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Within the next couple of years, the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) will start the deployment of its next-generation geostationary meteorological satellites. The Meteosat Third Generation (MTG) is composed of four imaging (MTG-I) and two sounding (MTG-S) platforms. The satellites are three-axis stabilized, unlike the two previous generations of Meteosat that were spin stabilized, and carry two sets of remote sensing instruments each. Hence, in addition to providing continuity, the new system will provide an unprecedented capability from geostationary orbit. The payload on the MTG-I satellites are the 16-channel Flexible Combined Imager (FCI) and the Lightning Imager (LI). The payloads on the MTG-S satellites are the hyperspectral Infrared Sounder (IRS) and a high-resolution Ultraviolet–Visible–Near-Infrared (UVN) sounder Sentinel-4/UVN, provided by the European Commission. Today, hyperspectral sounding from geostationary orbit is provided by the Chinese Fengyun-4A (FY-4A) satellite Geostationary Interferometric Infrared Sounder (GIIRS) instrument, and lightning mappers are available on FY-4A and on the National Oceanic and Atmospheric Administration (NOAA) GOES-16 and GOES-17 satellites. Consequently, the development of science and applications for these types of instruments have a solid foundation. However, the IRS, LI, and Sentinel-4/UVN are a challenging first for Europe in a geostationary orbit. The four MTG-I and two MTG-S satellites are designed to provide 20 and 15.5 years of operational service, respectively. The launch of the first MTG-I is expected at the end of 2022 and the first MTG-S roughly a year later. This article describes the four instruments, outlines products and services, and addresses the evolution of the further applications.

Hundreds of supercell proximity soundings obtained for field programs over the central United States are analyzed to reconcile differences in recent studies and to refine our knowledge of supercell environments. The large, storm-centric observation-based dataset and high vertical resolution of the sounding data provide an unprecedented look at supercell environments. Not surprisingly, storm-relative environmental helicity (SRH) is found to be larger in tornadic soundings than in nontornadic soundings. The primary finding that departs from previous studies is that storm-relative winds contribute substantially to the larger SRH. Stronger ground-relative winds and more rightward-deviant storm motions contribute to the larger storm-relative winds for the tornadic soundings. Spatial analyses of the soundings reveal lower near-ground pressure perturbations and stronger low- to midlevel cyclonic flow for the tornadic soundings, which suggests stronger mesocyclones, perhaps explaining the more rightward-deviant motions. Differences in the mean critical angle between the tornadic and nontornadic soundings are small and do not contribute to the larger mean SRH, but the tornadic soundings do have fewer instances of smaller (<60°) critical angles. Furthermore, the critical angle is shown to be a function of azimuth from the updraft. Other results include a low-to-the-ground (~250 m on average) hodograph kink for both the tornadic and nontornadic soundings and few notable differences in thermodynamic quantities, except for the expected lower LCLs related to higher RH for the tornadic soundings, somewhat smaller 0–3 km lapse rates in tornadic environments related to weaker/shallower capping inversions, and larger 0–3 km CAPE in near-field environments.

Subsurface reflectors in radar sounder data from the Mars Advanced Radar for Subsurface and Ionospheric Sounding instrument aboard the Mars Express spacecraft indicate significant dielectric contrasts between layers in the Martian Medusae Fossae Formation (MFF). Large density changes that create dielectric contrasts are less likely in deposits of volcanic ash, eolian sediments, and dust, and compaction models show that homogeneous fine‐grained material cannot readily account for the inferred density and dielectric constant where the deposits are more than a kilometer thick. The presence of subsurface reflectors is consistent with a multi‐layer structure of an ice‐poor cap above an ice‐rich unit analogous to the Martian Polar Layered Deposits. The volume of an ice‐rich component across the entire MFF below a 300–600 m dry cover corresponds to a global equivalent layer of water of ∼1.5 to ∼2.7 m or ∼30%–50% of the total estimated in the North Polar cap. Plain Language Summary The Medusae Fossae Formation (MFF), located near the equator of Mars along the dichotomy boundary between the lowlands of the northern hemisphere and the cratered highlands of the southern hemisphere, is one of the largest and least understood deposits on Mars. The Mars Advanced Radar for Subsurface and Ionospheric Sounding radar sounder detects echoes in MFF deposits that occur between the surface and the base which are interpreted as layers within the deposit like those found in Polar Layered Deposits of the North and South Poles. The subsurface reflectors suggest transitions between mixtures of ice‐rich and ice‐poor dust analogous to the multi‐layered, ice‐rich polar deposits. An ice‐rich part of the MFF deposit corresponds to the largest volume of water outside the polar caps, or a global equivalent layer of water of ∼1.5 to ∼2.7 m. Key Points Mars Advanced Radar for Subsurface and Ionospheric Sounding radar sounder data reveals layering in the Medusae Fossae Formation (MFF) deposits Layers are likely due to transitions between mixtures of ice‐rich and ice‐poor dust, analogous to those in Polar Layered Deposits An ice‐rich portion of the MFF deposit may contain the largest volume of water in the equatorial region of Mars

The increasing demands on lateritic gravels in road construction presently make it necessary to quantify the available resources that can be used in road construction. This study aims to estimate the tonnage and to valorize the lateritic gravels of the north flank of Mount Bangou (west Cameroon) in road construction. Interpretation of 48 vertical electrical soundings coupled with 20 pedological wells from five lateritic gravel sites was carried out to determine the thickness of the lateritic gravel level. The thickness of the lateritic gravel level obtained from the geoelectrical soundings is the greatest (8.88–12.45 m) compared to that obtained from the pedological wells (1.23–1.98 m), and thus shows the inadequacy of the pedological wells for the determination of the thickness of the lateritic gravels. Thus, the electrical resistivity method is appropriate to estimate the thickness of the lateritic gravel level. The lateritic gravels studied are characterized by the electrical resistivity curves of type K, HK, Q, QH, KQ, HKH, H, and KH. The medium-thick (8–36 m) and thick (13–44 m) zones are areas of high potential lateritic gravels. The proven reserves of lateritic gravels at the Chenye, Sekakouo, Bamendjou 1, Bamendjou 2, and Bangam sites are, respectively, 3,479,003 t, 1,389,522 t, 5,002,505 t, 839,455 t, and 2,663,105 t and can build, respectively, 53,298 m; 226,167 m; 131,574 m; 778,314 m and 401,068 m of road, either as a subgrade layer or sub-base layer.

A coherent portrayal of global bathymetry requires that depths are inferred between sparsely distributed direct depth measurements. Depths can be interpolated in the gaps using alternate information such as satellite‐derived gravity and a mapping from gravity to depth. We designed and trained a neural network on a collection of 50 million depth soundings to predict bathymetry globally using gravity anomalies. We find the best result is achieved by pre‐filtering depth and gravity in accordance with isostatic admittance theory described in previous predicted depth studies. When training the model, if the training and testing split is a random partition at the same resolution as the data, the training and testing sets will not be independent, and model misfit is underestimated. We solve this problem by partitioning the training and testing set with geographic bins. Our final predicted depth model improves on old predicted depth model RMSE by 16%, from 165 to 138 m. Among constrained grid cells, 80% of the predicted values are within 128 m of the true value. Improvements to this model will continue with additional depth measurements, but predictions at higher spatial resolution, being limited by upward continuation of gravity, should not be attempted with this method. Plain Language Summary Only a fraction of the seafloor has been mapped by shipboard measurements. In the unmapped regions of the ocean, we must estimate the depth of the seafloor using information from the Earth's gravity field. Models predicting seafloor depth using gravity typically determine the linear relationship between gravity and depth in some regions and use the established relationships to make global predicted depth maps. Here, we describe a new method for predicting depth globally using gravity, decades of shipboard depth measurements, and a neural network regression. Ultimately, our model shows a clear improvement over the reference model. Key Points We present a new method for global bathymetry prediction using a machine learning algorithm The new predicted depth model improves on the reference model by all error metrics

A three-dimensional electrical conductivity model of the mantle beneath South China is presented using the geomagnetic depth sounding method in this paper. The data misfit term in the inversion function is measured by the L1-norm to suppress the instability caused by large noises contained in the observed data. To properly correct the ocean effect in responses at coastal observatories, a high-resolution (1° × 1°) heterogeneous and fixed shell is included in inversion. The most striking feature of the obtained model is a continuous high-conductivity anomaly that is centered on ~(112° E, 27° N) in the mantle. The average conductivity of the anomaly appears to be two to four times higher than that of the global average models at the most sensitive depths (410–900 km) of geomagnetic depth sounding. Further analysis combining laboratory-measured conductivity models with the observed conductivity model shows that the anomaly implies excess temperature in the mantle. This suggests the existence of a mantle plume, corresponding to the Hainan plume, that originates in the lower mantle, passes through the mantle transition zone, and enters the upper mantle. Our electrical conductivity model provides convincing evidence for the mantle plume beneath South China.

The capability of all-sky microwave radiance assimilation in the Gridpoint Statistical Interpolation (GSI) analysis system has been developed at the National Centers for Environmental Prediction (NCEP). This development effort required the adaptation of quality control, observation error assignment, bias correction, and background error covariance to all-sky conditions within the ensemble–variational (EnVar) framework. The assimilation of cloudy radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) microwave radiometer for ocean fields of view (FOVs) is the primary emphasis of this study. In the original operational hybrid 3D EnVar Global Forecast System (GFS), the clear-sky approach for radiance data assimilation is applied. Changes to data thinning and quality control have allowed all-sky satellite radiances to be assimilated in the GSI. Along with the symmetric observation error assignment, additional situation-dependent observation error inflation is employed for all-sky conditions. Moreover, in addition to the current radiance bias correction, a new bias correction strategy has been applied to all-sky radiances. In this work, the static background error variance and the ensemble spread of cloud water are examined, and the levels of cloud variability from the ensemble forecast in single- and dual-resolution configurations are discussed. Overall, the all-sky approach provides more realistic simulated brightness temperatures and cloud water analysis increments, and improves analysis off the west coasts of the continents by reducing a known bias in stratus. An approximate 10% increase in the use of AMSU-A channels 1–5 and a 12% increase for channel 15 are also observed. The all-sky AMSU-A radiance assimilation became operational in the 4D EnVar GFS system upgrade of 12 May 2016.

The polar-orbiting meteorological satellites operating in an observing system composed of early morning (EM), midmorning (AM), and afternoon (PM) orbits are extremely important to global numerical weather prediction (NWP). Following the proposal of World Meteorological Organization (WMO), the China Meteorological Administration (CMA) launched Fengyun-3E ( FY-3E ), the world’s first EM-orbit meteorological satellite for civil use, on 5 July 2021. With 11 scientific instruments on board, FY-3E is capable of providing atmospheric sounding, low-light imaging, sea surface wind detection, and space weather monitoring. Six months after launch, we have finished the postlaunch test for all the payloads. This paper presents the FY-3E data obtained during the 6-month test period, their performance, and key geophysical products driven ready for downstream applications. Experiments have been conducted to better disseminate the sounding data within the 6-h NWP assimilation window. Further efforts have been made to benefit data application for severe weather monitoring, diurnal cycle of Earth data, quasi-continuous sun monitoring for space weather, and climate research.

The authors analyze the column-integrated moist static energy budget over the region of the tropical Indian Ocean covered by the sounding array during the Cooperative Indian Ocean Experiment on Intraseasonal Variability in the Year 2011 (CINDY2011)/Dynamics of the Madden–Julian Oscillation (DYNAMO) field experiment in late 2011. The analysis is performed using data from the sounding array complemented by additional observational datasets for surface turbulent fluxes and atmospheric radiative heating. The entire analysis is repeated using the ECMWF Interim Re-Analysis (ERA-Interim). The roles of surface turbulent fluxes, radiative heating, and advection are quantified for the two MJO events that occurred in October and November using the sounding data; a third event in December is also studied in the ERA-Interim data. These results are consistent with the view that the MJO’s moist static energy anomalies grow and are sustained to a significant extent by the radiative feedbacks associated with MJO water vapor and cloud anomalies and that propagation of the MJO is associated with advection of moist static energy. Both horizontal and vertical advection appear to play significant roles in the events studied here. Horizontal advection strongly moistens the atmosphere during the buildup to the active phase of the October event when the low-level winds switch from westerly to easterly. Horizontal advection strongly dries the atmosphere in the wake of the active phases of the November and December events as the westerlies associated with off-equatorial cyclonic gyres bring subtropical dry air into the convective region from the west and north. Vertical advection provides relative moistening ahead of the active phase and drying behind it, associated with an increase of the normalized gross moist stability.

Observed proximity soundings from Europe are used to highlight how well environmental parameters discriminate different kind of severe thunderstorm hazards. In addition, the skill of parameters in predicting lightning and waterspouts is also tested. The research area concentrates on central and western European countries and the years 2009–15. In total, 45 677 soundings are analyzed including 169 associated with extremely severe thunderstorms, 1754 with severe thunderstorms, 8361 with nonsevere thunderstorms, and 35 393 cases with nonzero convective available potential energy (CAPE) that had no thunderstorms. Results indicate that the occurrence of lightning is mainly a function of CAPE and is more likely when the temperature of the equilibrium level drops below −10°C. The probability for large hail is maximized with high values of boundary layer moisture, steep mid- and low-level lapse rates, and high lifting condensation level. The size of hail is mainly dependent on the deep layer shear (DLS) in a moderate to high CAPE environment. The likelihood of tornadoes increases along with increasing CAPE, DLS, and 0–1-km storm-relative helicity. Severe wind events are the most common in high vertical wind shear and steep low-level lapse rates. The probability for waterspouts is maximized in weak vertical wind shear and steep low-level lapse rates. Wind shear in the 0–3-km layer is the best at distinguishing between severe and extremely severe thunderstorms producing tornadoes and convective wind gusts. A parameter WMAXSHEAR multiplying square root of 2 times CAPE (WMAX) and DLS turned out to be the best in distinguishing between nonsevere and severe thunderstorms, and for assessing the severity of convective phenomena.