Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region

Tropospheric water vapor is one of the most important trace gases of the Earth\u27s climate system, and its temporal and spatial distribution is critical for the genesis of clouds and precipitation. Due to the pronounced dynamics of the atmosphere and the nonlinear relation of air temperature and saturated vapor pressure, it is highly variable, which hampers the development of high-resolution and three-dimensional maps of regional extent. With their complementary high temporal and spatial resolutions, Global Navigation Satellite Systems (GNSS) meteorology and Interferometric Synthetic Aperture Radar (InSAR) satellite remote sensing represent a significant alternative to generally sparsely distributed radio sounding observations. In addition, data fusion with collocation and tomographical methods enables the construction of detailed maps in either two or three dimensions. Finally, by assimilation of these observation-derived datasets with dynamical regional atmospheric models, tropospheric water vapor fields can be determined with high spatial and continuous temporal resolution. In the following, a collection of basic and processed datasets, obtained with the above-listed methods, is presented that describes the state and course of atmospheric water vapor for the extent of the GNSS Upper Rhine Graben Network (GURN) region. The dataset contains hourly 2D fields of integrated water vapor (IWV) and 3D fields of water vapor density (WVD) for four multi-week, variable season periods between April 2016 and October 2018 at a spatial resolution of (2.1 km)$^2$. Zenith total delay (ZTD) from GNSS and collocation and refractivities are provided as intermediate products. InSAR (Sentinel-1A/B)-derived double differential slant total delay phases (ddSTDPs) and GNSS-based ZTDs are available for March 2015 to July 2019. The validation of data assimilation with five independent GNSS stations for IWV shows improving Kling–Gupta efficiency (KGE) scores for all seasons, most notably for summer, with collocation data assimilation (KGE = 0.92) versus the open-cycle simulation (KGE = 0.69). The full dataset can be obtained from https://doi.org/10.1594/PANGAEA.936447 (Fersch et al., 2021)

Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region

Tropospheric water vapor is one of the most important trace gases of the Earth's climate system, and its temporal and spatial distribution is critical for the genesis of clouds and precipitation. Due to the pronounced dynamics of the atmosphere and the nonlinear relation of air temperature and saturated vapor pressure, it is highly variable, which hampers the development of high-resolution and three-dimensional maps of regional extent. With their complementary high temporal and spatial resolutions, Global Navigation Satellite Systems (GNSS) meteorology and Interferometric Synthetic Aperture Radar (InSAR) satellite remote sensing represent a significant alternative to generally sparsely distributed radio sounding observations. In addition, data fusion with collocation and tomographical methods enables the construction of detailed maps in either two or three dimensions. Finally, by assimilation of these observation-derived datasets with dynamical regional atmospheric models, tropospheric water vapor fields can be determined with high spatial and continuous temporal resolution. In the following, a collection of basic and processed datasets, obtained with the above-listed methods, is presented that describes the state and course of atmospheric water vapor for the extent of the GNSS Upper Rhine Graben Network (GURN) region. The dataset contains hourly 2D fields of integrated water vapor (IWV) and 3D fields of water vapor density (WVD) for four multi-week, variable season periods between April 2016 and October 2018 at a spatial resolution of (2.1 km)2. Zenith total delay (ZTD) from GNSS and collocation and refractivities are provided as intermediate products. InSAR (Sentinel-1A/B)-derived double differential slant total delay phases (ddSTDPs) and GNSS-based ZTDs are available for March 2015 to July 2019. The validation of data assimilation with five independent GNSS stations for IWV shows improving Kling–Gupta efficiency (KGE) scores for all seasons, most notably for summer, with collocation data assimilation (KGE = 0.92) versus the open-cycle simulation (KGE = 0.69). The full dataset can be obtained from https://doi.org/10.1594/PANGAEA.936447 (Fersch et al., 2021)

Interferometric Synthetic Aperture Radar for slow slip applications

Over the last two decades, Slow Slip Events (SSEs) have been observed across many subduction zones, primarily through continuous GNSS networks. SSEs represent shearing of two tectonic plates, at much slower rates than earthquakes but more rapidly than plate motion. They are not dangerous in themselves, but change the stress field and can potentially trigger devastating earthquakes. While highly valuable, GNSS networks at most locations lack the spatial-resolution required to describe the spatial extent of the slow slip at depth. A better constraint of slow slip at depth in combination with other observations from seismology could be essential in addressing key research questions. These include: “Why do slow slip events occurs in some regions and not others?”, “What drives slow slip events?”, “Do slow slip events delay the occurrence of devastating earthquakes?”, and “Can slow slip events trigger devastating earthquakes?”. Interferometric Synthetic Aperture Radar (InSAR) is an established and attractive technique to study surface displacements at high-spatial resolution. Until now, InSAR has not been fully exploited for the study of SSEs. Here, I provide the necessary InSAR methodology, and further demonstrate the use of InSAR for static and time-dependant slow slip modelling. My developments have a direct benefit for various other applications such as earthquake cycle processes. I Specifically address the following two challenges which limit the wide uptake of InSAR: (1) Decorrelation noise introduced by changing backscattering properties of the surface and a change in satellite acquisition geometry, making it difficult to correctly unwrap meaningful signal. I address this problem by applying existing advanced time-series InSAR processing methods. (2) Atmospheric delays masking the smaller slow slip signal. These are mainly due to spatial and temporal variations in pressure, temperature, and relative humidity in the lower part of the troposphere, which result in an apparent signal in the InSAR data. Different tropospheric correction methods exist, all with their own limitations. Auxiliary data methods often lack the spatial and temporal resolution, while the phase-based methods cannot account for a spatially-varying troposphere. In response, I develop a phase-based power-law representation of tropospheric delay that can be applied in the presence of deformation and which accounts for spatial variation of tropospheric properties. I demonstrate its application over Mexico, where it reduces tropospheric signals both locally (on average by ~0.45 cm for each kilometer of elevation) and the long wavelength components. Moreover, I provide to the research community a Toolbox for Reducing Atmospheric InSAR Noise (TRAIN), which includes all the state-of-the-art correction methods, implemented as opensource matlab routines. When comparing these methods, I find spectrometers give the largest reduction in tropospheric noise, but are limited to cloud-free and daylight acquisitions. I also find that all correction methods perform ~10-20% worse when there is cloud cover. As all methods have their own limitations, future efforts should aim at combining the different correction methods in an optimal manner. Additionally, I apply my InSAR methodology and power-law correction method to the study of the 2006 Guerrero SSE, where I jointly invert cumulative GNSS and InSAR SSE surface displacements. In Guerrero, SSEs have been observed in a “seismic gap”, where no earthquakes have occurred since 1911, accumulating a seismic potential of Mw 8.0-8.4. I find slow slip enters the seismogenic zone and the Guerrero Gap, with ~5 cm slip reaching depths as shallow as 12 km, and where the spatial extent of the slow slip collocates on the interface with a highly coupled inter-SSE region as found from an GNSS study. In addition, slow slip decreased the total accumulated moment since the previous SSE (4.7 years earlier) by ~50% Over time and while accounting for SSEs, the moment deficit in the Guerrero Gap increases each year by Mw ~6.8. Therefore I find that the Guerrero Gap still has the potential for a large earthquake, with a seismic potential of Mw ~8.15 accumulated over the last century. Finally, I show the application to use InSAR for time-dependant slow slip modelling. From a simulation of the 2006 SSE, I demonstrate that InSAR is able to provide valuable information to constrain the spatial extent of the slow slip signal. With a future perspective of continued high repeat acquisitions of various SAR platforms, my expansion of the Network Inversion Filter with InSAR will become a powerful tool for investigating the spatio-temporal correlation between slow slip and other phenomena such as non volcanic tremor. Moreover, this approach can apply to earthquake cycle processes. Studying the broader earthquake cycle will further our knowledge of seismic hazard and increase our resilience to such events

Atmospheric artifacts correction for InSAR using empirical model and numerical weather prediction models

lnSAR has been proved its unprecedented ability and merits of monitoring ground deformation on large scale with centimeter to millimeter scale accuracy. However, several factors affect the reliability and accuracy of its applications. Among them, atmospheric artifacts due to spatial and temporal variations of atmosphere state often pose noise to interferograms. Therefore, atmospheric artifacts m itigalion remains one of the biggest challenges to be addressed in the In SAR community. State-of-the-art research works have revealed atmospheric artifacts can be partially compensated with empirical models, temporal-spatial filtering approach in lnSAR time series, pointwise GPS zenith path delay and numerical weather prediction models. In this thesis, firstly, we further develop a covariance weighted linear empirical model correction method. Secondly, a realistic LOS direction integration approach based on global reanalysis data is employed and comprehensively compared with the conventional method that integrates along zenith direction. Finally, the realistic integration method is applied to local WRF numerical forecast model data. l'vbreover, detailed comparisons between different global reanalysis data and local WRF model are assessed. In terms of empirical models correcting methods, many publications have studied correcting stratified tropospheric phase delay by assuming a linear model between them and topography. However, most of these studies ha\19 not considered the effect of turbulent atmospheric artefacts when adjusting the linear model to data. In this thesis, an improved technique that minimizes the influence of turbulent atmosphere in the model adjustment has been presented. In the proposed algorithm, the model is adjusted to the phase differences of pixels instead of using the unwrapped phase of each pixel. In addition, the different phase differences are weighted as a function of its APS covariance estimated from an empirical variogram to reduce in the model adjustment the impact of pixel pairs with significant turbulent atmosphere. The performance of the proposed method has been validated with both simulated and real Sentinel-1 SAR data in Tenerife island, Spain. Considering methods using meteorological observations to mitigate APS, an accurate realistic com puling strategy utilizing global atmospheric reanalysis data has been implemented. With the approach, the realistic LOS path along satellite and the monitored points is considered, rather than converting from zenith path delay. Com pared with zenith delay based method, the biggest advantage is that it can avoid errors caused by anisotropic atmospheric behaviour. The accurate integration method is validated with Sentinel-1 data in three test sites: Tenerife island, Spain, Almeria, Spain and Crete island, Greece. Compared to conventional zenith method, the realistic integration method shows great improvement. A variety of global reanalysis data are available from different weather forecasting organizations, such as ERA-Interim, ERAS, MERRA2. In this study, the realistic integration mitigation method is assessed on these different reanalysis data. The results show that these data are feasible to mitigate APS to some extent in most cases. The assessment also demonstrates that the ERAS performs the best statistically, compared to other global reanalysis data. l'vbreover, as local numerical weather forecast models have the ability to predict high spatial resolution atmospheric parameters, by using which, it has the potential to achieve APS mitigation. In this thesis, the realistic integration method is also employed on the local WRF model data in Tenerife and Almeria test s ites. However, it turns out that the WRF model performs worse than the original global reanalysis data.Las técnicas lnSAR han demostrado su capacidad sin precedentes y méritos para el monitoreo de la deformaci6n del suelo a gran escala con una precisión centimétrica o incluso milimétrica. Sin embargo, varios factores afectan la fiabilidad y precisión de sus aplicaciones. Entre ellos, los artefactos atmosféricos debidos a variaciones espaciales y temporales del estado de la atm6sfera a menudo añaden ruido a los interferogramas. Por lo tanto, la mitigación de los artefactos atmosféricos sigue siendo uno de los mayores desafíos a abordar en la comunidad lnSAR. Los trabajos de investigaci6n de vanguardia han revelado que los artefactos atmosféricos se pueden compensar parcialmente con modelos empíricos, enfoque de filtrado temporal-espacial en series temporales lnSAR, retardo puntual del camino cenital con GPS y modelos numéricos de predicción meteorológica. En esta tesis, en primer lugar, desarrollamos un método de corrección de modelo empírico lineal ponderado por covarianza. En segundo lugar, se emplea un enfoque realista de integracion de dirección LOS basado en datos de reanálisis global y se compara exhaustivamente con el método convencional que se integra a lo largo de la dirección cenital. Finalmente, el método de integraci6n realista se aplica a los datos del modelo de pronóstico numérico WRF local. Ademas, se evalúan las comparaciones detalladas entre diferentes datos de reanálisis global y el modelo WRF local. En términos de métodos de corrección con modelos empíricos, muchas publicaciones han estudiado la corrección del retraso estratificado de la fase troposférica asumiendo un modelo lineal entre ellos y la topografía. Sin embargo, la mayoría de estos estudios no han considerado el efecto de los artefactos atmosféricos turbulentos al ajustar el modelo lineal a los datos. En esta tesis, se ha presentado una técnica mejorada que minimiza la influencia de la atm6sfera turbulenta en el ajuste del modelo. En el algoritmo propuesto, el modelo se ajusta a las diferencias de fase de los pixeles en lugar de utilizar la fase sin desenrollar de cada pixel. Además, las diferentes diferencias de fase se ponderan en función de su covarianza APS estimada a partir de un variograma empírico para reducir en el ajuste del modelo el impacto de los pares de pixeles con una atm6sfera turbulenta significativa. El rendimiento del método propuesto ha sido validado con datos SAR Sentinel-1 simulados y reales en la isla de Tenerife, España. Teniendo en cuenta los métodos que utilizan observaciones meteorológicas para mitigar APS, se ha implementado una estrategia de computación realista y precisa que utiliza datos de reanálisis atmosférico global. Con el enfoque, se considera el camino realista de LOS a lo largo del satélite y los puntos monitoreados, en lugar de convertirlos desde el retardo de la ruta cenital. En comparación con el método basado en la demora cenital, la mayor ventaja es que puede evitar errores causados por el comportamiento atmosférico anisotrópico. El método de integración preciso se valida con los datos de Sentinel-1 en tres sitios de prueba: la isla de Tenerife, España, Almería, España y la isla de Creta, Grecia. En comparación con el método cenital convencional, el método de integración realista muestra una gran mejora.Postprint (published version

Atmospheric artifacts correction for InSAR using empirical model and numerical weather prediction models

lnSAR has been proved its unprecedented ability and merits of monitoring ground deformation on large scale with centimeter to millimeter scale accuracy. However, several factors affect the reliability and accuracy of its applications. Among them, atmospheric artifacts due to spatial and temporal variations of atmosphere state often pose noise to interferograms. Therefore, atmospheric artifacts m itigalion remains one of the biggest challenges to be addressed in the In SAR community. State-of-the-art research works have revealed atmospheric artifacts can be partially compensated with empirical models, temporal-spatial filtering approach in lnSAR time series, pointwise GPS zenith path delay and numerical weather prediction models. In this thesis, firstly, we further develop a covariance weighted linear empirical model correction method. Secondly, a realistic LOS direction integration approach based on global reanalysis data is employed and comprehensively compared with the conventional method that integrates along zenith direction. Finally, the realistic integration method is applied to local WRF numerical forecast model data. l'vbreover, detailed comparisons between different global reanalysis data and local WRF model are assessed. In terms of empirical models correcting methods, many publications have studied correcting stratified tropospheric phase delay by assuming a linear model between them and topography. However, most of these studies ha\19 not considered the effect of turbulent atmospheric artefacts when adjusting the linear model to data. In this thesis, an improved technique that minimizes the influence of turbulent atmosphere in the model adjustment has been presented. In the proposed algorithm, the model is adjusted to the phase differences of pixels instead of using the unwrapped phase of each pixel. In addition, the different phase differences are weighted as a function of its APS covariance estimated from an empirical variogram to reduce in the model adjustment the impact of pixel pairs with significant turbulent atmosphere. The performance of the proposed method has been validated with both simulated and real Sentinel-1 SAR data in Tenerife island, Spain. Considering methods using meteorological observations to mitigate APS, an accurate realistic com puling strategy utilizing global atmospheric reanalysis data has been implemented. With the approach, the realistic LOS path along satellite and the monitored points is considered, rather than converting from zenith path delay. Com pared with zenith delay based method, the biggest advantage is that it can avoid errors caused by anisotropic atmospheric behaviour. The accurate integration method is validated with Sentinel-1 data in three test sites: Tenerife island, Spain, Almeria, Spain and Crete island, Greece. Compared to conventional zenith method, the realistic integration method shows great improvement. A variety of global reanalysis data are available from different weather forecasting organizations, such as ERA-Interim, ERAS, MERRA2. In this study, the realistic integration mitigation method is assessed on these different reanalysis data. The results show that these data are feasible to mitigate APS to some extent in most cases. The assessment also demonstrates that the ERAS performs the best statistically, compared to other global reanalysis data. l'vbreover, as local numerical weather forecast models have the ability to predict high spatial resolution atmospheric parameters, by using which, it has the potential to achieve APS mitigation. In this thesis, the realistic integration method is also employed on the local WRF model data in Tenerife and Almeria test s ites. However, it turns out that the WRF model performs worse than the original global reanalysis data.Las técnicas lnSAR han demostrado su capacidad sin precedentes y méritos para el monitoreo de la deformaci6n del suelo a gran escala con una precisión centimétrica o incluso milimétrica. Sin embargo, varios factores afectan la fiabilidad y precisión de sus aplicaciones. Entre ellos, los artefactos atmosféricos debidos a variaciones espaciales y temporales del estado de la atm6sfera a menudo añaden ruido a los interferogramas. Por lo tanto, la mitigación de los artefactos atmosféricos sigue siendo uno de los mayores desafíos a abordar en la comunidad lnSAR. Los trabajos de investigaci6n de vanguardia han revelado que los artefactos atmosféricos se pueden compensar parcialmente con modelos empíricos, enfoque de filtrado temporal-espacial en series temporales lnSAR, retardo puntual del camino cenital con GPS y modelos numéricos de predicción meteorológica. En esta tesis, en primer lugar, desarrollamos un método de corrección de modelo empírico lineal ponderado por covarianza. En segundo lugar, se emplea un enfoque realista de integracion de dirección LOS basado en datos de reanálisis global y se compara exhaustivamente con el método convencional que se integra a lo largo de la dirección cenital. Finalmente, el método de integraci6n realista se aplica a los datos del modelo de pronóstico numérico WRF local. Ademas, se evalúan las comparaciones detalladas entre diferentes datos de reanálisis global y el modelo WRF local. En términos de métodos de corrección con modelos empíricos, muchas publicaciones han estudiado la corrección del retraso estratificado de la fase troposférica asumiendo un modelo lineal entre ellos y la topografía. Sin embargo, la mayoría de estos estudios no han considerado el efecto de los artefactos atmosféricos turbulentos al ajustar el modelo lineal a los datos. En esta tesis, se ha presentado una técnica mejorada que minimiza la influencia de la atm6sfera turbulenta en el ajuste del modelo. En el algoritmo propuesto, el modelo se ajusta a las diferencias de fase de los pixeles en lugar de utilizar la fase sin desenrollar de cada pixel. Además, las diferentes diferencias de fase se ponderan en función de su covarianza APS estimada a partir de un variograma empírico para reducir en el ajuste del modelo el impacto de los pares de pixeles con una atm6sfera turbulenta significativa. El rendimiento del método propuesto ha sido validado con datos SAR Sentinel-1 simulados y reales en la isla de Tenerife, España. Teniendo en cuenta los métodos que utilizan observaciones meteorológicas para mitigar APS, se ha implementado una estrategia de computación realista y precisa que utiliza datos de reanálisis atmosférico global. Con el enfoque, se considera el camino realista de LOS a lo largo del satélite y los puntos monitoreados, en lugar de convertirlos desde el retardo de la ruta cenital. En comparación con el método basado en la demora cenital, la mayor ventaja es que puede evitar errores causados por el comportamiento atmosférico anisotrópico. El método de integración preciso se valida con los datos de Sentinel-1 en tres sitios de prueba: la isla de Tenerife, España, Almería, España y la isla de Creta, Grecia. En comparación con el método cenital convencional, el método de integración realista muestra una gran mejora

Generic interferometric synthetic aperture radar atmospheric correction model and its application to co- and post-seismic motions

PhD ThesisThe tremendous development of Interferometric Synthetic Aperture Radar (InSAR) missions in recent years facilitates the study of smaller amplitude ground deformation over greater spatial scales using longer time series. However, this poses more challenges for correcting atmospheric effects due to the spatial-temporal variability of atmospheric delays. Previous attempts have used observations from Global Positioning System (GPS) and Numerical Weather Models (NWMs) to separate the atmospheric delays, but they are limited by (i) the availability (and distribution) of GPS stations; (ii) the time difference between NWM and radar observations; and (iii) the difficulties in quantifying their performance. To overcome the abovementioned limitations, we have developed the Iterative Tropospheric Decomposition (ITD) model to reduce the coupling effects of the troposphere turbulence and stratification and hence achieve similar performances over flat and mountainous terrains. Highresolution European Centre for Medium-Range Weather Forecasts (ECMWF) and GPS-derived tropospheric delays were properly integrated by investigating the GPS network geometry and topography variations. These led to a generic atmospheric correction model with a range of notable features: (i) global coverage, (ii) all-weather, all-time usability, (iii) available with a maximum of two-day latency, and (iv) indicators available to assess the model’s performance and feasibility. The generic atmospheric correction model enables the investigation of the small magnitude coseismic deformation of the 2017 Mw-6.4 Nyingchi earthquake from InSAR observations in spite of substantial atmospheric contamination. It can also minimize the temporal correlations of InSAR atmospheric delays so that reliable velocity maps over large spatial extents can be achieved. Its application to the post-seismic motion following the 2016 Kaikoura earthquake shows a success to recover the time-dependent afterslip distribution, which in turn evidences the deep inactive subduction slip mechanism. This procedure can be used to map surface deformation in other scenarios including volcanic eruptions, tectonic rifting, cracking, and city subsidence.This work was supported by a Chinese Scholarship Council studentship. Part of this work was also supported by the UK NERC through the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET)

Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

Remote Sensing of Precipitation: Part II

Precipitation is a well-recognized pillar in the global water and energy balances. The accurate and timely understanding of its characteristics at the global, regional and local scales is indispensable for a clearer insight on the mechanisms underlying the Earth’s atmosphere-ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises the primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne. This volume hosts original research contributions on several aspects of remote sensing of precipitation, including applications which embrace the use of remote sensing in tackling issues such as precipitation estimation, seasonal characteristics of precipitation and frequency analysis, assessment of satellite precipitation products, storm prediction, rain microphysics and microstructure, and the comparison of satellite and numerical weather prediction precipitation products

The science case for the EISCAT_3D radar

The EISCAT (European Incoherent SCATer) Scientific Association has provided versatile incoherent scatter (IS) radar facilities on the mainland of northern Scandinavia (the EISCAT UHF and VHF radar systems) and on Svalbard (the electronically scanning radar ESR (EISCAT Svalbard Radar) for studies of the high-latitude ionised upper atmosphere (the ionosphere). The mainland radars were constructed about 30 years ago, based on technological solutions of that time. The science drivers of today, however, require a more flexible instrument, which allows measurements to be made from the troposphere to the topside ionosphere and gives the measured parameters in three dimensions, not just along a single radar beam. The possibility for continuous operation is also an essential feature. To facilitatefuture science work with a world-leading IS radar facility, planning of a new radar system started first with an EU-funded Design Study (2005–2009) and has continued with a follow-up EU FP7 EISCAT_3D Preparatory Phase project (2010–2014). The radar facility will be realised by using phased arrays, and a key aspect is the use of advanced software and data processing techniques. This type of software radar will act as a pathfinder for other facilities worldwide. The new radar facility will enable the EISCAT_3D science community to address new, significant science questions as well as to serve society, which is increasingly dependent on space-based technology and issues related to space weather. The location of the radar within the auroral oval and at the edge of the stratospheric polar vortex is also ideal for studies of the long-term variability in the atmosphere and global change. This paper is a summary of the EISCAT_3D science case, which was prepared as part of the EU-funded Preparatory Phase project for the new facility. Three science working groups, drawn from the EISCAT user community, participated in preparing this document. In addition to these working group members, who are listed as authors, thanks are due to many others in the EISCAT scientific community for useful contributions, discussions, and support

3-D observations of absolute humidity from the land surface to the lower troposphere with scanning differential absorption lidar

The water vapor (WV) distribution in the atmospheric boundary layer (ABL) is spatially and temporally highly variable. To investigate this behavior, the Institute of Physics and Meteorology at the University of Hohenheim (UHOH) developed a unique scanning differential absorption lidar (DIAL). This instrument allows for water vapor measurements with high temporal and spatial resolutions of the orders of seconds and tens of meters in the range of several kilometers from the surface up to the lower troposphere. Additionally, the UHOH DIAL system can perform scanning measurements which allows for observations down to the surface as well as for observations of the horizontal moisture variability. Within this thesis, three aspects regarding high-resolution observations of moisture in the ABL with scanning DIAL are demonstrated: 1) the development of a new seeder system for the laser transmitter, 2) the presentation of three scan modes, and 3) applications of 2-D to 3-D WV DIAL data. The newly developed seeder system is based on distributed feedback (DFB) laser diodes as seed lasers and an electro-optical deflector as optical switch. The setup and its specifications are presented. Scanning measurements were performed to capture the spatial WV structures. For this purpose, three scan modes with measurement examples are presented: 1) Range-height indicator (RHI) scans provide vertical cross-section images of the atmospheric humidity distribution. The presented series of four measurements show several humidity layers with different WV content and their evolution. Clouds appear in the last scan. 2) A volume scan captures the whole three-dimensional WV structure made out of several conical scans of different elevation angles. The horizontal variation of the layer heights can be related to the terrain profile with a small hill near the DIAL site. 3) Low elevation scans observe the WV distribution directly above the surface. Thus, relationships of the ground characteristics and vegetation with the humidity content above can be investigated. It is shown that there was more moisture above a maize field and above a forest than above grassland. For the analysis of scanning measurements, new analysis and visualization routines as well as new methods for the error estimation were developed. More scientific applications of high-resolution WV data from DIAL measurements are presented in three publications. A evaluation study compared humidity profiles from model simulations with different land-surface schemes with horizontal mean profiles of scanning DIAL measurements. High-resolution humidity fluctuations from vertical measurements were used to determine higher-order moments up to the fourth-order as well as skewness and kurtosis. Furthermore, such WV profiles were combined with profiles of temperature and vertical wind velocities and used for the development of new turbulence parameterizations and for model validation.Die Wasserdampfverteilung in der atmosphärischen Grenzschicht ist räumlich und zeitlich sehr variabel. Zur Untersuchung dieses Verhaltens entwickelte das Institut für Physik und Meteorologie an der Universität Hohenheim (UHOH) ein einzigartiges scannendes differentielles Absorptionslidar (DIAL). Dieses ermöglicht Wasserdampfmessungen mit einer zeitlichen und räumlichen Auflösung von wenigen Sekunden und einigen zehn Metern in einem Bereich von mehreren Kilometeren vom Boden bis zur unteren Troposphäre. Das UHOH DIAL-System erlaubt zudem scannende Messungen, die zum einen Messungen bis an den Boden und zum anderen Messungen der horizontalen Variabilität der Feuchtigkeit ermöglichen. Diese Arbeit behandelt drei Aspekte bezüglich hochaufgelöster Feuchtemessung in der atmosphärischen Grenzschicht mit scannendem DIAL: 1) Die Entwicklung eines neuen Seedersystems für den Lasertransmitter, 2) die Vorstellung verschiedener Scan-Modi und 3) Anwendungen von mit dem DIAL gemessenen 2-D bis 3-D Wasserdampfdaten. Das neu entwickelte Seedersystem basiert auf Distributed Feedback (DFB) Laserdioden als Seedlaser und einem elektro-optischen Strahlablenker als optischen Schalter. Der Aufbau und die Spezifikationen werden vorgestellt. Zur Erfassung der räumlichen Wasserdampfstruktur werden scannende Messungen durchgeführt. Dazu werden folgende 3 Scanverfahren mit Messbeispielen vorgestellt: 1) Range-height indicator (RHI) Scans liefern vertikale Schnittbilder der atmosphärischen Feuchteverteilung. Die vorgestellte Serie aus vier Messungen zeigt verschiedene Feuchteschichten mit unterschiedlichem Wasserdampfgehalt und deren Entwicklung. Im Messbeispiel treten im letzten durchgeführten Scan Wolken an der Oberkante der konvektiven Grenzschicht auf. 2) Der Volumenscan erfasst die gesamte 3-dimensionale Wasserdampfstruktur mittels mehrerer konischer Scans mit unterschiedlichen Elevationswinkeln. Die horizontalen Unterschiede der Schichtenhöhen können anhand des Geländeprofiles mit einem kleinen Hügel in der Nähe des DIAL-Standorts erklärt werden. 3) Bodennahe Scans geben die Wasserdampfverteilung direkt über dem Erdboden wieder. Damit können Beziehungen zwischen der Bodenbeschaffenheit und dem -bewuchs mit der darüber liegenden Atmosphäre untersucht werden. So zeigten sich über einem Maisfeld und über Wald höhere Wasserdampfwerte als über einer Grasfläche. Für die Analyse der scannenden Messungen wurden neue Auswerte- und Darstellungsroutinen, sowie neue Methoden zur Fehlerabschätzung entwickelt. Die wissenschaftliche Anwendung von hochaufgelösten Wasserdampfdaten aus DIAL Messungen werden anhand von drei Veröffentlichungen vorgestellt. Eine Evaluierungsstudie zu Modellsimulationen mit unterschiedlichen Land-Atmosphären-Austauschmodellen verglich Feuchtigkeitsprofile aus den Modellen mit horizontal gemittelten Wasserdampfdaten aus scannenden DIAL-Messungen. Hochaufgelöste Feuchtefluktuationen aus Vertikalmessungen wurden verwendet, um höhere Momente bis zur vierten Ordnung sowie Skewness und Kurtosis zu bestimmen. Weiter wurden solche Feuchteprofile mit Profilen von Temperatur und Vertikalwind kombiniert und genutzt, um neue Turbulenzparametrisierungen zu entwickeln und zu testen