Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data

The ice surface temperature (IST) is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions prevail during spring in the Arctic, while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveals that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C) and that the different in situ measurements complicate the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic, the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere

In situ observed relationships between snow and ice surface skin temperatures and 2 m air temperatures in the Arctic

To facilitate the construction of a satellite-derived 2&thinsp;m air temperature (T2 m) product for the snow- and ice-covered regions in the Arctic, observations from weather stations are used to quantify the relationship between the T2 m and skin temperature (Tskin). Multiyear data records of simultaneous Tskin and T2 m from 29 different in situ sites have been analysed for five regions, covering the lower and upper ablation zone and the accumulation zone of the Greenland Ice Sheet (GrIS), sea ice in the Arctic Ocean, and seasonal snow-covered land in northern Alaska. The diurnal and seasonal temperature variabilities and the impacts from clouds and wind on the T2 m–Tskin differences are quantified. Tskin is often (85&thinsp;% of the time, all sites weighted equally) lower than T2 m, with the largest differences occurring when the temperatures are well below 0&thinsp;∘C or when the surface is melting. Considering all regions, T2 m is on average 0.65–2.65&thinsp;∘C higher than Tskin, with the largest differences for the lower ablation area and smallest differences for the seasonal snow-covered sites. A negative net surface radiation balance generally cools the surface with respect to the atmosphere, resulting in a surface-driven surface air temperature inversion. However, Tskin and T2 m are often highly correlated, and the two temperatures can be almost identical (&lt;0.5&thinsp;∘C difference), with the smallest T2–Tskin differences around noon and early afternoon during spring, autumn and summer during non-melting conditions. In general, the inversion strength increases with decreasing wind speeds, but for the sites on the GrIS the maximum inversion occurs at wind speeds of about 5&thinsp;m&thinsp;s−1 due to the katabatic winds. Clouds tend to reduce the vertical temperature gradient, by warming the surface, resulting in a mean overcast T2 m–Tskin difference ranging from −0.08 to 1.63&thinsp;∘C, with the largest differences for the sites in the low-ablation zone and the smallest differences for the seasonal snow-covered sites. To assess the effect of using cloud-limited infrared satellite observations, the influence of clouds on temporally averaged Tskin has been studied by comparing averaged clear-sky Tskin with averaged all-sky Tskin. To this end, we test three different temporal averaging windows: 24&thinsp;h, 72&thinsp;h and 1 month. The largest clear-sky biases are generally found when 1-month averages are used and the smallest clear-sky biases are found for 24&thinsp;h. In most cases, all-sky averages are warmer than clear-sky averages, with the smallest bias during summer when the Tskin range is smallest.</p

Groundwater table fluctuations recorded in zonation of microbial siderites from end-Triassic strata

In a terrestrial Triassic–Jurassic boundary succession of southern Sweden, perfectly zoned sphaerosiderites are restricted to a specific sandy interval deposited during the end-Triassic event. Underlying and overlying this sand interval there are several other types of siderite micromorphologies, i.e. poorly zoned sphaerosiderite, spheroidal (ellipsoid) siderite, spherical siderite and rhombohedral siderite. Siderite overgrowths occur mainly as rhombohedral crystals on perfectly zoned sphaerosiderite and as radiating fibrous crystals on spheroidal siderite. Concretionary sparry, microspar and/or micritic siderite cement postdate all of these micromorphologies. The carbon isotope composition of the siderite measured by conventional mass spectrometry shows the characteristic broad span of data, probably as a result of multiple stages of microbial activity. SIMS (secondary ion mass spectrometry) revealed generally higher δ13C values for the concretionary cement than the perfectly zoned sphaerosiderite, spheroidal siderite and their overgrowths, which marks a change in the carbon source during burial. All the various siderite morphologies have almost identical oxygen isotope values reflecting the palaeo-groundwater composition. A pedogenic/freshwater origin is supported by the trace element compositions of varying Fe:Mn ratios and low Mg contents. Fluctuating groundwater is the most likely explanation for uniform repeated siderite zones of varying Fe:Mn ratios reflecting alternating physiochemical conditions and hostility to microbial life/activity. Bacterially mediated siderite precipitation likely incorporated Mn and other metal ions during conditions that are not favourable for the bacteria and continued with Fe-rich siderite precipitation as the physico-chemical conditions changed into optimal conditions again, reflecting the response to groundwater fluctuations

Autothermal reforming of palm empty fruit bunch bio-oil: thermodynamic modelling

This work focuses on thermodynamic analysis of the autothermal reforming of palm empty fruit bunch (PEFB) bio-oil for the production of hydrogen and syngas. PEFB bio-oil composition was simulated using bio-oil surrogates generated from a mixture of acetic acid, phenol, levoglucosan, palmitic acid and furfural. A sensitivity analysis revealed that the hydrogen and syngas yields were not sensitive to actual bio-oil composition, but were determined by a good match of molar elemental composition between real bio-oil and surrogate mixture. The maximum hydrogen yield obtained under constant reaction enthalpy and pressure was about 12 wt% at S/C = 1 and increased to about 18 wt% at S/C = 4; both yields occurring at equivalence ratio Φ of 0.31. The possibility of generating syngas with varying H2 and CO content using autothermal reforming was analysed and application of this process to fuel cells and Fischer-Tropsch synthesis is discussed. Using a novel simple modelling methodology, reaction mechanisms were proposed which were able to account for equilibrium product distribution. It was evident that different combinations of reactions could be used to obtain the same equilibrium product concentrations. One proposed reaction mechanism, referred to as the ‘partial oxidation based mechanism’ involved the partial oxidation reaction of the bio-oil to produce hydrogen, with the extent of steam reforming and water gas shift reactions varying depending on the amount of oxygen used. Another proposed mechanism, referred to as the ‘complete oxidation based mechanism’ was represented by thermal decomposition of about 30% of bio-oil and hydrogen production obtained by decomposition, steam reforming, water gas shift and carbon gasification reactions. The importance of these mechanisms in assisting in the eventual choice of catalyst to be used in a real ATR of PEFB bio-oil process was discussed