Sampling uncertainty in gridded sea surface temperature products and Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) data

Sea surface temperature (SST) data are often provided as gridded products, typically at resolutions of order 0.05 degrees from satellite observations to reduce data volume at the request of data users and facilitate comparison against other products or models. Sampling uncertainty is introduced in gridded products where the full surface area of the ocean within a grid cell cannot be fully observed because of cloud cover. In this paper we parameterise uncertainties in SST as a function of the percentage of clear-sky pixels available and the SST variability in that subsample. This parameterisation is developed from Advanced Along Track Scanning Radiometer (AATSR) data, but is applicable to all gridded L3U SST products at resolutions of 0.05-0.1 degrees, irrespective of instrument and retrieval algorithm, provided that instrument noise propagated into the SST is accounted for. We also calculate the sampling uncertainty of ~0.04 K in Global Area Coverage (GAC) Advanced Very High Resolution Radiometer (AVHRR) products, using related methods

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

An investigation of the oceanic skin temperature deviation

Satellite and in-situ radiometric measurements of sea surface temperature (SST) together with conventional SST and meteorological parameters are used to provide a description of the ocean surface skin temperature deviation (skin temperature - bulk temperature, AT) for a transect made across the Atlantic ocean from 50°N 00°W to 23°S 35°W during September and October 1992. Methods of in-situ SST measurement are discussed and the errors associated with each technique are given. The principles of infra red radiometry are explained. The differences between the calibration strategies used to determine SST using infra-red radiometers from both in-situ and satellite platforms are reviewed and the errors associated with each technique are given. Differences between published in-situ infra red SST data indicate that there may be a bias in these data as a consequence of the calibration strategy adopted. The need for an inter calibration of in-situ infra red radiometer systems used for the validation of satellite SST is highlighted. Satellite SST algorithms are discussed and the principles of atmospheric correction are explained. The difference between the radiometric 'skin' temperature of the ocean and the conventional 'bulk' temperature at depth is defined. A review of current observations of AT is given. Several theoretical treatments of AT are reviewed. The definitions of the surface fluxes of heat and momentum are given. A description of the collection of data and an analysis of the calibration of the infra-red radiometer used to measure the skin temperature is presented.Data have been processed to obtain AT and the surface fluxes of heat and momentum have been evaluated according to the bulk aerodynamic formulae. The relationships between AT and the measurements made are presented for the entire data set and for day and night time observations separately. Four time series of observed data are presented and the local conditions during the time of measurement are used to discuss AT. AT has a mean value of 0.39°C ±0.3°C and is shown to be a persistent feature of the Atlantic ocean. Correlation analyses reveal the skin and bulk temperature fields to be correlated at length scales > 155 km. Night time correlations are consistently higher than the day time at all length scales. For this reason it is recommended that satellite validation data are only collected during the night. High sea states are shown to affect both in-situ and satellite observations of SST biasing these data warm. The regional nature of AT is presented which is related to the dominant atmosphere-ocean conditions for each region. AT is shown to be greatest at the higher latitudes and weak in the tropical regions.Several parameterisations of AT are used to obtain estimates of AT using the data collected. These are found to be inadequate to predict AT at small temporal scales. A regional dependence of AT is found in these parameterisations. The coefficient A, of the Saunders (1969) parameterisation has been evaluated and is shown to have a regional dependence on the local atmosphere ocean conditions. The coefficient Ci and Ci of the Hasse (1971) parameterisation have been evaluated using the data collected. These are Ci=4.74 and C2=1.22.A comparison between the Along Track Scanning Radiometer Average SST is presented. Satellite - in-situ bulk AT has been obtained and shown to be comparable to that observed in-situ. This comparison highlights the need to make skin SST validation measurements rather than bulk SST measurements. The ATSR ASST data are shown to return a SST accurate to better than 0.3°C

Global measurement of sea surface temperature from space: some new perspectives

The measurement of global sea surface temperature (SST) from space is well established with 20 years of useful data already acquired, but the more stringent sampling requirements and the higher degree of accuracy now demanded for applications in both climate monitoring and operational oceanography are increasingly difficult to meet with the standard meteorological polar orbiting sensors that have been the basic sensors used for global SST mapping. The established methods and sensors for measuring SST, both in situ and in space, are reviewed, compared, and their major limitations are identified. Mention is made of phenomena which complicate an apparently simple measurement, including diurnal stratification, the presence of clouds and the contamination of the stratosphere by volcanic aerosols. Recent developments in remote sensing of SST are mentioned, noting the improved microwave sensors now becoming available, the calibrated infrared sensors planned for geostationary platforms, and weighing the benefits of merging these data. The conventional buoy-calibration of SST measurements from space is complicated by the variable thermal structure of the upper few metres of the ocean. The recent improvement of radiometers for ship deployment has led to better understanding of the thermal skin of the ocean which suggests a new approach for the validation of SST algorithms based on radiation transfer models. Finally, a future strategy is outlined for combining measurements from many types of sensor in order to achieve the required accuracy and sampling rate of SST data products, and to identify some of the remaining scientific challenges in this field

Towards an estimation of water masses formation areas from SMOS-based TS diagrams

European Geosciences Union General Assembly 2014 (EGU2014), 27 april - 2 may 2014, Vienna, Austria.-- 2 pagesTemperature-Salinity (TS) diagrams emphasize the mutual variability of ocean temperature and salinity values, relating them to the corresponding density. Canonically used in oceanography, they provide a means to characterize and trace ocean water masses. In [1], a first attempt to estimate surface-layer TS diagrams based on satellite measurements has been performed, profiting from the recent availability of spaceborne salinity data. In fact, the Soil Moisture and Ocean Salinity (SMOS, [2]) and the Aquarius/SAC-D [3] satellite missions allow to study the dynamical patterns of Sea Surface Salinity (SSS) for the first time on a global scale. In [4], given SMOS and Aquarius salinity estimates, and by also using Sea Surface Temperature (SST) from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA, [5]) effort, experimental satellite-based TS diagrams have been routinely derived for the year 2011. They have been compared with those computed from ARGO-buoys interpolated fields, referring to a customised partition of the global ocean into seven regions, according to the water masses classification of [6]. In [7], moreover, besides using TS diagrams as a diagnostic tool to evaluate the temporal variation of SST and SSS (and their corresponding density) as estimated by satellite measurements, the emphasis was on the interpretation of the geographical deviations with respect to the ARGO baseline (aiming at distinguishing between the SSS retrieval errors and the additional information contained in the satellite data with respect to ARGO). In order to relate these mismatches to identifiable oceanographic structures and processes, additional satellite datasets of ocean currents, evaporation/precipitation fluxes, and wind speed have been super-imposed. Currently, the main focus of the study deals with the exploitation of these TS diagrams as a prognostic tool to derive water masses formation areas. Firstly, following the approach described in [8], the surface density flux (i.e. the change in density induced by surface heat and freshwater fluxes) is computed, characterizing how the buoyancy of a water parcel is being transformed, by increasing or decreasing its density. Afterwards, integrating over a certain time/space and deriving with respect to density, the formation (in Sv) of water masses themselves can be computed, pinpointing the range of SST and SSS in the TS diagrams where a specific water mass is formed. A geographical representation of these points, ultimately, allows to provide a relevant temporal series of the spatial extent of the water masses formation areas (in the specific test zones chosen). This can be then extended over challenging ocean regions, also evaluating the sensitivity of the performances to the datasets used. With this approach, known water masses can be identified and their formation traced in time and space. Longer time series will give further insights by helping to identify inter-annual water mass formation variability and trends in the TS/geographical domains. Future work aims at exploring additional datasets and at connecting the surface information to the vertical structure and to buoyancy-driven ocean circulation processesPeer Reviewe

Long-term validation of AATSR SST data products using shipborne radiometry in the Bay of Biscay and English Channel

Radiometric measurements of the sea surface temperature (SST) made by the infrared SST autonomous radiometer (ISAR) deployed routinely between 2004 and 2009 from a passenger vessel traversing the English Channel and Bay of Biscay are used to validate satellite SST data products produced using the Advanced along-track scanning radiometer (AATSR) flown on Envisat. More than 1500 independent pairings between an ISAR record and an AATSR pixel, coincident within specified space–time matching windows, are analysed. These confirm good agreement between the in situ and the satellite derived SST estimates, based on the dual view AATSR algorithms, with a bias of less than 0.1 K which is the accuracy limit of the ISAR. The standard deviation of the comparisons depends on the coincidence criteria: for a match-up window of 1 km and 2 h it is around 0.3 K for the three channel (night only) algorithm and 0.4 K for the 2 channel algorithm. Separate validation statistics are produced for the periods before and after 7 Dec 2005 when a change was made to the AATSR algorithms. It is shown that the error distribution was narrowed by introducing the new algorithm and further narrowed by using only the AATSR data that have the highest Confidence Value. This is the first systematic use of autonomous underway shipboard radiometry on a vessel of opportunity for validating satellite data. The methodology is carefully assessed and shown to provide an effective and reliable means of confirming the high quality and stability of the SST data products from AATSR

One-dimensional modelling of convective CO2 exchange in the Tropical Atlantic

Diurnal changes in seawater temperature affect the amount of air–sea gas exchange taking place through changes in solubility and buoyancy-driven nocturnal convection, which enhances the gas transfer velocity. We use a combination of in situ and satellite derived radiometric measurements and a modified version of the General Ocean Turbulence Model (GOTM), which includes the National Oceanic and Atmospheric Administration Coupled-Ocean Atmospheric Response Experiment (NOAA-COARE) air–sea gas transfer parameterization, to investigate heat and carbon dioxide exchange over the diurnal cycle in the Tropical Atlantic. A new term based on a water-side convective velocity scale (w*w) is included, to improve parameterization of convectively driven gas transfer. Meteorological data from the PIRATA mooring located at 10°S10°W in the Tropical Atlantic are used, in conjunction with cloud cover estimates from Meteosat-7, to calculate fluxes of longwave, latent and sensible heat along with a heat budget and temperature profiles during February 2002. Twin model experiments, representing idealistic and realistic conditions, reveal that over daily time scales the additional contribution to gas exchange from convective overturning is important. Increases in transfer velocity of up to 20% are observed during times of strong insolation and low wind speeds (&lt;6 m s?1); the greatest enhancement from w*w to the CO2 flux occurs when diurnal warming is large. Hence, air–sea fluxes of CO2 calculated using simple parameterizations underestimate the contribution from convective processes. The results support the need for parameterizations of gas transfer that are based on more than wind speed alone and include information about the heat budget. <br/

Satellite-based T-S diagrams derived from SMOS, Aquarius and OSTIA data

33th European Association of Remote Sensing Laboratories (EARSeL) Symposium, Towards Horizon 2020: Earth Observation and Social Perspectives, 3-6 June 2013, Matera, ItalyTemperature Salinity (T-S) diagrams emphasize the relationship between observed values of temperature and salinity in the ocean and connect them to density. Specific T-S curves characterize water masses and can be used to identify them in regions other than their formation area. The SMOS and Aquarius/SAC-D satellite missions provide a means to study the temporal variation of the surface T-S signature for the first time on a global scale. The present study derives experimental satellite based T-S diagrams. The main objectives are to characterize the (co-) variability of Sea Surface Temperature (SST) and Sea Surface Salinity (SSS) and to understand the unique information that SMOS and Aquarius are providing with respect to existing climatology or in-situ data as well as the processes governing the distribution and variability of SSS. The T-S diagrams are produced from SMOS and Aquarius Optimal Interpolated SSS and OSTIA SST. They are compared with T-S diagrams derived from an ARGO Optimal Interpolated product and the World Ocean Atlas 2009 climatology, respectively. The temporal variability is studied for each ocean basin. Comparison with the ARGO based T-S diagrams might provide evidence of SSS biases and errors currently experienced by the satellites. A method is under investigation to separate the retrieval errors from the additional information that the satellite data may contain with respect to the ARGO data. Linking the information from the horizontal T-S diagrams with vertical profiles can hopefully provide insight into water mass formation and help to identify potential formation areasPeer Reviewe

Satellite Based TS Diagrams: A Prospective Tool To Trace Ocean Water Masses

European Space Agency (ESA) Living Planet Symposium, 9-13 September 2013, Edinburgh, United Kingdom.-- 6 pages, 5 figuresTemperature-Salinity (T-S) diagrams are derived from SMOS and Aquarius Sea Surface Salinity (SSS) and OSTIA Sea Surface Temperature (SST) in order to characterize the (co-)variability of SST and SSS in four regions of the North Atlantic. Comparison with in-situ data from Argo floats is used to assess the new information that the satellite data provide with respect to Argo and gain further insights into the processes that govern the near-surface stratification. The surface T-S signatures as seen by the satellites and Argo show similar patterns, with SMOS detecting fresher SSS values, as expected, and OSTIA showing a tendency to be warmer than Argo. Part of this fresher misfit can be attributed to precipitation, whilst the effect of other parameters are being assessed. On-going efforts are devoted to link these signatures with the water masses formationPeer reviewe