Radiance measurements of solar radiation that is backscattered by the Earth׳s atmosphere or surface contain information about the atmospheric composition and the state of the Earth׳s surface. ...Retrieving such information from satellite-based observations in nadir geometry employs a radiative transfer forward model. The forward model simulates the observed quantity, aiming to reproduce the observation.
LINTRAN v2.0 is a linearised vector radiative transfer forward model, employing forward-adjoint theory, that is capable of modelling cloud contaminated satellite observations and their derivatives with respect to the state of the atmosphere and the Earth׳s surface in a numerically efficient manner. A significant gain in efficiency with respect to its predecessor (LINTRAN v1.0) is achieved through a mathematical framework that combines an approximate iterative solving method using the forward-adjoint perturbation theory with separation of the first N orders of scattering from the diffuse intensity vector field. Contributions to the observable up to order of scattering N are recursively solved in an analytical manner. Contributions from higher orders of scattering are subsequently solved in a numerical manner, assuming that the intensity field varies linearly with the vertical coordinate within an optically homogeneous model layer. This method is implemented in LINTRAN v2.0, choosing N=2, within the general framework of forward-adjoint perturbation theory.
This new approach allows us to decrease the number of model layers and the degree of angular quadrature within the numerical solver by a factor of 10 and 1.4 respectively, compared to the previous model version, assuming a homogeneous atmosphere loaded with scattering Mie particles (size parameter χ≈35). In this homogeneous atmosphere, the reduced discretisation sampling in turn reduces the numerical effort associated with the numerical matrix solver by a factor of 42 relative to the previous model version, without a loss in model accuracy.
•We combine successive orders of scattering with forward-adjoint perturbation theory.•We analytically calculate double scattering intensities in cloudy atmospheres.•This reduces numerical effort 42 times assuming pure Mie scattering.
Satellite tropospheric propagation studies strongly rely on beacon receiver measurements. We were interested in performing a measurement campaign to characterize rain attenuation statistics. In this ...article, we outline some of the characteristics and drawbacks one faces when trying to perform a radio wave satellite beacon propagation experiment at the
-band with low-cost measurement equipment. We used an affordable beacon receiver consisting of a commercial low-noise block down-converter, an outdoor dual-reflector antenna, and a software-defined radio unit. To measure rain attenuation events, we needed to work out where the reference signal level was at all times. However, as we did not have a radiometer to remove the impact of gases and clouds, since it is a very expensive device, we used a procedure that involved the subtraction of a stable and reliable reference level (template) from the raw received beacon level. This template was extracted from observations during non-rainy periods. The procedure implemented for extracting the template was based on the same data processing methodology used by other authors in this field. Here, we describe through specific examples the main characteristics of the templates extracted on non-rainy days, as well as the impact of some meteorological parameters and unavoidable, but small antenna pointing errors.
Differential Global Positioning Systems (DGPS) and the European Geostationary Navigation Overlay Service (EGNOS) are included in a group of supporting systems (Ground-Based Augmentation System ...(GBAS)/Space-Based Augmentation System (SBAS)) for the American GPS. Their main task is to ensure better positioning characteristics (accuracy, reliability, continuity and availability) compared to GPS. Therefore, they are widely applied wherever GPS failures affect human safety, mainly in aviation, land and marine navigation. The aim of this paper is to assess the predictable positioning accuracy of DGPS and EGNOS receivers using a vessel manoeuvring in the Bay of Gdansk. Two receivers were used in the study: a Simrad MXB5 (DGPS) and a Trimble GA530 (EGNOS), which were simultaneously recording their coordinates. The obtained values were compared with the trajectory computed using a geodetic Global Navigation Satellite System (GNSS) receiver (Trimble R10) connected to a GNSS network, ensuring an accuracy of 2–3 cm (p = 0·95). During a four-hour measurement session, the accuracy statistics of these systems were determined based on around 11,500 positionings. Studies have shown that both positioning systems ensure a similar level of accuracy of their positioning services (approximately 0·5–2 m) and they meet the accuracy requirements set in published standards.
This paper proposes a convolutional neural network (CNN) method to estimate subsurface temperature (ST) in the Pacific Ocean from a suite of satellite remote sensing measurements. These include sea ...surface temperature(SST), sea surface height (SSH), and sea surface salinity (SSS). We propose using the multisource sea surface parameters to establish a monthly CNN model to reconstruct the ocean subsurface temperature (ST) and use Argo data for accurate validation. The results show that the CNN can accurately estimate the ST of the Pacific Ocean by using the model. We trained the model for 12 months. The most prominent months are January, April, July, and October with average mean square error (MSE) values of 0.2659, 0.3129, 0.5318, and 0.5160, and the average coefficients of determination (R 2 ) were 0.968, 0.971, 0.949, and 0.967, respectively. This study improves the accuracy of ST estimation and the good results based on reanalysis indicate that the model is promising to be applied to satellite observations.
We estimate the cooling flux from snow melting in the ocean through CloudSat satellite snowfall retrievals and reanalysis data. For snowfall events with less than 0.01 mm/hr, this flux is ...inconsequential. Melting snow begins to compete with other ocean surface heat fluxes as snowfall rates increase beyond 0.1 mm/hr, and it may often become the dominant heat flux as snowfall rates approach and exceed 1 mm/hr. The largest monthly average values of the melting snow cooling flux occur in winter months, approaching −10 W/m2 in both hemispheres. To determine the regional influence of melting snow on a seasonal basis, we calculate an impact metric that gauges the cooling flux of melting snow against the net flux in the ocean. This metric can be between 20% and 30% in the Northern Hemisphere during March, April, May; the Southern Ocean during March, April, May and September, October, November; and in high‐latitude polar oceans during sea ice freeze up seasons.
Plain Language Summary
Climate scientists are very interested in understanding how much heat is entering and leaving the ocean, as this heat budget has important connections to the weather, ocean, and ice patterns that are crucial to life as we know it. Melting snow cools the ocean surface, but this effect has not been studied as much as heat exchanges from wind or sunlight. Using satellites and weather models, we determine how much melting snow cools the ocean. The cooling from snowmelt is most often inconsequential, since most snowfall is light. During heavy snowstorms, however, the cooling from melting snow can become quite powerful, perhaps becoming the most powerful cooling source in the ocean at times. Melting snow also has a large impact on the ocean heat budget in polar oceans during sea ice freeze up seasons. This is an important result, as the loss of sea ice is one of the most visible and concerning signs of climate change today. Ultimately, we find that melting snow can be a powerful and influential cooling force in the ocean but only under appropriate circumstances.
Key Points
The cooling from melting snow in the ocean can be as strong as turbulent and radiative heat fluxes during heavy snow storms
At high latitudes, monthly average cooling fluxes from melting snow vary between 0 and ‐10 W/m2, depending on the season and latitude
Melting snow has a large influence on the ocean heat budget in high‐latitude oceans, especially during sea ice freeze up seasons
In 2019, the World Data Center for Solar-Terrestrial Physics in Moscow digitized the archive of observations of the Earth’s magnetic field carried out by the Soviet satellites Kosmos-49 (1964) and ...Kosmos-321 (1970). As a result, the scientific community for the first time obtained access to a unique digital data set, which was registered at the very beginning of the scientific space era. This article sets out three objectives. First, the quality of the obtained measurements is assessed by their comparison with the IGRF model. Second, we assess the quality of the models, which at that time were derived from the data of these two satellites. Third, we propose a new, improved model of the geomagnetic field secular variation based on the scalar measurements of the Kosmos-49 and Kosmos-321 satellites.
Graphical Abstract
Tracking Ultraviolet Set-up (TUS) on board the Lomonosov satellite measured the UV intensity pulsations in the auroral region. Sixty-four events with pulsations were registered during two measurement ...periods from 26 December 2016–10 January 2017 and 8–15 November 2017. During both periods, a high-intensity, long-duration, continuous auroral activity (HILDCAA) was detected. Simultaneous measurements in LEO by Lomonosov (DEPRON detector) and Meteor-M2 satellites show the enhanced fluxes of the trapped and precipitated energetic electrons in the region of the Earth’s outer radiation belt during these periods. We found that most of the UV-events correspond to energetic electron (E > 100 keV) precipitation. One can suggest that particles of these and higher energies cause a pulsating emission relatively deep in the atmosphere.
Biomass burning is a source of fine particulate matter (PM2.5) air pollution, which adversely impacts human health. However, quantifying the health effects from biomass burning PM2.5 is difficult. ...Monitoring networks generally lack the spatial density needed to capture the heterogeneity of biomass burning smoke. Satellite aerosol optical depth (AOD) can be used to fill spatial gaps but does not distinguish surface‐level aerosols. Plume height (PH) observations may provide constraints on the vertical distribution of smoke and its impact on surface concentrations. We assessed PH characteristics from Multi‐Angle Implementation of Atmospheric Correction (MAIAC) and evaluated its correlation with colocated PM2.5 and AOD measurements. PH is generally highest over the western United States. The ratio PM2.5:AOD generally decreases with increasing PH:PBLH (planetary boundary layer height), showing that PH has the potential to refine surface PM2.5 estimates for collections of smoke events.
COVID-19 lockdown has given us an opportunity to investigate the pollutant concentrations in response to the restricted anthropogenic activities. The atmospheric concentration levels of nitrogen ...dioxide (NO
2
), carbon monoxide (CO) and ozone (O
3
) have been analysed for the periods during the first wave of COVID-19 lockdown in 2020 (25th March–31st May 2020) and during the partial lockdowns due to second wave in 2021 (25th March–15th June 2021) across India. The trace gas measurements from Ozone Monitoring Instrument (OMI) and Atmosphere InfraRed Sounder (AIRS) satellites have been used. An overall decrease in the concentration of O
3
(5–10%) and NO
2
(20–40%) have been observed during the 2020 lockdown when compared with business as usual (BAU) period in 2019, 2018 and 2017. However, the CO concentration increased up to 10–25% especially in the central-west region. O
3
and NO
2
slightly increased or had no change in 2021 lockdown when compared with the BAU period, but CO showed a mixed variation prominently influenced by the biomass burning/forest fire activities. The changes in trace gas levels during 2020 lockdown have been predominantly due to the reduction in the anthropogenic activities, whereas in 2021, the changes have been mostly due to natural factors like meteorology and long-range transport, as the emission levels have been similar to that of BAU. Later phases of 2021 lockdown saw the dominant effect of rainfall events resulting in washout of pollutants. This study reveals that partial or local lockdowns have very less impact on reducing pollution levels on a regional scale as natural factors like atmospheric long-range transport and meteorology play deciding roles on their concentration levels.
PDF
