Impact of AVHRR channel 3b noise on climate data records: filtering method applied to the CM SAF CLARA-A2 data record

A method for reducing the impact of noise in the 3.7 micron spectral channel in climate data records derived from coarse resolution (4 km) global measurements from the Advanced Very High Resolution Radiometer (AVHRR) data is presented. A dynamic size-varying median filter is applied to measurements guided by measured noise levels and scene temperatures for individual AVHRR sensors on historic National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites in the period 1982–2001. The method was used in the preparation of the CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data—Second Edition (CLARA-A2), a cloud climate data record produced by the EUMETSAT Satellite Application Facility for Climate Monitoring (CM SAF), as well as in the preparation of the corresponding AVHRR-based datasets produced by the European Space Agency (ESA) Climate Change Initiative (CCI) project ESA-CLOUD-CCI. The impact of the noise filter was equivalent to removing an artificial decreasing trend in global cloud cover of 1–2% per decade in the studied period, mainly explained by the very high noise levels experienced in data from the first satellites in the series (NOAA-7 and NOAA-9). View Full-Tex

Correcting orbital drift signal in the time series of AVHRR derived convective cloud fraction using rotated empirical orthogonal function: Correcting orbital drift signal in the time series of AVHRR derivedconvective cloud fraction using rotated empirical orthogonal function

The Advanced Very High Resolution Radiometer (AVHRR) instruments onboard the series of National Oceanic and Atmospheric Administration (NOAA) satellites offer the longest available meteorological data records from space. These satellites have drifted in orbit resulting in shifts in the local time sampling during the life span of the sensors onboard. Depending upon the amplitude of the diurnal cycle of the geophysical parameters derived, orbital drift may cause spurious trends in their time series. We investigate tropical deep convective clouds, which show pronounced diurnal cycle amplitude, to estimate an upper bound of the impact of orbital drift on their time series. We carry out a rotated empirical orthogonal function analysis (REOF) and show that the REOFs are useful in delineating orbital drift signal and, more importantly, in subtracting this signal in the time series of convective cloud amount. These results will help facilitate the derivation of homogenized data series of cloud amount from NOAA satellite sensors and ultimately analyzing trends from them. However, we suggest detailed comparison of various methods and rigorous testing thereof applying final orbital drift corrections

Longer Leukocyte Telomere Length Is Associated with Smaller Hippocampal Volume among Non-Demented APOE ε3/ε3 Subjects

Telomere length shortens with cellular division, and leukocyte telomere length is used as a marker for systemic telomere length. The hippocampus hosts adult neurogenesis and is an important structure for episodic memory, and carriers of the apolipoprotein E ε4 allele exhibit higher hippocampal atrophy rates and differing telomere dynamics compared with non-carriers. The authors investigated whether leukocyte telomere length was associated with hippocampal volume in 57 cognitively intact subjects (29 ε3/ε3 carriers; 28 ε4 carriers) aged 49–79 yr. Leukocyte telomere length correlated inversely with left (rs = −0.465; p = 0.011), right (rs = −0.414; p = 0.025), and total hippocampus volume (rs = −0.519; p = 0.004) among APOE ε3/ε3 carriers, but not among ε4 carriers. However, the ε4 carriers fit with the general correlation pattern exhibited by the ε3/ε3 carriers, as ε4 carriers on average had longer telomeres and smaller hippocampi compared with ε3/ε3 carriers. The relationship observed can be interpreted as long telomeres representing a history of relatively low cellular proliferation, reflected in smaller hippocampal volumes. The results support the potential of leukocyte telomere length being used as a biomarker for tapping functional and structural processes of the aging brain

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

A NOAA AVHRR cloud climatology over Scandinavia covering the period 1991-2000

A ten-year NOAA A VHRR cloud climatology with a horizontal resolution of four km has been compiled over the Scandinavian region based on results from near real-lime cloud classifications of the SMHl SCANDlA mode!. The frequency and geographic distribution ofthe cloud groups Low-, Medium- and High-level clouds, water and ice clouds and deep convective clouds have been studied in addition to the ten-ycar monthly means of total fractional cloud cover in the region. Furthennore, attempts to estimatc the diurnal cycle of cloudiness and typieal cloud patterns in various weather rcgimes (e.g., North Atlantic Oscillation phases) have been made. The cloud climate in the region was found ta be significantly affected by the distribution of land and sea. In particular. the Baltic Sea was shown to suppress summertime cloudiness substantially and this effect was shown to influence cloud conditions in major parts of the Scandinavian region. Huwever, interesting deviations from this cloudiness pattern were found in the Scandinavian mountain range, in the northern part af Scandinavia and over the Norwegian Sea. The quality af the satellite-based cloud information was examined by comparing with corresponding surface-observations given by SYNOP-based cloud climatologies for the same period. Results showed good agreement but specific problems were found in winter. In addition, some effects of the degradation of visible AVHRR channels were notieed. Comparisons have also been rnade with internationally used global cloud climate data sets, namely the  SYNOP-based CRU data set and the cloud climatologics from the ISCCP D2 series

The use of a satellite-derived cloud climatology for studying cloud-aerosol processes and the performance of regional cloud climate simulations

The entry of satellite-derived decadal cloud datasets with homogeneous coverage in time and space enables studies not possible before. This thesis presents two such applications. The first study deals with cloud-aerosol processes and the second with an evaluation of cloud simulations from a regional climate model. The first part of the thesis describes the used satellite-derived dataset based on imagery from the Advanced Very High Resolution Radiometer (AVHRR) on the polar orbiting NOAA satellites. A method for cloud retrieval and the compilation of a 1991-2000 Scandinavian cloud climatology are described. The second part reveals an intriguing anti-correlation between monthly mean satellite-derived cloudiness and the concentration of the cosmogenetic isotope Beryllium-7 in near-surface aerosol samples for three measurement sites in Sweden. Large-scale transport processes are suggested as the most likely physical mechanism for this behaviour but more complex relations to cloud microphysical processes are not ruled out. The final part presents a thorough evaluation of cloud simulations of the SMHI Rossby Centre regional atmospheric model (RCA3). Several model-to-satellite adaptations are applied to avoid artificial biases of results. The study stresses the necessity to account for initial differences between observed and modelled clouds caused by satellite cloud detection limitations. Results show good agreement of modelled and observed cloud amounts while the vertical distribution of clouds appears largely different. RCA3 underestimates medium-level clouds while overestimating low- and high-level clouds. Also, the current use of the Maximum cloud overlap approach in the radiation scheme and an indicated excess of cloud condensate in modelled clouds appear to create excessive cloud optical thicknesses with serious implications for the surface radiation budget. Future applications are outlined based on greatly enhanced satellite-derived cloud and radiation budget datasets

Satellite-estimated cloudiness from NOAA AVHRR data in the Nordic are during 1993

A method to estimate monthly cloud conditions (total fractional cloud cover) from multispectral satellite data is described. The operational cloud classification scheme SCANDIA (the SMHI Cloud ANalysis model using DIgital AVHRR data), based on high resolution imagery from the polar orbiting NOAA satellites, is used to produce monthly cloud frequencies for all months of 1993. The annual mean is computed and the diurnal variation of cloudiness is investigated for June and December. Cloud analyses are made for an area covering the Nordic countries with a horizontal resolution of four km Comparisons with existing surface observations show very good agreement, especially in the summer half of the year. some problems are indicated in the winter season when a minor underestimation of cloudiness is noticed. The underestimation is mainly due to the non-separability of low-level water clouds from cloud-free areas at very low sun elevations. Despite these problems, general cloud patterns are well described also in cold winter situations. Improvements of the method are discussed and an enlargement of the analysis area is envisaged. The method is proposed as a valuable tool for local and regional monitoring of the cloud climatology. Comparisons with forecasted cloudiness from atmospheric models are suggested as well as special studies of cloud conditions in the Polar areas

Validation of modelled cloudiness using satellite-estimated cloud climatologies

A method to evaluate forecasts of total fractional cloud cover using satellite measurements is demonstrated. Cloud analyses in the form of monthly cloud climatologies are extracted from NOAA. AVHRR data which are compared to corresponding cloud forecast information from the HIRLAM and ECMWF numerical weather prediction models. The satellite-based cloud information is extracted for a summer month in 1994 and a winter month in 1995 by use of the SMHI cloud classification model SCANDIA. Cloud analyses are conducted for an area covering a substantial part of northern Europe. Deficiencies in forecasted cloud amounts are found for both models, especially the underestimation of cloudiness for short forecast lengths with the HIRLAM model. Forecast improvements using the HIRLAM model are indicated when introducing a cloud initialisation technique using cloud fields from initial 6-hour forecasts (first-guess fields). Future systematic validations using this technique are, however, needed to make firm conclusions on the general model behaviour. SCANDIA-derived cloud information is proposed as a valuable complement to other datasets used for cloud forecast validation (e.g., the SSM/I- and ISCCP data sets)