Observing and Studying Extreme Low Pressure Events with Altimetry

The ability of altimetry to detect extreme low pressure events and the relationship between sea level pressure and sea level anomalies during extra-tropical depressions have been investigated. Specific altimeter treatments have been developed for tropical cyclones and applied to obtain a relevant along-track sea surface height (SSH) signal: the case of tropical cyclone Isabel is presented here. The S- and C-band measurements are used because they are less impacted by rain than the Ku-band, and new sea state bias (SSB) and wet troposphere corrections are proposed. More accurate strong altimeter wind speeds are computed thanks to the Young algorithm. Ocean signals not related to atmospheric pressure can be removed with accuracy, even within a Near Real Time context, by removing the maps of sea level anomaly (SLA) provided by SSALTO/Duacs. In the case of Extra-Tropical Depressions, the classical altimeter processing can be used. Ocean signal not related to atmospheric pressure is along-track filtered. The sea level pressure (SLP)-SLA relationship is investigated for the North Atlantic, North Pacific and Indian oceans; three regression models are proposed allowing restoring an altimeter SLP with a mean error of 5 hPa if compared to ECMWF or buoys SLP. The analysis of barotropic simulation outputs points out the regional variability of the SLP/Model Sea Level relationship and the wind effects

Simultaneous ocean surface current and wind vectors retrieval with squinted SAR interferometry: Geophysical inversion and performance assessment

Simultaneous measurements of ocean surface current and wind vectors at the ocean submesoscale (O [1–10 km]) are needed to improve our understanding of upper ocean mixing, air-sea interactions, ocean biophysical processes and large-scale oceanic transports. A new satellite mission concept called SEASTAR aims to do just that. The concept is a Ku-band along-track interferometric Synthetic Aperture Radar (SAR) system with two squinted beams pointing ±45° from broadside and incidence angles around 30°. The paper presents an inversion strategy to retrieve simultaneously ocean surface current and wind vectors and reports on the performance obtained with different wind/current conditions and instrument configurations. Results are based on numerical simulations using a Bayesian approach and existing geophysical model functions (GMFs) of the microwave Normalized Radar Cross Section (NRCS) and Doppler shift. Using the baseline two-look instrument configuration and realistic instrument noise figures (radiometric resolution: kp = 5 and 12%; Δdf = 2 and 5 Hz), the root-mean square errors (RMSE) of the retrieved current and wind vectors are typically better than [0.1 m/s, 10°] for current and [0.5 m/s, 5°] for wind. This inversion setup yields four ambiguous solutions within a current range of ∼1 m/s. The addition of dual polarization (VV, HH) capability helps to discriminate these ambiguities. The retrieval performance depends weakly on geophysical parameters such as wind speed, current velocity or current direction, but is sensitive to wind direction because of its strong effect on current retrieval through the wind-wave induced artifact surface velocity (WASV). Larger retrieval errors are obtained when the wind is aligned with one of the antenna line-of-sight (LoS) directions, although errors remain typically below [0.2 m/s, 25°] for current and [0.5 m/s, 15°] for wind. Improving the retrieval performance regardless of wind direction could be achieved either with lower noise figures on σ0, or with higher incidence angles, or by including an additional third-look direction in azimuth (e.g. to achieve a configuration similar to Metop/ASCAT scatterometers) as per the SEASTAR mission concept submitted to EE10

Recent trends in the wind-driven California current upwelling system

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordLong-term changes in the marine ecosystems of the Eastern Boundary Upwelling Systems (EBUS) are predicted due to anthropogenic climate change. In particular, global ocean acidification is having a profound effect on the coastal waters of the EBUS, affecting the entire trophic chain, net primary production (NPP) and related economic activities such as fisheries. Another predicted change related to human activity is that of upwelling dynamics with expected long-term changes in upwelling winds as proposed by Bakun (1990), Bakun et al. (2015) and Rykaczewski et al. (2015). Although these predicted long-term changes may emerge only later in the 21st century, this has fueled many studies using historical data. Long-term increase in upwelling winds has thus been a much debated topic, showing that there is considerable uncertainty depending on the EBUS considered, the effect of natural climate fluctuations, the choice of wind dataset, the time period considered, and the methodologies and significance tests applied. Therefore, there is an immediate interest in being able to monitor upwelling using verified and self-consistent wind data sets. This work focused on a sensitivity study of the estimated trends in upwelling winds in the California Current Upwelling System (CCUS), for the most recent period 1996–2018, using the two state-of-the-art satellite wind analyses and two atmospheric model re-analyses. Embedded into the strong modulation by natural climate fluctuations on interannual and decadal time scales, we do see an increase in upwelling-favorable winds in the core of the CCUS, with a local increase of more than 25% in seasonal upwelling transport for the period considered. In this central upwelling zone, a good agreement on stronger equatorward winds for the winter and spring seasons is found between the different datasets, although with different significance levels. Conversely, conflicting results are found in the southernmost part of the CCUS between the satellite analyses and the model reanalyses. Systematic, time-dependent differences are found between the wind products, highlighting the need to further investigate the poorly documented temporal stability of these widely used wind long-term climatology products. The observed spatial structuring of the estimated wind trends is consistent with the trend analysis of water chlorophyll-a, partial pressure of CO2, and basity (pH) analysis products. This result is consistent with changes being important for modulating the carbonate system within the CCUS.European Space Agenc

Salinity from Space Unlocks Satellite-Based Assessment of Ocean Acidification

Approximately a quarter of the carbon dioxide (CO2) that we emit into the atmosphere is absorbed by the ocean. This oceanic uptake of CO2 leads to a change in marine carbonate chemistry resulting in a decrease of seawater pH and carbonate ion concentration, a process commonly called “Ocean Acidification”. Salinity data are key for assessing the marine carbonate system, and new space-based salinity measurements will enable the development of novel space-based ocean acidification assess- ment. Recent studies have highlighted the need to develop new in situ technology for monitoring ocean acidification, but the potential capabilities of space-based measurements remain largely untapped. Routine measurements from space can provide quasi-synoptic, reproducible data for investigating processes on global scales; they may also be the most efficient way to monitor the ocean surface. As the carbon cycle is dominantly controlled by the balance between the biological and solubility carbon pumps, innovative methods to exploit existing satellite sea surface temperature and ocean color, and new satellite sea surface salinity measurements, are needed and will enable frequent assessment of ocean acidification parameters over large spatial scales

Realizing Envisat's potential for rain cloud studies

Owing to the highly variable nature of rain both in space and time and the difficulties in obtaining accurate in situ measurements, increasing reliance is being placed on the various types of satellite data now available. The multi-sensor payload of Envisat is of particular interest because the data are co-located and simultaneous, thus reducing some of the uncertainty found in multi-platform analyses. This paper shows variations in cloud and precipitation data derived from AATSR, RA-2 and MWR-2 measurements in an overpass of Hurricane Juan, revealing significant asymmetry in the spatial distribution. The results are discussed in the context of similar data from other tropical and sub-tropical features in the western Atlantic. The combination of data from these sensors allows us to see the effects of different drop-size distribution at varying distances from the eye and to conclude that active microwave systems are needed for studying small-scale variations in rainfall

Comparison of Geophysical Model Functions for SAR Wind Speed Retrieval in Japanese Coastal Waters

Abstract: This work discusses the accuracies of geophysical model functions (GMFs) for retrieval of sea surface wind speed from satellite-borne Synthetic Aperture Radar (SAR) images in Japanese coastal waters characterized by short fetches and variable atmospheric stability conditions. In situ observations from two validation sites, Hiratsuka and Shirahama, are used for comparison of the retrieved sea surface wind speeds using CMOD (C-band model)4, CMOD_IFR2, CMOD5 and CMOD5.N. Of all the geophysical model functions (GMFs), the latest C-band GMF, CMOD5.N, has the smallest bias and root mean square error at both sites. All of the GMFs exhibit a negative bias in the retrieved wind speed. In order to understand the reason for this bias, all SAR-retrieved wind speeds are separated into two categories: onshore wind (blowing from sea to land) and offshore wind (blowing from land to sea). Only offshore winds were found to exhibit the large negative bias, and short fetches from the coastline may be a possible reason for this. Moreover, it is clarified that in both the unstable and stable conditions, CMOD5.N has atmospheric stability effectiveness, and can keep the same accuracy with CMOD5 in the neutral condition. In short, at the moment, CMOD5.N is thought to be the most promising GM

The Sea State CCI dataset v1: towards a sea state climate data record based on satellite observations

Sea state data are of major importance for climate studies, marine engineering, safety at sea and coastal management. However, long-term sea state datasets are sparse and not always consistent, and sea state data users still mostly rely on numerical wave models for research and engineering applications. Facing the urgent need for a sea state climate data record, the Global Climate Observing System has listed “Sea State” as an Essential Climate Variable (ECV), fostering the launch in 2018 of the Sea State Climate Change Initiative (CCI). The CCI is a programme of the European Space Agency, whose objective is to realise the full potential of global Earth observation archives established by ESA and its member states in order to contribute to the ECV database. This paper presents the implementation of the first release of the Sea State CCI dataset, the implementation and benefits of a high-level denoising method, its validation against in situ measurements and numerical model outputs, and the future developments considered within the Sea State CCI project. The Sea State CCI dataset v1 is freely available on the ESA CCI website (http://cci.esa.int/data, last access: 25 August 2020) at ftp://anon-ftp.ceda.ac.uk/neodc/esacci/sea_state/data/v1.1_release/ (last access: 25 August 2020). Three products are available: a multi-mission along-track L2P product (http://dx.doi.org/ 10.5285/f91cd3ee7b6243d5b7d41b9beaf397e1, Piollé et al., 2020a), a daily merged multi mission along-track L3 product (http://dx.doi.org/10.5285/3ef6a5a66e9947d39b356251909dc12b, Piollé et al., 2020b) and a multimission monthly gridded L4 product (http://dx.doi.org/10.5285/47140d618dcc40309e1edbca7e773478, Piollé et al., 2020c)

Satellites will address critical science priorities for quantifying ocean carbon

The ability to routinely quantify global carbon dioxide (CO2) absorption by the oceans has become crucial: it provides a powerful constraint for establishing global and regional carbon (C) budgets, and enables identification of the ecological impacts and risks of this uptake on the marine environment. Advances in understanding, technology, and international coordination have made it possible to measure CO2 absorption by the oceans to a greater degree of accuracy than is possible in terrestrial landscapes. These advances, combined with new satellite‐based Earth observation capabilities, increasing public availability of data, and cloud computing, provide important opportunities for addressing critical knowledge gaps. Furthermore, Earth observation in synergy with in‐situ monitoring can provide the large‐scale ocean monitoring that is necessary to support policies to protect ocean ecosystems at risk, and motivate societal shifts toward meeting C emissions targets; however, sustained effort will be needed

Buoy observations from the windiest location in the world ocean, Cape Farewell, Greenland

Author Posting. © American Geophysical Union, 2008. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 35 (2008): L18802, doi:10.1029/2008GL034845.Cape Farewell, Greenland's southernmost point, is a region of significant interest in the meteorological and oceanographic communities in that atmospheric flow distortion associated with the high topography of the region leads to a number of high wind speed jets. The resulting large air-sea fluxes of momentum and buoyancy have a dramatic impact on the region's weather and ocean circulation. Here the first in-situ observations of the surface meteorology in the region, collected from an instrumented buoy, are presented. The buoy wind speeds are compared to 10 m wind speeds from the QuikSCAT satellite and the North American Regional Reanalysis (NARR). We show that the QuikSCAT retrievals have a high wind speed bias that is absent from the NARR winds. The spatial characteristics of the high wind speed events are also presented.The support of the Canadian Foundation for Climate and Atmospheric Science, the support of the National Science Foundation grant OCE-0450658as well as the Natural Environmental Research Council grant NE/C003365/1