Abstract
Sub-seasonal to seasonal (S2S) prediction provides an extended range of lead time for decision-makers across multiple sectors. S2S forecast is crucial for a country that are susceptible to hydro-meteorological disasters like Nepal. However, S2S forecast requires assessment with reliable datasets before its application. Since, Nepal lacks a dense station network, multi-source precipitation estimates (MPEs) are the obvious alternatives. Therefore, using classical evaluation metrics and extreme precipitation indices, this study assessed eleven high-resolution datasets against 159-gauge stations over Nepal for the 2001–2020 period. These datasets are classified as gauge-interpolated (APHRODITE), merged (TPMFD, MSWEP, CLDAS, and CHIRPS), satellite-based (IMERGV7, IMERGV6, CMORPH, and PERSIANN), and reanalysis (ERA5-L and HAR). Satellite datasets (except IMERGV7) failed to capture the spatial pattern of mean annual precipitation, while others broadly captured it. Most MPEs struggled to accurately estimate wet season precipitation compared to dry season. Furthermore, increasing estimation error from light to extreme precipitation and decreasing skill metrics from flat to complex terrain, demonstrate the intensity and terrain-specific limitations of MPEs. In terms of precipitation extremes, APHRODITE exhibits the highest skill, followed by MSWEP, TPMFD, HAR, ERA5-L, IMERGV7, CLDAS, IMERGV6, CHIRPS, CMORPH, and PERSIANN. IMERGV7 exhibits increased skill in detecting extreme precipitation and precipitation over orography against IMERGV6. APHRODITE and TPMFD datasets performed consistently well in all scales, including weekly anomaly, with an average anomaly correlation of 0.84 and 0.66 respectively. However, since APHRODITE is not widely available, TPMFD can serve as a benchmark dataset for evaluating high-resolution S2S forecasts within the study region.
Abstract
Using the High attitude Interferometer WIND observation balloon and Antarctic Jang Bogo station high latitude conjugate observations of the thermospheric winds we investigate the seasonal and hemispheric differences between the northern and southern hemispheres in June 2018. We found that the summer (northern) hemisphere dayside meridional winds have a double-hump feature, whereas in the winter (southern) hemisphere the dayside meridional winds have a single hump feature. We attribute that to stronger summer, perhaps, northern hemisphere cusp heating. We also compared the observation with NCAR Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) model. The TIEGCM reproduced the double-hump feature because of added cusp heating. The summer hemisphere has stronger anti-sunward winds. This is the first time we have very high latitude conjugate thermospheric wind observations.
Abstract
Recent simulation studies using the RAM-SCB model showed that proton precipitation contributes significantly to the total energy flux deposited into the subauroral ionosphere thereby affecting the magnetosphere-ionosphere coupling. In this study, we use the BATS-R-US + RAM-SCB model to understand the evolution of ElectroMagnetic Ion Cyclotron (EMIC) waves in the inner magnetosphere, their correspondence to the proton precipitation into the subauroral ionosphere, and to assess the performance of the model in reproducing the EMIC wave-particle interactions. During the 27 May 2017 storm, Arase and RBSP-A satellites observed typical signatures of EMIC waves in the inner magnetosphere. Within this interval, Defense Meteorological Satellite Program (DMSP) and National Oceanic and Atmospheric Administration (NOAA)/MetOp satellites observed significant proton precipitation in the dusk-midnight sector. Simulation results show that H- and He-band EMIC waves are excited within regions of strong temperature anisotropy near the plasmapause. The simulated growth rates of EMIC waves show a similar trend to that of the EMIC wave power observed by the Arase and RBSP-A satellites, suggesting that the model can reproduce the EMIC wave activity qualitatively. The simulated H-band waves in the dusk sector are stronger than He-band waves possibly due to the presence of excess protons in the boundary conditions obtained from the BATS-R-US code. The precipitating proton fluxes reproduced by the simulation with EMIC waves are found to agree reasonably well with the DMSP and NOAA/MetOp satellite observations. It is suggested that EMIC wave scattering of ring current ions can account for proton precipitation observed by the DMSP and MetOp satellites during the 27 May 2017 storm.
Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, 2024
We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, 2024
This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Geostationary aerosol retrievals of extreme biomass burning plumes during the 2019–2020 Australian bushfires
Daniel J. V. Robbins, Caroline A. Poulsen, Steven T. Siems, Simon R. Proud, Andrew T. Prata, Roy G. Grainger, and Adam C. Povey
Atmos. Meas. Tech., 17, 3279–3302, https://doi.org/10.5194/amt-17-3279-2024, 2024
Extreme wildfire events are becoming more common with climate change. The smoke plumes associated with these wildfires are not captured by current operational satellite products due to their high optical thickness. We have developed a novel aerosol retrieval for the Advanced Himawari Imager to study these plumes. We find very high values of optical thickness not observed in other operational satellite products, suggesting these plumes have been missed in previous studies.
Performance evaluation of MeteoTracker mobile sensor for outdoor applications
Francesco Barbano, Erika Brattich, Carlo Cintolesi, Abdul Ghafoor Nizamani, Silvana Di Sabatino, Massimo Milelli, Esther E. M. Peerlings, Sjoerd Polder, Gert-Jan Steeneveld, and Antonio Parodi
Atmos. Meas. Tech., 17, 3255–3278, https://doi.org/10.5194/amt-17-3255-2024, 2024
The characterization of the urban microclimate starts with atmospheric monitoring using a dense array of sensors to capture the spatial variations induced by the different morphology, land cover, and presence of vegetation. To provide a new sensor for this scope, this paper evaluates the outdoor performance of a commercial mobile sensor. The results mark the sensor's ability to capture the same atmospheric variability as the reference, making it a valid solution for atmospheric monitoring.
Impact ionization double peaks analyzed in high temporal resolution on Solar Orbiter
Samuel Kočiščák, Andreas Kvammen, Ingrid Mann, Nicole Meyer-Vernet, David Píša, Jan Souček, Audun Theodorsen, Jakub Vaverka, and Arnaud Zaslavsky
Ann. Geophys., 42, 191–212, https://doi.org/10.5194/angeo-42-191-2024, 2024
In situ observations are crucial for understanding interplanetary dust, yet not every spacecraft has a dedicated dust detector. Dust encounters happen at great speeds, leading to high energy density at impact, which leads to ionization and charge release, which is detected with electrical antennas. Our work looks at how the transient charge plume interacts with Solar Orbiter spacecraft. Our findings are relevant for the design of future experiments and the understanding of present data.
Application of generalized aurora computed tomography to the EISCAT_3D project
Yoshimasa Tanaka, Yasunobu Ogawa, Akira Kadokura, Takehiko Aso, Björn Gustavsson, Urban Brändström, Tima Sergienko, Genta Ueno, and Satoko Saita
Ann. Geophys., 42, 179–190, https://doi.org/10.5194/angeo-42-179-2024, 2024
We present via simulation how useful monochromatic images taken by a multi-point imager network are for auroral research in the EISCAT_3D project. We apply the generalized-aurora computed tomography (G-ACT) to modeled multiple auroral images and ionospheric electron density data. It is demonstrated that G-ACT provides better reconstruction results than the normal ACT and can interpolate ionospheric electron density at a much higher spatial resolution than observed by the EISCAT_3D radar.
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, 2024
Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
GNNWR: An Open-Source Package of Spatiotemporal Intelligent Regression Methods for Modeling Spatial and Temporal Non-Stationarity
Ziyu Yin, Jiale Ding, Yi Liu, Ruoxu Wang, Yige Wang, Yijun Chen, Jin Qi, Sensen Wu, and Zhenhong Du
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-62,2024
Preprint under review for GMD (discussion: open, 1 comment)
In geography, understanding how relationships between different factors change over time and space is crucial. This study implements two neural network-based spatiotemporal regression models as well as an open-sourced Python package named GNNWR, to accurately capture the varying relationships between factors. This makes it a valuable tool for researchers in various fields, such as environmental science, urban planning, and public health.
Abstract
In recent studies, two-dimensional propagation model of fast magnetosonic (MS) waves has been proposed to interpret the satellite observations of MS waves knocking into a density boundary. Although the theoretical model is able to capture the main properties of the two-dimensional propagation of MS waves, quantitative description about the MS wave behaviors has not been given yet. Here, with the assumption of a parabolic function for the potential function near its minimum, we solve the wave equation only with a potential function to obtain the reflection coefficients. It is found that the wave equation with a potential function can describe the full reflection and full transmission of MS waves rather well. Furthermore, the first-order derivative term in the wave equation is utilized to modify the reflection coefficient when the minimum of the potential function is near zero. Our result is helpful for further understanding the two-dimensional propagation of MS waves.
Abstract
Plateau pikas, small mammals native to the Qinghai-Tibet Plateau (QTP), create bare patches through burrowing. No previous assessment exists on their impact on permafrost. This study fills this gap by simulating hypothetical scenarios in the Three Rivers Headwaters Region of the QTP using the Noah-MP model for the plant growing seasons during 2015–2018. Our findings reveal a significant increase in soil temperature in the active layer due to pika-induced bare patches, particularly during July–August. The average temperature rise at 2.5 cm depth was 0.36°C in permafrost regions and 0.29°C in seasonally frozen ground regions during August. Minimal impact on unfrozen water content was observed, with a slight increase in deep soil layers in permafrost regions, and negligible in seasonally frozen areas. These findings underscore the previously unexplored influence of pika burrowing on permafrost temperature, suggesting a potential risk of accelerating permafrost degradation, especially in permafrost-dominated regions.
Abstract
Elastic properties of Si0.95H0.21O2 with hydrogarnet substitution (4H+ = Si4+) across the post-stishovite transition (28–42 GPa) are determined up to 70 GPa using ab initio calculations and a pseudo-proper type Landau model. At 28 GPa, elastic coefficients C
11 and C
12 converge, and the average shear and compressional velocity (V
S
and V
P
) decrease by a maximum of 25.5% and 5.2%, respectively. Hydrogarnet substitution reduces ambient elastic moduli and sound velocities, and shifts shear softening to lower pressure. 2%–13% Si0.95H0.21O2 may cause a V
S
anomaly of −0.5% to −2.6% at 700–820 km depth, explaining low V
S
layers beneath North America and the European Alps. Additionally, 20 vol % SiO2 in subducted basalt, with decreasing water content from 3.2 wt% to zero, could cause a V
S
anomaly of up to −7(4) % from 700 to 1,900 km depth, aligning with seismic scatterers identified in some subduction regions.
Abstract
An unexpected Mw7.45 earthquake struck the Noto Peninsula on 1 January 2024, preceded by several long-living earthquake swarms, providing a valuable opportunity to study seismic and aseismic slips, as well as their interactions. We derived coseismic and 19-day postseismic slip distributions by inverting co- and post-seismic displacements from Global Navigation Satellite System (GNSS) data. The inverted coseismic slip distribution shows two slip patches, with a maximum slip of ∼4 m. The early postseismic afterslip is 0.1–0.25 m within coseismic slip asperity and 0.1–0.6 m northward of the rupture area. The afterslip within the rupture area is accompanied by numerous aftershocks and coincides with a ∼6 MPa stress drop, suggesting that aftershocks are likely driven by the afterslip. The pattern of poroelastic rebound implies a potential effect of fluid flow on aftershock triggering. This study sheds lights on the intricate interplay between seismic and aseismic processes following large earthquakes.
