@article{GrasslRitterSchulz2022, author = {Grassl, Sandra and Ritter, Christoph and Schulz, Alexander}, title = {The nature of the Ny-Alesund wind field analysed by high-resolution windlidar data}, series = {Remote sensing}, volume = {14}, journal = {Remote sensing}, number = {15}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {10.3390/rs14153771}, pages = {24}, year = {2022}, abstract = {In this work we present windlidar data for the research village Ny-Alesund located on Svalbard in the European Arctic (78.923 degrees N, 11.928 degrees F) from 2013 to 2021. The data have a resolution of 50 m and 10 min with an overlapping height of about 150 m. The maximum range depends on the meteorologic situation. Up to 1000 m altitude the data availability is better than 71\%. We found that the highest wind speeds occur in November and December, the lowest ones in June and July, up to 500 m altitude the wind is channelled strongly in ESE to NW direction parallel to the fjord axis and the synoptic conditions above 1000 m altitude already dominate. While the fraction of windy days (v > 10 m/s) varies significantly from month to month, there is no overall trend of the wind visible in our data set. We define gusts and jets by the requirement of wind maxima v > 2 m/s above and below a wind maximum. In total, more than 24,000 of these events were identified (corresponding to 6\% of the time), of which 223 lasted for at least 100 min ("Long Jets"). All of these events are fairly equally distributed over the months relatively to the available data. Further, gusts and jets follow different distributions (in terms of altitude or depths) and occur more frequently for synoptic flow from roughly a southerly direction. Jets do not show a clear correlation between occurrence and synoptic flow. Gusts and jets are not related to cloud cover. We conclude that the atmosphere from 400 m to 1000 m above Ny-Alesund is dominated by a turbulent wind shear zone, which connects the micrometeorology in the atmospheric boundary layer (ABL) with the synoptic flow.}, language = {en} } @article{AsgarimehrWickertReich2018, author = {Asgarimehr, Milad and Wickert, Jens and Reich, Sebastian}, title = {TDS-1 GNSS Reflectometry}, series = {IEEE journal of selected topics in applied earth observations and remote sensing}, volume = {11}, journal = {IEEE journal of selected topics in applied earth observations and remote sensing}, number = {11}, publisher = {Inst. of Electr. and Electronics Engineers}, address = {Piscataway}, issn = {1939-1404}, doi = {10.1109/JSTARS.2018.2873241}, pages = {4534 -- 4541}, year = {2018}, abstract = {This study presents the development and a systematic evaluation study of GNSS reflectometry wind speeds. After establishing a wind speed retrieval algorithm, UK TechDemoSat-1 (TDS-1) derived winds, from May 2015 to July 2017, are compared to the Advanced Scatterometer (ASCAT). ERA-Interim wind fields of the European Centre for Medium-range Weather Forecasts (ECMWF) and in situ observation from Tropical Atmosphere Ocean buoy array in the Pacific are taken as reference. One-year averaged TDS-1 global winds demonstrate small differences with ECMWF in a majority of areas as well as discuss under- and overestimations. The pioneering TDS-1 winds demonstrate a root-mean-squared error (RMSE) and bias of 2.77 and -0.33 m/s, which are comparable to the RMSE and bias derived by ASCAT winds, as large as 2.31 and 0.25 m/s, respectively. Using buoys measurements as reference, RMSE and bias of 2.23 and -0.03 m/s for TDS-1 as well as 1.40 and -0.68 m/s for ASCAT are obtained. Utilizing rain microwave-infrared estimates of the Tropical Rainfall Measuring Mission, rain-affected observation of both ASCAT and TDS-1 are collected and evaluated. Although ASCAT winds show a significant performance degradation resulting in an RMSE and bias of 3.16 and 1.03 m/s, respectively, during rain condition, TDS-1 shows a more reliable performance with an RMSE and bias of 2.94 and -0.21 m/s, respectively, which indicates the promising capability of GNSS forward scattering for wind retrievals during rain. A decrease in TDS-1-derived bistatic radar cross sections during rain events, at weak winds, is also demonstrated.}, language = {en} } @article{AsgarimehrWickertReich2019, author = {Asgarimehr, Milad and Wickert, Jens and Reich, Sebastian}, title = {Evaluating impact of rain attenuation on space-borne GNSS reflectometry wind speeds}, series = {Remote Sensing}, volume = {11}, journal = {Remote Sensing}, number = {9}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {10.3390/rs11091048}, pages = {18}, year = {2019}, abstract = {The novel space-borne Global Navigation Satellite System Reflectometry (GNSS-R) technique has recently shown promise in monitoring the ocean state and surface wind speed with high spatial coverage and unprecedented sampling rate. The L-band signals of GNSS are structurally able to provide a higher quality of observations from areas covered by dense clouds and under intense precipitation, compared to those signals at higher frequencies from conventional ocean scatterometers. As a result, studying the inner core of cyclones and improvement of severe weather forecasting and cyclone tracking have turned into the main objectives of GNSS-R satellite missions such as Cyclone Global Navigation Satellite System (CYGNSS). Nevertheless, the rain attenuation impact on GNSS-R wind speed products is not yet well documented. Evaluating the rain attenuation effects on this technique is significant since a small change in the GNSS-R can potentially cause a considerable bias in the resultant wind products at intense wind speeds. Based on both empirical evidence and theory, wind speed is inversely proportional to derived bistatic radar cross section with a natural logarithmic relation, which introduces high condition numbers (similar to ill-posed conditions) at the inversions to high wind speeds. This paper presents an evaluation of the rain signal attenuation impact on the bistatic radar cross section and the derived wind speed. This study is conducted simulating GNSS-R delay-Doppler maps at different rain rates and reflection geometries, considering that an empirical data analysis at extreme wind intensities and rain rates is impossible due to the insufficient number of observations from these severe conditions. Finally, the study demonstrates that at a wind speed of 30 m/s and incidence angle of 30 degrees, rain at rates of 10, 15, and 20 mm/h might cause overestimation as large as approximate to 0.65 m/s (2\%), 1.00 m/s (3\%), and 1.3 m/s (4\%), respectively, which are still smaller than the CYGNSS required uncertainty threshold. The simulations are conducted in a pessimistic condition (severe continuous rainfall below the freezing height and over the entire glistening zone) and the bias is expected to be smaller in size in real environments.}, language = {en} }