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Recently, a small rain radar in the 24GHz band is under development in Korea. This instrument is intended for the measurement of quantitative rainfall within a radius of 1 Km. Quantitative rainfall measurements for small watersheds are predicated on flood forecasting. The purpose of this device development was focused on the amount of rainfall reaching the ground rather than the amount of rainfall in the atmosphere. The device is currently being developed as a prototype and is undergoing various performance verification with the aim of commercialization.In this presentation, we show the comparison result of performance verification of small rain radar and show the performance superiority. In order to verify the performance of this device, it took a long time from the selection of the comparative verification site to the design and installation of a pit gauge. The comparative site was equipped with 2 parsivels, one pit gauge(composed of one weighing type of rain gauge and 12 tipping bucket type rain gauges) and 17 tipping bucket type gauges. The comparative analysis method of the measurement result converts the scanning result of this device into the reflectance and compares it with the verification device. [ABSTRACT FROM AUTHOR]

The Korean Peninsula experiences lots of rain every summer due to typhoons, rainstorms,and a localized heavy rain, etc. To predict those severe weather events, weather forecasts needto be accurate. High-resolution numerical weather prediction (NWP)-based approach is oneof available methods to fulfill such a task. However, operational weather centers havegenerally produced forecasts at regular intervals (e.g. 00, 06, 12, and 18 UTC), whichimplies that those forecasts could not be optimal to make an accurate prediction whenconsidering the high spatio-temporal variability of summer rainfall events in the KoreanPeninsula. In recent years, many high-performance community models have been developed andhave become available. Moreover, availability of observational data and global modelproducts also increases due to the advance in technology. Thus, the local-scale rainfallprediction system that produces short-range precipitation forecasts for specific regions can bebuilt using the aforementioned data and models. In this study, the community model-based short-range precipitation forecast system wasdeveloped and the system performance was evaluated. Radar and surface automated weatherstation (AWS) observation data of the Korea Meteorological Administration (KMA) wereassimilated into the developed NWP system which consists of Advanced Research WeatherResearch and Forecasting (WRF-ARW) model and Local Transform Ensemble Kalman Filter(LETKF) data assimilation to produce short-range precipitation forecasts. Observationoperators for radar observation were also developed. Compared to the operational modelwith regular initiation times of model integration, the system developed has theadvantage of being able to start model integration from any time when the userwants. WRF simulations were conducted for two weeks of summer for the KoreanPeninsula and simulation results were verified against observed precipitation data ofAWS. Simulation results reveal that performance of short-range precipitation forecasts from thecommunity model-based NWP system is comparable with that of the KMA UnifiedModel (UM) Local Data assimilation and Prediction System (LDPS). In particular, ahigher level of rain detection exists in this system when compared to the KMA UMLDPS. This study is worthwhile because it proves that the performance of the communitymodel-based NWP system using WRF and LETKF can be comparable to that of operationalNWP system, which provides opportunities for a near-real-time forecasts targeting severeprecipitation weather events. Acknowledgement This study was supported by a National Research Foundation of Korea (NRF) grantfunded by the South Korean government (Ministry of Science and ICT) (Grant2017R1E1A1A03070968). [ABSTRACT FROM AUTHOR]

Flash flood disaster occur frequently, causing major economic losses to society. The distribution of rainfall in mountainous areas is uneven and mostly is local heavy rains, which leads to inaccurate monitoring of rainfall data at ground rainfall stations and in turn leads to inaccurate flash flood forecasting. In order to study the application prospect of radar quantitative precipitation estimation in flash flood forecasting, taking the Guanshan River Basin as an example, Xin'anjiang model, SCS model and TOPMODEL model are used to simulate floods in the case of rainfall station rainfall or radar quantitative precipitation estimation as input conditions. The model parameters were calibrated by the 10 observed flood events from 2009-2011, and the 10 observed floods events from 2012-2015 were used to validate the performance of the model. The results show that under the condition of the radar quantitative precipitation estimation as input conditions, the simulation accuracy of Xin'anjiang model, SCS model and TOPMODEL model is improved. The Nash-Sutcliffe efficiency coefficient of the three models during the verification period increased from 45.28%, 42.37%, and 43.46% to 63.25%, 58.91%, and 61.34%, respectively. Therefore, the radar quantitative precipitation estimation can be considered as input condition for the flash flood forecasting of the Guanshan River Basin. [ABSTRACT FROM AUTHOR]

The intensity of return signal by the atmosphere depends mainly on the water vapor and on the thermal gradients resulting in the refraction. When the dielectric properties of the medium changes along the ultra-high frequency wave path, they induce a diffusion, reflection or refraction of the wave in any directions. In the clear atmosphere these phenomena are related to the air refractive index in function of pressure, temperature and humidity. The first source of the refractive index is the atmospheric turbulence which tends to mix air parcels with different properties. Wind profiler radar can retrieves wind vectors, heat fluxes, turbulent dissipation rate and boundary layer height. UHF Wind profiler radars are operated by the Korea Meteorological Administration at nine sites on the Korean Peninsula. Diurnal variations of the reflectivity, the vertical wind velocity and the turbulent dissipation rate show a typical clear air evolution. The maximum of reflectivity delineates the top of atmospheric boundary during the daytime. The turbulence is concentrated below this canopy with high value of dissipation rate between sunrise and sunset. The skewness coefficient is calculated with the Doppler velocity of vertical beam. It is so negative on average that the vertical velocity distribution spreads much more over the right side (toward updrafts). After sunset, when the turbulence ceases, a nocturnal low level jet may also develop and reach 15 m/s near a height of 400 m. [ABSTRACT FROM AUTHOR]

Quantitative precipitation estimation (QPE) from weather radar data is crucial forhydrological applications, which benefit of the high spatio-temporal resolution of X-bandradar imagery. Nonetheless, radar rainfall retrieval process involves a challenging correctionof reflectivity, which is particularly difficult for single polarized technology. In addition, highmountain topography as the Andean cordillera deeply increases the complexity of radar QPE.This study explores a Random Forest (RF), state-of-the-art data-driven model, for optimizingthe radar rainfall derivation of the highest X-band radar in the world (4450 m a.s.l.) by meansof single Plan Position Indicator (PPI) scans. Several features were derived from rawreflectivity to account for the evolution of rainfall along the beam. Performance of the RFmodel was evaluated in comparison with the well-known step-wise approach. Forthis, the Marshall-Palmer and a site-specific Z-R relationship were used. The biasadjustment step was omitted from the step-wise correction chain due to the lack ofevenly distributed gauge networks in mountain regions. Results showed that thestep-wise approach slightly improved when using the site-specific instead of theMarshall-Palmer Z-R relationship. However, both models performed poorly for radarQPE (R2 < 0.1). Conversely, the RF model remarkably outperformed the othermodels in all different testing locations and rainfall events (R2 up to 0.85). This is thefirst time a QPE random forest model is applied on single polarized X-band radarimagery. The results are outstanding and provide a simplified model to overcome thecomplexity of deriving QPE from single polarized radars. Further work will focus onblending techniques to enhance the radar rainfall maps obtained using this RF model. [ABSTRACT FROM AUTHOR]

Improving the accuracy of flood forecasting is critical in reducing the damage that can occur during flood disasters. In Japan, the flood prediction system is in operation in the first class rivers – relatively large and important rivers. However, small rivers, especially urban rivers, are so difficult to predict the river stage because of the quick rainfall-runoff responses. Such rivers are regarded as difficult to deliver the real time information on flood risk.Recently in Japan, X-band radar rainfall data can be used in real-time prediction for operation. X-band radar is highly resolution in both spatially and temporally. Furthermore, deep learning model has been applied to the river stage prediction and confirmed to have a good accuracy. By applying the X-band radar data to the deep learning model, river-stage prediction could be possible to the urban small rivers.In this study, we developed the deep learning river stage prediction model using the x-band radar rainfall data. We applied the model to the small urban rivers in Tokyo and confirmed the good prediction result. [ABSTRACT FROM AUTHOR]

The Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) on board the Mars Express spacecraft is a radar sounder used to probe the topside Martian ionosphere. MARSIS measures the electron density through both remote radar sounding and excitation of local plasma oscillations, providing a unique way to study the steep density gradient existing on the top of the dayside ionosphere, called the ionopause. Our ultimate goal is to address the conditions under which the Martian ionopause forms. This study, based on over ten thousand orbits from 2005 to 2017, shows that the ionopause occurs at altitudes between 250 km and 600 km, with a sharp cut-off altitude at 250 km for solar zenith angle (SZA) smaller than 70 degrees. Unlike the ionopause of Venus, which seems to appear almost all the time, the Martian ionopause is only observed in about 10% of all the orbits used in the study. In addition, the study shows that the ionopause mainly appears over weak crustal fields with a cut-off magnitude of ~10 nT. The dependence of the ionopause altitude on solar zenith angle, solar wind dynamic pressure, and solar EUV irradiance will also be discussed. [ABSTRACT FROM AUTHOR]

A wavelet based method for bathymetry retrieval from X-band radar images is proposed. Themethod combines traditional FFT techniques for retrieving peak frequency mapsby evaluation of spectral peaks in the time domain and localized 2D ContinuousWavelet Transform (CWT) for retrieving corresponding peak wavenumbers. Inorder to verify the proposed method 1D and 2D simulations of the wave shoalingover several bottom topographies based on a mild slope equation were performed.This model allows simulating wave shoaling and refraction. Wave breaking andreflection were neglected in our simulations. As a testing case, the shoaling of anincident monochromatic and JONSWAP spectrum-based wavefields were evaluated. Aradar image model including tilt and shadowing modulations together with specklenoise was applied to both 1D and 2D surface elevations. The method’s ability toreconstruct the original bathymetry is shown to be robust in intermediate to shallow waterdepths (kph < 1.2) for all the synthetic cases with varied probing geometry, bottomtopography and sea state conditions. After stochastic simulations checks, the methodwas also applied to the real data acquired by WaMoS system in Haifa Bay (Israel).Preliminary comparisons with known bathymetric surveys will be presented anddiscussed. [ABSTRACT FROM AUTHOR]

Accurate and timely hydrological forecasts highly depend on the meteorological input. Current numerical weather predictions (NWP) do not have sufficiently high spatial and temporal resolutions for adequate use for short lead times (<6 hours) in fast responding lowland and polder catchments. Radar nowcasting seems to be a solution and an increasing number of nowcasting algorithms is becoming available. However, best practice for the use and choice of these algorithms within operational forecasting systems is not available yet. In this study, we performed an analysis in time over 12 catchments in the Netherlands, by making use of state-of-the-art nowcasting algorithms (pySTEPS and SBMcast), benchmarking systems (RainyMotion) and the local NWP (HARMONIE). We focussed on the rainfall predictability of different nowcasting algorithms and the choice for simple advection, deterministic or probabilistic nowcasting. We quantified this as a function of lead time, rainfall type, initial conditions, catchment size and catchment location with regard to the radar rainfall estimates. [ABSTRACT FROM AUTHOR]

In this contribution we analyze the topographic influence on snow precipitation, in terms of variability and microphysics, by interpreting polarimetric radar data. The former is related to the dynamics i.e. growth and decay analysis of the snowfall field, obtained by re-sampling high resolution radar observations (83m in range). The latter is related to the 3D hydrometeor classification of precipitation, supplemented by the hydrometeor de-mixing approach. The analysis focuses on three different events observed in the region around the Weissfluhgipfel (WFG) radar, in the vicinity of Davos, in the Eastern Swiss Alps.The growth and decay analysis is based on the advection (semi-Lagrangian scheme) of the snowfall field and the comparison with the following actual measurement. Basically, we shift the precipitation field without incorporating the impact of the local topography and then compare it with the measurement which obviously accounts for the micro-scale influence. The growth and decay maps are obtained by averaging the instantaneous estimates over several different time periods (to smooth out the noise), allowing us to conduct analysis at various temporal resolutions.The applied hydrometeor classification is a semi-supervised approach, adapted to the technical specificities of a radar, capable of distinguishing between 9 different hydrometeor classes, among which rimed ice particles (RP), aggregates (AG), crystals (CR) and vertically aligned ice. An additional hydrometeor de-mixing step allows to estimate, beside the primary hydrometeor type, the proportions of secondary hydrometeor types present within radar sampling volumes, which proves to be very relevant for such a spatially concentrated study. Links between both variability (snowfall growth) and microphysics (intense riming + AG/CR co-occurrence) observation to the local topography are assessed through multi-scale spatial wavelet analysis. In particular, the gradient of the local topography in the direction of the flow is considered. The analysis shows a correspondence between the zones of snowfall growth on one side and the zones of relatively more intense riming and AG/CR co-occurrence on other side, as well as the interesting influence of the local topography at smaller scales. [ABSTRACT FROM AUTHOR]

The Global Precipitation Measurement (GPM) mission provides a new generation of precipitation measurements from space. In particular, Dual-frequency Precipitation Radar (DPR), on board the GPM core observatory, has the advantage in precipitation retrievals compared to its single-frequency counterparts on Tropical Rainfall Measurement Mission (TRMM). However, it is still challenging for DPR to obtain instantaneous rainfall rate with higher accuracy, especially for widely varying rainfall types (e.g., hurricane, storms, etc). In this study, we propose a hierarchal Bayesian approach for improving the DPR rainfall retrievals and perform an initial experiment in Southeastern United States (US), where the US Weather Service Dual-Polarization Radar network is used to obtain locally accurate rainfall estimates for each event. The analysis presented here demonstrates the feasibility of this method for enhancing the DPR instantaneous rainfall product. In summary, this approach demonstrates the potential for enhancing the GPM rainfall product. [ABSTRACT FROM AUTHOR]

An HF radar has been operating in the Gulf of Naples (Southeastern Tyrrhenian Sea) since 2004. The system is a SeaSonde manufactured by CODAR Ocean Sensors Ltd. Three mono-static radar units working at about 25 Mhz ensure the surface current mapping over nearly the entire Gulf of Naples area. The grid resolution is 1 Km with a range of approximately 40 Km. Usually HF radar data present gaps, especially near the open boundary where the performances of the system are reduced. A regular coverage with no gaps is essential to utilize HF radar-derived surface velocities in a number of applications which go beyond the straightforward local dynamics investigations, such as pollutant transport studies, search and rescue situations etc. It is thus necessary to apply interpolation processes aimed at obtaining a regular grid without gaps, plausibly characterized by a resolution equal to that of the system. In this work, three techniques are applied to fill the gaps in the hourly surface current fields. The techniques are: self organizing maps (SOM), open boundary modal analyses (OMA) and data interpolating empirical orthogonal functions (DINEOF). To establish which one is the best, we evaluated the error associated with each method. The error is obtained subtracting the actual radial surface current measured in a grid point from the value derived by one of the three techniques in the same point, assuming there an absence of measurement. The gaps are artificially created over different areas, of different size and differently distributed over the Gulf of Naples, following two approaches: the first is based on a non-random gap generation with the intent of obtaining a gradually increasing gap area; the second is based on a completely random gap generation. In both cases the gap percentage ranges from 10% to 60% of the total gulf area with an increase of 10%. The SOM and DINEOF methods give a lower RMSE, both in direction and magnitude, in both scenarios. The performance of OMA worsen significantly if the gaps are concentrated in a subarea of the domain with at least 30% of holes. [ABSTRACT FROM AUTHOR]

The accurate measurement of precipitation is important to understand some meteorologicalsystems. Weather systems are complex and evolve rapidly and to measure rain, snow and othertypes of precipitation on the ground is challenging. However, satellite sensors can provideobservations from which precipitation estimates can be generated. In this work, the level 2instantaneous swath based precipitation products generated by the Goddard Profiling algorithmGPROF2014 scheme are evaluated using standard descriptive and statistical scores againstSOS-CHUVA surface radar dataset, over the southeast of Brazil. It was used the passivemicrowave sensors such as Special Sensor Microwave Imager/Sounder (SSMIS), MicrowaveHumidity Sounder (MHS), Advanced Technology Microwave Sounder (ATMS), Global MicrowaveImager (GMI), Advanced Scanning Microwave Radiometer (AMSR2) ​ which are products ofsatellites F16, F17, F18, NOAA18, METOPA, METOPB, NPP, GPM, GCOMW, respectively.Preliminary results show that the current GPROF retrieval technique tends to overestimate theoccurrence of light precipitation, leading to an overestimation of the volumetric contribution by lightprecipitation intensities, while it underestimates moderate to heavy precipitation. [ABSTRACT FROM AUTHOR]

Thinning rates of ice shelves vary widely around Antarctica and basal melting is a major component in the mass loss of ice shelves. In this study, we present observational data of the spatial and temporal varying basal melting of Nivlisen Ice Shelf, central Dronning Maud Land, in 2017 and 2018, using autonomous phase-sensitive radars. These unique records for East Antarctica show in general moderate yearly melt rates of approximately 1 m/yr. High melt rates (4 m/yr) were observed close to a grounded feature near the ice shelf front. Daily time-varying measurements of basal melt rates show a strong seasonal signal 3 km from the ice shelf front, with the highest melt rates (5 m/yr) occurring in summer. Comparing with atmospheric reanalysis data, we hypothesize that the seasonality was caused by summer-warmed surface water pushed by wind into the ice shelf cavity. 35 km into the ice-shelf cavity, we observe a clear tidal signal and no melt seasonality. Radar profiling of the ice-shelf show variable ice thickness from smooth beds to basal crevassing and down-warping englacial features. We conclude that warm deep ocean waters have a limited effect on the basal melting of this relatively thin ice shelf, in contrast to thicker (>400 m) ice shelves elsewhere in Antarctica. On the other hand, warmer surface water, affected by decreased sea-ice cover, have the potential to increase basal melting. [ABSTRACT FROM AUTHOR]

Ice is one of the most anisotropic natural materials but it is common knowledge in our community that anisotropy in ice is: a) a second order factor that can be ignored, b) easily assimilated into isotropic models by tuning certain parameters, or c) so complicated that it is better to ignore. Interestingly, any measurement of anisotropy in polar ice shows that ice develops crystalline preferred-orientation fabrics that produce strong mechanical, optical and dielectric anisotropic properties. Here, we look in detail at polarimetric radar measurements in different regions of East and West Antarctica. We use a ground-based phase-sensitive frequency-modulated continuous-wave radar (ApRES) and a matrix-based model to study the radio-waves depolarization and anisotropic scattering (Fujita et al, 2006). We find that anisotropy is widespread and an excellent archive of past ice flow conditions. We use it here to extract details of the recent deglaciation of the Ross and Ronny ice shelves over the last thousands of years. Also, because the length of the record is related to the advection time of the ice flow, we use our method to show that a candidate ice core location near Dome C, for the Beyond Epica Oldest Ice Core project, has been under steady ice-flow conditions over the last million years or so. [ABSTRACT FROM AUTHOR]

The vertical englacial velocity structure is an important indicator and result of the dynamic, rheological, and subglacial configuration of ice sheets. Previous studies have measured englacial velocities with invasive and time-consuming techniques using strain gauges and inclinometers installed in boreholes.More recently, ground-based radar systems (e.g., a-pRES) have been used to measure vertical velocities from the temporal changes in the position and phase of reflections from englacial layers. These stationary ground-based radar systems transmit and received complex electromagnetic signals that penetrate the surface and measure the layer boundaries that correspond to dielectric discontinuities in ice. The phase difference among two acquisition separated in time can be converted in vertical displacement enabling the velocity estimation of each layer. Despite their ability to provide vertical englacial velocity estimates without drilling, these stationary radars only provided englacial velocity information as a single point.The aim of our work is to demonstrate that the vertical englacial velocity profiles can also be estimated using airborne multi-temporal radar sounding. Airborne radar sounder acquisition can represent a unique opportunity to observe ice sheet dynamics at a wider scale then ground-based radar systems, which could be combined with InSAR-derived surface velocities to estimate the 3D velocity structure of ice sheets. To this end, we propose a processing technique that allows the estimation of the layer vertical displacement at the centimetre scale using airborne radar sounding data by exploiting the phase difference between radar signals acquired on the crossing points repeat tracks.We present a trade study based on simulations to inform both the radar parameters design (e.g., central frequency, bandwidth and polarimetry configuration) and the acquisition mission planning (e.g., angle between the multi-temporal tracks and number of repeat pass needed) for this approach. [ABSTRACT FROM AUTHOR]

The main aim of the COMBAT Project (CMEMS Service Evolution 2) is computing an improved local solution of the Mean Dynamic Topography for the southeastern Bay of Biscay, by including in its computation the existing long time-series of high-quality HF radar velocity measurements. The prerequisites for the computation of this new Mean Dynamic Topography is to remove the non-geostrophic signal from the HF radar measured velocities and to identify the scales resolved by the altimetry in the study area. The latter is characterized by the presence of a narrow shelf in the south and east and a deeper area gently sloping from east to west (the so-called 'Plateau des Landes'). In order to remove the ageostrophic part of the current from the HF radar data, different methods can be applied. For assessing their performance in the study area, we have first applied them to two different regional model simulations. This way, we can assess the methodology by comparing the results with the geostrophy computed from the simulated Sea Surface Height. The first simulation is the Reanalysis over the Irish-Biscay-Iberian domain, provided by the CMEMS, with around 8.3 km resolution. The second model is Symphonie in a Bay of Biscay configuration, with variable horizontal resolution (about 800 m in the study area). Daily surface data from 2011 to 2012 have been analysed. First, simulated surface currents have been compared with the HF radar measurements at daily time scales. We find that both models tend to overestimate the slope current in winter, while the time variability is consistent with the data. The comparison between the two simulations evidences differences on the mesoscale patterns. These patterns are more energetic in the higher resolution model, showing characteristics consistent with those reported in the literature. Then, we estimate the geostrophic component from the total current using two different approaches and compare the results when applied to the two simulations. At last, we conclude on recommendations on the use of the HF radar measurements for the MDT calculation. [ABSTRACT FROM AUTHOR]

This work is part of the EU-funded FloodCitiSense project, the aim of which is to develop an urban pluvial flood forecasting and warning service for and by the citizens. The specific focus of this work is to characterise convective storm features over one of the project pilot cities – Birmingham (UK) – and in turn to provide useful 'local' knowledge that can contribute to the development of the pluvial flood forecasting service. The proposed work comprises two stages: 1) development of a regional convective rain cell database, and 2) characterisation of storm cells' features in relation to the pilot. In the initial development of the database, individual convective rain cells and the traces between any two successive cells were extracted from the high-resolution UK Met Office (Nimrod) radar rainfall archive for the period of 2005-2017 over a 500 × 500 km2 area centred at Birmingham city. These cells and traces were identified using a new object-based convective storm cell tracking algorithm developed by Muñoz et al. (2018). Incorporating an optical flow-based rain-field tracking and a multi-threshold object identification techniques, this new algorithm enables the accurate isolation and tracking of convective rain cells from high-resolution radar reflectivity data. The extracted rain cells and traces were then stored in an open-source database, called TimescaleDB (http://www.timescale.com/). In the second stage, the specific properties of the identified cells and traces and their relationship to the pilot city were extracted from the database for further analyses. These include characterising statistical features of rain cells' intensities, extents, lifespans and their inter-relationships, and mapping the locations of rain cells, traces and given properties over the pilot city. Preliminary results of rain cell and trace mapping enable us to locate the 'hotspots' that are prone to the initiation and maturing of convective cells. In addition, the mapping of the traces suggests the existence of certain storm 'corridors' in the southern part of Birmingham city. This provides valuable 'local' knowledge to the development of urban pluvial flood forecasting and warning services. [ABSTRACT FROM AUTHOR]

Crystal Orientation Fabric (COF) of c-axes in ice cores reveals information about deformation within ice sheets. While this is a well established analysis technique for deep ice cores from ice divides, information about COF in ice streams is just now becoming available: the EastGRIP ice core is situated inside the largest ice stream in Greenland, the North East Greenland Ice Stream (NEGIS). With the ongoing analysis of samples from the EastGRIP ice core, COF is now available down to 1714 m, revealing an extremely more rapid evolution of COF anisotropy with depth compared to all other ice cores. This enables us to study the ability of polarimetric radar measurements to infer an overall pattern of COF from measurements conducted at the surface. Depending on whether the COF is isotropic or anisotropic, a radar signal is reflected differently in terms of angle dependence and polarization. We conducted these polarimetric measurements around the EastGRIP drill site and we compare them to COF data obtained from 778 thin sections, prepared and measured at EastGRIP drill site. We investigate the hypothesis that the same pattern of COF can be retrieved from the polarimetric measurements as is available from the ice core. If confirmed, this would provide an addition constraint on the (an)isotropy at locations where no ice core is available. This would potentially provide quasi spatial coverage and greatly improve our understanding of the evolution of anisotropy over from ice divides to outlet glaciers. [ABSTRACT FROM AUTHOR]

Atmospheric tides and planetary waves (PWs) play an important role in shaping the day-to-day and seasonal variability of the Mesosphere-Lower-Thermosphere (MLT). Measurements of tidal and PW variability in the mid-latitude MLT have however remained sparse. This study uses a longitudinal array of SuperDARN radars, which provide hourly measurements at ~95km altitude, to investigate tides and PWs in the MLT at 65 degrees North. Using the array of SuperDARNs, we can identify east and westward traveling S1, S2 and S3 wave components over a broad range of frequencies. The approach to extract the wave components is based on wave-fitting and the Stockwell-transform, which results in time-frequency diagrams of wave amplitudes. Using this technique, variations in amplitude on the scale of days can be identified for individual waves (e.g. the 5-day Rossby normal-mode). The approach is tested and validated using NAVGEM High Top (HT). NAVGEM-HT is a global reanalysis product which is data driven to approximately 114km. Initial results are in agreement with previous studies on (low frequency) quasi-stationary planetary waves and (high frequency) tides in the MLT. The temporal resolution provided by the proposed approach can give insight in sources of MLT variability such as nonlinear wave-wave interaction, selective gravity wave filtering and energetic particle precipitation. [ABSTRACT FROM AUTHOR]

Radar data have been used to retrieve and monitor the surface soil moisture (SM) changes in various conditions. However, the calibration of radar models whether empirically or physically-based, is still subject to large uncertainties especially at high-spatial resolution. To help calibrate radar-based retrieval approaches to supervising SM at high resolution, this paper presents an innovative synergistic method combining Sentinel-1 (S1) microwave and Landsat-7/8 (L7/8) thermal data. First, the S1 backscatter coefficient was normalized by its maximum and minimum values obtained during 2015-2016 agriculture season. Second, the normalized S1 backscatter coefficient was calibrated from reference points provided by a thermal-derived SM proxy named soil evaporative efficiency (SEE, defined as the ratio of actual to potential soil evaporation). SEE was estimated as the radiometric soil temperature normalized by its minimum and maximum values reached in a water-saturated and dry soil, respectively. We estimated both soil temperature endmembers by using a soil energy balance model forced by available meteorological forcing. The proposed approach was evaluated against in situ SM measurements collected over three bare soil fields in a semi-arid region in Morocco and we compared it against a classical approach based on radar data only. The two polarizations VV (vertical transmit and receive) and VH (vertical transmit and horizontal receive) of the S1 data available over the area are tested to analyse the sensitivity of radar signal to SM at high incidence angles (39°-43°). We found that the VV polarization was better correlated to SM than the VH polarization with a determination coefficient of 0.47 and 0.28, respectively. By combining S1 (VV) and L7/8 data, we reduced the root mean square difference between satellite and in situ SM to 0.03 m3 m-3, which is far smaller than 0.16 m3 m-3 when using S1 (VV) only. [ABSTRACT FROM AUTHOR]

The melting layer height is especially important for aviation meteorology because it can help determining the precipitation type and assessing the risk of freezing rain. A new method using the Micro Rain Radar (MRR) to determine the melting layer height is presented. The MRR is a small vertically pointing FMCW Radar which measures Doppler Spectra of precipitation. From these Doppler Spectra, various variables such as Doppler velocity or spectral width can be derived. The melting layer is visible through a higher reflectivity and an acceleration of the falling particles, among others. These characteristics are fed to a neural network to determine the melting layer height. For the training of the neural network, the melting layer height is determined manually. The neural network is tested using data from two sites covering all seasons. For most cases, it is well able to detect the correct melting layer height. [ABSTRACT FROM AUTHOR]

To investigate the air-land-sea interaction in the Maritime Continent (the world's largest archipelago bridging tropical Indian Ocean and tropical western Pacific), a series of the field campaign "YMC-Sumatra" was conducted as part of the project "Years of the Maritime Continent (YMC)". In "YMC-Sumatra 2017", we deploy the research vessel "Mirai" at one station near the west coast of Sumatra Island to obtain time series. The continuous dataset from C-band polarimetric radar is converted to the rainrate (i.e. fresh water flux) by utilizing the data from disdrometers and raingauges. The estimated fresh water flux is compared to the oceanic near-surface stratifications measured by the unmanned surface vehicle "wave glider". The observed salinity at 0.2m and 6m depths differ under a precipitating event with weak wind (< 5 m/s). The event was followed by the strong wind (>10 m/s) precipitation. After the event, low salinity layer was captured down to 30~40 m depth for more than half days. [ABSTRACT FROM AUTHOR]

Heavy precipitation events (HPE) are a significant hydrometeorological phenomenon in thehighly variable climate of the eastern Mediterranean (EM). They can cause flash-floods, andare closely-related to water availability. The formation of a HPE requires specific atmosphericconditions that result in relatively high precipitation efficiency, and causes distinctspatiotemporal rainfall patterns. Analyses of rainfall patterns during HPEs traditionally utilizeatmospheric or hydrological indices, Intensity-Duration-Frequency curves based onrain gauges, high-resolution meteorological simulation of case studies, or coarserresolution climatological simulations. However, these are insufficient to characterize thespatiotemporal rainfall patterns in HPEs, and high resolution simulation of large number ofHPEs are scarce. To characterize the rainfall patterns in HPEs in the EM, and toevaluate the ability to simulate them using a weather model we (a) identified HPEsin the EM using a uniquely long calibrated weather radar data, consisting of 24years, (b) simulated the same HPEs using a convection-permitting, high-resolutionnumerical weather research and forecasting model (WRF). Then we analyzed jointly therainfall patterns derived both from the radar record and the WRF, and evaluated themodel&#x2019;s ability to simulate the observed patterns through fractional skill scores,structure-amplitude-location analysis, temporal and spatial autocorrelation of rain-cells,among other techniques. Pixel-based (1X1 km2) identification of HPEs from the radar record yielded 41 eventsthat were later simulated by the WRF. Model simulated rainfall patterns are in goodagreement with the radar data, except for two highly-localized, short duration HPEs. EMrainfall in HPEs, derived both from the radar and the model, consists of small (∼10 kmdecorrelation distance) and intense rain-cells, oriented WSW-ENE, covering a smallportion of the region at each stage of the event (the median fraction of the areacovered by at least 50 mm for 30 min is less than 5%). However, given enough time,frequent arrival of rain-cells accounts for the accumulation of high rainfall depthsover increasingly wider area (&#x003E;80% of the area is covered by &#x003E;150 mm for 24h). The methodology and analyses presented above, of high-resolution, event-basedsimulations, is highly valuable in representing the specifics of rainfall patterns during HPEsand allow the investigation of causative meteorological ingredients for HPEs. Thus, it will befurther used in our future research to study and simulate rainfall patterns under a changingclimate. [ABSTRACT FROM AUTHOR]

High Frequency Radar (HFR) is the unique land-based remote sensing technology that allows the mapping of ocean surface currents over wide areas with high spatial and temporal resolution. HFR products are applied in many sectors such as research in coastal oceanography and marine environment, safety, coastal management, fishery, navigation and renewable energy. Furthermore, it is expected that HFR data will be systematically ingested in Data Assimilation processes necessary for predictive model adjustment.HFR technology is rapidly expanding in Europe (at a rate of 7 new systems per year since 2016), with over 62 HFR sites currently operating and a number in the planning stage.The coordinated development of coastal HFR technology and its products is essential to ensure that the potential of HFRs is fully exploited in the development of the European operational oceanography. The EuroGOOS HFR Task Team is leading, with the support of the European Marine Observation and Data Network (EMODnet), many ongoing initiatives aiming at promoting the HFR technology in Europe. These efforts brought to the the inclusion of HFR data into the major European platforms for marine data distribution, which are: Copernicus Marine Environment Monitoring Service In Situ Thematyic Assembly Center (CMEMS-INSTAC), SeaDataCloud (SDC) and EMODnet Physics. Building on these achievements, the European HFR Node was established as the infrastructure to drive the needed steps to reach the added-value of a coordinated network like: central archiving, homogenized protocols for data distribution, development of standards for quality assurance, control and data structures. The European platforms for marine data distribution operate through a decentralized architecture based on National Oceanographic Data Centers (NODC), Production Units (PUs) organized by region for the global ocean and the six European seas and a Global Distribution Unit (DU). The European HFR Node acts as the focal point for the European HFR data providers toward this decentralized structure, since it implements the HFR data stream from the data providers to the distribution platforms.The European HFR Node is founded on a simple and very effective rule: if the data provider can set up the data flow according to the defined standards, the node only checks and includes the new catalogue and data stream. If the data centre cannot setup the data flow, the HFR Node harvests the raw data from the provider, harmonizes, quality-controls and formats these data and makes them available.The strength and flexibility of this solution reside in the architecture of the European HFR node, that is based on a centralized database, fed both by the operators via a webform and by the software routines running on the node, containing updated metadata of the HFR networks and the needed information for processing/archiving the data. A set of shared software tools uses all those information for processing native HFR data for QC and converting them to the standard format for distribution.The European HFR Node is pre-operational since November 2018 and will be fully operational in April 2019 for CMEMS-INSTAC, EMODnet Physics and SDN/SDC data delivery. [ABSTRACT FROM AUTHOR]

The work presents an analysis of a Pc5 wave registered on November 22, 2014 simultaneously by Ekaterinburg decameter coherent radar (EKB radar) in the night ionosphere and by Van Allen Probes in the conjugate region of the magnetosphere near the geomagnetic equator between 5.5 and 5.8 L-shells. The wave had frequency about 1.8 mHz and was observed after an increase in geomagnetic activity, in the recovery phase of a substorm. Probably, the observed wave is a drift-compressional mode: its frequency was much lower than the estimated lowest Alfvén frequency; the wave had a predominant longitudinal magnetic component in antiphase to the observed plasma pressure oscillations, and was accompanied by an increase in the flux of energetic protons. Besides, the direction of wave propagation coincided with the direction of the magnetic drift of the energetic protons: the azimuthal wave number m calculated on the basis of radar and satellite data was about -10. And indeed, a modulation of proton fluxes with energies 81.6 and 99.4 keV at the wave frequency was found. The magnetic drift velocity of protons with these energies is close to the phase velocity of the wave. Therefore, it is possible that the wave was generated due to the resonant wave-particle interaction (drift instability). The work was supported by the Russian Science Foundation under grant 18-17-00021. [ABSTRACT FROM AUTHOR]

High-power-large-aperture (HPLA) VHF radars at the lower frequency band around 50 MHz have been employed to observe the atmosphere for several decades, which can collect not only the echoes from clear-air turbulence in the neutral atmosphere and plasma irregularities in the ionosphere, but also the returns from aircrafts, meteors, precipitation, and so on. In this study, we examined the meteor echoes collected by the middle and upper (MU) atmosphere radar, operated by Research Institute for Sustainable Humanosphere, Kyoto University, Japan. Twenty receivers and five frequencies (46.25, 46.375, 46.5, 46.625, 46.75 MHz) were utilized in observation. With multi-channel echoes, angular and range distributions of the meteor heads and long-duration trails in the radar volume have been resolved by using adaptive constrained methods such as the Capon method and its modified version, the so-called norm-constrained Capon method. Some results will be shown. For example, fragmentation of the meteoroid can be disclosed from the range imaging of the long-duration trail echoes, angular imaging can make an identification of multiple echo centers that could be associated with meteoric fragmentation. [ABSTRACT FROM AUTHOR]

The weather radar has the advantage of providing a very high spatial resolution of rainfall information. Recently, radar precipitation has been widely used in the field of hydrology especially for flood warnings and flash flood in urban areas. Radar rainfall is routinely estimated by using the existing reflectivity-rainfall intensity relationship so that there may be biases in their measurements. In this study, a generalized linear model (GLM) for calibrating the radar rainfall is proposed within a Bayesian framework. The biased corrected radar rainfall from the GLM can lead to more accurate rainfall estimates than the existing mean field biased correction method. Moreover, we explored the variability in the bias correction parameters corresponding to the geomorphological characteristics (e.g. latitude, longitude, altitude and separation distance) and further proposed a regionalized formula of the bias correction factors with the height and the separation distance. KEYWORDS: Radar rainfall, Bias correction, Bayesian, Generalized linear model, RegionalizationAcknowledgementThis research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1A6A3A11047264). [ABSTRACT FROM AUTHOR]

The global demand for products and services using Global Navigation Satellite System (GNSS) is continuously increasing in the modern society. However, GNSS-based technologies experience disruption of service and outages during adverse ionospheric conditions. Plasma gradients forming in the ionosphere over large-to-small scales during adverse space weather conditions introduce signals and services disruptions in terms of scintillation and temporal fluctuations in the Total Electron Content (TEC). The presence of plasma gradients can limit the GNSS receiver tracking capability and therefore degrades the positioning and timing accuracy. In the particular case of magnetic auroral latitudes, ionospheric gradients originate from particle precipitation and are associated with disruption of GNSS services. These disruptions are a consequence of the coupling between link geometry and propagation through specific plasma structures. An experiment was designed in order to appreciate and model such a propagation problem by combining measurements from EISCAT/ESR radars and geodetic GNSS receivers. The objective of the experiment was to estimate the ionisation structures responsible for TEC fluctuations on GPS signals in the auroral ionosphere by means of EISCAT/ESR electron density profiles. To achieve this, a multi-instrument approach experiment was designed to estimate the electron density gradients across a given GNSS ray path between 20:00 and 24:00 UT on several days in March 2018. The electron density structures were analysed by means of radar electron density profiles measured from Tromsø/Longyearbyen in combination with GNSS ray paths measured from an International GNSS Service (IGS) station in Kiruna/Ny Ålesund respectively. The main point of the experiment was to relate plasma structures in phase screens across specific GPS ray paths to TEC temporal fluctuations observed along these GPS ray paths. For example, the ionisation structures forming after particle precipitation were associated with enhanced GPS TEC temporal fluctuations. In this experiment, the radar electron density profiles and the GPS TEC fluctuations are used to infer the origin of the observed signature on the GPS signals from large-scale ionisation structures in the E and F regions during the time of observation. This contribution will discuss methodology and results of such an experiment, together with appreciation of the impact on positioning. The results will assist in the design of robust GNSS receivers and positioning algorithm for enhanced performance and reliability. [ABSTRACT FROM AUTHOR]

In the process of oil drilling, mud filtrate penetrates into porous formations and alters their pore fluid properties. This, in turn, complicates the formation evaluation process based on conventional well logging. If adequately characterized, the mud-contaminated part of the formation does, however, also carry valuable information, notably with regard to its key hydraulic properties. To achieve this objective, we propose to use borehole radar logging to determine the mud invasion depth, which critically depends of the formation's porosity and permeability. A series of 3D numerical simulations has been carried out to assess the feasibility and potential of this approach. The underlying electromagnetic (EM) model is coupled with a multi-phase fluid flow model to simulate the responses of borehole radar to the mud-invaded formation. The EM model is constructed using gprMax, an open-source software package that employs the finite-difference time-domain method (FDTD) to numerically solve Maxwell's equations, while the fluid flow model is based on a numerical solution of the corresponding governing equations with an implicit pressure and explicit saturation (IMPES) method. The two models are coupled via electrical material property formulas based on petrophysical mixing models. Simulations of the time-lapse logging response is performed to extract the generally weak EM signals associated with the mud invasion. The corresponding results suggest that observable reflections arise from the invasion transition zones, which demonstrates the potential of borehole radar logging in oil exploration in the presence of water-based drilling muds of low salinity. The technical challenges reside in developing a radar logging tool that is able to support the antennas against the borehole wall, in order to focus the EM energy towards the formation. [ABSTRACT FROM AUTHOR]

We report on a combined magnetic–GPR survey performed in July 2018 at a Roman castrum located 10 km north of Gjirokaster (Albania), close to the village of Paleokastër. Integrated magnetic and GPR surveys were carried out to determine the arrangement of buried structures and reconstruct the archaeological history of the settlement. Magnetic data were collected in gradiometer configuration using a Geometrics G–858 caesium vapor magnetometer. Vertical gradient and total field anomalies were used jointly in the forward modelling of the distribution of magnetization. The radar survey was carried out through the same area using a GSSI SIR-4000 system equipped with a 400 MHz central-frequency antenna. Filtered radar profiles were processed to create horizontal amplitude maps and 3D isosurfaces. An initial basic chart of buried structures was generated starting from such horizontal slices of amplitude reflections data. This map was locally integrated by the modelled magnetization distribution where GPR data were either missing or unable to delineate a buried structure. In these cases, vertical GPR profiles were correlated with magnetic gradient and magnetic anomaly profiles to constrain the physical nature and geometry of the buried structures. The analysis of the integrated data set allowed to trace the complete structure of the Roman fortification but also revealed the presence of deeper and older features of probable Hellenistic age and younger buildings of Byzantine age. This interpretation is supported by archaeological considerations. The Roman settlement was built in the early fourth century and destroyed during the Gothic incursion of 378 AD. Later, the area hosted a Byzantine civilian settlement during the fifth and sixth centuries. During this period, a Christian church was founded inside the fortress walls. The Hellenistic age of older structures is suggested by the materials used in the construction of the walls, which include several large opera quadrata blocks. [ABSTRACT FROM AUTHOR]

Observing and understanding processes of the daily water cycle (DWC) over land with a high spatial resolution is one of the outstanding grand challenges in Earth Observation (EO). This challenge has been taken up by the G-Glass mission, which is a geosynchronous C-band radar satellite that was recently selected by ESA as one of the candidate mission for its 10th Earth Explorer. Among other variables, G-Class will observe soil moisture and precipitation, which are key to understand the DWC. Both variables can be retrieved from spaceborne radar observations in a sequential manner: Firstly, soil moisture can be estimated by inverting a backscatter model that describes the interaction of the microwave pulses with the vegetation and soil surface. Secondly, precipitation can be derived from the soil moisture data by inverting a soil water balance model. Research has already demonstrated the feasibility of this approach, and a number of operational services do exist (for soil moisture) or are about to be introduced soon (for precipitation). However, existing services do not properly resolve the DWC as they rest on polar-orbiting radar satellites that capture soil moisture at best twice a day at their ascending and descending passes respectively. Even though daily rainfall can be estimated from such data, estimates remain rather noisy. To more densely sample soil moisture across one day, and to reduce the noise in the daily rainfall estimates it is essential to collect several backscatter measurements per day. This may be achieved, as proposed by G-Class, by a geosynchronous satellite that observes the same land surface areas every few hours (1-3 hours). In this presentation the current planning for C-Glass will be reviewed. Furthermore, we will discuss expected strengths and limitations of G-Class based on results obtained with METOP ASCAT and Sentinel-1 that measure, like G-Class, backscatter at C-band. [ABSTRACT FROM AUTHOR]

Radar penetration correction is an essential part in glacier mass balance estimation using DEM differential methods. Previous studies have shown that radar penetration depth is different for clean ice and glacial debris, which is widely distributed in High Mountain Asia (HMA), especially in Pamir and Karakoram. However, few studies are conducted on this subject-area. Up to now, we know very little about the effects of radar penetration depth on the estimation of glacier mass balances in these two areas. This study focuses on estimation of radar penetration depth of the clear ice and debris cover in glaciers in HMA and evaluation of the potential effect of radar penetration of thick debris cover on glacier mass balance. Specifically, the differences between C band and X band SRTM DEMs are quantified to estimate the radar penetration depth of glacier debris covers in Hissar Alay, Pamir and Karakoram. Furthermore, we analyze the penetration depth differences in each 50-m elevation bin and establish a linear or polynomial model between elevation and radar penetration. Our experimental results show that the average penetration depth differences in the Hissar Alay, Pamir and Karakoram glacier regions are 2.42m ± 0.23 m,0.41m ± 0.12 m, and 2.05m ± 0.17 m, respectively. The penetration depth of surface debris covered area is about 1.0 m less than that of clean ice area. Penetration correction of the debris-covered ice and clean ice can effectively reduce the systematic error in glacier mass balance estimation, which should be considered to obtain a robust estimate of glacier mass balance in HMA. [ABSTRACT FROM AUTHOR]

Operation of powerful satellite- and rocket-born sounding radars is often accompanied by a heating/acceleration of the local electrons and ions. On earlier missions, intense fluxes of sounder accelerated particles were detected in Earth's ionosphere when the frequency of the radar transmitter was close to one of the fundamental plasma resonances: harmonic of the electron-cyclotron frequency, plasma or upper-hybrid frequencies. Recently it was found that running a sounder in the ionosphere of the non-magnetized Mars results in the similar effects. Ion and electron sensors of the ASPERA-3 experiment (Analyzer of Space Plasma and Energetic neutral Atoms) onboard the Mars Express spacecraft discovered acceleration of the local ionospheric ions and electrons from thermal threshold energies to 100's of eV during the active sounding phase of the onboard sounder. ESA and NASA missions in development or under study to Jupiter (JUICE- JUpiter ICy moon Explorer in 2022, Europa Clipper in 2023) and to Venus (EnVision in 2032) will also carry powerful sounding radars. In this report we review mechanisms that can cause acceleration of the plasma particles during operations of the proposed sounding radars in the Jovian system and Venusian ionosphere. Using the results of previous studies and characteristics of the proposed sounding radars onboard JUICE, Europa Clipper, and EnVision we define the optimal conditions for observations of sounder accelerated particles, depending on the local conditions, such as plasma density, composition, and intensity of the magnetic field. The EnVision radar operation is expected to results in the most pronounced acceleration of ions and electrons, an effect can be used to improve the local plasma diagnostics. [ABSTRACT FROM AUTHOR]

The cone volcano Anak Krakatau, which is largely built on the steep northeast caldera wall ofthe 1883 Krakatau eruption, is currently featuring activity on its southwest slope and thusgrowing into the 1883 caldera and this position makes the edifice unstable. On 22 December2018, tsunami took place in Sunda strait, the deadliest in this area since the 1883 Krakataueruption. We have collected multitemporal datasets from the multisensory (radar, thermal,multi-spectral) satellite images to assess the changes in the form of the Anak Krakatau edificefollowing the collapse and to evaluate if these changes may be related to the formation of thetsunami. The capacity of radar to penetrate clouds as well as ash plume are an advantage forobservations during the eruption. Radar images from Sentinel-1 indicate that the SW flankof Anak Krakatau collapsed on 22 December 2018. Hence, it is likely that thiscollapse generated the tsunami in Sunda strait. Comparing radar imagery from 10December 2018, 22 December 2018 and 25 December 2018 indicates further changes toSW flank of Anak Krakatau, estimated ∼0.49 km2 of the area have been lost afterthe initial collapse. According to the thermal and optical satellite, during 17-19February 2017 produced a relatively extensive lava that flow down the SW flankthen the eruption continues from the end of June 2018 to December 2018. Theloading of these new additions of erupted material onto SW slopes of Anak Krakataulead the possible trigger for the collapse. Eventually, the over steepening of theflanks reaches a critical point and it collapse. The integration of multitemporalremote sensing datasets gives insight of the eruptive activity, dynamic from thesurface and detection of the collapse which possible induced tsunami in Sunda strait. [ABSTRACT FROM AUTHOR]

Radar reflectivity data is crucial to improve initial field of numerical model. However, the method of Ensemble Kalman Filtering (EnKF) can not directly assimilate radar reflectivity data. We explore a method of modifying the initial thermodynamic field of numerical model by using radar reflectivity data. Two experiments are carried out to reveal the forecast improvement of a squall line occurred in the Eastern China by assimilating reflectivity data. One experiment is assimilating some observational data without radar reflectivity data using EnKF method (hereafter called No-Ref experiment), and the other is modifying the initial thermodynamic field using radar reflectivity data after conducting EnKF experiment (called Ref experiment). Compared with the simulation results of No-Ref experiment, the forecast is improved in Ref experiment. The results show that thermodynamic field adjustment leads to the adjustment of the dynamic field, and plays an important role in the improvement of squall line forecast. [ABSTRACT FROM AUTHOR]

Understanding ice microphysical processes is equally challenging for modelers and observationalists because of the vast number of degrees of freedom involved. Even state-of-the-art two-moment schemes, such as implemented in the new German ICOsahedral Nonhydrostatic (ICON) model, are still facing problems to correctly reproduce basic ice microphysical processes such as depositional growth and aggregation. Retrieval algorithms based on remote sensing observations face similar challenges due the necessary assumptions in the inversion methods. In this study, we combine novel multi-frequency cloud radar observations with a versatile model framework which allows us to perform specific experiments to explore the potential sources of model-observation discrepancies. This contribution aims to exemplarily show how we can utilize the rich microphysical fingerprint in modern remote sensing observations to evaluate and improve the parametrizations of microphysical processes.The observational basis are data of three ground-based vertically pointing Doppler radars (X, Ka and W band) which are continuously recorded at the Jülich Observatory of Cloud Evolution (JOYCE) in Jülich, Germany since 2018. The reflectivity differences in the triple-frequency observations have been previously shown to contain information about the average ice particle size and density. The Doppler velocity provides additional constraint to the average particle sedimentation velocity which is a very critical quantity in model parametrizations.During intensive observation periods, we also continuously run 200 km wide nested ICON simulations with 600 m horizontal resolution centered over the JOYCE site. In order to compare the model simulations with the radar observations, we use the Passive and Active Microwave Transfer Tool (PAMTRA) which allows to exactly match the ICON assumptions about ice and snow particles (e.g. mass-size relation) using the self-similar Rayleigh-Gans Approximation for their scattering properties.Thanks to the long-term statistics of high-resolution model simulations together with multi-frequency radar observations, we are able to identify discrepancies between model and observations statistics which we can relate to microphysical processes using the information in the multi-frequency space. After this identification, we run several microphysical experiments for case studies to test the influence of microphysical choices such as particle geometry, fall speeds, or particle size distribution on depositional growth and aggregation and their associated simulated radar reflectivities and Doppler velocities. First results reveal for example that a major difference between model and observations origins from fall velocity parametrizations for the snow component which cause the snow to fall much faster in the model than observed. This discrepancy in fall velocities has a direct impact on the aggregation process itself. [ABSTRACT FROM AUTHOR]

Juventas is a 6U CubeSat designed as part of the HERA mission to provide bonus science to the mission. HERA is a candidate ESA mission to be launched to the Didymos binary asteroid system, which will carry two CubeSats. The CubeSats will be deployed by the HERA spacecraft once the Early Characterization Phase has completed. Didymos is a binary asteroid system, and the scientific objectives for the Juventas CubeSat are to measure the gravity field and interior structure of the Didymoon. From its orbit, Juventas will perform satellite-to-satellite radio science over the Inter-Satellite radio link with the HERA spacecraft. A low-frequency radar will survey the Didymoon in order to determine the internal structure. Once the primary science is complete, Juventas will attempt to land on the Didymoon surface in order to determine the dynamical properties of the asteroid through measurements during impact and bouncing events. If landing is successful, Juventas will end its mission with several days of surface operations. [ABSTRACT FROM AUTHOR]

After major geo-hydrological disasters, the rapid detection of both location and extension of the areas struck by floods and landslides is essential to manage recovery operations. In these cases, one of the most important tools required by decision-makers is a georeferenced map showing the affected areas. Preliminary maps reporting the potential location of landslides, for example, may also represents a starting point for field Geologists engaged in the production of detailed event landslides inventories, allowing optimize time and efforts. Optical and radar satellite images are experiencing an increasing use in the emergency operations due to improved revisiting times and spatial resolution. However, optical scenes are often useless for long times because of a permanent cloud cover or shadow effects hiding the collapsed mountain slopes. For this reason, the landslide research community is dedicating more efforts to implement new approaches based on satellite radar data, which typically are not affected by these types of disturbance. Even if the development of landslide inventories from radar images is still a challenge, such data represent a valuable support to generate archives of information acquired systematically, forming therefore clusters of "Big data" that can be useful in the context of susceptibility, hazard, and landslide risk analysis. In the innovative approach presented in this contribution, we faced many of the issues related to the use of satellite radar data for supporting the production of event landslides inventories. The research activities have been carried out in the framework of the STRESS (Strategies, Tools and new data for REsilient Smart Societies) project, devoted to design, implement and test a prototype of a Spatial Data Infrastructure (SDI) to support decision makers in the geo-hydrological risk management. Specifically, our group have implemented an automatic processing chain that, starting from the downloading of Sentinel-1 satellite images, produces a georeferenced map highlighting the likely location of landslides. The procedure exploits multi-temporal variations of the radar backscattered signal induced by significant land cover changes, which can be associated to the occurrence of rapid-moving landslides. This map is sent to local scientists and citizens by means of a Smart App developed to collect, store and analyze Volunteered Geographic Information (VGI), to ease and improve results obtained from satellites. The STRESS project is also aimed at promoting and exploiting VGI freely provided by citizens involved as "human sensors" in the production of landslide inventories, providing direct information if no evidences are available from remote sensing. Outcomes resulting from both remote sensing and VGI activities should thereby support the updating of existing landslides susceptibility models and hazard assessment. The test site of the project is located in the Central Alps (Italy), where the steep slopes are very prone to landslides and debris flow processes. However, a preliminary application of the automatic processing chain has been successfully performed for a wide area of the Papua New Guinea affected by dozens of landslides in 2018, as well as the implementation of the VGI Smart App has been completed and verified. [ABSTRACT FROM AUTHOR]

The HYD2M project (HYDrodynamics of Raz Blanchard: Measurements and Modelling) constitutes a research program designed to study how surface waves and extreme events modify the tidal stream energy estimate, with the ultimate goal of improving such estimates. In order to achieve this goal, the project relies on a combination of models, in situ measurements, and remote sensing. The later group is represented by a pair of HF radars set to transmit at two frequencies, 13.5 MHz and 24.5 MHz, with measurements at each frequency being collected twice in each hour. In this work, the performance of HF radar in measuring the wave field and the highly energetic current of the Alderney Race (Raz Blanchard in French) is examined by comparing its results against measurements collected by a bottom-mounted ADCP deployed in the area. In addition, the spatial currents are compared against numerical results obtained with MARS3D. Discrepancies between methods increase with increasing current speeds, and in relation to the location within the radar's field of view. Over a tidal cycle, the bias between the radar and ADCP velocity estimates is 11 cm/s, while the absolute differences range between few mm/s to a maximum of 53 cm/s at the time of maximum current velocity. Similarly, inspection of the radar's wave results indicate a variation on the quality and extent of the results over the tidal cycle. The reasons of the discrepancies are discussed, and the driving mechanisms of the differences examined. [ABSTRACT FROM AUTHOR]

Space-borne radar interferometry (InSAR) is an excellent tool for measuring surface displacements. Using the phase information stored in the SAR images it is possible to calculate the phase difference due to surface movements between two acquisitions and from the differential phase, calculate the surface displacements.This method can be used reliably to create surface deformation time-series for mapping large areas and monitoring single reflecting targets. Some areas, however, are not suitable for InSAR analysis due to heavy vegetation or other factors that decrease phase coherence. In such cases, it is possible to install artificial reflecting objects (radar reflectors) that provide a stable phase over a long period of time.The MTA CSFK Geodetic and Geophysical Institute in collaboration with the Department of Broadband Infocommunications and Electromagnetic Theory of the Budapest University of Technology and Economics under ESA PECS project (project ID: 4000118850/16/NL/SC) developed such artificial reflectors.To overcome the other limitation of InSAR, namely that only deformation that is parallel to the satellite line-of-sight (LOS) can be measured, we have also carried out GNSS measurements at our reflector benchmarks.Three reflector networks were deployed in Hungary, two along the loess banks of River Danube, where landslide activity is frequent and one near Lake Balaton in an area affected by landslides as well.We used Sentinel-1 A and B satellite data between two GNSS campaign measurements (from July of 2016 to March of 2017) to calculate ascending and descending LOS displacements at our reflector benchmarks and through a technique called Kalman-filtering we fused data from ascending and descending satellite passes and the GNSS measurements to calculate the 3D displacements of our reflector networks, relative to a single reference reflector for each network.We present the 3D movements we have calculated with the previously described method at the three reflector networks and comment on the potential error sources and the possible improvements to our methodology. [ABSTRACT FROM AUTHOR]

The effects of different soil moisture states on the environment and climate system are wellknown. General hydrological processes like runoff generation heavily depend on thisessential climate variable. Therefore, exact knowledge on state and development of thisvariable is crucial for a wide range of applications. However, gridded soil moisture products&#x2019;temporal resolution mostly is limited to daily data sets. E.g., Soil Moisture and OceanSalinity (SMOS) or the Soil Moisture Active Passive (SMAP) Mission&#x2019;s products actuallyrecorded by the instrument are of daily resolution, whereas the 3-hourly Level 4 data is theoutput of a land surface model. In contrast, measurements of precipitation, which is the maindriver for soil moisture, are available at sub-daily temporal resolution. Precipitation radarstations even have sub-hourly sampling rates that allow detection of short precipitationevents. This study presents a simple soil moisture proxy derived from an hourly precipitationradar product. The aim is to take advantage of the high detection rate and finer temporal (andspatial) resolution of the precipitation measurements compared to existing gridded soilmoisture products. The proxy is based on the German RADOLAN weather radar dataset withintensity, spatial and temporal resolution of 0.1 mm, 1 km and 1 hour respectively. Inparticular, for the retrieval of soil moisture an Antecedent Precipitation Index is calculatedfrom the precipitation data. This index uses a dampening coefficient to simulate the dry-downperiod in-between precipitation events. Empirical values in dependency of different soilproperties control the dampening factor. The index is compared to soil moisturemeasurements at the Munich North Isar test site, where soil properties, soil moisture andother environmental variables were recorded in an extensive field campaign 2017and 2018. Furthermore, the portability of the results to other regions is evaluatedusing measurement data from the International Soil Moisture Network (ISMN)sites. [ABSTRACT FROM AUTHOR]

Mid-latitude mesospheric summer echoes (MSEs) appear in radar observations during summer months. Geophysical factors controlling the formation of MSEs include solar and energetic particle ionisation, neutral atmosphere temperature, turbulence, and meridional wind transport. 12 years of summer month observations by OSWIN VHF radar in Northern Germany have been analysed to detect MSE events and to analyse statistical connections to these controlling factors. A more sensitive and consistent method for deriving signal-to-noise ratio has been utilised. Daily and monthly composite analysis demonstrates strong daytime preference and early summer seasonal preference for MSEs. It is shown that the meridional wind transport from colder high-latitude summer mesosphere is the important controlling factor, while no clear connection to geomagnetic and solar activity is found. [ABSTRACT FROM AUTHOR]

We have carried out an experiment using a 3.2 mm-wavelength scanning Doppler radar and a laser disdrometer to investigate ash plumes of Sabancaya volcano (Peru) in May 2018. Our main objectives were to retrieve the mass loading parameters (concentration, mass flux) which are critical for the modelling of ash dispersal, as well as to study the dimensions and internal dynamics of the eruptive columns, plumes and fallout. The radar and the disdrometer were respectively located at 4.5 km NNE and 4.5 km E from the vent. Multiple radar sounding configurations were tested either in fixed-pointing mode, generally close to the source, or using scans across various regions of the plumes. Particle Size Distribution, shapes and density were characterized from microphysical analyses, sieving and water pycnometry of ash samples collected on the ground. A Parsivel2 disdrometer also recorded the sizes, and settling velocities of fallout, allowing us to estimate sedimentation rates on the ground and to derive an empirical law relating calculated ash concentrations and reflectivities. Comparing the latter with reflectivities measured by the radar at unprecedented space-time resolutions (down to 12.5 m and 0.25 s) allowed us to obtain the internal mass distribution of eruptive columns, plumes, and fallout at various distances from the emission source. [ABSTRACT FROM AUTHOR]

The presence of liquid water at the base of the Martian polar caps has long been suspected but not observed. We surveyed the Planum Australe region using the Mars Advanced Radar for Subsurface and Ionosphere Sounding, a low-frequency radar on the Mars Express spacecraft. Radar profiles collected between May 2012 and December 2015, contain evidence of liquid water trapped below the ice of the South Polar Layered Deposits. Anomalously bright subsurface reflections were found within a well-defined, 20km wide zone centered at 193°E, 81°S, surrounded by much less reflective areas. Quantitative analysis of the radar signals shows that this bright feature has high dielectric permittivity >15, matching water-bearing materials. We interpret this feature as a stable body of liquid water on Mars. [ABSTRACT FROM AUTHOR]

Back-scatter echoes from irregularities in the polar ionosphere are detected by HF radars only when propagation conditions along the entire propagation path are favorable. Therefore, occurrence of HF echoes depends on several factors as the radar location, season and time of the day. Solar cycle and interplanetary conditions plays an important role, as well. The Dome C East radar, part of the Super Dual Auroral Radar Network (SuperDARN) is located at the Concordia station in Antartica, nearby the geomagnetic pole. Its 16 beams fan out from the geomagnetic pole towards the southern auroral latitudes along the geomagnetic meridians. Here, we present a statistical study of the ionospheric scatter echoes detected by Dome C East for the period 2013 - 2017, where echoes occurrence is investigated as a function of geomagnetic latitude and MLT location, season and interplanetary conditions. [ABSTRACT FROM AUTHOR]

We demonstrate that the Super Dual Auroral Radar Network (SuperDARN) can be used to detect energetic particle precipitation (EPP) events by observing high frequency radio wave attenuation in the D region ionosphere. The radars can detect polar cap absorption during solar proton events, as well as weaker ionisation associated with substorms and pulsating aurora. Energetic electron precipitation occurrence rates over Syowa Station, Antarctica have been determined as a function of magnetic local time (MLT) using a database of 555 events identified in 2011. The post-midnight and morning sector occurrence rates were found to exhibit significant seasonal variations. The SuperDARN dataset consists of more than 20 years of continuous observations covering sub-auroral, auroral and polar latitudes. This provides a new opportunity to determine long-term EPP occurrence rates for use in studies of the atmospheric effects of particle precipitation. [ABSTRACT FROM AUTHOR]

Low latitude horizontal divergence in the mesosphere and lower thermosphere (MLT) region are presented from multiple meteor radars using the SVVP method. Multi-years dataset of the radial velocity in the altitude range of 80-100 km is observed from two low-latitude stations with distance of 123 km. We first derive the horizontal winds in each 1hr and 2 km bin at each station using the traditional method. Both volume velocity processing (VVP) and step volume velocity processing (SVVP) are then used to get the 3D distribution of the background winds especially their horizontal structures around these two stations with radius of ~300 km and in the MLT region with higher horizontal resolution, taking advantage of the combined horizontal sampling observed by the two stations. Gradient terms of the horizontal winds are also obtained and their detailed local time, day-to-day and seasonal variations of the horizontal divergence, relative vorticity, and the stretching and shearing deformation at different altitudes are further studied. Comparing with the traditional method, the SVVP method is proved to be more stable and sensitive during obtaining the background winds and horizontal divergence. [ABSTRACT FROM AUTHOR]

The Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) onboard Mars Express (MEX) and the Shallow Radar (SHARAD) onboard Mars Reconnaissance Orbiter (MRO) suffer from severe degradation in the ground reflection signal almost every time a solar energetic particle (SEP) event strikes Mars. The most notable case occurred in September 2017, when the signals of both radars were completely absent for several days. Thanks to the MAVEN mission, we now know that the cause was likely the precipitation of SEP electrons of a few tens of keV, associated with a series of powerful space weather events that struck Mars during 10-22 September 2017. Such energetic electron precipitation is believed to produce a lower ionospheric layer within the collision-dominated atmosphere, which can absorb the radar signal at the radar operational frequencies, around 5 MHz for MARSIS and 20 MHz for SHARAD. In this study, we assess the properties of this low ionospheric layer around the planet based on these radar attenuation estimates. In addition, taking advantage of a larger dataset during over the lifetime of both the MEX and MRO missions, we evaluate when and under which conditions this absorption layer appears. As it is leading to the loss of radar signals at least between 5 and 20 MHz, the outcome of his work will allow better assessment of high frequency radar performance during future space weather events. [ABSTRACT FROM AUTHOR]

We analyze diurnal, semidiurnal, terdiurnal, and quarterdiurnal tidal amplitudes, phases, and related wind shear in the mesosphere/lower thermosphere, which has been observed by a meteor radar at Collm (51.3°N, 13.0°E). We present the climatology of wind shear, and analyze interannual variability and trends from 2007 – 2016. The wind shear phases are compared with those of sporadic E (Es) occurrence rate phases, which were derived from GPS radio occultation signal-to-noise ratio (SNR) profiles measured by the COSMIC/FORMOSAT-3 satellites. Es are produced by wind shear which, in the presence of a horizontal component of the Earth magnetic field, leads to ion convergence in the region where the wind shear is negative. Consequently, we find good correspondence between radar derived wind shear and Es phases for the semidiurnal, terdiurnal and quarterdiurnal tidal components. Diurnal tidal wind shear does not agree with Es occurrence rate phases. [ABSTRACT FROM AUTHOR]