Search

By the end of 2017, the European Space Agency (ESA) will launch the Atmospheric laser Doppler instrument (ALADIN), a direct detection Doppler wind lidar operating at 355 nm. An important tool for the validation and optimization of ALADIN’s hardware and data processors for wind retrievals with real atmospheric signals is the ALADIN airborne demonstrator A2D. In order to be able to validate and test aerosol retrieval algorithms from ALADIN, an algorithm for the retrieval of atmospheric backscatter and extinction profiles from A2D is necessary. The A2D is utilizing a direct detection scheme by using a dual Fabry-Pérot interferometer to measure molecular Rayleigh signals and a Fizeau interferometer to measure aerosol Mie returns. Signals are captured by accumulation charge coupled devices (ACCD). These specifications make different steps in the signal preprocessing necessary. In this paper, the required steps to retrieve aerosol optical products, i. e. particle backscatter coefficient βp, particle extinction coefficient αp and lidar ratio Sp from A2D raw signals are described.

Cirrus clouds impose high uncertainties on climate prediction, as knowledge on important processes is still incomplete. For instance it remains unclear how cloud microphysical and radiative properties change as the cirrus evolves. Recent studies classify cirrus clouds into categories including in situ, orographic, convective and liquid origin clouds and investigate their specific impact. Following this line, we present a novel scheme for the classification of cirrus clouds that addresses the need to determine specific stages of cirrus evolution. Our classification scheme is based on airborne Differential Absorption and High Spectral Resolution Lidar measurements of atmospheric water vapor, aerosol depolarization, and backscatter, together with model temperature fields and simplified parameterizations of freezing onset conditions. It identifies regions of supersaturation with respect to ice (ice-supersaturated regions, ISSRs), heterogeneous and homogeneous nucleation, depositional growth, and ice sublimation and sedimentation with high spatial resolution. Thus, all relevant stages of cirrus evolution can be classified and characterized. In a case study of a gravity lee-wave-influenced cirrus cloud, encountered during the ML-CIRRUS flight campaign, the applicability of our classification is demonstrated. Revealing the structure of cirrus clouds, this valuable tool might help to examine the influence of evolution stages on the cloud's net radiative effect and to investigate the specific variability of optical and microphysical cloud properties in upcoming research.

For the first time an upconversion based detection scheme is demonstrated for lidar measurements of atmospheric CO2-concentrations, with a hard target at a range of 3 km and atmospheric backscatter from a range of similar to 450 m. The pulsed signals at 1572 nm are upconverted to 635 nm, and detected by a photomultiplier tube, to test how the upconversion technology performs in a long range detection system. The upconversion approach is compared to an existing direct detection scheme using a near-IR detector with respect to signal-to-noise ratio and quantum efficiency. It is for the first time analyzed how the field-of-view of a receiver system, for long range detection, depends critically on the parameters for the nonlinear upconversion process, and how to optimize these parameters in future systems. (C) 2016 Optical Society of America

Large scale mapping of snow water equivalent (SWE) is a long-lasting request in many scientific and economical fields. Active and passive microwave remote sensing methods are explored, as local methods cannot be generalized due to the spatial inhomogeneity of the snow pack. Microwaves interact with snow by absorption, scattering, and refraction. For dry snow of a few meters depth and frequencies below 20 GHz, absorption and scattering in the snow volume are negligible compared with the backscattered energy from the underlying ground. The signal delay caused by refraction can be measured with differential radar interferometry, but phase wrapping errors and temporal decorrelation must be considered. We demonstrate that large $\Delta\text{SWE}$ can be accurately determined from dense time series of differential interferograms at X- and Ku-band by temporal integration. Lost phase cycles are reconstructed with a two-frequency approach. Temporal decorrelation is minimized by a temporal resolution of 4h. A linear function between $\Delta\text{SWE}$ and phase difference is derived, which deviates only a few percent from the exact solution and which depends negligibly on snow density and stratigraphy. $\Delta\text{SWE}$ retrieved from observations of the SnowScat instrument (SSI) were validated against observed SWE from different reference instruments, installed at a test site near the town of Sodankyla, Finland. An accuracy below $\pm 6\;\text{mm}$ SWE was achieved at frequencies of 10 and 16 GHz for up to 200 mm of $\Delta$ SWE. An exceptionally high temporal coherence was observed for up to 30 days for dry snow, whereas for wet snow it decayed within hours.

The German TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) mission (TDM) collects two global data sets of very high resolution (VHR) synthetic aperture radar (SAR) images between 2011 and 2013. Such imagery provides a unique information source for the identification of built-up areas in a so far unique spatial detail. This letter presents the novel implementation of a fully automated processing system for the delineation of human settlements worldwide based on the SAR data acquired in the context of the TDM. The proposed Urban Footprint Processor (UFP) includes three main processing stages dedicated to: i) the extraction of texture information suitable for highlighting regions characterized by highly structured and heterogeneous built-up areas; ii) the generation of a binary settlement layer (built-up, non-built-up) based on an unsupervised classification scheme accounting for both the original backscattering amplitude and the extracted texture; and iii) a final post-editing and mosaicking phase aimed at providing the final Urban Footprint (UF) product for arbitrary geographical regions. Experimental results assess the high potential of the TDM data and the proposed UFP to provide highly accurate geo-data for an improved global mapping of human settlements.

In recent years, there has been increased interest in using synthetic aperture radar (SAR) to study and monitor glaciers and ice sheets for glaciological and climate change research. However, due to the medium's complexity, SAR backscattering from ice remains poorly understood, including the relative importance of scattering from surface and volume layers and also dependences on frequency and glacier zone. Extreme weather conditions can result in quickly changing surface conditions influencing backscatter signatures while leaving the underlying volume of interest unchanged. Surface and volume components must thus be separated in order to infer information regarding the properties of the ice volume. This paper describes a three-component scattering model to decompose polarimetric SAR (PolSAR) images of glacier ice. Total backscatter is modeled as the incoherent summation of surface, volume, and sastrugi (wind-induced feature) components. The proposed model adapts and extends the Freeman and Durden decomposition for an ice volume scenario in which the volume is a dielectric medium. Forms of the model for both random and oriented volumes are considered, and a new oriented sastrugi component is introduced which is able to explain backscatter behavior between different winter scenes. Validation is performed with airborne PolSAR data at L- and P-band collected using the E-SAR system of the German Aerospace Center over the Austfonna ice cap in Svalbard, Norway, as part of the ICESAR campaign.

In this paper, the decomposition of fully polarimetric SAR data into three canonical scattering mechanisms is investigated with respect to forest biomass retrieval. It is demonstrated that the dominant backscattering contribution depends strongly on the frequency, incidence angle, and stand condition. The relation between in-situ biomass measurements and the individual decomposition components is examined.

The thesis describes the acquisition, cleaning and visualisation of multibeam data which were collected on RV Polarstern and USCGC Healy during the Arctic Mid-Ocean-Ridge Expedition (AMORE) 2001. The data sets are combined in a high-resolution digital terrain model and a bathymetric chart of the Gakkel Ridge (8W-88E, 82N-87N). In order to process acoustic backscatter from two different sonar systems, Hydrosweep DS-2 and Seabeam 2112, an extensive software package was developed. The angle-normalised and beam pattern corrected backscatter values are compared in five areas. The variation of the backscatter strength is analysed over different rock types, sediment cores and seismogram sections that were measured by the sediment echosounder Parasound. Using angle-invariant backscatter data the Gakkel Ridge is classified in a Western Volcanic Zone (WVZ), a Sparsely Magmatic Zone (SMZ) and an Eastern Volcanic Zone (EVZ). While the basaltic WVZ and EVZ show high backscatter values the backscattering in the SMZ, consisting of mainly peridotites, is rather low. The result of the classification is verified by a second procedure in selected clusters.

As part of the CryoSat Calibration and Validation Experiment (CryoVEx) this work is related to the calibration and validation of ESA's AirborneSAR/Interferometric Radar Altimeter System (ASIRAS). ASIRAS was designed to simulate the CryoSat SAR Interferometric Radar Altimeter (SIRAL) for reasons of pre-launch and simultaneous accuracy and backscatter studies by using a similar instrument. The purpose of the ASIRAS calibration and data validation is to provide confidence in estimates of the uncertainty of the ASIRAS data products such as surface elevation and phase difference. Error estimates of the ASIRAS surface elevation in different snow zones were assessed using simultaneously acquired reference surfaceheights from an airborne laser scanner (reference digital elevation model). The phase difference and coherence tests were performed using data acquired over corner reflectors. The data were collected over the main validation sites in Greenland (EGIG line), Austfonna (Svalbard) and Devon Ice Cap (Canadian Arctic) during five CryoVEx sea- and land icecampaigns in 2004, 2005, 2006 and 2007. Prior to the validation of the ASIRAS data, a calibration and dating concept was designed and implemented. The latter was necessary in order to align all instruments (GPS, INS, laser scanner and ASIRAS) exactly to one reference time(GPS-UTC). Several dating and instrument uncertainties (e.g. systematic errors in the laser scanner raw data and ASIRAS time shifts) could be solved and corrected. In order to derive the surface elevation, processing software for the determination of laser squinting angles, the geocoding of the laser heights, the interferometric processing, and the retracking of the ASIRAS echoes was developed. The accuracy of the ASIRAS surface elevation was examined along selected \mbox{2 km to 3 km} long profiles for four different surface types (runway, dry snow and percolation zone of Greenland, and accumulation zone of Austfonna) byusing five different retracker algorithms. An overall rms accuracy of 0.05~m was found, however with a varying offset to the reference DEM reaching from 0.0~m for the runway to 1.50~m for the dry snow zone. The findings are related to roughness and backscatter variations along the chosen profiles. In general, higher accuracy could be found in regions of lower radar wavelength related surface roughness. The large offset in the dry snow zone is most likely not caused by surface roughness but related to volume scattering within the snowpack. Furthermore, in\citet{helm_grl_2007} the feasibility was demonstrated to derive the winter snow accumulation in the percolation zone of Greenland based on ASIRAS data. In the high altitude mode, ASIRAS allows the determination of across track surface slopes by means of interferometric processing.The analysis showed a difference of -0.43 /- 0.81 m to the reference DEM with high rms values related to low coherence and unwrapping errors. Additional measurements, possibly at higher flight levels, are needed to investigate the overall low coherence. In summary, this comprehensive study proves the concept of ASIRAS as the core instrument for the Cryosat satellite validation. In addition, ASIRAS on its own may contribute significantly to a fundamental understanding of microwave signatures over land and sea ice. In this context, a forward model which simulates the ASIRAS response over different layered and non layered media will help to better understand and exploit the presented findings.