AOSbotJan 15, 2024

Title: Organic hazes as a source of life's building blocks to warm little ponds on the Hadean Earth.

Over 4 billion years ago, Earth is thought to have been a hazy world akin to
Saturn's moon Titan. The organic hazes in the atmosphere at this time could
contain a vast inventory of life's building blocks, and thus may have seeded
warm little ponds for life. In this work, we pro [...]

Authors: Ben K. D. Pearce, Sarah M Hörst, Joshua A. Sebree, Chao He

Link: http://arxiv.org/abs/2401.06212

Organic hazes as a source of life's building blocks to warm little ponds on the Hadean Earth

Over 4 billion years ago, Earth is thought to have been a hazy world akin to Saturn's moon Titan. The organic hazes in the atmosphere at this time could contain a vast inventory of life's building blocks, and thus may have seeded warm little ponds for life. In this work, we produce organic hazes in the lab in atmospheres with high (5%) and low (0.5%) CH4 abundances and analyze the solid particles for nucleobases, amino acids, and a few other organics using GC/MS/MS to obtain their concentrations. We also analyze heated (200 $^{\circ}$C) samples from the high methane organic haze experiment to simulate these particles sitting on an uninhabitable surface. Finally, we use our experimental results and estimates of atmospheric haze production as inputs for a comprehensive numerical pond model to calculate the concentrations of nucleobases from organic hazes in these environments. We find that organic hazes typically provide up to 0.2-6.5 $μ$M concentrations of nucleobases to warm little ponds for potentially habitable Hadean conditions. However, without seepage, uracil and thymine can reach ~100 $μ$M concentrations, which is the present lower experimental limit to react these species to form nucleotides. Heating samples leads to partial or complete decay of biomolecules, suggesting that biomolecule stockpiling on the hot surface is unlikely. The ideal conditions for the delivery of life's building blocks from organic hazes would be when the Hadean atmosphere is rich in methane, but not so rich as to create an uninhabitable surface.

arXiv.org
AOSbotDec 12, 2023

Title: Improving the representation of the atmospheric boundary layer by direct assimilation of ground-based microwave radiometer observations.

In a joint effort, MeteoSwiss and Deutscher Wetterdienst (DWD) address the
need for improving the initial state of the atmospheri [...]

Authors: Jasmin Vural, Claire Merker, Moritz Löffler, Daniel Leuenberger, Christoph Schraff, Olaf Stiller, Annika Schomburg, Christine Knist, Alexander Haefele, Maxime Hervo

Link: http://arxiv.org/abs/2312.05691

Improving the representation of the atmospheric boundary layer by direct assimilation of ground-based microwave radiometer observations

In a joint effort, MeteoSwiss and Deutscher Wetterdienst (DWD) address the need for improving the initial state of the atmospheric boundary layer (ABL) by exploiting ground-based profiling observations that aim to fill the existing observational gap in the ABL. We implemented the brightness temperature observations from ground-based microwave radiometers (MWRs) into our data assimilation systems using a local ensemble transform Kalman filter (LETKF) with RTTOV-gb (Radiative Transfer for TOVS, ground-based) as a forward operator. We were able to obtain a positive impact on the brightness temperature first guess and analysis as well as a slight impact on the ABL humidity using two MWRs at MeteoSwiss. These results led to a subsequent operational implementation of the observing system at MeteoSwiss. Furthermore, we performed an extensive set of assimilation experiments at DWD to further investigate various aspects such as the vertical localisation of selected single channels. We obtained a positive impact on the 6h-forecast of ABL temperature and humidity by assimilating two channels employing a dynamical localisation based on the sensitivity functions of RTTOV-gb but also with a static localisation in a single-channel setup. Our experiments indicate the importance of the vertical localisation when using more than one channel, although reliable improvements are challenging to obtain without a larger number of observations for both assimilation and verification.

arXiv.org
AOSbotDec 7, 2023

Title: Simulation-Based Inference of Surface Accumulation and Basal Melt Rates of an Antarctic Ice Shelf from Isochronal Layers.

The ice shelves buttressing the Antarctic ice sheet determine the rate of
ice-discharge into the surrounding oceans. The geometry of ice shelves, and
hence their buttressing strength, i [...]

Authors: Guy Moss, Vjeran Višnjević, Olaf Eisen, Falk M. Oraschewski, Cornelius Schröder, Jakob H. Macke, Reinhard Drews

Link: http://arxiv.org/abs/2312.02997

Simulation-Based Inference of Surface Accumulation and Basal Melt Rates of an Antarctic Ice Shelf from Isochronal Layers

The ice shelves buttressing the Antarctic ice sheet determine the rate of ice-discharge into the surrounding oceans. The geometry of ice shelves, and hence their buttressing strength, is determined by ice flow as well as by the local surface accumulation and basal melt rates, governed by atmospheric and oceanic conditions. Contemporary methods resolve one of these rates, but typically not both. Moreover, there is little information of how they changed in time. We present a new method to simultaneously infer the surface accumulation and basal melt rates averaged over decadal and centennial timescales. We infer the spatial dependence of these rates along flow line transects using internal stratigraphy observed by radars, using a kinematic forward model of internal stratigraphy. We solve the inverse problem using simulation-based inference (SBI). SBI performs Bayesian inference by training neural networks on simulations of the forward model to approximate the posterior distribution, allowing us to also quantify uncertainties over the inferred parameters. We demonstrate the validity of our method on a synthetic example, and apply it to Ekström Ice Shelf, Antarctica, for which newly acquired radar measurements are available. We obtain posterior distributions of surface accumulation and basal melt averaging over 42, 84, 146, and 188 years before 2022. Our results suggest stable atmospheric and oceanographic conditions over this period in this catchment of Antarctica. Use of observed internal stratigraphy can separate the effects of surface accumulation and basal melt, allowing them to be interpreted in a historical context of the last centuries and beyond.

arXiv.org
AOSbotSep 19, 2023

Title: Earth Virtualization Engines -- A Technical Perspective.

Participants of the Berlin Summit on E [...]

Authors: Torsten Hoefler, Bjorn Stevens, Andreas F. Prein, Johanna Baehr, Thomas Schulthess, Thomas F. Stocker, John Taylor, Daniel Klocke, Pekka Manninen, Piers M. Forster, Tobias Kölling, Nicolas Gruber, Hartwig Anzt, Claudia Frauen, Florian Ziemen, Milan Klöwer, Karthik Kashinath, Christoph Schär, Oliver Fuhrer, Bryan N. Lawrence

Link: http://arxiv.org/abs/2309.09002

Earth Virtualization Engines -- A Technical Perspective

Participants of the Berlin Summit on Earth Virtualization Engines (EVEs) discussed ideas and concepts to improve our ability to cope with climate change. EVEs aim to provide interactive and accessible climate simulations and data for a wide range of users. They combine high-resolution physics-based models with machine learning techniques to improve the fidelity, efficiency, and interpretability of climate projections. At their core, EVEs offer a federated data layer that enables simple and fast access to exabyte-sized climate data through simple interfaces. In this article, we summarize the technical challenges and opportunities for developing EVEs, and argue that they are essential for addressing the consequences of climate change.

arXiv.org
AOSbotSep 11, 2023

Title: Postprocessing of Ensemble Weather Forecasts Using Permutation-invariant Neural Networks.

Statistical postprocessing is used to translate ensembles of raw numerical
weather forecasts into reliable probabilistic forecast distributions. In this
study, we examine the use of permutation-invariant neural networks for this
task. In contrast to previous approache [...]

Authors: Kevin Höhlein, Benedikt Schulz, Rüdiger Westermann, Sebastian Lerch

Link: http://arxiv.org/abs/2309.04452

Postprocessing of Ensemble Weather Forecasts Using Permutation-invariant Neural Networks

Statistical postprocessing is used to translate ensembles of raw numerical weather forecasts into reliable probabilistic forecast distributions. In this study, we examine the use of permutation-invariant neural networks for this task. In contrast to previous approaches, which often operate on ensemble summary statistics and dismiss details of the ensemble distribution, we propose networks that treat forecast ensembles as a set of unordered member forecasts and learn link functions that are by design invariant to permutations of the member ordering. We evaluate the quality of the obtained forecast distributions in terms of calibration and sharpness and compare the models against classical and neural network-based benchmark methods. In case studies addressing the postprocessing of surface temperature and wind gust forecasts, we demonstrate state-of-the-art prediction quality. To deepen the understanding of the learned inference process, we further propose a permutation-based importance analysis for ensemble-valued predictors, which highlights specific aspects of the ensemble forecast that are considered important by the trained postprocessing models. Our results suggest that most of the relevant information is contained in a few ensemble-internal degrees of freedom, which may impact the design of future ensemble forecasting and postprocessing systems.

arXiv.org
AOSbotSep 1, 2023

Title: Limits to predictability of the asymptotic state of the Atlantic Meridional Overturning Circulation in a conceptual climate model.

Anticipating critical transitions in the Earth system is of great societal
relevance, yet there may be intrinsic limitations to their predictability. For
instance, from the theory of dynamical systems possessing multiple chaotic
attractors, it is known t [...]

Authors: Oliver Mehling, Reyk Börner, Valerio Lucarini

Link: http://arxiv.org/abs/2308.16251

Limits to predictability of the asymptotic state of the Atlantic Meridional Overturning Circulation in a conceptual climate model

Anticipating critical transitions in the Earth system is of great societal relevance, yet there may be intrinsic limitations to their predictability. For instance, from the theory of dynamical systems possessing multiple chaotic attractors, it is known that the asymptotic state depends sensitively on the initial condition in the proximity of a fractal basin boundary. Here, we approach the problem of final-state sensitivity of the Atlantic Meridional Overturning Circulation (AMOC) using a conceptual climate model, composed of a slow bistable ocean coupled to a fast chaotic atmosphere. First, we explore the occurrence of long chaotic transients in the monostable regime, which can mask a loss of stability near bifurcations. In the bistable regime, we explicitly construct the chaotic saddle using the edge tracking technique. Quantifying the final-state sensitivity through the maximum Lyapunov exponent and the lifetime of the saddle, we find that the system exhibits a fractal basin boundary with almost full phase space dimension, implying vanishing predictability of the second kind near the basin boundary. Our results demonstrate the usefulness of studying non-attracting chaotic sets in the context of predicting climatic tipping points, and provide guidance for the interpretation of higher-dimensional models such as general circulation models.

arXiv.org
AOSbotAug 3, 2023

Title: Interpreting Observed Interactions between Near-Inertial Waves and Mesoscale Eddies.

The evolution of wind-generated near-inertial waves (NIWs) is known to be
influenced by the mesoscale eddy field, yet it remains a challenge to
disentangle the effects of this interaction in observations. NIWs are often
modeled using a slab mixed-layer model with no horizontal structure. Here, the
the [...]

Authors: Scott Conn, Joseph Fitzgerald, Jörn Callies

Link: http://arxiv.org/abs/2308.00889

Interpreting Observed Interactions between Near-Inertial Waves and Mesoscale Eddies

The evolution of wind-generated near-inertial waves (NIWs) is known to be influenced by the mesoscale eddy field, yet it remains a challenge to disentangle the effects of this interaction in observations. Here, the model of Young and Ben Jelloul (YBJ), which describes NIW evolution in the presence of slowly evolving mesoscale eddies, is compared to observations from a mooring array in the Northeast Atlantic Ocean. The model captures the evolution of both the observed NIW amplitude and phase much more accurately than a slab mixed layer model. The YBJ model allows for the identification of specific physical processes that drive the observed evolution. It reveals that differences in the NIW amplitude across the mooring array are caused by the refractive concentration of NIWs into anticyclones. Advection and wave dispersion also make important contributions to the observed wave evolution. Stimulated generation, a process by which mesoscale kinetic energy acts as a source of NIW potential energy, is estimated to be 20$μ$W/m$^2$ in the region of the mooring array, which is two orders of magnitude smaller than the global average input to mesoscale kinetic energy and likely not an important contribution to the mesoscale kinetic energy budget in this region. Overall, the results show that the YBJ model is a quantitatively useful tool to interpret observations of NIWs.

arXiv.org
AOSbotMay 12, 2023

Title: From trees to rain: Enhancement of cloud glaciation and precipitation by pollen.

The ability of pollen to enable the glaciation of supercooled liquid water
has been demonstrated in laboratory studies; however, the potential large-scale
effect of trees and pollen on clouds, precipitation and climate is pressing
knowledge to better understa [...]

Authors: Jan Kretzschmar, Mira Pöhlker, Frank Stratmann, Heike Wex, Christian Wirth, Johannes Quaas

Link: http://arxiv.org/abs/2305.06758

From trees to rain: Enhancement of cloud glaciation and precipitation by pollen

The ability of pollen to enable the glaciation of supercooled liquid water has been demonstrated in laboratory studies; however, the potential large-scale effect of trees and pollen on clouds, precipitation and climate is pressing knowledge to better understand and project clouds in the current and future climate. Combining ground-based measurements of pollen concentrations and satellite observations of cloud properties within the United States, we show that enhanced pollen concentrations during springtime lead to a higher cloud ice fraction. We further establish the link from the pollen-induced increase in cloud ice to a higher precipitation frequency. In light of anthropogenic climate change, the extended and strengthened pollen season and future alterations in biodiversity can introduce a localized climate forcing and a modification of the precipitation frequency and intensity.

arXiv.org
AOSbotApr 7, 2023

Title: Vertical-slice ocean tomography with seismic waves.

Seismically generated sound waves that propagate through the ocean are used
to infer temperature anomalies and their vertical structure in the deep East
Indian Ocean. These T waves are generated by earthquakes off Sumatra and
received by hydrophone stations off Diego Garcia and Cape Leeuwin. Between
repeating earthquakes, a T [...]

Authors: Jörn Callies, Wenbo Wu, Shirui Peng, Zhongwen Zhan

Link: http://arxiv.org/abs/2304.02791

Vertical-slice ocean tomography with seismic waves

Seismically generated sound waves that propagate through the ocean are used to infer temperature anomalies and their vertical structure in the deep East Indian Ocean. These T waves are generated by earthquakes off Sumatra and received by hydrophone stations off Diego Garcia and Cape Leeuwin. Between repeating earthquakes, a T wave's travel time changes in response to temperature anomalies along the wave's path. What part of the water column the travel time is sensitive to depends on the frequency of the wave, so measuring travel time changes at a few low frequencies constrains the vertical structure of the inferred temperature anomalies. These measurements reveal anomalies due to equatorial waves, mesoscale eddies, and decadal warming trends. By providing direct constraints on basin-scale averages with dense sampling in time, these data complement previous point measurements that alias local and transient temperature anomalies.

arXiv.org
AOSbotMar 16, 2023

Title: A machine-learning approach to thunderstorm forecasting through post-processing of simulation data.

Thunderstorms pose a major hazard to society and economy, which calls for
reliable thunderstorm forecasts. In this work, we introduce SALAMA, a
feedforward neural network model for identifying thunderstorm occurrence in
numerical weather prediction (NWP) d [...]

Authors: Kianusch Vahid Yousefnia, Tobias Bölle, Isabella Zöbisch, Thomas Gerz

Link: http://arxiv.org/abs/2303.08736

A machine-learning approach to thunderstorm forecasting through post-processing of simulation data

Thunderstorms pose a major hazard to society and economy, which calls for reliable thunderstorm forecasts. In this work, we introduce a Signature-based Approach of identifying Lightning Activity using MAchine learning (SALAMA), a feedforward neural network model for identifying thunderstorm occurrence in numerical weather prediction (NWP) data. The model is trained on convection-resolving ensemble forecasts over Central Europe and lightning observations. Given only a set of pixel-wise input parameters that are extracted from NWP data and related to thunderstorm development, SALAMA infers the probability of thunderstorm occurrence in a reliably calibrated manner. For lead times up to eleven hours, we find a forecast skill superior to classification based only on NWP reflectivity. Varying the spatiotemporal criteria by which we associate lightning observations with NWP data, we show that the time scale for skillful thunderstorm predictions increases linearly with the spatial scale of the forecast.

arXiv.org