A reprocessing for climate of sea surface temperature from the Along-Track Scanning Radiometers: initial validation, accounting for skin and diurnal variability

An initial validation of the Along Track Scanning Radiometer (ATSR) Reprocessing for Climate (ARC) retrievals of sea surface temperature (SST) is presented. ATSR-2 and Advanced ATSR (AATSR) SST estimates are compared to drifting buoy and moored buoy observations over the period 1995 to 2008. The primary ATSR estimates are of skin SST, whereas buoys measure SST below the surface. Adjustment is therefore made for the skin effect, for diurnal stratification and for differences in buoy–satellite observation time. With such adjustments, satellite-in situ differences are consistent between day and night within ~ 0.01 K. Satellite-in situ differences are correlated with differences in observation time, because of the diurnal warming and cooling of the ocean. The data are used to verify the average behaviour of physical and empirical models of the warming/cooling rates. Systematic differences between adjusted AATSR and in-situ SSTs against latitude, total column water vapour (TCWV), and wind speed are less than 0.1 K, for all except the most extreme cases (TCWV < 5 kg m–2, TCWV > 60 kg m–2). For all types of retrieval except the nadir-only two-channel (N2), regional biases are less than 0.1 K for 80% of the ocean. Global comparison against drifting buoys shows night time dual-view two-channel (D2) SSTs are warm by 0.06 ± 0.23 K and dual-view three-channel (D3) SSTs are warm by 0.06 ± 0.21 K (day-time D2: 0.07 ± 0.23 K). Nadir-only results are N2: 0.03 ± 0.33 K and N3: 0.03 ± 0.19 K showing the improved inter-algorithm consistency to ~ 0.02 K. This represents a marked improvement from the existing operational retrieval algorithms for which inter-algorithm inconsistency is > 0.5 K. Comparison against tropical moored buoys, which are more accurate than drifting buoys, gives lower error estimates (N3: 0.02 ± 0.13 K, D2: 0.03 ± 0.18 K). Comparable results are obtained for ATSR-2, except that the ATSR-2 SSTs are around 0.1 K warm compared to AATSR

A reprocessing for climate of sea surface temperature from the Along-Track Scanning Radiometers: a new retrieval scheme

We present a new coefficient-based retrieval scheme for estimation of sea surface temperature (SST) from the Along Track Scanning Radiometer (ATSR) instruments. The new coefficients are banded by total column water vapour (TCWV), obtained from numerical weather prediction analyses. TCWV banding reduces simulated regional retrieval biases to < 0.1 K compared to biases ~ 0.2 K for global coefficients. Further, detailed treatment of the instrumental viewing geometry reduces simulated view-angle related biases from ~ 0.1 K down to < 0.005 K for dual-view retrievals using channels at 11 and 12 μm. A novel analysis of trade-offs related to the assumed noise level when defining coefficients is undertaken, and we conclude that adding a small nominal level of noise (0.01 K) is optimal for our purposes. When applied to ATSR observations, some inter-algorithm biases appear as TCWV-related differences in SSTs estimated from different channel combinations. The final step in coefficient determination is to adjust the offset coefficient in each TCWV band to match results from a reference algorithm. This reference uses the dual-view observations of 3.7 and 11 μm. The adjustment is independent of in situ measurements, preserving independence of the retrievals. The choice of reference is partly motivated by uncertainty in the calibration of the 12 μm of Advanced ATSR. Lastly, we model the sensitivities of the new retrievals to changes to TCWV and changes in true SST, confirming that dual-view SSTs are most appropriate for climatological applications

A reprocessing for climate of sea surface temperature from the Along-Track Scanning Radiometers: basis in radiative transfer

We present new radiative transfer simulations to support determination of sea surface temperature (SST) from Along Track Scanning Radiometer (ATSR) imagery. The simulations are to be used within the ATSR Reprocessing for Climate project. The simulations are based on the “Reference Forward Model” line-by-line model linked with a sea surface emissivity model that accounts for wind speed and temperature, and with a discrete ordinates scattering model (DISORT). Input to the forward model is a revised atmospheric profile dataset, based on full resolution ERA-40, with a wider range of high-latitude profiles to address known retrieval biases in those regions. Analysis of the radiative impacts of atmospheric trace gases shows that geographical and temporal variation of N2O, CH4, HNO3, and CFC-11 and CFC-12 have effects of order 0.05, 0.2, 0.1 K on the 3.7, 11, 12 μm channels respectively. In addition several trace gases, neglected in previous studies, are included using fixed profiles contributing ~ 0.04 K to top-of-atmosphere BTs. Comparison against observations for ATSR2 and AATSR indicates that forward model biases have been reduced from 0.2 to 0.5 K for previous simulations to ~ 0.1 K.

Multiwavelength Observations of EXO 0748-676. I. Reprocessing of X-Ray Bursts

We present high time-resolution multiwavelength observations of X-ray bursts in the low-mass X-ray binary UY Vol. Strong reprocessed signals are present in the ultraviolet and optical, lagged and smeared with respect to the X-rays. The addition of far-ultraviolet coverage for one burst allows much tighter constraints on the temperature and geometry of the reprocessing region than previously possible. A blackbody reprocessing model for this burst suggests a rise in temperatures during the burst from 18,000 to 35,000 K and an emitting area comparable to that expected for the disk and/or irradiated companion star. The lags are consistent with those expected. The single-zone blackbody model cannot reproduce the ratio of optical to ultraviolet flux during the burst, however. The discrepancy seems too large to explain with deviations from a local blackbody spectrum and more likely indicates that a range of reprocessing temperatures are required. Comparable results are derived from other bursts, and in particular the lag and smearing both appear shorter when the companion star is on the near side of the disk as predicted. The burst observed by HST also yielded a spectrum of the reprocessed light. It is dominated by continuum, with a spectral shape consistent with the temperatures derived from lightcurve modeling. Taken as a whole, our observations confirm the standard paradigm of prompt reprocessing distributed across the disk and companion star, with the response dominated by a thermalized continuum rather than by emission lines.

On the reprocessing and reanalysis of observations for climate

The long observational record is critical to our understanding of the Earth’s climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. The purpose of this paper is to both review recent progress in reprocessing and reanalyzing observations, and summarize the challenges that must be overcome in order to improve our understanding of climate and variability. Reprocessing improves data quality through more scrutiny and improved retrieval techniques for individual observing systems, while reanalysis merges many disparate observations with models through data assimilation, yet both aim to provide a climatology of Earth processes. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Oceanic reanalyses have made significant advances in recent years, but will only be discussed here in terms of progress toward integrated Earth system analyses. Climate data sets are generally adequate for process studies and large-scale climate variability. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. It must be emphasized that careful investigation of the data and processing methods are required to use the observations appropriately.

Some new strategies for the chemical separation of actinides and lanthanides

A future goal in nuclear fuel reprocessing is the conversion or transmutation of the long-lived radioisotopes of minor actinides, such as americium, into short-lived isotopes by irradiation with neutrons. In order to achieve this transmutation, it is necessary to separate the minor actinides(III), [An(Ill)], from the lanthanides(III), [Ln(Ill)], by solvent extraction (partitioning), because the lanthanides absorb neutrons too effectively and hence limit neutron capture by the transmutable actinides. Partitioning using ligands containing only carbon, hydrogen, nitrogen and oxygen atoms is desirable because they are completely incinerable and thus the final volume of waste is minimised [1]. Nitric acid media will be used in the extraction experiments because it is envisaged that the An(III)/Ln(III) separation process could take place after the PUREX process. There is no doubt that the correct design of a molecule that is capable of acting as a ligand or extraction reagent is required for the effective separation of metal ions such as actinides(III) from lanthanides. Recent attention has been directed towards heterocyclic ligands with for the preferential separation of the minor actinides. Although such molecules have a rich chemistry, this is only now becoming sufficiently well understood in relation to the partitioning process [2]. The molecules shown in Figures I and 2 will be the principal focus of this study. Although the examples chosen here are used rather specific, the guidelines can be extended to other areas such as the separation of precious metals [3].

Use of soft heterocyclic N‑donor ligands to separate actinides and lanthanides

The removal of the most long-lived radiotoxic elements from used nuclear fuel, minor actinides, is foreseen as an essential step toward increasing the public acceptance of nuclear energy as a key component of a low-carbon energy future. Once removed from the remaining used fuel, these elements can be used as fuel in their own right in fast reactors or converted into shorter-lived or stable elements by transmutation prior to geological disposal. The SANEX process is proposed to carry out this selective separation by solvent extraction. Recent efforts to develop reagents capable of separating the radioactive minor actinides from lanthanides as part of a future strategy for the management and reprocessing of used nuclear fuel are reviewed. The current strategies for the reprocessing of PUREX raffinate are summarized, and some guiding principles for the design of actinide-selective reagents are defined. The development and testing of different classes of solvent extraction reagent are then summarized, covering some of the earliest ligand designs right through to the current reagents of choice, bis(1,2,4-triazine) ligands. Finally, we summarize research aimed at developing a fundamental understanding of the underlying reasons for the excellent extraction capabilities and high actinide/lanthanide selectivities shown by this class of ligands and our recent efforts to immobilize these reagents onto solid phases.

A twenty-year independent record of sea surface temperature for climate from Along-track Scanning Radiometers

A new record of sea surface temperature (SST) for climate applications is described. This record provides independent corroboration of global variations estimated from SST measurements made in situ. Infrared imagery from Along-Track Scanning Radiometers (ATSRs) is used to create a 20 year time series of SST at 0.1° latitude-longitude resolution, in the ATSR Reprocessing for Climate (ARC) project. A very high degree of independence of in situ measurements is achieved via physics-based techniques. Skin SST and SST estimated for 20 cm depth are provided, with grid cell uncertainty estimates. Comparison with in situ data sets establishes that ARC SSTs generally have bias of order 0.1 K or smaller. The precision of the ARC SSTs is 0.14 K during 2003 to 2009, from three-way error analysis. Over the period 1994 to 2010, ARC SSTs are stable, with better than 95% confidence, to within 0.005 K yr−1(demonstrated for tropical regions). The data set appears useful for cleanly quantifying interannual variability in SST and major SST anomalies. The ARC SST global anomaly time series is compared to the in situ-based Hadley Centre SST data set version 3 (HadSST3). Within known uncertainties in bias adjustments applied to in situ measurements, the independent ARC record and HadSST3 present the same variations in global marine temperature since 1996. Since the in situ observing system evolved significantly in its mix of measurement platforms and techniques over this period, ARC SSTs provide an important corroboration that HadSST3 accurately represents recent variability and change in this essential climate variable.

Sea surface temperature climate change initiative: alternative image classification algorithms for sea-ice affected oceans

We present a Bayesian image classification scheme for discriminating cloud, clear and sea-ice observations at high latitudes to improve identification of areas of clear-sky over ice-free ocean for SST retrieval. We validate the image classification against a manually classified dataset using Advanced Along Track Scanning Radiometer (AATSR) data. A three way classification scheme using a near-infrared textural feature improves classifier accuracy by 9.9 % over the nadir only version of the cloud clearing used in the ATSR Reprocessing for Climate (ARC) project in high latitude regions. The three way classification gives similar numbers of cloud and ice scenes misclassified as clear but significantly more clear-sky cases are correctly identified (89.9 % compared with 65 % for ARC). We also demonstrate the poetential of a Bayesian image classifier including information from the 0.6 micron channel to be used in sea-ice extent and ice surface temperature retrieval with 77.7 % of ice scenes correctly identified and an overall classifier accuracy of 96 %.