An ocean-colour time series for use in climate studies: the experience of the ocean-colour climate change initiate (OC-CCI)

Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea viewingWide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel

CO2 wettability of seal and reservoir rocks and the implications for carbon geo-sequestration

We review the literature data published on the topic of CO2 wettability of storage and seal rocks. We first introduce the concept of wettability and explain why it is important in the context of carbon geo-sequestration (CGS) projects, and review how it is measured. This is done to raise awareness of this parameter in the CGS community, which, as we show later on in this text, may have a dramatic impact on structural and residual trapping of CO2. These two trapping mechanisms would be severely and negatively affected in case of CO2-wet storage and/or seal rock. Overall, at the current state of the art, a substantial amount of work has been completed, and we find that: 1. Sandstone and limestone, plus pure minerals such as quartz, calcite, feldspar, and mica are strongly water wet in a CO2-water system. 2. Oil-wet limestone, oil-wet quartz, or coal is intermediate wet or CO2 wet in a CO2-water system. 3. The contact angle alone is insufficient for predicting capillary pressures in reservoir or seal rocks. 4. The current contact angle data have a large uncertainty. 5. Solid theoretical understanding on a molecular level of rock-CO2-brine interactions is currently limited. 6. In an ideal scenario, all seal and storage rocks in CGS formations are tested for their CO2 wettability. 7. Achieving representative subsurface conditions (especially in terms of the rock surface) in the laboratory is of key importance but also very challenging

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Calibrated digital images of Campbell–Stokes recorder card archives for direct solar irradiance studies

A systematic, semi-automatic method for imaging the cards from the widely used Campbell–Stokes sunshine recorder is described. We show how the application of inexpensive commercial equipment and practices can simply and robustly build an archive of high-quality card images and manipulate them into a form suitable for easy further analysis. Rectified and registered digital images are produced, with the card's midday marker in the middle of the longest side, and with a temporal scaling of 150 pixels per hour. The method improves on previous, mostly manual, analyses by simplifying and automating steps into a process capable of handling thousands of cards in a practical timescale. A prototype method of extraction of data from this archive is then tested by comparison with records from a co-located pyrheliometer at a resolution of the order of minutes. The comparison demonstrates that the Campbell–Stokes recorder archive contains a time series of downwelling solar-irradiance-related data with similar characteristics to that of benchmark pyrheliometer data from the Baseline Surface Radiation Network. A universal transfer function for card burn to direct downwelling short-wave radiation is still some way off and is the subject of ongoing research. Until such time as a universal transfer function is available, specific functions for extracting data in particular circumstances offer a useful way forward. The new image-capture method offers a practical way to exploit the worldwide sets of long-term Campbell–Stokes recorder data to create a time series of solar irradiance and atmospheric aerosol loading metrics reaching back over 100 yr from the present day

From Operational Ceilometer Network to Operational Lidar Network

During the eruption of Eyjafjallajökull in 2010, the Met Office ceilometers (Laser Cloud Based Recorders - LCBR) provided reasonable information about volcanic ash plumes over the United Kingdom [1]. This capability triggered the development of an operational system to provide quick looks of the range corrected signals (RCS) in near-real-time (NRT). Moreover, the Met Office acquired eleven Jenoptik ceilometers to supplement the operational ceilometer network. The combined network became operational in 2012 and currently comprises a total of 43 ceilometers reporting backscatter profiles in NRT. In 2013, Civil Aviation Authority (CAA) and the Department for transport (DfT) sponsored the acquisition of 9 fixed lidars and one mobile unit (each accompanied by a sunphotometer), to further improve the quantitative monitoring of volcanic ash. The current status of both ceilometer and lidar/sun-photometer networks is discussed and further developments are proposed

From Operational Ceilometer Network to Operational Lidar Network

During the eruption of Eyjafjallajökull in 2010, the Met Office ceilometers (Laser Cloud Based Recorders - LCBR) provided reasonable information about volcanic ash plumes over the United Kingdom [1]. This capability triggered the development of an operational system to provide quick looks of the range corrected signals (RCS) in near-real-time (NRT). Moreover, the Met Office acquired eleven Jenoptik ceilometers to supplement the operational ceilometer network. The combined network became operational in 2012 and currently comprises a total of 43 ceilometers reporting backscatter profiles in NRT. In 2013, Civil Aviation Authority (CAA) and the Department for transport (DfT) sponsored the acquisition of 9 fixed lidars and one mobile unit (each accompanied by a sunphotometer), to further improve the quantitative monitoring of volcanic ash. The current status of both ceilometer and lidar/sun-photometer networks is discussed and further developments are proposed

The uk Lidar-sunphotometer operational volcanic ash monitoring network

The Met Office completed the deployment of ten lidars (UV Raman and depolarization), each accompanied by a sunphotometer (polarized model), to provide quantitative monitoring of volcanic ash over UK for VAAC London. The lidars provide range corrected signal and volume depolarization ratio in near-real time. The sunphotometers deliver aerosol optical depth, Ångstrom exponent and degree of linear polarization. Case study analyses of Saharan dust events (as a proxy for volcanic ash) are presented

The uk Lidar-sunphotometer operational volcanic ash monitoring network

The Met Office completed the deployment of ten lidars (UV Raman and depolarization), each accompanied by a sunphotometer (polarized model), to provide quantitative monitoring of volcanic ash over UK for VAAC London. The lidars provide range corrected signal and volume depolarization ratio in near-real time. The sunphotometers deliver aerosol optical depth, Ångstrom exponent and degree of linear polarization. Case study analyses of Saharan dust events (as a proxy for volcanic ash) are presented

The Ocean Colour Climate Change Initiative: III. A Round-robin Comparison on In-water Bio-optical Algorithms

Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situ Rrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies