Impact of high frequency waves on the ocean altimeter range bias

New aircraft observations are presented on the range determination error in satellite altimetry associated with ocean waves. Laser-based measurements of the cross correlation between the gravity wave slope and elevation are reported for the first time. These observations provide direct access to a long, O(10 m), gravity wave statistic central to nonlinear wave theory prediction of the altimeter sea state bias. Coincident Ka-band radar scattering data are used to estimate an electromagnetic (EM) range bias analogous to that in satellite altimetry. These data, along with ancillary wind and wave slope variance estimates, are used alongside existing theory to evaluate the extent of long- versus short-wave, O(cm), control of the bias. The longer wave bias contribution to the total EM bias is shown to range from 25 to as much as 100%. Moreover, on average the term is linearly related to wind speed and to the gravity wave slope variance, consistent with WNL theory. The EM bias associated with interactions between long and short waves is obtained assuming the effect is additive to the independently observed long-wave factor. This second component is also a substantial contributor, is observed to be quadratic in wind speed or wave slope, and dominates at moderate wind speeds. The behavior is shown to be consistent with EM bias prediction based in hydrodynamic modulation theory. Study implications for improved correction of the on-orbit satellite sea state bias are discussed

Sea state bias in altimeter sea level estimates determined by combining wave model and satellite data

This study documents a method for increasing the precision of satellite-derived sea level measurements. Results are achieved using an enhanced three-dimensional (3-D) sea state bias (SSB) correction model derived from both Jason-1 altimeter ocean observations (i.e., sea state and wind) and estimates of mean wave period from a numerical ocean wave model, NOAA’s WAVEWATCH III. A multiyear evaluation of Jason-1 data indicates sea surface height variance reduction of 1.26 (±0.2) cm2 in comparison to the commonly applied two-parameter SSB model. The improvement is similar for two separate variance reduction metrics and for separate annual data sets spanning 2002–2004. Spatial evaluation of improvement shows skill increase at all latitudes. Results indicate the new model can reduce the total Jason-1 and Jason-2 altimeter range error budgets by 7.5%. In addition to the 2-D (two-dimensional) and 3-D model differences in correcting the range for wavefield variability, mean model regional differences also occur across the globe and indicate a possible 1–2 cm gradient across ocean basins linked to the zonal variation in wave period (short fetch and period in the west, swells and long period in the east). Overall success of this model provides first evidence that operational wave modeling can support improved ocean altimetry. Future efforts will attempt to work within the limits of wave modeling capabilities to maximize their benefit to Jason-1 and Jason-2 SSB correction methods

A New Tool Preliminary Assessment on Temporal-Comorbidity Adjusted Risk of Emergency Readmission (T-CARER)

Patients’ comorbidities, operations and complications can be associated with reduced long-term survival probability and increased healthcare utilisation. The aim of this research was to produce an adjusted case-mix model of comorbidity risk and develop a user-friendly toolkit to encourage public adaptation and incremental development.It has been shown in healthcare research that demographics, temporal dimensions, length-of-stay and time between admissions, can noticeably improve the statistical measures related to comorbidities. The proposed model incorporates temporal aspects, medical procedures, demographics, and admission details, as well as diagnoses.The research resulted in the development of Temporal-Comorbidity Adjusted Risk of Emergency Readmission (T-CARER) model using routinely collected hospital data

Deep endometriosis infiltrating the recto-sigmoid: critical factors to consider before management

Mauricio Simoes Abrao1,, Felice Petraglia2, Tommaso Falcone3, Joerg Keckstein4, Yutaka Osuga5, and Charles Chapron6,7,8 Endometriosis Division, Obstetrics and Gynecological Department – Sao Paulo University, Sao Paulo, Brazil Obstetrics and Gynecology, Department of Molecular and Developmental Medicine, University of Siena, Siena, Italy Obstetrics, Gynecology andWomen's Health Institute, Cleveland Clinic, Cleveland, OH, USA Department of Obstetrics and Gynecology, Center for Endometriosis, Villach Hospital, Villach, Austria Department of Obstetrics and Gynecology, Faculty of Medicine, University of Tokyo, Hongo, Bunkyo, Tokyo, Japan Universite Paris Descartes, Sorbonne Paris Cite, Faculte de Medecine, Assistance Publique – Hopitaux de Paris (APHP), Groupe Hospitalier Universitaire (GHU) Ouest, Centre Hospitalier Universitaire (CHU) Cochin, Department of Gynecology Obstetrics II and Reproductive Medicine, 75679 Paris, France Institut Cochin, Universite Paris Descartes, Sorbonne Paris Cite CNRS (UMR 8104), Paris, France Inserm, Universite Paris Descartes, Sorbonne Paris Cite, Unite de recherche U1016, Paris, Franc

ROWS wave spectral data collected in SAXON-FPN, November 1990

High-resolution directional wave spectra obtained with the NASA Ku-band radar ocean wave spectrometer (ROWS) on the Naval Research Laboratory P-3 aircraft during SAXON-FPN (SAR and X-Band Ocean Nonlinearities Experiment-Forschungsplattform Nordsee) experiments in the North Sea in November 1990 are presented. This experiment was the first in which the ROWS was operated with its new pc-based high-speed digital data acquisition system

International Wildlife Law : Understanding and Enhancing Its Role in Conservation

We gratefully acknowledge valuable input by Kees Bastmeijer, Sanja Bogojevic, Jennifer Dubrulle, and Han Somsen.Peer reviewedPublisher PD

Exploitation of error correlation in a large analysis validation: GlobCurrent case study

An assessment of variance in ocean current signal and noise shared by in situ observations (drifters) and a large gridded analysis (GlobCurrent) is sought as a function of day of the year for 1993–2015 and across a broad spectrum of current speed. Regardless of the division of collocations, it is difficult to claim that any synoptic assessment can be based on independent observations. Instead, a measurement model that departs from ordinary linear regression by accommodating error correlation is proposed. The interpretation of independence is explored by applying Fuller's (1987) concept of equation and measurement error to a division of error into shared (correlated) and unshared (uncorrelated) components, respectively. The resulting division of variance in the new model favours noise. Ocean current shared (equation) error is of comparable magnitude to unshared (measurement) error and the latter is, for GlobCurrent and drifters respectively, comparable to ordinary and reverse linear regression. Although signal variance appears to be small, its utility as a measure of agreement between two variates is highlighted. Sparse collocations that sample a dense (high resolution) grid permit a first order autoregressive form of measurement model to be considered, including parameterizations of analysis-in situ error cross-correlation and analysis temporal error autocorrelation. The former (cross-correlation) is an equation error term that accommodates error shared by both GlobCurrent and drifters. The latter (autocorrelation) facilitates an identification and retrieval of all model parameters. Solutions are sought using a prescribed calibration between GlobCurrent and drifters (by variance matching). Because the true current variance of GlobCurrent and drifters is small, signal to noise ratio is near zero at best. This is particularly evident for moderate current speed and for the meridional current component