Publication date: 1 July 2024
Source: Advances in Space Research, Volume 74, Issue 1
Author(s): Weipeng Hu, Bo Tang, Zhengqi Han, Pingwei Deng, Zichen Deng
Publication date: 1 July 2024
Source: Advances in Space Research, Volume 74, Issue 1
Author(s): Yuning Qiu, Yi Liang, Xinqi Chen, Zhe Zhang, Shengli Xie, Guoxu Zhou
Publication date: 1 July 2024
Source: Advances in Space Research, Volume 74, Issue 1
Author(s): Quoc Bao Pham, Sk Ajim Ali, Farhana Parvin, Vo Van On, Lariyah Mohd Sidek, Bojan Đurin, Vlado Cetl, Sanja Šamanović, Nguyen Nguyet Minh
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.
The important role of the Southern Ocean in global biological processes and the carbon cycle has been confirmed anew by a study published in Science that, for the first time based on field evidence, reveals the underappreciated role of inorganic zinc (Zn) particles in these cycles.
The U.S. Pacific Northwest experienced an unprecedented heat wave in summer 2021, with many locations in the region breaking all-time maximum temperature records by more than 9 °F (5 °C). Although weather models had forecasted the warmer-than-average conditions that summer, the extreme temperatures caught the climate science community by surprise. In the past year, so have catastrophic, deadly floods in such places as Libya and China and record-breaking wildfires in Canada.
The buried China-Russia Crude Oil Pipeline (CRCOP), with its oil temperature above 0°C, interacts with the permafrost environment in a complex way, causing permafrost degradation, frost geohazards, and various environmental problems along its route.
The radiative climate and environmental effects of cirrus clouds is an international cutting-edge field of scientific research in the atmospheric sciences. Understanding how the characteristics of cirrus clouds over the ocean evolve is critical for comprehending the dynamics of climate change. In this respect, due to their unique regional characteristics, the cirrus clouds over the South China Sea (SCS) hold particularly significant scientific and practical value.
Video footage of Iceland's 2010 Eyjafjallajökull eruption is providing researchers from the University of Cambridge with rare, up-close observations of volcanic ash clouds—information that could help better forecast how far explosive eruptions disperse their hazardous ash particles.
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.
Australia has a long history of bushfires. The 2019-2020 Black Summer was the worst in recorded history. But was that the worst it could get?
When it comes to the ocean's response to global warming, we're not in entirely uncharted waters. A UC Riverside study shows that episodes of extreme heat in Earth's past caused the exchange of waters from the surface to the deep ocean to decline.
During a 2017 research field trip to the Ichinokawa Mine (Ehime prefecture), which is famous for beautiful, sword-shaped stibnite crystals, Noriyoshi Tsuchiya found something unexpected. Although most would be entranced by the glittering crystals, it was a sedimentary rock bundle called breccia that caught his eye.
Climate changes, but not always for the same reason. Today's rapid climate change is due entirely to man. The Holocene—the last 12,000 years—has been seen as having a stable climate, with a lack of chaos that allowed humans to settle down, develop agriculture, build civilizations and thrive.
