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Sea surface winds influence shipping, fisheries, and coastal projects. However, the current sea surface wind forecast exhibits noticeable biases. This study introduces a deep learning (DL)-based bias correction model, WindNet, to improve the Global Forecast System (GFS) sea surface wind field forecast in the Northwest Pacific Ocean (NWPO). WindNet reduces the Root Mean Squared Errors (RMSEs) of wind speed at lead times of 24, 48, and 72 hr from 1.41–1.95 to 1.11–1.55 m s−1, achieving percentage reductions of 20.51%–21.28%. Simultaneously, the RMSEs of wind direction are reduced from 29.67–41.45° to 25.38–36.81°, demonstrating percentage reductions of 11.19%–14.46%. During typhoon passages, the RMSEs of wind speed and direction at three forecast lead times after using WindNet are reduced from 1.57–2.42 to 1.24–1.95 m s−1 and from 30.31–42.35° to 25.88–37.64°, demonstrating percentage reductions of 19.42%–21.02% and 11.12%–14.62%. By integrating a Squeeze-and-Excitation Network into WindNet, we find that utilizing information from the circulation field, apart from the zonal and meridional wind components at 10 m height, is crucial for the correction of the sea surface wind speed. WindNet can effectively capture the non-linear relationship between other low-level-circulation-related variables and sea surface wind speed. Therefore, WindNet remarkably enhances sea surface wind field forecast accuracy in NWPO.

Explicitly Resolving Lightning and Electrification Processes From the 10–12 April 2019 Thundersnow Outbreak

JGR–Atmospheres - Wed, 06/26/2024 - 20:13

Abstract

The 10–12 April 2019 thundersnow (i.e., lightning within snowfall) outbreak was examined via ground- and space-based lightning observations and was simulated using a numerical weather prediction model with an explicit electrification parameterization. When compared to observations, the simulation propagated the synoptic snowband two to six hours faster while also exaggerating the 3-D reflectivity structure. Throughout the event, the simulation produced 1,733 thundersnow flashes which was less than what was observed by ground- and space-based lightning sensors. In general, simulated thundersnow flashes were spatially offset from the largest reflectivities within the synoptic snowband and tended to occur within elevated convection that traversed isentropically along the top of mid-level frontogenesis. These simulated thundersnow flashes were associated with a tripole charge structure with ice/snow hydrometeors contributing most to the main negative charge region. Both simulated and observed thundersnow flashes initiated in conditionally unstable environments. Lastly, a conceptual model was developed to explain the spatial separation between the largest reflectivities in the snowband and the occurrence of thundersnow. It is hypothesized that the spatial offset of thundersnow initiation from the reflectivity cores within the synoptic snowband arose from a thermal circulation—induced by mid-level frontogenesis—that advects positively charged ice/snow hydrometeors toward the surface and creates a nearly homogeneous vertical charge structure.

Enrichment of Phosphates, Lead, and Mixed Soil‐Organic Particles in INPs at the Southern Great Plains Site

JGR–Atmospheres - Wed, 06/26/2024 - 19:51

Abstract

Ice nucleating particles (INPs) are rare particles that initiate primary ice formation, a critical step required for subsequent important cloud microphysical processes that ultimately govern cloud phase and cloud radiative properties. Laboratory studies have found that organic-rich dusts, such as those found in soils, are more efficient INPs compared to mineral dust. However, the atmospheric relevance of these organic-rich dusts are not well understood, particularly in regions with significant agricultural activity. The Agricultural Ice nuclei at the Southern Great Plains field campaign (AGINSGP) was conducted in rural Oklahoma to investigate how soil dusts contribute to INP populations in the Great Plains. We present chemical characterization of ambient and ice crystal residual particles from a single day of sampling, using single particle mass spectrometry (SPMS) and scanning microscopy. Ambient particles were primarily carbonaceous or secondary aerosol, while the fraction of dust particles was higher in the residual particles. We also observed an unusual particle type consisting of a carbonaceous core mixed with dust fragments on the surface, which was found in higher proportion in residuals. Dust particles measured during residual sampling contained greater proportions of phosphate (63PO2− ${\text{PO}}_{2}^{-}$ and 79PO3− ${\text{PO}}_{3}^{-}$) and lead (206Pb+). Strong sulfate signals were not seen in the residual dust particles measured by the SPMS, while nitrate was slightly depleted relative to ambient dust. This study shows that organic-rich soils may be important contributors to the ambient INP population in agricultural regions.

Lithological Impact on Radon Levels: A Study of Indoor and Soil Gas Radon in the Centre Region of Cameroon

JGR–Atmospheres - Wed, 06/26/2024 - 19:36

Abstract

The objectives of the current study are to carry out soil gas radon (Rn) measurements, to evaluate the total inhalation effective dose, to determine risk levels over the lithological formations of the study area. The behavior investigation of Rn activity concentration distributions in dwellings and soils, and soil Rn mapping were also conducted. Soil gas Rn measurements were made at 102 sampling points by Markus 10 instrument. This data was combined with previously reported results from 140 indoor Rn RADTRAK dosimeters to determine the total inhalation effective dose and to conduct a statistical analysis. Overall, the Rn activity concentrations in soil and dwellings range from 4 to 66 kBq m−3 and from 15 to 140 Bq m−3, with averages of 31 ± 15 kBq m−3 and 41 ± 24 Bq m−3 respectively. The corresponding total inhalation effective dose ranges from 0.35 to 3.53 mSv y−1, with a mean value of 1.37 ± 0.58 mSv y−1. For soil gas Rn, the chlorite schist lithology showed the highest average concentration level. Which could be justified by the possible presence, within chlorite minerals, highly emitting zones of alpha particles, leading to the formation of radioactive halos. Normal and high-risk level of Rn were found for about 82% and 11% of the total area surveyed respectively. These findings highlight the need for preventive measure against Rn exposure in homes within the investigated areas. This study contributes valuable insights into Rn distribution patterns and risk assessment, offering a basis for targeted interventions in the region.

Refining Planetary Boundary Layer Height Retrievals From Micropulse‐Lidar at Multiple ARM Sites Around the World

JGR–Atmospheres - Wed, 06/26/2024 - 19:35

Abstract

Knowledge of the planetary boundary layer height (PBLH) is crucial for various applications in atmospheric and environmental sciences. Lidar measurements are frequently used to monitor the evolution of the PBLH, providing more frequent observations than traditional radiosonde-based methods. However, lidar-derived PBLH estimates have substantial uncertainties, contingent upon the retrieval algorithm used. In addressing this, we applied the Different Thermo-Dynamic Stabilities (DTDS) algorithm to establish a PBLH data set at five separate Department of Energy's Atmospheric Radiation Measurement sites across the globe. Both the PBLH methodology and the products are subject to rigorous assessments in terms of their uncertainties and constraints, juxtaposing them with other products. The DTDS-derived product consistently aligns with radiosonde PBLH estimates, with correlation coefficients exceeding 0.77 across all sites. This study delves into a detailed examination of the strengths and limitations of PBLH data sets with respect to both radiosonde-derived and other lidar-based estimates of the PBLH by exploring their respective errors and uncertainties. It is found that varying techniques and definitions can lead to diverse PBLH retrievals due to the inherent intricacy and variability of the boundary layer. Our DTDS-derived PBLH data set outperforms existing products derived from ceilometer data, offering a more precise representation of the PBLH. This extensive data set paves the way for advanced studies and an improved understanding of boundary-layer dynamics, with valuable applications in weather forecasting, climate modeling, and environmental studies.

Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?

Geoscientific Model Development - Wed, 06/26/2024 - 18:17

Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, 2024
Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.

Updates and evaluation of NOAA’s online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System

Geoscientific Model Development - Wed, 06/26/2024 - 18:17

Updates and evaluation of NOAA’s online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, Raffaele Montuoro, and Robert C. Gilliam
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-107,2024
Preprint under review for GMD (discussion: open, 0 comments)
The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during August 2023 shows that the updated model greatly improves the simulation of MDA8 O3 by reducing the bias by 72 % in the contiguous US. PM2.5 prediction is only enhanced in regions less affected by wildfire, highlighting the need for future refinements.

An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation

Geoscientific Model Development - Wed, 06/26/2024 - 18:17

An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev. Discuss., https//doi.org/10.5194/gmd-2024-109,2024
Preprint under review for GMD (discussion: open, 0 comments)
This study updates CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosols (SOA) formation. Dust emission modifications make deflation areas more continuous, improving results in North America and the subarctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation, advance CESM's aerosol modelling results.