Incremental analysis update (IAU) in the Model for Prediction Across Scales coupled with the Joint Effort for Data assimilation Integration (MPAS–JEDI 2.0.0)
Soyoung Ha, Jonathan J. Guerrette, Ivette Hernández Baños, William C. Skamarock, and Michael G. Duda
Geosci. Model Dev., 17, 4199–4211, https://doi.org/10.5194/gmd-17-4199-2024, 2024
To mitigate the imbalances in the initial conditions, this study introduces our recent implementation of the incremental analysis update (IAU) in the Model for Prediction Across Scales – Atmospheric (MPAS-A) component coupled with the Joint Effort for Data assimilation Integration (JEDI) through the cycling system. A month-long cycling run demonstrates the successful implementation of the IAU capability in the MPAS–JEDI cycling system.
Atmospheric motion vector (AMV) error characterization and bias correction by leveraging independent lidar data: a simulation using an observing system simulation experiment (OSSE) and optical flow AMVs
Hai Nguyen, Derek Posselt, Igor Yanovsky, Longtao Wu, and Svetla Hristova-Veleva
Atmos. Meas. Tech., 17, 3103–3119, https://doi.org/10.5194/amt-17-3103-2024, 2024
Accurate global wind estimation is crucial for weather prediction and environmental modeling. Our study investigates a method to refine atmospheric motion vectors (AMVs) by comparing them with high-precision active-sensor winds. Leveraging supervised learning, we discovered that using high-precision active-sensor data can significantly reduce biases in passive-sensor winds in addition to providing estimates of the wind errors, thereby improving their reliability.
Intercomparison of AOD retrievals from GAW-PFR and SKYNET sun photometer networks and the effect of calibration
Angelos Karanikolas, Natalia Kouremeti, Monica Campanelli, Victor Estellés, Masahiro Momoi, Gaurav Kumar, and Stelios Kazadzis
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-84,2024
Preprint under review for AMT (discussion: open, 0 comments)
Different sun photometer networks use different instruments, post processing algorithms and calibration protocols for aerosol optical depth (AOD) retrieval. Such differences can affect the homogeneity and comparability of their measurements. In this study, we assess the homogeneity between the sun photometer networks GAW-PFR and SKYNET analysing common measurements during 3 campaigns between 2017–2021 and investigate the main cause of the differences.
Simulating sea level extremes from synthetic low-pressure systems
Jani Särkkä, Jani Räihä, Mika Rantanen, and Matti Kämäräinen
Nat. Hazards Earth Syst. Sci., 24, 1835–1842, https://doi.org/10.5194/nhess-24-1835-2024, 2024
We study the relationship between tracks of low-pressure systems and related sea level extremes. We perform the studies by introducing a method to simulate sea levels using synthetic low-pressure systems. We test the method using sites located along the Baltic Sea coast. We find high extremes, where the sea level extreme reaches up to 3.5 m. In addition, we add the maximal value of the mean level of the Baltic Sea (1 m), leading to a sea level of 4.5 m.
Modelling seismic ground motion and its uncertainty in different tectonic contexts: challenges and application to the 2020 European Seismic Hazard Model (ESHM20)
Graeme Weatherill, Sreeram Reddy Kotha, Laurentiu Danciu, Susana Vilanova, and Fabrice Cotton
Nat. Hazards Earth Syst. Sci., 24, 1795–1834, https://doi.org/10.5194/nhess-24-1795-2024, 2024
The ground motion models (GMMs) selected for the 2020 European Seismic Hazard Model (ESHM20) and their uncertainties require adaptation to different tectonic environments. Using insights from new data, local experts and developments in the scientific literature, we further calibrate the ESHM20 GMM logic tree to capture previously unmodelled regional variation. We also propose a new scaled-backbone logic tree for application to Europe's subduction zones and the Vrancea deep seismic source.
