coverage. With the upcoming launches of 3MI on MetOp-SG and SPEXone on NASA's PACE mission, remote sensing of aerosols will soon take a huge step forward. The infrastructure for air quality modeling will need to advance appropriately to get the most significant benefits from these technology expenditures.

In order to assimilate satellite data from atmospheric chemistry missions on reactive trace gases and aerosols, this effort will ultimately integrate the regional model LOTOS-EUROS fitted with a Local Ensemble Transform Kalman Smoother (LETKS) data assimilation module. The data assimilation algorithm will be put into practice with the ability to optimize surface emissions. All simulations are performed in the European domain to be used as inputs for future high-resolution simulations of urban dynamics in the Netherlands. Finally, following the main objective mentioned above, we develop OSSEs (Observing System Simulation Experiments) to benefit future satellite missions, understanding the opportunities and challenges these observations will bring.
An observational view of rainfall characteristics and evaluation of rainfall products in the Yarlung Tsangbo Grand Canyon, China
Authors: Chen Xuelong
Published: February 2023

The Yarlung Tsangbo Grand Canyon (YGC), one of the world’s deepest canyons, is located within the East Himalayas, which are remote and poorly instrumented. A rain‐gauge network was established around the YGC region. More than three years data collected from the network, disclose that the spatial pattern of rainfall distribution. There are two regions (500 m and 2500 m AMSL) with high precipitation in the YGC. Diurnal cycles showed some variations among sites, but a clear floor was visible around afternoon and peak values exhibited in the early morning. The monthly precipitation in the YGC region shows two peaks in April and July. Vertical convection and vapor transport are important for extreme rainfall in this region.GPM IMERG evaluation demonstrates that the data reasonably captured the observed seasonal and diurnal variations in the precipitation but with much weaker seasonal and diurnal variations compared with the gauge data. The GPM IMERG overestimated and underestimated the light and heavy precipitation, respectively, leading to a significant underestimation of the rainfall frequency and intensity at both the daily and monthly scales. Some possible mechanism for the underestimation was investigated to help scientists to improve the satellite precipitation product.Our observations indicate that ERA5 cannot reproduce the diurnal patterns of precipitation in the YGC region. ERA5 showed a wet bias when estimating light cumulus rainfall and a dry bias when estimating heavier (convective) precipitation. The erroneous diurnal variation of ERA5 precipitation (false afternoon rainfall) was due to the CAPE (Convectively Available Potential Energy)-based convective precipitation scheme. The higher ERA5 precipitation than observation was due to the large-scale rainfall scheme in the Integrated Forecasting System (IFS) of ERA5.These analysis have help us understanding the impacts of YGC valley on the water vapor transport and extreme rainfall outbreak mechanism.
DRivers and Impacts of Ionospheric Variability with EISCAT_3D (DRIIVE)
Authors: Kavanagh Andrew ,   DRIIVE Collaboration
Published: February 2023

EISCAT_3D provides an unprecedented opportunity to study key processes in the auroral latitude ionosphere across multiple scales.DRIIVE exploits the unique capabilities of EISCAT_3D to identify the key atmospheric and space weather drivers of variability in the ionosphere-thermosphere system, and to determine the impact of small-scale processes on thermospheric density and the satellite orbital environment.The project will identify the effects of lower atmosphere forcing and changes to local composition, while measuring energy input from space weather processes.  Findings on the impact of small-scale changes will be fed into the next generation of large-scale models, working closely with stakeholders across the space and atmosphere communities. DRIIVE involves 24 scientists from 19 UK institutes, partnering with international colleagues from 9 other countries.This poster provides an overview of the project science, key data sets and techniques that will be applied to advance our understanding of multi-scale processes in the ionosphere.
Gaps in network infrastructure limit our understanding of biogenic methane emissions
Authors: Malone Sparkle , Varner Ruth ,   Continental Methane Observatory
Published: February 2023

Understanding the biogenic sources and sinks of methane (CH4) is critical to both predicting and mitigating future climate change. Methane is 28-34 times more effective at trapping heat in the atmosphere compared to an equivalent mass of carbon dioxide over a 100-year time frame and accounts for ∼ 42 % of warming since the pre-industrial period. Biogenic sources are likely responsible for driving dramatic increases in atmospheric CH4 over the past decade, yet these are the least constrained and most uncertain fluxes in the global methane budget. A lack of long-term measurements across a variety of ecosystems has resulted in many unanswered questions about both the processes driving methane fluxes and how to scale these fluxes across space and over time. There is an urgent need to address these questions. With an atmospheric residence time of ~9 years, mitigating CH4 emissions has the potential to be an important global warming mitigation strategy. Here, we show how the current infrastructure to measure CH4 limits our ability to constrain the natural biogenic CH4 flux. Using dissimilarity, multidimensional scaling, and cluster analysis, the United States of America was divided into 10 clusters distributed across temperature and precipitation gradients. Through our analysis using climate, land cover, and location variables, we identified priority areas for research infrastructure to provide a more complete understanding of the CH4 flux potential of ecosystem types.
Copernicus services and data to support a sustainable and adaptive water resource management
Authors: Capolupo Alessandra , Barletta Carlo , Tarantino Eufemia
Published: February 2023

An effective, efficient, and sustainable allocation of resources has gained prominence on a global scale in recent years, taking into account far more than in the past the environmental needs of the ecosystems linked to them. Proper resource management and planning, as well as the detection of specific sustainable indicators, are required to respond to increasing demand while keeping in mind that its increase corresponds to a gradual reduction in the availability and usability of resources, which is also a result of climate change. This becomes even more important when the resource under consideration is water, which is essential for human survival and well-being as, after all, agricultural production. In comparison to other European countries, Italy has an abundance of meteoric inflows, albeit unevenly distributed across its entire territory. Because of this, the Italian country is particularly vulnerable to water crises, which are becoming more common, particularly in South Italy. The management of water resources, which is already complex, becomes even more so when dealing with scarcity situations, an area in which it is critical, to begin with the cognitive assumption of hydrological balance. Remote Sensing (RS) approaches are essential for investigating and assessing water bodies, meteoric inflows, and water balance parameters, allowing for effective surface water management support. RS is widely used for the aforementioned purposes due to the increasing availability of novel medium-high-resolution remote sensing big data, as well as Copernicus services and data related to water management (https://climate.copernicus.eu/water-management). Thus, the goal of this study is to take a "snapshot" of the current state of natural water resource availability in the Apulian region by extracting and estimating the main hydrological balance components introduced by the BIGBANG model (Braca et al., 2021) by exploiting Copernicus services and freely available medium-high resolution satellite data. Following the collection of all necessary input data, such as high-resolution Digital Elevation Model (DEM), Corine Land Cover maps, remote sensing-based soil sealing maps, mean monthly air temperature and rainfall, Google Earth Engine (GEE) environment, a free cloud platform recently released by Google to manage big geospatial data, were used to handle and estimate the main hydrological balance components. The proposed approach, based on the integration of Copernicus services and the BIGBANG model, appears as a useful and operational tool for supporting sustainable and adaptive resource management activities, particularly in water crisis situations. In fact, it allows extracting trustworthiness water balance components quickly. 
Combining Object-Oriented and Deep Learning Methods to Estimate Photosynthetic and Non-Photosynthetic Vegetation Cover in the Desert from Unmanned Aerial Vehicle Images with Consideration of Shadows
Authors: He Jie , Lyu Du , He Liang , Zhang Yujie , Xu Xiaoming , Yi Haijie , Tian Qilong , Liu Baoyuan , Zhang Xiaoping , Gomez Jose Alfonso , Krasa Josef , Dostal Tomas , Laburda Tomas
Published: February 2023

Soil erosion is a global environmental problem.  The rapid monitoring of the coverage changes in and spatial patterns of photosynthetic vegetation (PV) and non-photosynthetic vegetation (NPV) at regional scales can help improve the accuracy of soil erosion evaluations.  Three deep learning semantic segmentation models, DeepLabV3+, PSPNet, and U-Net, are often used to extract features from unmanned aerial vehicle (UAV) images;  however, their extraction processes are highly dependent on the assignment of massive data labels, which greatly limits their applicability.  At the same time, numerous shadows are present in UAV images.  It is not clear whether the shaded features can be further classified, nor how much accuracy can be achieved.  This study took the Mu Us Desert in northern China as an example with which to explore the feasibility and efficiency of shadow-sensitive PV/NPV classification using the three models.  Using the object-oriented classification technique alongside manual correction, 728 labels were produced for deep learning PV/NVP semantic segmentation.  ResNet 50 was selected as the backbone network with which to train the sample data.  Three models were used in the study;  the overall accuracy (OA), the kappa coefficient, and the orthogonal statistic were applied to evaluate their accuracy and efficiency.  The results showed that, for six characteristics, the three models achieved OAs of 88.3–91.9% and kappa coefficients of 0.81–0.87.  The DeepLabV3+ model was superior, and its accuracy for PV and bare soil (BS) under light conditions exceeded 95%;  for the three categories of PV/NPV/BS, it achieved an OA of 94.3% and a kappa coefficient of 0.90, performing slightly better (by ~2.6% (OA) and ~0.05 (kappa coefficient)) than the other two models.  The DeepLabV3+ model and corresponding labels were tested in other sites for the same types of features: it achieved OAs of 93.9–95.9% and kappa coefficients of 0.88–0.92.  Compared with traditional machine learning methods, such as random forest, the proposed method not only offers a marked improvement in classification accuracy but also realizes the semiautomatic extraction of PV/NPV areas.  The results will be useful for land-use planning and land resource management in the areas.
Climate variability, droughts, and temporal yield stability in Ethiopia
Authors: Menesch Joseph , Waha Katharina , Godde Cecile , Venables William , Renard Delphine , Richardson Anthony , Cobelli Oceane
Published: February 2023

Climate variability threatens food system stability, particularly among smallholders in developing countries who depend on rainfed agriculture. Drought and shifts in the onset of the rainy season are typical events in Ethiopia and there were at least three major droughts in the last decade.

In this study, we aim to explore relationships between climate variability, agricultural diversity, and crop yield stability. The stability of food production is an important dimension of food security but less often studied than other dimensions due to the lack of multi-year microdata for households or individuals. Farm diversification could be a relevant adaptation strategy in this context as a greater number of species or a more even distribution of crops is postulated to have a stabilizing effect on farm output as compared to a homogeneous farm.

We use agriculture-focused panel data from Ethiopia’s Socioeconomic Survey over four waves from 2011 to 2018, CRU TS v4.05 1901-2020 and CHIRPS 1981-2019 to derive measures of climate variability, drought frequency and crop yield stability. In a twofold analytical approach, we use mixed effects models to separately model i) farm richness and pastoralism prevalence with climate variability as predictors, and ii) crop yield stability with diversity, farm input, and climate characteristics as predictors.

We find that temporal yield stability calculated from 23 crops commonly grown in Ethiopia is quite low at on average 2-3 kcal/ha, which means that the temporal mean yield is only 2-3 times the standard deviation over the same time. Long-term climate variability significantly affects the type of farming system, mixed or specialized with pastoralism more prevalent in the drier areas with larger rainfall variability. The frequency of past droughts had a positive effect on yield stability, although it was not a significant effect. Temperature variability, precipitation variability and the average temperature and rainfall in the wettest 3-months had a negative effect on yield stability, but it was not a significant effect either. Yield stability was most strongly and positively associated with farm diversity and the ratio of harvested to planted area which is a measure of crop failure. The effects were greater than from irrigation, fertilizer use and pesticide usage.

Together, these findings suggest that shifts in typical ranges of climate variability could destabilize farm-level crop yield for smallholders by limiting diversification opportunities. Our findings highlight the need for researchers and policymakers to consider not only the direct effects of climate variability on crop yield, but also its indirect effects on yield stability caused by increasingly limited adaptation choices.
Exploring links between the North Atlantic Igneous Province and Paleocene–Eocene climate change using sedimentary mercury
Authors: Frieling Joost , Mather Tamsin , Jones Morgan , Fendley Isabel , Xu Weimu , Berndt Christian , Planke Sverre , Alvarez Zarikian Carlos ,   IODP Expedition 396 scientists
Published: February 2023

The North Atlantic Igneous Province (NAIP), a large igneous province (LIP), was emplaced between ~62 and 50 million years ago (Ma), with a voluminous burst of volcanic activity centred around 56-54 Ma. Global paleoclimate reconstructions from this Paleocene and Early Eocene interval indicate progressively warmer conditions, with several superimposed warming events or ‘hyperthermals’, such as the Paleocene–Eocene Thermal Maximum (PETM; 56 Ma). These hyperthermals represent transient massive perturbations to the carbon cycle, marked by substantial global warming, ocean acidification and negative stable carbon isotope excursions. International Ocean Discovery Program Expedition 396 to the Mid-Norwegian continental margin recovered a suite of Paleocene–Eocene sedimentary and igneous materials. This notably includes a unique and extremely expanded succession comprising of up to ~80m of PETM (ash-rich) sediments and volcanic ash layers infilling a hydrothermal vent crater. The craters on the Mid-Norwegian margin and similar structures associated with other LIPs were previously identified as surface expressions of a potent carbon release mechanism: the venting of thermogenic carbon generated in the thermal aureoles around volcanic dikes and sills intruded into the underlying sedimentary basins.In recent years, much progress has been made towards understanding the role of deep earth processes and particularly LIP volcanism on paleoclimate through the application and refinement of proxies as sedimentary mercury (Hg) content. Large scale and especially LIP volcanism are considered important Hg emitters that may result in increased sedimentary Hg content. Here, we present high-resolution bulk sedimentary Hg content data from the sedimentary strata within the hydrothermal crater, spanning the PETM. We use our new data with biostratigraphic, stable carbon isotope, and lithological constraints, to shed light on the timing of hydrothermal crater formation, duration and re-activation of hydrothermal activity within the crater after formation. Finally, these new findings are placed in a global Hg and carbon cycle framework to assess the timing, characteristics, and impact of NAIP activity during the PETM.
Uncertainty quantification for mantle convection models
Authors: Burkhart Andreas
Published: February 2023

In the field of geophysics and geoscience in general many properties of the earth are difficult to measure or deduce and available information is often fraught with uncertainties. It is therefore important to understand how these uncertainties affect and propagate through geophysical models.
Focusing on the topic of compressible mantle convection there are many uncertainties at play, most notably the viscosity, temperature and chemical composition of the earth's interior. Another topic of interest are the plate movement reconstructions used as boundary conditions for mantle convection models.
Starting with the implementation of a robust numerical simulation of compressible mantle convection (notably including mineral phase transitions) suitable for high performance computing, we aim to understand and quantify the forward and backward uncertainties of mantle flow evolution.