Feed aggregator | Отдел физики околоземного космического пространства

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.