Application of Reflected Global Navigation Satellite System (GNSS-R) Signals in the Estimation of Sea Roughness Effects in Microwave Radiometry

In February-March 2009 NASA JPL conducted an airborne field campaign using the Passive Active L-band System (PALS) and the Ku-band Polarimetric Scatterometer (PolSCAT) collecting measurements of brightness temperature and near surface wind speeds. Flights were conducted over a region of expected high-speed winds in the Atlantic Ocean, for the purposes of algorithm development for salinity retrievals. Wind speeds encountered were in the range of 5 to 25 m/s during the two weeks deployment. The NASA-Langley GPS delay-mapping receiver (DMR) was also flown to collect GPS signals reflected from the ocean surface and generate post-correlation power vs. delay measurements. This data was used to estimate ocean surface roughness and a strong correlation with brightness temperature was found. Initial results suggest that reflected GPS signals, using small low-power instruments, will provide an additional source of data for correcting brightness temperature measurements for the purpose of sea surface salinity retrievals

Airborne Radar Interferometric Repeat-Pass Processing

Earth science research often requires crustal deformation measurements at a variety of time scales, from seconds to decades. Although satellites have been used for repeat-track interferometric (RTI) synthetic-aperture-radar (SAR) mapping for close to 20 years, RTI is much more difficult to implement from an airborne platform owing to the irregular trajectory of the aircraft compared with microwave imaging radar wavelengths. Two basic requirements for robust airborne repeat-pass radar interferometry include the ability to fly the platform to a desired trajectory within a narrow tube and the ability to have the radar beam pointed in a desired direction to a fraction of a beam width. Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) is equipped with a precision auto pilot developed by NASA Dryden that allows the platform, a Gulfstream III, to nominally fly within a 5 m diameter tube and with an electronically scanned antenna to position the radar beam to a fraction of a beam width based on INU (inertial navigation unit) attitude angle measurements

Validating SMAP SSS with in situ measurements

Sea surface salinity (SSS) retrieved from SMAP radiometer measurements are validated against in situ salinity from Argo floats, tropical moored buoys and ship-based thermosalinograph (TSG) data. SMAP SSS achieved an accuracy of 0.2 PSU on a monthly basis in comparison with Argo gridded data in the tropics and mid-latitudes. In the tropical oceans, time series comparison of salinity measured at 1 m by moored buoys indicates that SMAP can track large salinity changes occurred within a month. Synergetic analysis of SMAP, SMOS and Argo data allows us to identify and exclude erroneous jumps or drift in some real-time buoy data from the assessment of the satellite data. The resulting SMAP-buoy matchup analysis gives an average standard deviation of 0.22 PSU and correlation coefficient of 0.73 on weekly scale. On monthly time scales, the average standard deviation reduced to 0.17 PSU and the correlation coefficient improved to 0.8. SMAP L3 daily maps reveals salty water intrusions from the Arabian Sea into the Bay of Bengal during the Indian summer monsoon, consistent with the daily measurements collected from Argo floats deployed during the Bay of Bengal Boundary Layer Experiment (BoBBLE) project field campaign. In the Mediterranean Sea, the spatial pattern of SSS from SMAP is confirmed by the ship-based TSG. Comparison with individual Argo floats suggests the SMAP retrieval algorithm performs better in the Western Mediterranean region, but suffers from radio-frequency interference (RFI) and land contamination in the Eastern Mediterranean region and Adriatic Sea. © 2017 Elsevier Inc

Situational awareness within objective structured clinical examination stations in undergraduate medical training - a literature search

Background: Medical students may not be able to identify the essential elements of situational awareness (SA) necessary for clinical reasoning. Recent studies suggest that students have little insight into cognitive processing and SA in clinical scenarios. Objective Structured Clinical Examinations (OSCEs) could be used to assess certain elements of situational awareness. The purpose of this paper is to review the literature with a view to identifying whether levels of SA based on Endsley's model can be assessed utilising OSCEs during undergraduate medical training. Methods: A systematic search was performed pertaining to SA and OSCEs, to identify studies published between January 1975 (first paper describing an OSCE) and February 2017, in peer reviewed international journals published in English. PUBMED, EMBASE, PsycINFO Ovid and SCOPUS were searched for papers that described the assessment of SA using OSCEs among undergraduate medical students. Key search terms included "objective structured clinical examination", "objective structured clinical assessment" or "OSCE" and "non-technical skills", "sense-making", "clinical reasoning", "perception", "comprehension", "projection", "situation awareness", "situational awareness" and "situation assessment". Boolean operators (AND, OR) were used as conjunctions to narrow the search strategy, resulting in the limitation of papers relevant to the research interest. Areas of interest were elements of SA that can be assessed by these examinations. Results: The initial search of the literature retrieved 1127 publications. Upon removal of duplicates and papers relating to nursing, paramedical disciplines, pharmacy and veterinary education by title, abstract or full text, 11 articles were eligible for inclusion as related to the assessment of elements of SA in undergraduate medical students. Discussion: Review of the literature suggests that whole-task OSCEs enable the evaluation of SA associated with clinical reasoning skills. If they address the levels of SA, these OSCEs can provide supportive feedback and strengthen educational measures associated with higher diagnostic accuracy and reasoning abilities. Conclusion: Based on the findings, the early exposure of medical students to SA is recommended, utilising OSCEs to evaluate and facilitate SA in dynamic environment

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits

Cross Calibration Between QuikSCAT and Oceansat-2

No abstract availabl

Retrieval of Sea Surface Salinity and Wind from the NASA Soil Moisture Active Passive Mission Data

No abstract availabl

QuikSCAT Climatological Data Record: Land Contamination Flagging and Correction

We develop, utilize, and validate techniques to produce a global data set of accurate coastal ocean surface vector winds. The dataset extends as near to the coast as 5 km and includes 10 years of SeaWinds on QuikSCAT ocean scatterometer data obtained from 1999 to 2009. We demonstrate improved retrievals over other large land-locked bodies of water as well, such as the Caspian Sea and the Great lakes. To determine the coastal winds we quantify the extent of land contamination in each scatterometer backscatter measurement and to the extent possible remove that contamination. After the measurements are thus corrected we retrieve winds with the corrected measurements using a previously published algorithm which has been extensively used for JPL scatterometer wind products. The coastal processing vastly increases the number of wind vector cells near coasts. We have ten times the number of wind vectors within 10 km of coast as without coastal processing, and over twice as many at 20 km from coast. These new wind vectors are high-quality, and have zero effect on non-coastal wind vectors. The effect of residual land contamination is quantified by comparing to buoys at varying distance from the coast and comparing coastal wind vector cells to oceanward neighbors. We show that the non-coastal QuikSCAT processing has very few good wind vectors nearer to the coast than about 22.5 km. In comparison to buoys, and oceanward neighbors, we find a small increase in speed errors of these new coastal wind vectors versus the performance of non-coastal QuikSCAT at 22.5 km, indicating the high-quality of these new coastal wind vectors. A quality control scheme is employed that flags regions where the coastal wind retrieval is poor due to the assumptions inherent in the technique being locally invalid. The coastal winds retrieved in this manner have been publicly distributed to the oceanography community and utilized in other published works