The contemporary air‐sea flux of CO₂ is investigated by the use of an air‐sea flux equation, with particular attention to the uncertainties in global values and their origin with respect to that equation. In particular, uncertainties deriving from the transfer velocity and from sparse upper ocean sampling are investigated. Eight formulations of air‐sea gas transfer velocity are used to evaluate the combined standard uncertainty resulting from several sources of error. Depending on expert opinion, a standard uncertainty in transfer velocity of either ~5% or ~10% can be argued and that will contribute a proportional error in air‐sea flux. The limited sampling of upper ocean fCO₂ is readily apparent in the Surface Ocean CO₂ Atlas databases. The effect of sparse sampling on the calculated fluxes was investigated by a bootstrap method, that is, treating each ship cruise to an oceanic region as a random episode and creating 10 synthetic data sets by randomly selecting episodes with replacement. Convincing values of global net air‐sea flux can only be achieved using upper ocean data collected over several decades but referenced to a standard year. The global annual referenced values are robust to sparse sampling, but seasonal and regional values exhibit more sampling uncertainty. Additional uncertainties are related to thermal and haline effects and to aspects of air‐sea gas exchange not captured by standard models. An estimate of global net CO₂ exchange referenced to 2010 of −3.0 ± 0.6 Pg C/year is proposed, where the uncertainty derives primarily from uncertainty in the transfer velocity.

High resolution imaging spectrometers are prerequisite to address significant data gaps in inland optical water quality monitoring. In this work, we provide a data-driven alignment of chlorophyll-a and turbidity derived from the Sentinel-2 MultiSpectral Imager (MSI) with corresponding Sentinel-3 Ocean and Land Colour Instrument (OLCI) products. For chlorophyll-a retrieval, empirical ‘ocean colour’ blue-green band ratios and a near infra-red (NIR) band ratio algorithm, as well as a semi-analytical three-band NIR-red ratio algorithm, were included in the analysis. Six million co-registrations with MSI and OLCI spanning 24 lakes across five continents were analysed. Following atmospheric correction with POLYMER, the reflectance distributions of the red and NIR bands showed close similarity between the two sensors, whereas the distribution for blue and green bands was positively skewed in the MSI results compared to OLCI. Whilst it is not possible from this analysis to determine the accuracy of reflectance retrieved with either MSI or OLCI results, optimizing water quality algorithms for MSI against those previously derived for the Envisat Medium Resolution Imaging Spectrometer (MERIS) and its follow-on OLCI, supports the wider use of MSI for aquatic applications. Chlorophyll-a algorithms were thus tuned for MSI against concurrent OLCI observations, resulting in significant improvements against the original algorithm coefficients. The mean absolute difference (MAD) for the blue-green band ratio algorithm decreased from 1.95 mg m⁻³ to 1.11 mg m⁻³, whilst the correlation coefficient increased from 0.61 to 0.80. For the NIR-red band ratio algorithms improvements were modest, with the MAD decreasing from 4.68 to 4.64 mg m⁻³ for the empirical red band ratio algorithm, and 3.73 to 3.67 for the semi-analytical 3-band algorithm. Three implementations of the turbidity algorithm showed improvement after tuning with the resulting distributions having reduced bias. The MAD reduced from 0.85 to 0.72, 1.22 to 1.10 and 1.93 to 1.55 FNU for the 665, 708 and 778 nm implementations respectively. However, several sources of uncertainty remain: adjacent land showed high divergence between the sensors, suggesting that high product uncertainty near land continues to be an issue for small water bodies, while it cannot be stated at this point whether MSI or OLCI results are differentially affected. The effect of spectrally wider bands of the MSI on algorithm sensitivity to chlorophyll-a and turbidity cannot be fully established without further availability of in situ optical measurements.

The North Atlantic is a substantial sink for anthropogenic CO₂. Understanding the mechanisms driving the sink's variability is key to assessing its current state and predicting its potential response to global climate change. Here we apply a time series decomposition technique to satellite and in situ data to examine separately the factors (both biological and nonbiological) that affect the sea‐air CO₂ difference (ΔpCO₂) on seasonal and interannual time scales. We demonstrate that on seasonal time scales, the subpolar North Atlantic ΔpCO₂ signal is predominantly correlated with biological processes, whereas seawater temperature dominates in the subtropics. However, the same factors do not necessarily control ΔpCO₂ on interannual time scales. Our results imply that the mechanisms driving seasonal variability in ΔpCO₂ cannot necessarily be extrapolated to predict how ΔpCO₂, and thus the North Atlantic CO₂ sink, may respond to increases in anthropogenic CO₂ over longer time scales.

16033 Background: Tyrosine kinase inhibitors (TKIs) improve progression free survival in both first line (sunitinib) and second line (sorafenib) treatment of metastatic renal cell carcinoma (mRCC). We performed a Retrospective Population based study to assess the impact of TKIs on overall survival (OS) in patients (pts) treated for mRCC in Alberta, Canada. Methods: 130 pts were identified who commenced either sorafenib, or sunitinib between December 2003 and June 2007 for mRCC at one of two referral cancer centres in Alberta. Survival was compared to that of an earlier cohort of 141 pts treated with Interferon α (IFN) at the same centres between May 1995 and March 2003. Data was collected enabling stratification into risk categories according to the MSKCC prognostic model. The primary endpoint was OS measured from date of commencement of TKI in the recent cohort, and IFN in the earlier cohort. The Kaplan Meier method was used to determine OS, with Cox Regression analysis used to determine hazard ratios (HR) and confidence intervals (CI). Results: Of the 130 pts treated with a TKI, 78 received treatment in the first line setting, whereas 52 received treatment after prior IFN therapy. All 141 pts from the IFN cohort received treatment in the 1st line setting. Patients treated on TKIs had an improved OS compared with the earlier IFN cohort with a HR of 0.621 (95% CI .45–.857, p=0.004). Median OS was 16.5 months and 10.2 months, respectively. There was no significant impact on OS based on whether the TKI was received after prior IFN therapy or in first line (HR .774, 95% CI .451–1.327, p=.351). Survival according to MSKCC risk groups is outlined in Table 1. Factors associated with improved survival on multivariate analysis were treatment with a TKI, time between diagnosis and treatment greater than 12 months, LDH ≤ 1.5 ULN, normal Hb, normal corr. Ca++ and Karnofsky PS ≥80%. Conclusions: TKIs improve OS compared with IFN in mRCC with significant benefits in favourable and intermediate risk groups.