Publication date: 15 September 2024
Source: Advances in Space Research, Volume 74, Issue 6
Author(s): Bruno Bertrand, Pascale Defraigne, Aurélien Hees, Alexandra Sheremet, Clément Courde, Julien Chabé, Javier Ventura-Traveset, Florian Dilssner, Erik Schoenemann, Luis Mendes, Pacôme Delva
Evaluation of on-site calibration procedures for SKYNET Prede POM sun–sky photometers
Monica Campanelli, Victor Estellés, Gaurav Kumar, Teruyuki Nakajima, Masahiro Momoi, Julian Gröbner, Stelios Kazadzis, Natalia Kouremeti, Angelos Karanikolas, Africa Barreto, Saulius Nevas, Kerstin Schwind, Philipp Schneider, Iiro Harju, Petri Kärhä, Henri Diémoz, Rei Kudo, Akihiro Uchiyama, Akihiro Yamazaki, Anna Maria Iannarelli, Gabriele Mevi, Annalisa Di Bernardino, and Stefano Casadio
Atmos. Meas. Tech., 17, 5029–5050, https://doi.org/10.5194/amt-17-5029-2024, 2024
To retrieve columnar aerosol properties from sun photometers, some calibration factors are needed. The on-site calibrations, performed as frequently as possible to monitor changes in the machine conditions, allow operators to track and evaluate the calibration status on a continuous basis, reducing the data gaps incurred by the periodic shipments for performing centralized calibrations. The performance of the on-site calibration procedures was evaluated, providing very good results.
In situ observations of supercooled liquid water clouds over Dome C, Antarctica, by balloon-borne sondes
Philippe Ricaud, Pierre Durand, Paolo Grigioni, Massimo Del Guasta, Giuseppe Camporeale, Axel Roy, Jean-Luc Attié, and John Bognar
Atmos. Meas. Tech., 17, 5071–5089, https://doi.org/10.5194/amt-17-5071-2024, 2024
Clouds in Antarctica are key elements affecting climate evolution. Some clouds are composed of supercooled liquid water (SLW; water held in liquid form below 0 °C) and are difficult to forecast by models. We performed in situ observations of SLW clouds at Concordia Station using SLW sondes attached to meteorological balloons in summer 2021–2022. The SLW clouds were observed in a saturated layer at the top of the planetary boundary layer in agreement with ground-based lidar observations.
Thermal tides in the middle atmosphere at mid-latitudes measured with a ground-based microwave radiometer
Witali Krochin, Axel Murk, and Gunter Stober
Atmos. Meas. Tech., 17, 5015–5028, https://doi.org/10.5194/amt-17-5015-2024, 2024
Atmospheric tides are global-scale oscillations with periods of a fraction of a day. Their observation in the middle atmosphere is challenging and rare, as it requires continuous measurements with a high temporal resolution. In this paper, temperature time series of a ground-based microwave radiometer were analyzed with a spectral filter to derive thermal tide amplitudes and phases in an altitude range of 25–50 km at the geographical locations of Payerne and Bern (Switzerland).
Classification accuracy and compatibility across devices of a new Rapid-E+ flow cytometer
Branko Sikoparija, Predrag Matavulj, Isidora Simovic, Predrag Radisic, Sanja Brdar, Vladan Minic, Danijela Tesendic, Evgeny Kadantsev, Julia Palamarchuk, and Mikhail Sofiev
Atmos. Meas. Tech., 17, 5051–5070, https://doi.org/10.5194/amt-17-5051-2024, 2024
We assess the suitability of a Rapid-E+ particle counter for use in pollen monitoring networks. The criterion was the ability of different devices to provide the same signal for the same pollen type, which would allow for unified reference libraries and recognition algorithms for Rapid-E+. We tested three devices and found notable differences between their fluorescence measurements. Each one showed potential for pollen identification, but the large variability between them needs to be addressed.
SORAS, A ground-based 110 GHz microwave radiometer for measuring the stratospheric ozone vertical profile in Seoul
Soohyun Ka and Jung Jin Oh
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-108,2024
Preprint under review for AMT (discussion: open, 0 comments)
We developed a ground-based 110.836 GHz radiometer developed to measure the stratospheric ozone profile over Seoul, Korea. To ensure precise measurements and correct the atmospheric spectrum, we employed hot-cold calibration along with continuous tipping curve calibration. Prior to the retrieval process, both pointing and frequency offsets were corrected. We provide stratospheric ozone profiles from 2016 to 2021 which are compared with collocated satellite observations.
This August, Japan and South Korea, particularly Japan, have experienced a dramatic surge in typhoon activity. From August 8 to August 13, within just six days, Typhoons Maria, Son-Tinh, Ampil, and Wukong consecutively formed over the waters east of Japan. Among them, Tropical Storm Maria caused record-breaking rainfall in parts of northern Japan, while just a few days later, Typhoon Ampil arrived during Japan's Obon holiday week, causing significant damage in Japan.
Global estimates of 100-year return values of daily precipitation from ensemble weather prediction data
Florian Ruff and Stephan Pfahl
Nat. Hazards Earth Syst. Sci., 24, 2939–2952, https://doi.org/10.5194/nhess-24-2939-2024, 2024
High-impact river floods are often caused by extreme precipitation. Flood protection relies on reliable estimates of the return values. Observational time series are too short for a precise calculation. Here, 100-year return values of daily precipitation are estimated on a global grid based on a large set of model-generated precipitation events from ensemble weather prediction. The statistical uncertainties in the return values can be substantially reduced compared to observational estimates.
Recent large inland lake outbursts on the Tibetan Plateau: Processes, causes and mechanisms
Fenglin Xu, Yong Liu, Guoqing Zhang, Ping Zhao, R. Iestyn Woolway, Yani Zhu, Jianting Ju, Tao Zhou, Xue Wang, and Wenfeng Chen
Nat. Hazards Earth Syst. Sci. Discuss., https//doi.org/10.5194/nhess-2024-127,2024
Preprint under review for NHESS (discussion: open, 0 comments)
Glacial lake outbursts have been widely studied, but large inland lake outbursts have received less attention. Recently, with the rapid expansion of inland lakes, signs of potential outbursts have increased. However, the processes, causes, and mechanisms are still not well understood. Here, the outburst processes were investigated using a combination of field surveys, remote sensing mapping, and hydrodynamic modelling. The causes and mechanisms that triggered the two events were investigated.
Abstract
Synthetic Aperture Radar (SAR) has emerged as a pivotal technology in geosciences, offering unparalleled insights into Earth's surface. Indeed, its ability to provide high-resolution, all-weather, and day-night imaging has revolutionized our understanding of various geophysical processes. Recent advancements in SAR technology, that is, developing new satellite missions, enhancing signal processing techniques, and integrating machine learning algorithms, have significantly broadened the scope and depth of geosciences. Therefore, it is essential to summarize SAR's comprehensive applications for geosciences, especially emphasizing recent advancements in SAR technologies and applications. Moreover, current SAR-related review papers have primarily focused on SAR technology or SAR imaging and data processing techniques. Hence, a review that integrates SAR technology with geophysical features is needed to highlight the significance of SAR in addressing challenges in geosciences, as well as to explore SAR's potential in solving complex geoscience problems. Spurred by these requirements, this review comprehensively and in-depth reviews SAR applications for geosciences, broadly including various aspects in air-sea dynamics, oceanography, geography, disaster and hazard monitoring, climate change, and geosciences data fusion. For each applied field, the scientific advancements produced because of SAR are demonstrated by combining the SAR techniques with characteristics of geophysical phenomena and processes. Further outlooks are also explored, such as integrating SAR data with other geophysical data and conducting interdisciplinary research to offer comprehensive insights into geosciences. With the support of deep learning, this synergy will enhance the capability to model, simulate, and forecast geophysical phenomena with greater accuracy and reliability.
Author(s): R. Jorge, W. Dorland, P. Kim, M. Landreman, N. R. Mandell, G. Merlo, and T. Qian
Turbulent transport is regarded as one of the key issues in magnetic confinement nuclear fusion, both for tokamaks and stellarators. In this work, we show that a significant decrease in a microstability-based proxy, as opposed to a geometric one, for the turbulent heat flux, namely the quasilinear h…
[Phys. Rev. E 110, 035201] Published Tue Sep 03, 2024
Author(s): Timothée Devergne, Leon Huet, Fabio Pietrucci, and A. Marco Saitta
The computational exploration of reactive processes is challenging due to the requirement of thorough sampling across the free energy landscape using accurate ab initio methods. To address these constraints, machine learning potentials are employed, yet their training for this kind of problem is sti…
[Phys. Rev. E 110, L033301] Published Tue Sep 03, 2024
Nature Geoscience, Published online: 03 September 2024; doi:10.1038/s41561-024-01521-2
A global analysis of post-fire vegetation productivity recovery reveals that the recovery time shows spatial variations across vegetation types and regions. The dominant factors that influence the recovery time in the majority of the global burned area are the post-fire climate conditions, such as soil moisture, vapour pressure deficit and air temperature.
Abstract
The parameterizations of air-sea turbulent heat flux are one of the major bottlenecks in atmosphere-ocean coupled model development, which play a crucial role in sea surface temperature (SST) prediction. Recently, neural networks start to be applied for the development of parameterizations of interface turbulent heat flux. However, these new parameterizations are primairily developed for specific regions and have not been tested in real atmosphere-ocean coupled models. In this study, we propose a new air-sea heat flux parameterization using a physical-informed neural network (PINN) based on multiple observational data sets worldwide. Evaluated with an independent observation data set, it is shown that the PINN can significantly reduce the RMSE of latent heat flux by at least about 48.6% compared to three traditional bulk formulas. Moreover, the PINN can be flexibly updated with new observational data by transfer learning. To test the performance of the new parameterization in realistic application, we implement the PINN into a global ocean-atmosphere coupled model and make seasonal forecasts for the first time. The PINN markedly reduce the errors of equatorial SST forecast, indicating a good performance of the PINN-based air-sea turbulent heat flux scheme. Noticeably, due to limited observational data, the NN-based parameterizations tend to underestimate heat flux at high wind speeds compared with bulk formula-based parameterizations. With more data available at extreme conditions, the PINN can be improved via transfer learning and need to be futher evaluated. This study suggests that PINN-based air-sea heat flux parameterization is promising to improve SST simulation.
Abstract
Arctic cyclones are key drivers of sea ice and ocean variability. During the 2019–2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, joint observations of the coupled air-ice-ocean system were collected at multiple spatial scales. Here, we present observations of a strong mid-winter cyclone that impacted the MOSAiC site as it drifted in the central Arctic pack ice. The sea ice dynamical response showed spatial structure at the scale of the evolving and translating cyclonic wind field. Internal ice stress and ocean stress play significant roles, resulting in timing offsets between the atmospheric forcing and the ice response and post-cyclone inertial ringing in the ice and ocean. Ice motion in response to the wind field then forces the upper ocean currents through frictional drag. The strongest impacts to the sea ice and ocean from the passing cyclone occur as a result of the surface impacts of a strong atmospheric low-level jet (LLJ) behind the trailing cold front and changing wind directions between the warm-sector LLJ and post cold-frontal LLJ. Impacts of the cyclone are prolonged through the coupled ice-ocean inertial response. Local impacts of the approximately 120 km wide LLJ occur over a 12 hr period or less and at scales of a kilometer to a few tens of kilometers, meaning that these impacts occur at combined smaller spatial scales and faster time scales than most satellite observations and coupled Earth system models can resolve.
Abstract
Dry- and wet-bulb temperature (T
d
and T
w
) are usually to define heatwaves (HWs) which have been enhanced under anthropogenic climate change (ACC) and urbanization. However, responses of various types of HWs (i.e., dry HWs, only high T
d
; humid HWs, only high T
w
; hybrid HWs, both high T
d
and T
w
; total HWs, high T
d
or T
w
), to ACC and urbanization remain unknown. In this study, both observations and simulations show significantly increasing occurrence probability of total HWs over China during 1971–2020, whereas this increase is mainly reflected in hybrid HWs, followed by dry HWs and humid HWs. 68.2%–93.0% of the observed increases in the above four types of HWs can be attributed to ACC; on the other hand, urbanization tends to suppress humid HWs but enhance dry HWs, as a result of contributing to the increase of hybrid HWs by 10.9%. Under future ACC, total HWs are projected to be more frequent as expected, which is mainly sourced from the increasing hybrid HWs because dry/humid HWs are projected to be steady/downward. As a consequence, urban population exposure to ACC-induced total HWs would remarkably increase to 83.55 billion person-days by the 2090s, 89.5% of which can be attributed to hybrid HWs. Urbanization would amplify this population exposure of ACC-induced hybrid HWs from 74.79 billion person-days to 110.9 billion person-days. Our results underscore the importance of improving understanding of hybrid HWs in urban areas and developing targeted adaptation planning on a warmer planet.
Abstract
As a significant macrophysical property, cloud horizontal scales play a role in cloud radiation, precipitation and vertical cloud overlap. Until now, however, the mechanisms behind the variations in cloud scale distribution have received far less attention. This study utilizes active satellite data from 2007 to 2016 to investigate the spatiotemporal distribution of cloud horizontal scales, and explains the variations through two meteorological factors: wind shear and atmospheric stability. Cloud scales exhibit a distinct power-law behavior when scale break is not considered, and the power-law exponent β is a characteristic measure of cloud scale distribution. A smaller power-law exponent β indicates a higher frequency of large clouds. During boreal summer season, the amount of large clouds is extremely large south of the 40°S but rather small between 10°S and 20°S. As wind shear decreases or atmospheric stability increases, more large clouds occur globally. The underlying mechanisms might be associated with cloud entrainment which can be promoted by wind shear but inhibited by atmospheric stability. However, our analysis of the impacts of these two factors on cloud scale distribution across different regions and heights reveals that both wind shear and atmospheric stability play dual roles on the values of the exponent β. The potential physical mechanisms, including the effects of precipitation, are further discussed. It is observed that precipitation also exerts a dual impact on the values of the exponent β. These findings underscore the significance of considering the impacts of meteorological factors on cloud scale distribution in numerical weather prediction models.
Implementing the iCORAL (version 1.0) coral reef CaCO3 production module in the iLOVECLIM climate model
Nathaelle Bouttes, Lester Kwiatkowski, Manon Berger, Victor Brovkin, and Guy Munhoven
Geosci. Model Dev., 17, 6513–6528, https://doi.org/10.5194/gmd-17-6513-2024, 2024
Coral reefs are crucial for biodiversity, but they also play a role in the carbon cycle on long time scales of a few thousand years. To better simulate the future and past evolution of coral reefs and their effect on the global carbon cycle, hence on atmospheric CO2 concentration, it is necessary to include coral reefs within a climate model. Here we describe the inclusion of coral reef carbonate production in a carbon–climate model and its validation in comparison to existing modern data.
OpenFOAM-avalanche 2312: depth-integrated models beyond dense-flow avalanches
Matthias Rauter and Julia Kowalski
Geosci. Model Dev., 17, 6545–6569, https://doi.org/10.5194/gmd-17-6545-2024, 2024
Snow avalanches can form large powder clouds that substantially exceed the velocity and reach of the dense core. Only a few complex models exist to simulate this phenomenon, and the respective hazard is hard to predict. This work provides a novel flow model that focuses on simple relations while still encapsulating the significant behaviour. The model is applied to reconstruct two catastrophic powder snow avalanche events in Austria.
Refactoring the elastic–viscous–plastic solver from the sea ice model CICE v6.5.1 for improved performance
Till Andreas Soya Rasmussen, Jacob Poulsen, Mads Hvid Ribergaard, Ruchira Sasanka, Anthony P. Craig, Elizabeth C. Hunke, and Stefan Rethmeier
Geosci. Model Dev., 17, 6529–6544, https://doi.org/10.5194/gmd-17-6529-2024, 2024
Earth system models (ESMs) today strive for better quality based on improved resolutions and improved physics. A limiting factor is the supercomputers at hand and how best to utilize them. This study focuses on the refactorization of one part of a sea ice model (CICE), namely the dynamics. It shows that the performance can be significantly improved, which means that one can either run the same simulations much cheaper or advance the system according to what is needed.
