A new method to detect long term trends of methane (CH₄) and nitrous oxide (N₂O) total columns measured within the NDACC ground-based high resolution solar FTIR network

Total columns measured with the ground-based solar FTIR technique are highly variable in time due to atmospheric chemistry and dynamics in the atmosphere above the measurement station. In this paper, a multiple regression model with anomalies of air pressure, total columns of hydrogen fluoride (HF) and carbon monoxide (CO) and tropopause height are used to reduce the variability in the methane (CH4) and nitrous oxide (N2O) total columns to estimate reliable linear trends with as small uncertainties as possible. The method is developed at the Harestua station (60°N, 11°E, 600ma.s.l.) and used on three other European FTIR stations, i.e. Jungfraujoch (47°N, 8°E, 3600ma.s.l.), Zugspitze (47°N, 11°E, 3000ma.s.l.), and Kiruna (68°N, 20°E, 400ma.s.l.). Linear CH4 trends between 0.13±0.01-0.25±0.02%yr−1 were estimated for all stations in the 1996-2009 period. A piecewise model with three separate linear trends, connected at change points, was used to estimate the short term fluctuations in the CH4 total columns. This model shows a growth in 1996–1999 followed by a period of steady state until 2007. From 2007 until 2009 the atmospheric CH4 amount increases between 0.57±0.22–1.15±0.17%yr−1. Linear N2O trends between 0.19±0.01–0.40±0.02%yr−1 were estimated for all stations in the 1996-2007 period, here with the strongest trend at Harestua and Kiruna and the lowest at the Alp stations. From the N2O total columns crude tropospheric and stratospheric partial columns were derived, indicating that the observed difference in the N2O trends between the FTIR sites is of stratospheric origin. This agrees well with the N2O measurements by the SMR instrument onboard the Odin satellite showing the highest trends at Harestua, 0.98±0.28%yr−1, and considerably smaller trends at lower latitudes, 0.27±0.25%yr−1. The multiple regression model was compared with two other trend methods, the ordinary linear regression and a Bootstrap algorithm. The multiple regression model estimated CH4 and N2O trends that differed up to 31% compared to the other two methods and had uncertainties that were up to 300% lower. Since the multiple regression method were carefully validated this stresses the importance to account for variability in the total columns when estimating trend from solar FTIR data

Validation and data characteristics of methane and nitrous oxide profiles observed by MIPAS and processed with Version 4.61 algorithm

The ENVISAT validation programme for the atmospheric instruments MIPAS, SCIAMACHY and GOMOS is based on a number of balloon-borne, aircraft, satellite and ground-based correlative measurements. In particular the activities of validation scientists were coordinated by ESA within the ENVISAT Stratospheric Aircraft and Balloon Campaign or ESABC. As part of a series of similar papers on other species [this issue] and in parallel to the contribution of the individual validation teams, the present paper provides a synthesis of comparisons performed between MIPAS CH4 and N2O profiles produced by the current ESA operational software (Instrument Processing Facility version 4.61 or IPF v4.61, full resolution MIPAS data covering the period 9 July 2002 to 26 March 2004) and correlative measurements obtained from balloon and aircraft experiments as well as from satellite sensors or from ground-based instruments. In the middle stratosphere, no significant bias is observed between MIPAS and correlative measurements, and MIPAS is providing a very consistent and global picture of the distribution of CH4 and N2O in this region. In average, the MIPAS CH4 values show a small positive bias in the lower stratosphere of about 5%. A similar situation is observed for N2O with a positive bias of 4%. In the lower stratosphere/upper troposphere (UT/LS) the individual used MIPAS data version 4.61 still exhibits some unphysical oscillations in individual CH4 and N2O profiles caused by the processing algorithm (with almost no regularization). Taking these problems into account, the MIPAS CH4 and N2O profiles are behaving as expected from the internal error estimation of IPF v4.61 and the estimated errors of the correlative measurements

Wolcott-Rallison syndrome

Wolcott-Rallison syndrome (WRS) is a rare autosomal recessive disease, characterized by neonatal/early-onset non-autoimmune insulin-requiring diabetes associated with skeletal dysplasia and growth retardation. Fewer than 60 cases have been described in the literature, although WRS is now recognised as the most frequent cause of neonatal/early-onset diabetes in patients with consanguineous parents. Typically, diabetes occurs before six months of age, and skeletal dysplasia is diagnosed within the first year or two of life. Other manifestations vary between patients in their nature and severity and include frequent episodes of acute liver failure, renal dysfunction, exocrine pancreas insufficiency, intellectual deficit, hypothyroidism, neutropenia and recurrent infections. Bone fractures may be frequent. WRS is caused by mutations in the gene encoding eukaryotic translation initiation factor 2α kinase 3 (EIF2AK3), also known as PKR-like endoplasmic reticulum kinase (PERK). PERK is an endoplasmic reticulum (ER) transmembrane protein, which plays a key role in translation control during the unfolded protein response. ER dysfunction is central to the disease processes. The disease variability appears to be independent of the nature of the EIF2AK3 mutations, with the possible exception of an older age at onset; other factors may include other genes, exposure to environmental factors and disease management. WRS should be suspected in any infant who presents with permanent neonatal diabetes associated with skeletal dysplasia and/or episodes of acute liver failure. Molecular genetic testing confirms the diagnosis. Early diagnosis is recommended, in order to ensure rapid intervention for episodes of hepatic failure, which is the most life threatening complication. WRS should be differentiated from other forms of neonatal/early-onset insulin-dependent diabetes based on clinical presentation and genetic testing. Genetic counselling and antenatal diagnosis is recommended for parents of a WRS patient with confirmed EIF2AK3 mutation. Close therapeutic monitoring of diabetes and treatment with an insulin pump are recommended because of the risk of acute episodes of hypoglycaemia and ketoacidosis. Interventions under general anaesthesia increase the risk of acute aggravation, because of the toxicity of anaesthetics, and should be avoided. Prognosis is poor and most patients die at a young age. Intervention strategies targeting ER dysfunction provide hope for future therapy and prevention