bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of morphology on the spatial variability of rainstorms over Italy
Authors: Mazzoglio Paola , Butera Ilaria , Alvioli Massimiliano , Claps Pierluigi
Published: March 2022

The investigation of the influence of terrain morphology on rainfall extremes has never been conducted over the entire Italy, where some studies have been carried out over limited areas. We then present the first systematic investigation of the role of elevation and other morphological attributes on rainfall extremes over Italy, that is made possible by using the Improved Italian – Rainfall Extreme Dataset (I2-RED). I2-RED is a database of short duration (1 to 24 hours) annual maximum rainfall depths collected from 1916 until 2019 by more than 5200 rain gauges.

The analyses involved the relations between morphology and the mean annual rainfall extremes (index rainfall) using univariate and multivariate regressions. These relations, built countrywide, demonstrated that the elevation alone can explain only a part of the spatial variance. The inclusion of regression covariates as longitude, latitude, distance from the coastline, indexes of obstructions and the mean annual rainfall depth demonstrated to be significant in relations built at the national scale.

However, high local bias with notable spatial correlation derives from the national-scale analysis. This led us to focus on smaller areas. We started dividing Italy into 4 main regions: the Alps, the Apennines, and the two main islands (i.e. Sicily and Sardinia). A dedicated multiple linear regression analysis was conducted over each of these areas. Evident improvements were obtained through this approach; nevertheless, clusters of high residuals persisted, especially in orographically-complex areas. A different approach was then undertaken, based on a preemptive subdivision of Italy in morphologically similar regions, to both reduce the clustering of errors and better define the role of elevation. Using four morphological classifications of Italy from the literature, we applied simple regression models to the rain gauges available inside each region. Among all, the classification that embeds hydrological information turned out to produce the best results in terms of local bias, MAE and RMSE, outperforming the multivariate relations obtained at the national scale. This approach proved to better reproduce the effects of geography and morphology on the spatial variability of rainfall extremes.

Our analysis confirmed a general increase of 24-hour rainfall depths with elevation, as already pointed out by studies conducted over smaller areas. For 1-hour rainfall depths, in flat or in pre-hill zones a modest increase with elevation is visible, while over the Alps and in most of the Apennines a reverse orographic effect (i.e., a reduction of rainfall depth with increasing elevation) is clearly detected, confirming previous outcomes in those areas.
Arctic Mixed-Phase Clouds Sometimes Dissipate Due to Insufficient Aerosol - Evidence from Idealized Large Eddy Simulations
Authors: Sterzinger Lucas , Sedlar Joseph , Guy Heather , Neely III Ryan , Igel Adele
Published: March 2022

Aerosol concentrations in the Arctic can get quite low, and recent work has shown that low aerosol concentrations could affect Arctic cloud formation and structure. Arctic mixed-phase clouds have been observed to persist for days at a time and dissipate suddenly, and it has been hypothesized that some instances of cloud dissipation are caused by aerosol concentrations falling below some critical value required to sustain the cloud.

We found three cases - from a Department of Energy ARM site on the north slope of Alaska, the ICECAPS-ACE project at the NSF Summit Station in Greenland, and the ASCOS field campaign - where clouds are observed to dissipate coincidentally with a drop of surface aerosol concentration. These cases were used to initialize idealized large eddy simulations in which aerosol concentrations were held constant at observed values before being immediately removed. The resulting simulations are considered to be the fastest possible aerosol-limited dissipation. Comparing simulated liquid water path (LWP) to observations, we find that the ARM case dissipated much faster than our simulations, indicating that the observed dissipation was not driven by lack of available aerosol. The Summit Station and ASCOS simulations dissipate (with respect to LWP) at approximately the same rate as observations, which suggests aerosol-limited dissipation may indeed be occurring in these cases.

Furthermore, we find that the microphysical response to aerosol removal varies between the specific cases we simulate. Simulations where the cloud produces constant liquid drizzle dissipate, within 3-4 hours,  via an acceleration of precipitation once aerosols are removed. Conversely, the case with a non-precipitating liquid layer dissipates more quickly (< 2 hours), possibly by glaciation via the Wegener-Bergeron-Findeisen (WBF) in which ice grows and precipitates at the expense of liquid droplets. The simulations suggest that aerosol-limited dissipation in the Arctic is plausible, and we present two microphysical pathways by which this dissipation can occur.
A New Statistical Reduced Complexity Climate Model
Authors: Bennedsen Mikkel , Hillebrand Eric , Koopman Siem Jan
Published: March 2022

In this paper, we propose a new, fully statistical, reduced complexity climate model. The starting point for our model is a number of physical equations for the global climate system, which we show how to cast in non-linear state-space form. The resulting model incorporates measurement errors, capturing the fact that observations of physical quantities might be contaminated by error, as well as internal stochastic error processes, capturing the fact that the physical equations used are approximations to the true underlying  climate system. The state-space formulation allows for statistical estimation of the parameters in the model, using the method of maximum likelihood, as well as filtering and smoothing of latent quantities in the model, such as ocean and surface temperatures. Further, the explicit statistical formulation of the model allows for conducting a number of useful analyses, such as the estimation of parameter uncertainty, model selection, and probabilistic scenario analysis. 

 

By considering a range of different scenarios for greenhouse gas emissions, we set up simulation studies that can be used to investigate  the effect that a given scenario has on parameter estimates. We find substantial differences in the performance of the estimation procedure, depending on the precise scenario considered. These investigations can help decide what kind of data are best suited for estimating/calibrating the parameters of reduced complexity climate models, e.g. to what extend the historical data record can be used to reliably estimate parameters and/or which CMIP experiments are best suited for calibrating such models.

 

Using a data set of historical observations from 1959-2020, we estimate the model and report key parameter estimates and associated standard errors. A likelihood ratio test sheds light on the most appropriate equation for converting the atmospheric concentration of carbon dioxide (GtC) into forcings (W/m2). We then use the estimated model and assumptions on future greenhouse gas emissions to project global mean surface temperature out to the year 2100. The statistical nature of the model allows us to attach uncertainty bands to the projections, as well as quantify how much of the uncertainty is "aleatoric" (uncertainty arising from the internal variability of the climate system) and how much is "epistemic" (uncertainty arising from unknown model parameters). We find that epistemic uncertainty is by far the most important contributor to the uncertainty on the projected future global temperature increase.
Combined storm and meteotsunami hazards: Data analysis and numerical simulation of Christina (Jan. 2014) and Leslie (Oct. 2018) events on the coast of Portugal
Authors: Kim Jihwan , Omira Rachid , Dutsch Cora
Published: March 2022

Two hazardous storms, Christina (January 2014) and Leslie (October 2018), destructively affected the coast of Portugal and generated extreme sea level variations. We analyzed both the sea-level and meteorological data, and performed numerical simulations to examine the observed wave-induced coastal hazard and identify the background harbor resonances at each port. The results revealed that the sea-level variation is affected by the combined effect of low-frequency sea level rise (surges) and high-frequency (HF) waves. For the 2014 event, we found that wind was the main source of the HF sea surface variation, which excited the background harbor resonance. For the 2018 event, storm surges were significantly stronger and HF amplitudes were mostly induced by the movement of a pressure jump, leading to a meteotsunami formation. Commonly, wind is considered as a principal factor of the storm-generated HF waves, but we show herein  that the atmospheric pressure jump can play an important role in their formation through meteotsunami. The latter, when combined to a storm surge, can cause serious impact on the threatened coastal areas. 
Flow changes in the wake of a large sediment wave: helping to understand geological and ecological impacts of seabed infrastructure.
Authors: Van Landeghem Katrien , Unsworth Christopher , Austin Martin , Waggitt James
Published: March 2022

During this pivotal time of energy transition, it is of crucial importance to unlock the potential of the seabed for offshore energy conversion and electrical power transport. With the construction of ever larger offshore windfarms plus other coastal infrastructure, a better understanding of the interactions between the infrastructure and the flow, the flow and the seabed, and all the above with marine life has never been more pressing, as they define feasibility and sustainability of the offshore projects. 

To better understand the dynamics of the flow in the wake of a large object, the School of Ocean Sciences at Bangor University deployed a bed frame with an Acoustic Doppler Current profiler in the wake of a 10 m-high and steep-crested sediment wave on a seabed 60 meters deep. Vessel-mounted ADCP data was collected simultaneously in orthogonal transects. Velocity profiles near the seabed diverge from the standard law of the wall. On the flood tides, when the flow interacted with the large bedform, increased turbulence in the water column vertically mixed the suspended sediments (measured via the ADCP) into a vertically uniform suspension. On the ebb tides, without any interactions with the bedform, the backscatter shows a boundary layer bursting structure.  

The enhanced turbulence can affect the sediment composition and bed mobility in these large wakes whether they are natural or anthropogenic, and to numerically model these effects is complex. We discuss the wider impacts of this work, as changes to sediment, seabed and water column properties can affect aggregations of prey that crucially depend on it. These changes can then extend through the food chain and contribute to the ecological impacts of windfarms, both as risks and as opportunities.
Compounding Wet and Cold-Extremes driven by an increasing Pan-Atlantic wave-4-pattern 
Authors: Kornhuber Kai , Messori Gabriele
Published: March 2022

Wintertime extremes such as cold spells and heavy precipitation events can have severe societal impacts, disrupting critical infrastructures, traffc and affecting human well-being. Here, we relate the occurrence of local and concurrent cold and wet wintertime extremes in North America and Western Europe to a recurrent, quasi-hemispheric wave-4 Rossby wave pattern in the Jetstream. We identify this pattern as a fundamental mode of Northern Hemisphere (NH) winter circulation exhibiting phase-locking behavior as the associated atmospheric circulation and surface anomalies re-occur over the same locations when the pattern's wave amplitude is high. The wave pattern is strongest over the pan-Atlantic region, and is associated with an increased probability of extreme cold or wet events by up to 300 % in certain areas of North America and Western Europe. We identify a significant increase in frequency over the past four decades (1979- 2021), which we hypothesise may derive from increased convective activity in the tropical Pacific, from where the pattern originates, while a weakened meridional temperature gradient linked to Arctic warming appears to have no direct effect on its occurrence. The identified pattern and its remote forcing might provide pathways for early prediction of local and concurrent cold or wet wintertime extremes in North America and Western Europe.
The potential of coralline algae as SST proxy and for climate model evaluation: A New Zealand case study
Authors: Kropač Elena , Mölg Thomas , Teichert Sebastian
Published: March 2022

General circulation models (GCMs) are currently the most important tools for obtaining projections about future climate. In addition, they provide data input for regional atmospheric models that translate global climate change to regional and local scales where humans and environments face the impacts. To ensure the accurateness of their simulations, GCMs need to be evaluated as thoroughly as possible against past climate records, where one focus is on the so-called "historical period" (1850–present). However, the evaluation task is difficult for the period before World War II and earlier due to a frequent lack of reliable observations. This problem is exacerbated for the Southern Hemisphere, which has been notoriously understudied in comparison to the climate of the Northern Hemisphere.

In New Zealand, variations in sea surface temperature (SST) are reflected on a variety of spatial and temporal scales and are statistically detectable through to temperature anomalies and glacier mass balance changes in the high mountains of the Southern Alps. The correct simulation of SST by GCMs is therefore crucial, especially when investigating the physical mechanisms that transform large-scale SST signals into local climate anomalies by using regional atmospheric modeling.

In the project “NZ-PROXY”, we utilize crustose coralline algae (CCA) – a rather recently discovered proxy archive – to extend the observational time series of SST in the New Zealand region back to ~1850. The SST reconstruction is then employed in GCM evaluation to reveal their skill in representing the large-scale climate of New Zealand. Finally, high-resolution sensitivity simulations are obtained from a regional atmospheric model to investigate the added value of the advanced GCM selection for regional climate modeling.
Flood Forecasting With LSTM Networks: Enhancing the Input Data With Statistical Precipitation Information
Authors: Morgenstern Tanja , Grundmann Jens , Schütze Niels
Published: March 2022

Reliable forecasts of water level and discharge are necessary for efficient disaster management in case of a flood event. The methods of flood forecasting are rapidly developing, part of this being artificial neural networks (ANN). These belong to the data-driven models and therefore are sensitive to the quality, quantity and relevance of their input and training data.

Previous studies at the Institute of Hydrology and Meteorology at the TU Dresden used both hourly discharge and precipitation time series to model the precipitation-runoff process with ANN, e.g. Deep Learning LSTM networks (Long Short-Term Memory – a subcategory of ANN). The precipitation data were derived of area averages of radar data, in which the spatial structure of the precipitation and thus important information for rainfall-runoff modelling is lost. This is a problem especially for small-scale convective rainfall events.

As part of the KIWA project, we carry out a study with the aim of improving the reliability of flood forecasts of our LSTM networks by supplementing the input data with statistical precipitation information. For this purpose, we are adding statistical information such as area maximum and minimum of precipitation intensity, as well as its standard deviation over the area, to the area mean values of precipitation from the hourly radar data.

As this information contains details on the precipitation intensity distribution over the area, we expect an improvement of the discharge prediction quality, as well as an improvement of the timing. In addition, we expect the LSTM network to learn from the statistical information to better assess the relevance and quality of the given precipitation values and to recognize the spatial uncertainties inherent to the area means. The resulting knowledge of the network should now enable it to forecast the discharge while communicating information on the uncertainty of the current discharge forecast.

We present the preliminary results of this investigation based on small pilot catchments in Saxony (Germany) with differing hydrological and geographical characteristics.
The Albedo-Ablation couple: a complex relationship with severe consequences
Authors: Naegeli Kathrin , Barandun Martina
Published: March 2022

Glaciers in Central Asia provide essential water resources for an increasing socio-economic water demand. However, glacier ablation is spatio-temporally highly heterogeneous, revealing hot-spots of the complex glacier response to climate change. A darkening of glacier surfaces caused by varying sources ranging from light absorbing mineral particles and black carbon to organic matter such as algal bloom, impacts the surface energy balance of glaciers. The albedo of the bare-ice surface is particularly crucial in regard to the ablation magnitude.

In this study, we present across scale results of the dependence of glacier mass balance on surface albedo for a large number of glaciers in the Tien Shan and Pamir Mountains. We used over 3000 surface reflectance scenes from the Landsat suite over the last two decades to produce distributed albedo maps. Annual mass balance time series are modelled using a temperature-index and distributed accumulation model for each glacier and year individually. The modelled estimates are annually calibrated with transient snowlines and further constrained by multiyear geodetic mass balances.

A comprehensive analysis of albedo variability and trends is performed at varying scales, ranging from pixel to catchment. A relationship between the distributed albedo information and the detected trends with the mass balance rates and variabilities is established. We highlight the sensitivity of glacier mass balance on surface albedo and stress the importance of the enhanced albedo feedback that will be amplified due to atmospheric warming and suspected darkening of glacier surfaces in the near future. This feedback will accelerate glacier melt and thus put the availability of melt water to river run off at sustainable risk. 
Evaluating urban risks in Europe using publicly available continental-scale data
Authors: Li Zeting , Mill Gerald , Demuzere Matthias , Bechtel Benjamin
Published: March 2022

Cities are major drivers of climate change and are especially at risk from projected changes, such as more frequent and enhanced flood and heatwave events. Many of these hazards are elevated for cities because of their topographic settings (e.g., low-elevation and close to coasts) and urban layout (e.g., impervious fraction), the details of which are unique to each city. While there have been studies of the impact of climate change on cities, these have generally examined exposure in individual cities to projected changes or of urbanized landscapes to one change, such as sea-level rise. This research uses the Local Climate Zone (LCZ) map of Europe as a framework to examine city-based mitigation and adaptation options at a continental scale. The LCZ scheme describes types of urban landscapes and their physical properties that can be used to assess degrees of hazard exposure. These data will be combined with other publicly available geographic datasets on projected climate changes, topography, population, greenhouse gas emissions, etc., to provide a large-scale evaluation of urban risk and responses.
Evaluating the relative contribution of stratospheric and tropospheric drivers for the North Atlantic jet response after sudden stratospheric warmings
Authors: Gerstman Hilla , Jimenez-Esteve Bernat , Domeisen Daniela I.V.
Published: March 2022

Sudden stratospheric warmings (SSWs) are extreme stratospheric events which can be followed by a significant impact on surface weather. Roughly two thirds of the observed SSW events are followed by an equatorward shift of the tropospheric midlatitude jet in the North Atlantic, while a third of the events generally show a poleward jet shift. However, it is not yet resolved which factors lead to the large inter-event variability in the surface impact.

Here, the sensitivity of the North Atlantic jet response to stratospheric forcing is investigated using an intermediate complexity atmospheric model. We analyze the contribution of different stratospheric and tropospheric drivers for determining the downward response, focusing on persistent anomalies in the lower stratosphere, downstream influence from the northeastern Pacific, and local tropospheric conditions in the North Atlantic at the time of the initial response. Both the model and reanalysis show that most of the variance in the tropospheric jet response after SSW events can be explained by the lower stratospheric geopotential height anomalies. To isolate the role of the stratosphere from tropospheric variability, we use model runs where the zonal mean stratospheric winds are nudged towards climatology. When stratospheric variability is suppressed, the coupling between the North Atlantic and the northeastern Pacific is found to be weaker. 

These findings shed light on the relative contribution of the stratosphere and the troposphere to the diverse downward impacts of SSW events. The implications of these results for improved long-range prediction of tropospheric jet variability the North Atlantic will be discussed.
Analysis of ensemble forecasts over successive forecast lead times for decision support in flood management
Authors: Grundmann Jens , Philipp Andy
Published: March 2022

Reliable warnings and forecasts of extreme precipitation and resulting floods are an important prerequisite for disaster mangers to initiate flood defence measures. Thus, disaster managers are interested in extended lead times, which can be obtained by employing forecast of numerical weather models as driving data for hydrological models. To portray the inherent uncertainty of weather model output, ensemble hydro-meteorological forecasts can be used, which offers the opportunity of probability based decision making for disaster managers. However, especially for changing weather systems under unstable atmospheric conditions and for small, fast-responding catchments, the signals of extreme precipitation in the forecasting models may change quickly in magnitude and ensemble spread for successive forecast in expectation of an approaching event.

With this contribution, we analyse the behaviour and reliability of ensemble hydro-meteorological forecasts depending on their lead time in order to derive appropriate indicators for decision making. We use results of our operational web-based demonstration platform for ensemble hydrological forecasting in small catchments, which is established for three pilot regions with different hydrological settings in Saxony, Germany. The demonstration platform processes ensemble forecasts of the ICON/COSMO-D2-EPS product of the German Weather Service, which provides an ensemble of 20 members each three hours, for lead times up to 27 hours.  Each member is evaluated regarding specific extreme precipitation thresholds. If these thresholds are exceeded in a specific region, rainfall-runoff models for the associated catchments are used to propagate the meteorological uncertainty into the resulting runoff, followed by statistical post processing and visualization. In addition, different options for the visualization of the uncertainty information were developed to monitor the behaviour and reliability of the forecast ensemble over successive forecast lead times. These options contain exceedance probabilities for thresholds in rainfall and resulting runoff and were discussed with decision makers regarding their applicability for decision making. First results are presented for observed extreme events in the small pilot regions.
Using EisNet to Extract Bedrock and Internal layers from Digital and Analog Radiostratigraphy in Ice Sheets 
Authors: Dong Sheng , Tang Xueyuan , Fu Lei
Published: March 2022

The radar detection of bedrock interface and internal ice layers is a widely used technique for observing interiors and bottoms of ice sheets, which is also an important indicator of inferring the evolution of glaciers and explaining subglacial topographies. The conventional methods, such as the filtering denoise, are limited by the low contrast in ice radar image with noise and interferes and thus the automatic method in tracing and extracting layers' features is trapped. The manual and semiautomatic methods are widely applied but with large time-consuming especially for the large-scale radar image with continuous bedrock and internal layers. To extract and identify the bedrock interface and internal ice layers automatically, we propose EisNet, a fusion system consisting of three sub neural networks. Because of the limitations of conventional manual methods, it is relatively rare that the high-precision extraction of layer features, which can be applied as labels in training. To obtain sufficient radar images with high-quality training labels, we also propose a novel synthetic method to simulate the not only visual texture of the bedrock interface and internal layers but also the artifact noise and interference to match the feature in field data. EisNet is first verified on synthetic data and shows capacity on the extraction of multi types of layer targets. Second, the application on observational radar images reveals EisNet’s generalized performance from synthetic data to the CHINARE data. EisNet is also applied to extract bedrock interfaces from the radar film from the Antarctic. EisNet is now open open-accessing. We hope that EisNet could be applied in more ice radar images from other regions and different forms to promote glacial research.
The role of the stratosphere in tropical-extratropical interactions arising from slow MJO episodes.
Authors: Yadav Priyanka , Domeisen Daniela , Garfinkel Chaim
Published: March 2022

The sporadic nature of the Madden-Julian Oscillation (MJO) can influence the extratropical circulation response. However, there are differences in the extratropical response depending on the propagation speed of the MJO in the tropics. Here, we define slow (fast) MJO events as events that take more (less) than 20 (10) days to propagate from the Indian Ocean (phase 3) to the Pacific Ocean (phase 6). The slowly propagating MJO episodes lead to a positive North Atlantic Oscillation (NAO) response at a lag of 10 days following phase 4 of the MJO, whereas fast MJO episodes lead to a development of a positive NAO response 10-15 days following phase 2-3. The slowly propagating MJO episodes can lead to a stronger positive (negative) NAO response after a lag of 10 days following phase 4 (7-8).

In addition to this tropospheric pathway, the MJO can also impact the stratospheric circulation, which in turn can impact the NAO via downward coupling. The stronger impact on the NAO during slow MJO episodes suggests that the stratosphere plays a role in the teleconnection of the MJO to the North Atlantic region. This is evident from the zonal wind response within the stratospheric polar vortex at 60oN and 10hPa and the geopotential height response at 500 hPa and 100 hPa. In this study, we discuss the stratospheric pathways during fast and slow MJO episodes using ERA-Interim reanalysis with respect to the strength of the Northern Hemisphere stratospheric polar vortex and for stratosphere-troposphere coupling.
On the glass transition temperature of organic compounds via molecular dynamics simulations
Authors: Siachouli Panagiota , Karadima Katerina S. , Mavrantzas Vlasis G. , Pandis Spyros N.
Published: March 2022

The organic fraction of atmospheric particulate matter contains tens of thousands of complex compounds that have one or more functional groups. Quantifying the physical and chemical properties of each of these compounds experimentally is challenging and time consuming. The glass transition temperature, Tg, is one of these properties since it can help determine the phase state of aerosols in different parts of the atmosphere. This phase state influences gas-particle partitioning of semi-volatile compounds, the timescales of diffusion inside the particle, water uptake, as well as the rates and kinetics of heterogeneous reactions and oxidation that take place on aerosols. Experimental Tg determination can be demanding, because of the challenges presented by the synthesis and purification of the corresponding organic compounds.
Molecular Dynamics (MD) simulations have the advantage of detailed prediction of the desired properties on the molecular level with relatively low cost compared to actual experiments. In our work, we implement MD simulations to determine Tg of various organic compounds. Although Tg of organic compounds has been examined experimentally, the discrepancies in the bibliography are vast not only between experiments but also between experimental and predicted values, derived from theoretical or semi-empirical proposed equations. In the current work we focus on organic compounds of atmospheric interest, and we investigate in detail the contributions of the various functional groups to Tg. The investigated organic compounds vary in the carbon chain length as well as in the number and type of functional groups (i.e., hydroxyl and carboxylic groups). The Tg is determined by applying different cooling rates over a wide temperature span for several independent initial configurations of the examined organic molecules in bulk phase and by analyzing properties such as the density and the energy of non-bonded interactions. The results of the molecular simulations are compared with available experimental data in the bibliography, and theoretical or empirical Tg predictions.
Geoethics Issues for the 21st Century: Perspectives from the AGU Ethics and Equity Center - A Call for Education and Action      
Authors: Williams Billy , Davidson Eric , Fraiser Margaret , Pandya Raj , Hanson Brooks
Published: March 2022

The American Geophysical Union (AGU), a scientific society of >60,000 members worldwide, has established a set of scientific integrity and professional ethics guidelines for the actions of its members, the governance of the union in its internal activities, and the operations and participation in its publications and scientific meetings.  The actions around the AGU Ethics policy have in recent years focused on establishing and reinforcing professional conduct standards, including professional conduct during field research.  However, the recently updated AGU Strategic plan has a strong focus on applied transdisciplinary science; growing respect for Indigenous data, cultural heritages, and Knowledges; and emphasis on geoscientists’ responsibility to support traditionally underserved communities with respect to environmental justice, issues of equity and inclusion, and the impact of global anthropogenic change. Additional emerging ethics issues for the geosciences include a need to establish ethical AI frameworks for effective decision-making without misuse of data, and a need for ethical guidance around testing proposed climate intervention technologies.

 

These combined foci have heightened AGU’s attention to global Geoethics and have led to a re-examination of the partnerships necessary to deliver important education and impacts on such pressing issues. This presentation will highlight a few of the Geoethics issues currently being addressed by the AGU Ethics and Equity Center, including results to date and actions underway to secure and support the necessary broad partnerships. 
How far into a rain shaft can mm-wave vertically pointing radars detect raindrops?
Authors: Williams Christopher
Published: March 2022

Vertically pointing radars (VPRs) provide detailed observations of precipitating cloud systems as they pass directly over the radar site. Two VPRs operating side-by-side and at different millimeter wavelengths (mm-wave) will observe the same raindrops but will have different return signals due to wavelength dependent raindrop backscattering and attenuation characteristics. These differences enable the retrieval of raindrop size distributions and vertical air motions. Yet, as the rain rate increases, the attenuation increases. Eventually, at some combination of path length [km] and rain specific attenuation [dB/km], the attenuation [dB] will extinguish high frequency VPR return signals; limiting high frequency VPRs to studying rain processes close to the ground. 

In order to estimate how far VPRs can measure into rain shafts, this study simulated constant rain rate precipitation columns and then estimated the path length needed to produced enough attenuation to drop the VPR signal-to-noise ratio below the VPR’s detection limit. This study used surface disdrometer observations and publically available T-Matrix scattering code to produce realistic VPR measurements at frequencies from 3 to 200 GHz.

These simulations found that in order to observe raindrops above a 3.5 km rain shaft, the constant rain rate needed to be less than 138, 67, 26, 14, and 4 mm/h for VPRs operating in the X-, Ku-, K-, Ka-, and W-bands, respectively (i.e., 9, 13.6, 24, 35.6, and 94 GHz). Additionally, due solely to atmospheric gas attenuation, the G-band (200 GHz) VPR return signal will be completely extinguished by 3.5 km. Preventing a G-band VPR from detecting raindrops above 3.5 km.
On the contribution of global, local, and tropospheric ties to TRF and CRF in GNSS and VLBI integrated solution
Authors: Wang Jungang , Ge Maorong , Glaser Susanne , Balidakis Kyriakos , Heinkelmann Robert , Schuh Harald
Published: March 2022

The international celestial and terrestrial reference frames (ICRF and ITRF) are two important realizations of the global geodetic reference frame (GGRF). As the basis for high-accuracy astrometry and space exploration, ICRF is currently determined by the Very Long Baseline Interferometry (VLBI) technique solely and independently from the ITRF, whereas a consistent determination of TRF and CRF by a combination of different techniques is highly desirable. We conduct the Global Navigation Satellite Systems (GNSS) and VLBI integrated processing on the observation level and investigate the impact of applying global ties (that is, Earth Orientation Parameters, EOP), local ties, and tropospheric ties on the precision of both TRF and CRF. The GNSS and VLBI observations in VLBI continuous campaigns from CONT05 to CONT17 are processed simultaneously in the common least-squares estimator using the Positioning And Navigation Data Analyst (PANDA) software. We present that the precision of the VLBI station coordinates is significantly improved in the integrated solution, such as the horizontal components by global ties and the vertical components by local and tropospheric ties. Focusing on the precision of active galactic nuclei (AGN) coordinates, we demonstrate that the global ties can slightly reduce the AGN coordinate formal errors by up to 4%, and the local ties mainly improve the declination precision by about 10%. As for the tropospheric ties, the formal error of AGN coordinate can be reduced by 10% on average, and the repeatability can also be improved, especially the declination (10%). Moreover, the southern AGN are more improved than the northern ones, due to the observation geometry of the VLBI ground station distribution.
Empirical rainfall thresholds for landslide activity based on long-term Portuguese meteorological stations
Authors: Vaz Teresa , Zêzere José Luís
Published: March 2022

In this research the occurrence of landslides triggered by rainfall is investigated through the assessment of rainfall thresholds for three regions in Portugal: Lisbon, Oporto, and Coimbra. An historical landslide inventory is used, based on newspapers published between 1865 and 2010, associated with daily precipitation databases from three long-term meteorological stations. An empirical approach based on antecedent rainfall is applied to define the rainfall thresholds for landslides occurrence. The analysis is focused on each single rain gauge, for which the spatial representativeness is evaluated. The daily rainfall data is analysed using the Gumbel probability distribution for different durations. The critical rainfall combinations (cumulated rainfall duration) with the highest return period are associated with the landslide occurrence.

For the three regions, rainfall thresholds are defined from regression (linear and potential), extreme values (upper and lower) and probability (probability of a rainfall event resulting in a landslide event when the threshold is exceeded), and the results are assessed and calibrated using the receiver operating characteristic (ROC) metrics. The thresholds comparation reveal regional patterns in rainfall thresholds. The differences in regional critical rainfall conditions for landslide occurrence between regions are associated with geological, geomorphological, and climatic features.

 

This work is part of the project BeSafeSlide (BSS) - Landslide Early Warning soft technology prototype to improve community resilience and adaptation to environmental change [PTDC/GES-AMB/30052/2017]. JL Zêzere was supported by the RiskCoast project - Development of tools to prevent and manage geological risks on the coast linked to climate change, Interreg SUDOE [SOE3/P4/EO868]
Apocalypse Now? Projecting CO2 Emissions with Neural Networks
Authors: Jensen Sebastian , Hillebrand Eric , Bennedsen Mikkel
Published: March 2022

We project carbon dioxide emissions through 2100 using a reduced-form model and national-level scenarios for per capita gross domestic product from the Shared Socioeconomic Pathways (SSPs). We propose a novel neural network-based panel data model that combines country fixed effects with a long short-term memory (LSTM) recurrent neural network regression component that takes into account time implicitly by building memory and letting model predictions depend on the income path of a country. For scenarios with low socioeconomic challenges for mitigation SSP1 and SSP4, our emissions projections appear consistent with baseline projections from structural integrated assessment models (IAMs) that are meant to describe future developments in absence of new climate policies. For scenarios with medium and high socioeconomic challenges for mitigation SSP2, SSP3, and SSP5, our emissions projections appear the most consistent with mitigation projections from IAMs that target a forcing level of 6.0 W/m2 by 2100.
Latitudinal dependence of the fall-effect observed in the D-region and mesosphere
Authors: Macotela Liliana , Clilverd Mark , Chau Jorge , Banyś Daniela , Raulin Jean-Pierre , Raita Tero
Published: March 2022

The seasonal variation of the daytime lower ionosphere over the North Atlantic, monitored using the propagation of Very Low Frequency (VLF) radio waves, shows an asymmetry when comparing the spring and autumn transitions. The signal variability shows a faster rate of change from summer to winter than from winter to summer, for which the responsible mechanism is still unknown. In this study, we perform a climatological (2008–2021) analysis to determine the northern-hemisphere latitudinal dependence of the spring-fall asymmetry. We employ VLF receivers located in Peru (low-latitude), USA (middle-latitude), UK (middle-latitude), Finland (high-latitude), and Norway (high-latitude). At the same time, we employ neutral mesospheric temperature from MLS, nitric oxide (NO) from SOFIE, and gravity wave (GW) kinetic energy derived from mesospheric horizontal winds. We find that at high-latitude the VLF amplitude variability before summer and during winter follows the seasonal variation of the solar zenith angle, but the measurements during fall do not. After removing the VLF background level, a large deviation is observed during fall, which we call the fall-effect. We explore the processes behind this effect by comparing against mean temperature, NO, and GW seasonal variabilities after removing their respective background levels. We found that the three mesospheric parameters display a fall-effect. Performing a similar analysis for middle latitudes shows that the fall-effect is not clearly observed in both ionospheric and mesospheric parameters. In the case of low-latitudes, no fall-effect is observed. We discuss the possible association between the mesospheric temperature and the VLF variability through collision and absorption. We also discuss the possible role of GW on the D-region.
Equatorward North Atlantic jet biases in CMIP models and implications for simulated regional atmosphere-ocean linkages
Authors: Bracegirdle Tom , Lu Hua , Robson Jon
Published: March 2022

Climate model biases in the North Atlantic (NA) low-level tropospheric westerly jet are a major impediment to reliably representing variability of the NA climate system and its wider influence, in particular over western Europe. We highlight an early-winter equatorward jet bias in Coupled Model Inter-comparison Project (CMIP) models and assess whether this bias is reduced in the CMIP6 models in comparison to the CMIP5 models. Historical simulations from the CMIP5 and CMIP6  are further compared against reanalysis data over the period 1862-2005.  

The results show that an equatorward bias remains significant in CMIP6 models in early winter. Almost all CMIP5 and CMIP6 model realizations exhibit equatorward climatological jet latitude biases with ensemble mean biases of 3.0° (November) and 3.0° (December) for CMIP5 and 2.5° and 2.2° for CMIP6. This represents an approximately one-fifth reduction for CMIP6 compared to CMIP5. The equatorward jet latitude bias is mainly associated with a weaker-than-observed frequency of poleward daily-weekly excursions of the jet to its northern position. A potential explanation is provided.  Our results indicate a strong link between NA jet latitude bias and systematically too-weak model-simulated low-level baroclinicity over eastern North America in early-winter.  

Implications for model representation of NA atmosphere-ocean linkages will be presented. In particular CMIP models with larger equatorward jet biases tend to exhibit weaker correlations between temporal variability in jet speed and sea surface conditions over the NA sub-polar gyre (SPG). This has implications for the ability of climate models to represent key aspects of atmospheric variability and predictability that are associated with atmosphere-ocean interactions in the SPG region.  
Fluvial Morphodynamics of Kampar River, Sumatra, Indonesia
Authors: Yuskar Yuniarti , Bartz Melanie , Schmidt Christoph , Choanji Tiggi , Revanda Muhammad , Lane Stuart Nicholas , King Georgina Elizabeth
Published: March 2022

The relationship between alluviation and environmental change in tropical fluvial environments remains extremely poorly known, especially over late Pleistocene to Holocene time scales. At the same time, new developments in dating allow more precise quantification of associated deposits, opening up the opportunity to determine the alluvial history and relate it to environmental change. The Kampar River is a meandering tropical river in Sumatra island, Indonesia. This river has a gentle slope, gravel bed-river, and their bends migrate because of bank erosion. Fluvial dynamics are recorded by vertically and laterally changing sediment facies due to bend growth. This study develops a chrono-stratigraphical framework at the time scale of the Late Quaternary for the Kampar River to better understand its long-term fluvial dynamics and flooding frequency relative to changing climate and vegetation. We applied sedimentological analysis utilizing XRD and granulometry analysis to investigate mineralogy and facies changes. However, sedimentological analysis is insufficient to correlate sediment facies because this river is highly dynamic. Therefore, the reconstruction of morpho-dynamics in the meandering river is a challenge. Satellite images and drone imagery are utilized to document the geometry of the river. Then, to clarify the chrono-stratigraphy, sediment dating becomes essential. Due to the challenging characteristics of quartz optical stimulated luminescence (OSL), we applied infra-red stimulated luminescence (IRSL) of K-feldspar to constrain a chronology for the fluvial deposits. As a result, we concluded that sediment deposition began with a sediment channel dominated by gravel deposits in this study. It is then gradually transformed to low amplitude point bars reflected in lateral accretion deposits characterized by fining-upward sandy gravels. The onset of large-scale flooding is reflected in more intensive bend-growth and also evidence of overbank deposition. Chute bar formation was also identified, characterized by gravelly sand with a basal lag deposit. Preliminary dating suggests fluvial aggradation spanning Late Pleistocene – Holocene time scales. We highlight the potential for these new dating methods in studying Holocene fluvial dynamics in highly active tropical river systems sensitive to climatic shifts.
Two types of Coastal El Niño events
Authors: Martinez-Villalobos Cristian , Dewitte Boris , Garreaud René D. , Loyola Leandra , Concha Emilio
Published: March 2022

Coastal El Niño events —instances of anomalous surface ocean warming in the eastern Tropical Pacific not associated to basin-wide events— have received a great deal of attention following the strong coastal event of early 2017. This event was associated to large increases in precipitation and widespread damage in Ecuador and Northern Peru comparable to that during the 1997/98 El Niño event. Despite their importance, it is currently not well understood whether these events are essentially driven by local dynamics or are a local manifestation of large-scale modes of climate variability, a possibility that may increase their predictability prospects. We identify three Coastal El Niño events and 7 Coastal La Niña events occurring in the last 40 years. We show that these events are at least partially driven by large-scale processes and can be grouped in two types. The first type is driven by westerly wind bursts in the western Pacific and occur in the initial stages of the development of basin-wide El Niño events. The second type occurs in association with active phases of the North Pacific Meridional Mode and are characterized by large-scale positive wind-evaporation-SST (WES) feedback. We develop a simple model that provides theoretical underpinnings for the WES feedback-driven type of events. Finally, we show that these two types of events have counterparts in the CESM Large Ensemble and discuss their projected change under global warming.