Modeling Envisat RA-2 waveforms in the coastal zone: case-study of calm water contamination

Radar altimeters have so far had limited use in the coastal zone, the area with most societal impact. This is due to both lack of, or insufficient accuracy in the necessary corrections, and more complicated altimeter signals. This paper examines waveform data from the Envisat RA-2 as it passes regularly over Pianosa (a 10 km2 island in the NW Mediterranean). Forty-six repeat passes were analysed, with most showing a reduction in signal upon passing over the island, with weak early returns corresponding to the reflections from land. Intriguingly one third of cases showed an anomalously bright hyperbolic feature. This feature may be due to extremely calm waters in the Golfo della Botte (northern side of the island), but the cause of its intermittency is not clear. The modelling of waveforms in such a complex land/sea environment demonstrates the potential for sea surface height retrievals much closer to the coast than is achieved by routine processing. The long-term development of altimetric records in the coastal zone will not only improve the calibration of altimetric data with coastal tide gauges, but also greatly enhance the study of storm surges and other coastal phenomena

Cross-calibrating ALES Envisat and CryoSat-2 Delay-Doppler: a coastal altimetry study in the Indonesian Seas

A regional cross-calibration between the first Delay-Doppler altimetry dataset from Cryosat-2 and a retracked Envisat dataset is here presented, in order to test the benefits of the Delay-Doppler processing and to expand the Envisat time series in the coastal ocean. The Indonesian Seas are chosen for the calibration, since the availability of altimetry data in this region is particularly beneficial due to the lack of in-situ measurements and its importance for global ocean circulation. The Envisat data in the region are retracked with the Adaptive Leading Edge Subwaveform (ALES) Retracker, which has been previously validated and applied successfully to coastal sea level research. The study demonstrates that CryoSat-2 is able to decrease the 1-Hz noise of sea level estimations by 0.3 cm within 50 km of the coast, when compared to the ALES-reprocessed Envisat dataset. It also shows that Envisat can be confidently used for detailed oceanographic research after the orbit change of October 2010. Cross-calibration at the crossover points indicates that in the region of study a sea state bias correction equal to 5% of the significant wave height is an acceptable approximation for Delay-Doppler altimetry. The analysis of the joint sea level time series reveals the geographic extent of the semiannual signal caused by Kelvin waves during the monsoon transitions, the larger amplitudes of the annual signal due to the Java Coastal Current and the impact of the strong La Niña event of 2010 on rising sea level trends

A new phase in the production of quality-controlled sea level data

Sea level is an essential climate variable (ECV) that has a direct effect on many people through inundations of coastal areas, and it is also a clear indicator of climate changes due to external forcing factors and internal climate variability. Regional patterns of sea level change inform us on ocean circulation variations in response to natural climate modes such as El Niño and the Pacific Decadal Oscillation, and anthropogenic forcing. Comparing numerical climate models to a consistent set of observations enables us to assess the performance of these models and help us to understand and predict these phenomena, and thereby alleviate some of the environmental conditions associated with them. All such studies rely on the existence of long-term consistent high-accuracy datasets of sea level. The Climate Change Initiative (CCI) of the European Space Agency was established in 2010 to provide improved time series of some ECVs, including sea level, with the purpose of providing such data openly to all to enable the widest possible utilisation of such data. Now in its second phase, the Sea Level CCI project (SL_cci) merges data from nine different altimeter missions in a clear, consistent and well-documented manner, selecting the most appropriate satellite orbits and geophysical corrections in order to further reduce the error budget. This paper summarises the corrections required, the provenance of corrections and the evaluation of options that have been adopted for the recently released v2.0 dataset (https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612). This information enables scientists and other users to clearly understand which corrections have been applied and their effects on the sea level dataset. The overall result of these changes is that the rate of rise of global mean sea level (GMSL) still equates to ∼ 3.2 mm yr−1 during 1992–2015, but there is now greater confidence in this result as the errors associated with several of the corrections have been reduced. Compared with v1.1 of the SL_cci dataset, the new rate of change is 0.2 mm yr−1 less during 1993 to 2001 and 0.2 mm yr−1 higher during 2002 to 2014. Application of new correction models brought a reduction of altimeter crossover variances for most corrections

Variation rs2235503 C > A Within the Promoter of MSLN Affects Transcriptional Rate of Mesothelin and Plasmatic Levels of the Soluble Mesothelin-Related Peptide

Soluble mesothelin-related peptide (SMRP) is a promising biomarker for malignant pleural mesothelioma (MPM), but several confounding factors can reduce SMRP-based test’s accuracy. The identification of these confounders could improve the diagnostic performance of SMRP. In this study, we evaluated the sequence of 1,000 base pairs encompassing the minimal promoter region of the MSLN gene to identify expression quantitative trait loci (eQTL) that can affect SMRP. We assessed the association between four MSLN promoter variants and SMRP levels in a cohort of 72 MPM and 677 non-MPM subjects, and we carried out in vitro assays to investigate their functional role. Our results show that rs2235503 is an eQTL for MSLN associated with increased levels of SMRP in non-MPM subjects. Furthermore, we show that this polymorphic site affects the accuracy of SMRP, highlighting the importance of evaluating the individual’s genetic background and giving novel insights to refine SMRP specificity as a diagnostic biomarker

A new phase in the production of quality-controlled sea level data

Sea level is an essential climate variable (ECV) that has a direct effect on many people through inundations of coastal areas, and it is also a clear indicator of climate changes due to external forcing factors and internal climate variability. Regional patterns of sea level change inform us on ocean circulation variations in response to natural climate modes such as El Niño and the Pacific Decadal Oscillation, and anthropogenic forcing. Comparing numerical climate models to a consistent set of observations enables us to assess the performance of these models and help us to understand and predict these phenomena, and thereby alleviate some of the environmental conditions associated with them. All such studies rely on the existence of long-term consistent high-accuracy datasets of sea level. The Climate Change Initiative (CCI) of the European Space Agency was established in 2010 to provide improved time series of some ECVs, including sea level, with the purpose of providing such data openly to all to enable the widest possible utilisation of such data. Now in its second phase, the Sea Level CCI project (SL_cci) merges data from nine different altimeter missions in a clear, consistent and well-documented manner, selecting the most appropriate satellite orbits and geophysical corrections in order to further reduce the error budget. This paper summarises the corrections required, the provenance of corrections and the evaluation of options that have been adopted for the recently released v2.0 dataset (https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612). This information enables scientists and other users to clearly understand which corrections have been applied and their effects on the sea level dataset. The overall result of these changes is that the rate of rise of global mean sea level (GMSL) still equates to ∼ 3.2 mm yr−1 during 1992–2015, but there is now greater confidence in this result as the errors associated with several of the corrections have been reduced. Compared with v1.1 of the SL_cci dataset, the new rate of change is 0.2 mm yr−1 less during 1993 to 2001 and 0.2 mm yr−1 higher during 2002 to 2014. Application of new correction models brought a reduction of altimeter crossover variances for most corrections

Decomposers and root feeders interactively affect plant defence in Sinapis alba

Aboveground herbivory is well known to change plant growth and defence. In contrast, effects of soil organisms, acting alone or in concert, on allocation patterns are less well understood. We investigated separate and combined effects of the endogeic earthworm species Aporrectodea caliginosa and the root feeding nematode species Pratylenchus penetrans and Meloidogyne incognita on plant responses including growth and defence metabolite concentrations in leaves of white mustard, Sinapis alba. Soil biota had a strong impact on plant traits, with the intensity varying due to species combinations. Nematode infestation reduced shoot biomass and nitrogen concentration but only in the absence of earthworms. Earthworms likely counteracted the negative effects of nematodes. Infestation with the migratory lesion-nematode P. penetrans combined with earthworms led to increased root length. Earthworm biomass increased in the presence of this species, indicating that these nematodes increased the food resources of earthworms—presumably dead and decaying roots. Nitrogen-based defence compounds, i.e. glucosinolates, did not correlate with nitrogen levels. In the presence of earthworms, concentrations of aromatic glucosinolates in leaves were significantly increased. In contrast, infection with P. penetrans strongly decreased concentrations of glucosinolates (up to 81%). Infestation with the sedentary nematode M. incognita induced aromatic glucosinolates by more than 50% but only when earthworms were also present. Myrosinase activities, glucosinolate-hydrolysing enzymes, were unaffected by nematodes but reduced in the presence of earthworms. Our results document that root-feeding nematodes elicit systemic plant responses in defence metabolites, with the responses varying drastically with nematode species of different functional groups. Furthermore, systemic plant responses are also altered by decomposer animals, such as earthworms, challenging the assumption that induction of plant responses including defence traits is restricted to herbivores. Soil animals even interact and modulate the individual effects on plant growth and plant defence, thereby likely also influencing shoot herbivore attack