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The proposed "Guanlan" ocean science satellite, led by China's Laoshan Laboratory, includes an interferometric radar altimeter (IRA) as a key payload. As an integral part of its development, an airborne IRA experiment was conducted on 6 November 2021, with a flight path of approximately 90 km in the South China Sea. This study investigates the IRA's ability to observe ocean sea surface height (SSH) across scales ranging from meters to mesoscale. The sea surface height anomaly (SSHA) of the IRA is aligned with the SSHA of the AVISO at scales greater than 30 km, but also demonstrates the ability to capture small-scale SSHA changes in two dimensions. We analyzed wavenumber spectra of SSHA obtained from the airborne IRA, ICESat-2, and SARAL/AltiKa satellite for this region. The results show a good agreement in power spectral density (PSD) levels between ICESat-2, SARAL/AltiKa and IRA at scales larger than 30 km. Within the submesoscale range of 1–10 km, the IRA SSHA spectrum exhibits a distinctly negative slope and the lowest energy level. The minimum PSD level of the IRA fell in the range of 10−4–10−3 m2/cycle/km, at scales around 1 km, which is more than an order of magnitude lower than that of ICESat-2, forming a spectral gap that is in agreement with the theoretical expectation. Furthermore, IRA-derived wave direction and significant wave height matched well with the MFWAM wave data. The results of this study underscore the considerable potential of airborne IRA in capturing SSHA across a range of scales, from oceanic waves to submesoscale. [ABSTRACT FROM AUTHOR]

Background: The American Heart Association (AHA) has recently introduced the concept of Cardiovascular-Kidney-Metabolic (CKM) syndrome, which is the result of an increasing emphasis on the interplay of metabolic, renal and cardiovascular diseases (CVD). Furthermore, there is substantial evidence of a correlation between the triglyceride glucose-body mass index (TyG-BMI ) and CVD as an assessment of insulin resistance (IR). However, it remains unknown whether this correlation exists in population with CKM syndrome., Methods: All data for this study were obtained from the China Health and Retirement Longitudinal Study (CHARLS). The exposure was the participants' TyG-BMI at baseline, which was calculated using a combination of triglycerides (TG), fasting blood glucose (FBG) and body mass index (BMI). The primary outcome was CVD, which were determined by the use of a standardised questionnaire during follow-up. To examine the relationship between TyG-BMI and CVD incidence in population with CKM syndrome, both Cox regression analyses and restricted cubic spline (RCS) regression analyses were performed., Results: A total of 7376 participants were included in the final analysis. Of these, 1139, 1515, 1839, and 2883 were in CKM syndrome stages 0, 1, 2, and 3, respectively, at baseline. The gender distribution was 52.62% female, and the mean age was 59.17 ± 9.28 (years). The results of the fully adjusted COX regression analyses indicated that there was a 6.5% increase in the risk of developing CVD for each 10-unit increase in TyG-BMI,95% confidence interval (CI):1.041-1.090. The RCS regression analyses demonstrated a positive linear association between TyG-BMI and the incidence of CVD in the CKM syndrome population (P for overall < 0.001, P for nonlinear = 0.355)., Conclusions: This cohort study demonstrated a positive linear association between TyG-BMI index and increased CVD incidence in a population with CKM syndrome stage 0-3. This finding suggests that enhanced assessment of TyG-BMI index may provide a more convenient and effective tool for individuals at risk for CVD in CKM syndrome stage 0-3., (© 2024. The Author(s).)