Compound droughts under climate change in Switzerland
Christoph Nathanael von Matt, Regula Muelchi, Lukas Gudmundsson, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 1975–2001, https://doi.org/10.5194/nhess-24-1975-2024, 2024
The simultaneous occurrence of meteorological (precipitation), agricultural (soil moisture), and hydrological (streamflow) drought can lead to augmented impacts. By analysing drought indices derived from the newest climate scenarios for Switzerland (CH2018, Hydro-CH2018), we show that with climate change the concurrence of all drought types will increase in all studied regions of Switzerland. Our results stress the benefits of and need for both mitigation and adaptation measures at early stages.
Estimating the refractivity bias of FORMOSAT-7/COSMIC-2 Global Navigation Satellite System (GNSS) radio occultation in the deep troposphere
Gia Huan Pham, Shu-Chih Yang, Chih-Chien Chang, Shu-Ya Chen, and Cheng Yung Huang
Atmos. Meas. Tech., 17, 3605–3623, https://doi.org/10.5194/amt-17-3605-2024, 2024
This research examines the characteristics of low-level GNSS radio occultation (RO) refractivity bias over ocean and land and its dependency on the RO retrieval uncertainty, atmospheric temperature, and moisture. We propose methods for estimating the region-dependent refractivity bias. Our methods can be applied to calibrate the refractivity bias under different atmospheric conditions and thus improve the applications of the GNSS RO data in the deep troposphere.
A random forest algorithm for the prediction of cloud liquid water content from combined CloudSat–CALIPSO observations
Richard M. Schulte, Matthew D. Lebsock, John M. Haynes, and Yongxiang Hu
Atmos. Meas. Tech., 17, 3583–3596, https://doi.org/10.5194/amt-17-3583-2024, 2024
This paper describes a method to improve the detection of liquid clouds that are easily missed by the CloudSat satellite radar. To address this, we use machine learning techniques to estimate cloud properties (optical depth and droplet size) based on other satellite measurements. The results are compared with data from the MODIS instrument on the Aqua satellite, showing good correlations.
Stability requirements of satellites to detect long-term stratospheric ozone trends based upon Monte Carlo simulations
Mark Weber
Atmos. Meas. Tech., 17, 3597–3604, https://doi.org/10.5194/amt-17-3597-2024, 2024
We investigate how stable the performance of a satellite instrument has to be to be useful for assessing long-term trends in stratospheric ozone. The stability of an instrument is specified in percent per decade and is also called instrument drift. Instrument drifts add to uncertainties of long-term trends. From simulated time series of ozone based on the Monte Carlo approach, we determine stability requirements that are needed to achieve the desired long-term trend uncertainty.
Design and evaluation of BOOGIE: a collector for the analysis of cloud composition and processes: Biological, Organics, Oxidants, soluble Gases, inorganic Ions and metal Elements
Mickael Vaitilingom, Christophe Bernard, Mickael Ribeiro, Christophe Berthod, Angelica Bianco, and Laurent Deguillaume
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-95,2024
Preprint under review for AMT (discussion: open, 0 comments)
The new collector BOOGIE has been designed and evaluated to sample cloud droplets. Computational fluid dynamic simulations are performed to evaluate the sampling efficiency for different droplets size. In situ measurements show very good water collection rates and sampling efficiency. BOOGIE is compared to other cloud collectors and the efficiency is comparable, as well as the chemical and biological compositions.
Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, 2024
The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0
Jacquelyn K. Shuman, Rosie A. Fisher, Charles Koven, Ryan Knox, Lara Kueppers, and Chonggang Xu
Geosci. Model Dev., 17, 4643–4671, https://doi.org/10.5194/gmd-17-4643-2024, 2024
We adapt a fire behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime, and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Multivariate adjustment of drizzle bias using machine learning in European climate projections
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, 2024
This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
2021 Alaska Earthquake: entropy approach to its precursors and aftershock regimes
Eugenio E. Vogel, Denisse Pastén, Gonzalo Saravia, Michel Aguilera, and Antonio Posadas
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-106,2024
Preprint under review for NHESS (discussion: open, 0 comments)
For the first time, an entropy analysis has been performed in Alaska, a seismic-rich region located in a subduction zone that shows non-trivial behavior: the subduction arc changes seismic activity from the eastern zone to the western zone, showing a decrease in this activity along subduction. This study shows how an entropy approach can help understand seismicity in subduction zones.
Scale size estimation and flow pattern recognition around a magnetosheath jet
Adrian Pöppelwerth, Georg Glebe, Johannes Z. D. Mieth, Florian Koller, Tomas Karlsson, Zoltán Vörös, and Ferdinand Plaschke
Ann. Geophys., 42, 271–284, https://doi.org/10.5194/angeo-42-271-2024, 2024
In the magnetosheath, a near-Earth region of space, we observe increases in plasma velocity and density, so-called jets. As they propagate towards Earth, jets interact with the ambient plasma. We study this interaction with three spacecraft simultaneously to infer their sizes. While previous studies have investigated their size almost exclusively statistically, we demonstrate a new method of determining the sizes of individual jets.
Abstract
There are many uncertainties in future climate, including how the Earth may react to different types of radiative forcing, such as CO2, aerosols, and even geoengineered changes in the amount of sunlight absorbed by Earth's surface. Here, we analyze model simulations where the climate system is subjected to an abrupt change of the solar constant by ±4%, and where the atmospheric CO2 concentration is abruptly changed to quadruple and half its preindustrial value. Using these experiments, we examine how clouds respond to changes in solar forcing, compared to CO2, and feedback on global surface temperature. The total cloud response can be decomposed into those responses driven by changes in global surface temperature, called the temperature mediated cloud feedbacks, and responses driven directly by the forcing that are independent of the global surface temperature. In this paper, we study the temperature mediated cloud changes to answer two primary questions: (a) How do temperature mediated cloud feedbacks differ in response to abrupt changes in CO2 and solar forcing? And (b) Are there symmetrical (equal and opposite) temperature mediated cloud feedbacks during global warming and global cooling? We find that temperature mediated cloud feedbacks are similar in response to increasing solar and increasing CO2 forcing, and we provide a short review of recent literature regarding the physical mechanisms responsible for these feedbacks. We also find that cloud responses to warming and cooling are not symmetric, due largely to non-linearity introduced by phase changes in mid-to-high latitude low clouds and sea ice loss/formation.
Abstract
The divergence method, a lightweight approach for estimating emission fluxes from satellite images, rests on a few implicit assumptions. This paper explicitly outlines these assumptions by deriving the method from first principles. The assumptions are: the enhanced mass flux is dominated by advection, normal fluxes vanish at the top and bottom of the atmosphere, steady-state conditions apply, sources are multiplications of temporal and spatial functions, sinks are described as first-order reactions, and effective wind fields are concentration-weighted wind fields. No such assumptions have to be made for the background field. A “topography correction term” does not follow from the theory, but is rather shown to be a practical correction for topography-dependent effective wind speed errors. The cross-sectional flux method follows naturally from the derived theory, and the methods are compared. Effects of discrete pixels and finite-difference operations are explored, leading to recommendations, primarily the recommendation to integrate over small regions only to minimize the influence of noise. Numerical examples featuring Gaussian plumes and COSMO-GHG simulated plumes are provided. The Gaussian plume example suggests that the divergence method might underestimate emissions when assuming only advection in the presence of cross-wind diffusion. Conversely, the cross-sectional flux method remains unaffected, provided fluxes are integrated across the entire plume. The COSMO-GHG example reveals frequent violations of the steady-state assumption, although the assumption remains valid proximal to the source (<20 km in this example). It is the hope that this paper provides a solid theoretical foundation for the divergence and cross-sectional flux methods.
