The Ohio State University Stackfiles for Satellite Radar Altimeter Data

The original version of stackfiles was designed by Gerhard L.H. Kruizinga, Center for Space Research, University of Texas at Austin, 1994. Most part of the text in this document was borrowed from the CSR technical memo "The New Stackfiles" originally written by G.L.H. Kruizinga in the summer of 1994 and updated on August 21, 1998.This document describes the OSU stackfile database for satellite radar altimetry and software that is used to access and maintain the database system. The stackfile database system can be viewed as a reformatted version of Geophysical Data Record (GDR) data products of satellite radar altimeters. A stackfile database is accessible using 2- dimensional location indices of nominal ground tracks while the GDR products are registered in time along actual ground tracks. The third dimension of a stackfile is the repeat cycle of a satellite altimeter mission. The purpose of this document is to use it as a user’s guide of the OSU stackfile databases installed on a unix/linux server

Multi-satellite altimetry and GOCE geoid based surface and subsurface currents in the Mediterranean Sea

Peer ReviewedPostprint (published version

Feasibility of GNSS-R Altimetry Using CyGNSS 8-Satellite Constellation Mission Data

Ponencia expuesta en Scientific Assembly of the International Association of Geodesy (2021) celebrado en Beijing del 28 de junio al 2 de juli

CYGNSS Ocean Altimetry: A Status Report

Comunicación expuesta online en el CYGNSS Science Team Summer Meeting celebrado del 27 al 29 de julio de 202

Health Consequences Among COVID-19 Convalescent Patients 30 Months Post-Infection in China

The health consequences among COVID-19 convalescent patients 30 months post-infection were described and the potential risk factors were determined. In August 2022 we recruited 217 COVID-19 convalescent patients who had been diagnosed with COVID-19 in February 2020. These convalescent patients were residents of multiple districts in Wuhan, China. All convalescent patients completed a detailed questionnaire, laboratory testing, a 6-min walk test, a Borg dyspnea scale assessment, lung function testing, and had a chest CT. The potential risk factors for health consequences among COVID-19 convalescent patients 30 months post-infection were identified using a multivariate logistic regression model. The majority of convalescent patients were in good overall health and returned to work 30 months post-infection; however, 62.2% of the convalescent patients had long COVID symptoms. The most common symptoms were chest pain, fatigue, and dizziness or headaches. The convalescent patients with severe symptoms had a significantly higher proportion of depression disorder ( P = 0.044) and lower health-related quality of life ( P = 0.034) compared to the convalescent patients with mild symptoms. Compared to convalescent patients who were not vaccinated, convalescent patients who received three vaccines had significantly less fatigue, lower anxiety and depression scores, and had a better health-related quality of life (all P < 0.05). Older age was associated with a higher risk of long COVID (OR = 1.52, 95% CI = 1.16–2.02) and chest CT abnormalities (OR = 1.75, 95% CI = 1.33–2.36). Female gender was associated with a higher risk of anxiety (OR = 3.20, 95% CI = 1.24–9.16) and depression disorders (OR = 2.49, 95% CI = 1.11–5.92). Exercise was associated with a lower risk of anxiety (OR = 0.41, 95% CI = 0.18–0.93). Notably, vaccination protected convalescent patients from developing long COVID symptoms (OR = 0.18, 95% CI = 0.06–0.50), anxiety disorders (OR = 0.22, 95% CI = 0.07–0.71), and depression disorders (OR = 0.33, 95% CI = 0.12–0.92). The majority of COVID-19 convalescent patients were in good overall health 30 months post-infection and returned to work. More attention should be paid to convalescent patients who are older, female, physically inactive, and not vaccinated

Application of TOPEX Altimetry for Solid Earth Deformation Studies

This study demonstrates the use of satellite radar altimetry to detect solid Earth deformation signals such as Glacial Isostatic Adjustment (GIA). Our study region covers moderately flat land surfaces seasonally covered by snow/ice/vegetation. The maximum solid Earth uplift of ~10 mm yr-1 is primarily due to the incomplete glacial isostatic rebound that occurs around Hudson Bay, North America. We use decadal (1992 - 2002) surface height measurements from TOPEX/POSEIDON radar altimetry to generate height changes time series for 12 selected locations in the study region. Due to the seasonally varying surface characteristics, we first perform radar waveform shape classification and have found that most of the waveforms are quasi-diffuse during winter/spring and specular during summer/fall. As a result, we used the NASA £]-retracker for the quasi-diffuse waveforms and the Offset Center of Gravity or the threshold retracker for the specular waveforms, to generate the surface height time series. The TOPEX height change time series exhibit coherent seasonal signals (higher amplitude during the winter and lower amplitude during the summer), and the estimated deformation rates agree qualitatively well with GPS vertical velocities, and with altimeter/tide gauge combined vertical velocities around the Great Lakes. The TOPEX observations also agree well with various GIA model predictions, especially with the ICE-5G (VM2) model with differences at 0.2 ¡_ 1.4 mm yr-1, indicating that TOPEX has indeed observed solid Earth deformation signals manifested as crustal uplift over the former Laurentide Ice Sheet region

Evidences of Seasonal Variation in Altimetry Derived Ocean Tides in the Subarctic Ocean

While the barotropic ocean tides in the deep ocean are well modeled to ~2 cm RMS, accurate tidal prediction in the ice-covered polar oceans and near coastal regions remain elusive. A notable reason is that the most accurate satellite altimeters (TOPEX/Jason-1/-2), whose orbits are optimized to minimize the tidal aliasing effect, have spatial coverage limited to largely outside of the polar ocean. Here, we update the assessment of tidal models using 7 contemporary global and regional models, and show that the altimetry sea surface height (SSH) anomaly residual after tidal correction is 9 - 12 cm RMS in the Subarctic Ocean. We then address the hypothesis whether plausible evidence of variable tidal signals exist in the seasonally ice-covered Subarctic Ocean, where the sea ice cover is undergoing rapid thinning. We first found a difference in variance reduction for multi-mission altimeter SSH anomaly residuals during the summer and winter seasons, with the residual during winter season 15 - 30% larger than that during the summer season. Experimental seasonal ocean tide solutions derived from satellite altimetry reveals that the recovered winter and summer tidal constituents generally differ by a few cm in amplitude and tens of degrees in phase. Relatively larger seasonal tidal patterns, in particular for M2, S2 and K1 tides, have been identified in the Chukchi Sea study region near eastern Siberia, coincident with the seasonal presence and movement of sea ice

Vertical Motion Determined Using Satellite Altimetry and Tide Gauges

A robust method to estimate vertical crustal motions by combining geocentric sea level measurements from decadal (1992 - 2003) TOPEX/POSEIDON satellite altimetry and long-term (> 40 years) relative sea level records from tide gauges using a novel Gauss-Markov stochastic adjustment model is presented. These results represent an improvement over a prior study (Kuo et al. 2004) in Fennoscandia, where the observed vertical motions are primarily attributed to the incomplete Glacial Isostatic Adjustment (GIA) in the region since the Last Glacial Maximum (LGM). The stochastic adjustment algorithm and results include a fully-populated a priori covariance matrix. The algorithm was extended to estimate vertical motion at tide gauge locations near open seas and around semi-enclosed seas and lakes. Estimation of nonlinear vertical motions, which could result from co- and postseismic deformations, has also been incorporated. The estimated uncertainties for the vertical motion solutions in coastal regions of the Baltic Sea and around the Great Lakes are in general < 0.5 mm yr-1, which is a significant improvement over existing studies. In the Baltic Sea, the comparisons of the vertical motion solution with 10 collocated GPS radial rates and with the BIFROST GIA model show differences of 0.2 ¡_ 0.9 and 1.6 ¡_ 1.8 mm yr-1, respectively. For the Great Lakes region, the comparisons with the ICE-3G model and with the relative vertical motion estimated using tide gauges only (Mainville and Craymer 2005) show differences of -0.2 ¡_ 0.6 and -0.1 ¡_ 0.5 mm yr-1, respectively. The Alaskan vertical motion solutions (linear and nonlinear models) have an estimated uncertainty of ~1.2 - 1.6 mm yr-1, which agree qualitatively with GPS velocity and tide gauge-only solutions (Larsen et al. 2003). This innovative technique could potentially provide improved estimates of the vertical motion globally where long-term tide gauge records exist