Review of the CALIMAS Team Contributions to European Space Agency's Soil Moisture and Ocean Salinity Mission Calibration and Validation

Camps, Adriano ... et al.-- 38 pages, 22 figuresThis work summarizes the activities carried out by the SMOS (Soil Moisture and Ocean Salinity) Barcelona Expert Center (SMOS-BEC) team in conjunction with the CIALE/Universidad de Salamanca team, within the framework of the European Space Agency (ESA) CALIMAS project in preparation for the SMOS mission and during its first year of operation. Under these activities several studies were performed, ranging from Level 1 (calibration and image reconstruction) to Level 4 (land pixel disaggregation techniques, by means of data fusion with higher resolution data from optical/infrared sensors). Validation of SMOS salinity products by means of surface drifters developed ad-hoc, and soil moisture products over the REMEDHUS site (Zamora, Spain) are also presented. Results of other preparatory activities carried out to improve the performance of eventual SMOS follow-on missions are presented, including GNSS-R to infer the sea state correction needed for improved ocean salinity retrievals and land surface parameters. Results from CALIMAS show a satisfactory performance of the MIRAS instrument, the accuracy and efficiency of the algorithms implemented in the ground data processors, and explore the limits of spatial resolution of soil moisture products using data fusion, as well as the feasibility of GNSS-R techniques for sea state determination and soil moisture monitoringThis work has been performed under research grants TEC2005-06863-C02-01/TCM, ESP2005-06823-C05, ESP2007-65667-C04, AYA2008-05906-C02-01/ESP and AYA2010-22062-C05 from the Spanish Ministry of Science and Innovation, and a EURYI 2004 award from the European Science FoundationPeer Reviewe

The contribution of the Barcelona World Race to improved ocean surface information. A validation of the SMOS remotely sensed salinity

12 pages, 14 figures[EN] The oceans not only cover about three quarters of the Earth’s surface but they also constitute the most relevant climate driver. However, our present knowledge about the oceans is by no means comparable to that of terrestrial or atmospheric systems. Salinity and temperature are key parameters to understand the dynamics of the oceans; but a global network of observations is lacking in spite of valuable data on the oceans that are being accumulated through oceanographic campaigns and by using automated devices, fixed moorings, drifting instrumented buoys, and ships of opportunity. In addition, during the last 40 years, remotely sensed data from satellites have offered almost synoptic information describing the Earth’s surface. This information includes sea surface temperature, which has been routinely monitored; by contrast, ocean surface salinity was not remotely measured until very recently. The Soil Moisture and Ocean Salinity (SMOS) satellite, launched in November 2009, has been the first attempt to obtain remotely sensed surface salinity data. In this context, the Barcelona World Race has provided new opportunities not only to obtain a worldwide sequence of sea surface temperature and salinity data, through one of the participating ships, but also to validate the first salinity data obtained by the SMOS[CAT] Els oceans no solament cobreixen aproximadament tres quartes parts de la superfície de la Terra, sinó que constitueixen el controlador més rellevant del clima. Així i tot, el coneixement que es té actualment dels oceans no es pot comparar amb el que es té dels sistemes terrestres o atmosfèrics. La salinitat i la temperatura són factors clau per entendre la dinàmica dels oceans, però encara no existeix una xarxa global d’observacions. Així i tot, s’estan obtenint dades molt valuoses dels oceans mitjançant campanyes oceanogràfiques i l’ús de dispositius automatitzats, ancoratges o boies a la deriva instrumentades i vaixells d’oportunitat. A més, durant els darrers quaranta anys, les dades obtingudes per teledetecció per satèl·lits han ofert informació gairebé sinòptica sobre la superfície de la Terra, que inclou la temperatura de la superfície del mar, monitoritzada de manera rutinària. En canvi, la salinitat superficial de l’oceà no s'ha pogut obtenir remotament fins fa molt poc. El satèl·lit SMOS (per les sigles en anglès de «humitat del sòl i salinitat oceànica»), llançat el novembre del 2009, n’ha estat el primer intent satisfactori. En aquest context, la Barcelona World Race ha ofert noves oportunitats per obtenir una seqüència de temperatura i salinitat superficials a escala global, a través d’un dels vaixells participants, així com per validar les primeres dades sobre salinitat obtingudes amb l’SMOSThis work was performed with the support of the MIDAS-6 project of the Spanish R+D+I National Plan (AYA2010-22062-C05) and is a contribution of the SMOS Barcelona Expert Centre (SMOS-BEC, CSIC/UPC)Peer reviewe

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

High resolution 3-D temperature and salinity fields derived from in situ and satellite observations

This paper describes an observation-based approach that efficiently combines the main components of the global ocean observing system using statistical methods. Accurate but sparse in situ temperature and salinity profiles (mainly from Argo for the last 10 yr) are merged with the lower accuracy but high-resolution synthetic data derived from satellite altimeter and sea surface temperature observations to provide global 3-D temperature and salinity fields at high temporal and spatial resolution. The first step of the method consists in deriving synthetic temperature fields from altimeter and sea surface temperature observations, and salinity fields from altimeter observations, through multiple/simple linear regression methods. The second step of the method consists in combining the synthetic fields with in situ temperature and salinity profiles using an optimal interpolation method. Results show the revolutionary nature of the Argo observing system. Argo observations now allow a global description of the statistical relationships that exist between surface and subsurface fields needed for step 1 of the method, and can constrain the large-scale temperature and mainly salinity fields during step 2 of the method. Compared to the use of climatological estimates, results indicate that up to 50% of the variance of the temperature fields can be reconstructed from altimeter and sea surface temperature observations and a statistical method. For salinity, only about 20 to 30% of the signal can be reconstructed from altimeter observations, making the in situ observing system essential for salinity estimates. The in situ observations (step 2 of the method) further reduce the differences between the gridded products and the observations by up to 20% for the temperature field in the mixed layer, and the main contribution is for salinity and the near surface layer with an improvement up to 30%. Compared to estimates derived using in situ observations only, the merged fields provide a better reconstruction of the high resolution temperature and salinity fields. This also holds for the large-scale and low-frequency fields thanks to a better reduction of the aliasing due to the mesoscale variability. Contribution of the merged fields is then illustrated to describe qualitatively the temperature variability patterns for the period from 1993 to 2009

Influence of nonseasonal river discharge on sea surface salinity and height

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chandanpurkar, H. A., Lee, T., Wang, X., Zhang, H., Fournier, S., Fenty, I., Fukumori, I., Menemenlis, D., Piecuch, C. G., Reager, J. T., Wang, O., & Worden, J. Influence of nonseasonal river discharge on sea surface salinity and height. Journal of Advances in Modeling Earth Systems, 14(2), (2022): e2021MS002715, https://doi.org/10.1029/2021MS002715.River discharge influences ocean dynamics and biogeochemistry. Due to the lack of a systematic, up-to-date global measurement network for river discharge, global ocean models typically use seasonal discharge climatology as forcing. This compromises the simulated nonseasonal variation (the deviation from seasonal climatology) of the ocean near river plumes and undermines their usefulness for interdisciplinary research. Recently, a reanalysis-based daily varying global discharge data set was developed, providing the first opportunity to quantify nonseasonal discharge effects on global ocean models. Here we use this data set to force a global ocean model for the 1992–2017 period. We contrast this experiment with another experiment (with identical atmospheric forcings) forced by seasonal climatology from the same discharge data set to isolate nonseasonal discharge effects, focusing on sea surface salinity (SSS) and sea surface height (SSH). Near major river mouths, nonseasonal discharge causes standard deviations in SSS (SSH) of 1.3–3 practical salinity unit (1–2.7 cm). The inclusion of nonseasonal discharge results in notable improvement of model SSS against satellite SSS near most of the tropical-to-midlatitude river mouths and minor improvement of model SSH against satellite or in-situ SSH near some of the river mouths. SSH changes associated with nonseasonal discharge can be explained by salinity effects on halosteric height and estimated accurately through the associated SSS changes. A recent theory predicting river discharge impact on SSH is found to perform reasonably well overall but underestimates the impact on SSH around the global ocean and has limited skill when applied to rivers near the equator and in the Arctic Ocean.This research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004) with support from the Physical Oceanography (PO) and Modeling, Analysis, and Prediction (MAP) Programs. High-end computing resources for the numerical simulation were provided by the NASA Advanced Supercomputing Division at the Ames Research Center

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM), chlorophyll-a, and pollutants). A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water’s surface. In this review paper, various properties (spectral, spatial and temporal, etc.) of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD)