ALBERT

Description: Göte–2005 was a measurement campaign in the city of Göteborg with the aim of studying the influence of the winter thermal inversions on urban air pollution. Elemental speciation of PM2.5 aerosol particles, collected on Teflon filters at three urban sites and one rural site in the Göteborg region, was a major part of the study. Trace element analysis was done by Energy Dispersive X-Ray Fluorescence (EDXRF) spectrometry and the concentrations of S, Cl, K, Ca, Ti, V, Mn, Fe, Ni, Cu, Zn, Br and Pb were determined. The elemental content of the particles in combination with information of local wind speed and direction and also backward trajectories were used to estimate the source areas of the pollutants. We can conclude that S, V, Ni, Br, and Pb have their main sources outside the Göteborg area, since we cannot see elevated concentrations of these elements during an inversion episode. Sea traffic and harbour activities were also identified, primarily by the S and V content of the particles. This study proves that the elemental analysis by EDXRF presents valuable information for tracing the origin of air masses arriving at a measurement site.

Description: The Göte–2005 measurement campaign aimed at studying the influence of the winter thermal inversions on urban air pollution. Elemental speciation of PM2.5 aerosol particles, collected on Teflon filters at three urban sites and one rural site in the Göteborg region, was a major part of the study. Trace element analysis was done by Energy Dispersive X-Ray Fluorescence (EDXRF) spectrometry and the concentrations of S, Cl, K, Ca, Ti, V, Mn, Fe, Ni, Cu, Zn, Br and Pb were determined. The elemental content of the particles, local wind speed and direction, and backward trajectories were used to investigate possible sources for the pollutants. We concluded that S, V, Ni, Br, and Pb had their main sources outside the central Göteborg area, since elevated concentrations of these elements were not observed during an inversion episode. Sea traffic and harbour activities were identified, primarily by the S and V content of the particles. This study showed that the elemental analysis by EDXRF presents valuable information for tracing the origin of air masses arriving at a measurement site.

Description: First results of radar derived climatology have emerged over the last years, as datasets of appropriate extent are becoming available. Usually, these statistics are based on time series lasting up to ten years as continuous storage of radar data was often not achieved before. This kind of climatology demands a high level of data quality. Small deviations or minor systematic under- or overestimations in single radar images become a major cause of error in statistical analysis. Extensive corrections of radar data are a crucial prerequisite for radar derived climatology. We present a new statistical post-correction scheme based on a climatological analysis of seven years of radar data of the Munich weather radar (2000–2006) operated by DWD (German Weather Service). Original radar products are used subject only to corrections within the signal processor without any further corrections on single radar images. The aim of this statistical correction is to make up for the average systematic errors caused by clutter, propagation, or measuring effects but to conserve small-scale natural variations in space. The statistical correction is based on a thorough analysis of the different causes of possible errors for the Munich weather radar. This analysis revealed the following basic effects: the decrease of rain amount as a function of height and distance from the radar, clutter effects such as clutter remnants after filtering, holes by eliminated clutter or shading effects from obstacles near the radar, visible as spokes, as well as the influence of the bright band. The correction algorithm is correspondingly based on these results. It consists of three modules. The first one is an altitude correction which minimises measuring effects. The second module corrects clutter effects and disturbances and the third one realises a mean adjustment to selected rain gauges. Two different sets of radar products are used. The statistical analysis as well as module 1 and module 2 of the correction algorithm are based on frequencies of the six reflectivity levels within the so-called PX product. For correction module 3 and for the validation of the correction algorithm, rain amounts are calculated from the 8-bit so-called DX product. The correction algorithm is created to post-correct climatological or statistical analysis of radar data with a temporal resolution larger than one year. The correction algorithm is used for frequencies of occurrence of radar reflectivities which enables its application even for radar products such as DWD's cell-tracking-product CONRAD. Application (2004–2006) and validation (2007–2009) periods of this correction algorithm with rain gauges show an increased conformity for radar climatology after the statistical correction. In the years 2004 to 2006 the Root-Mean-Square-Error (RMSE) between mean annual rain amounts of rain gauges and corresponding radar pixels decreases from 262 mm to 118 mm excluding those pairs of values where the rain gauges are situated in areas of obviously corrupted radar data. The results for the validation period 2007 to 2009 are based on all pairs of values and show a decline of the RMSE from 322 mm to 174 mm.

Description: Extensive corrections of radar data are a crucial prerequisite for radar derived climatology. This kind of climatology demands a high level of data quality. Little deviations or minor systematic underestimations or overestimations in single radar images become a major cause of error in statistical analysis. First results of radar derived climatology have emerged over the last years, as data sets of appropriate extent are becoming available. Usually, these statistics are based on time series lasting up to ten years as storage of radar data was not achieved before. We present a new statistical post-correction scheme, which is based on seven years of radar data of the Munich weather radar (2000–2006) that is operated by DWD (German Weather Service). The typical correction algorithms for single radar images, such as clutter corrections, are used. Then an additional statistical post-correction based on the results of a climatological analysis from radar images follows. The aim of this statistical correction is to correct systematic errors caused by clutter effects or measuring effects but to conserve small-scale natural variations in space. The statistical correction is based on a thorough analysis of the different causes of possible errors for the Munich weather radar. This robust analysis revealed the following basic effects: the decrease of rain rate in relation to height and distance from the radar, clutter effects such as remaining clutter, eliminated clutter or shading effects from obstacles near the radar, visible as spokes, as well as the influence of the Bright Band. The correction algorithm is correspondingly based on these results. It consists of three modules. The first one is an altitude correction, which minimizes measuring effects. The second module corrects clutter effects and the third one realizes a mean adjustment to selected rain gauges. Two different radar products are used. The statistical analysis as well as module one and module two of the correction algorithm are based on frequencies of occurrence of the so-called PX-product with six reflectivity levels. For correction module 3 and for the validation of the correction algorithm rain rates are calculated from the 8-bit-depth so-called DX-product. An application (2004–2006) and a validation (2007–2009) of this correction algorithm with rain gauges show a much higher conformity for radar climatology after the statistical correction. In the years 2004 to 2006 the Root-Mean-Square-Error (RMSE) decreases from 262 mm to 118 mm excluding those pair of values where the rain gauges are situated in areas of obviously corrupted radar data. The results for the validation period 2007 to 2009 are based on all pairs of values and show a decline of the RMSE from 322 mm to 174 mm.

Description: As a consequence of climate change, extreme and flood-causing precipitation events are expected to increase in magnitude and frequency, especially in today's high-precipitation areas. During the north-east monsoon seasons, Nakhon Si Thammarat in southern Thailand is flash-flooded every 2.22 years on average. This study investigates frequency and intensity of harmful discharges of the Tha Di River regarding the IPCC emission scenarios A2 and B2. The regional climate model (RCM) PRECIS was transformed using the advanced delta change (ADC) method. The hydrologic response model HBV-Light was calibrated to the catchment and supplied with ADC-scaled daily precipitation and temperature data for 2010–2089. Under the A2 (B2) scenario, the flood threshold exceedance frequency on average increases by 133 % (decreases by 10 %), average flood intensity increases by 3 % (decreases by 2 %) and the annual top five discharge peaks intensities increase by 46 % (decrease by 5 %). Yearly precipitation sums increase by 30 % (10 %) towards the end of the century. The A2 scenario predicts a precipitation increase during the rainy season, which intensifies flood events; while increases projected exclusively for the dry season are not expected to cause floods. Retention volume demand of past events was calculated to be up to 12 × 106 m3. Flood risks are staying at high levels under the B2 scenario or increase dramatically under the A2 scenario. Results show that the RCM scaling process is inflicted with systematic biases but is crucial to investigate small, mountainous catchments. Improvement of scaling techniques should therefore accompany the development towards high-resolution climate models.

Description: A radar-based rainfall statistic demands high quality data that provide realistic precipitation amounts in space and time. Instead of correcting single radar images, we developed a post-correction scheme for long-term composite radar data that corrects corrupted areas, but preserves the original precipitation patterns. The post-correction scheme is based on a 5 year statistical analysis of radar composite data and its constituents. The accumulation of radar images reveals artificial effects that are not visible in the individual radar images. Some of them are already inherent to single radar data such as the effect of increasing beam height, beam blockage or clutter remnants. More artificial effects are introduced in the process of compositing such as sharp gradients at the boundaries of overlapping areas due to different beam heights and resolution. The cause of these disturbances, their behaviour with respect to reflectivity level, season or altitude is analysed based on time-series of two radar products: the single radar reflectivity product PX for each of the 16 radar systems of the German Meteorological Service (DWD) for the time span 2000 to 2006 and the radar composite product RX of DWD from 2005 through to 2009. These statistics result in additional quality information on radar data that is not available elsewhere. The resulting robust characteristics of disturbances, e.g. the dependency of the frequencies of occurrence of radar reflectivities on beam height, are then used as a basis for the post-correction algorithm. The scheme comprises corrections for shading effects and speckles, such as clutter remnants or overfiltering, as well as for systematic differences in frequencies of occurrence of radar reflectivities between the near and the far ranges of individual radar sites. An adjustment to rain gauges is also included. Applying this correction, the Root-Mean-Square-Error for the comparison of radar derived annual rain amounts with rain gauge data decreases from 1181 to 171 mm a−1 (application period: 2005, 2006 and 2009) and from 317 to 178 mm a−1 (validation period: 2007, 2008). The entire correction scheme is applicable on an annual scale. The correction of mean annual rain amounts derived from radar composite data for the whole period leads to an almost undisturbed and homogeneous distribution of rain amounts for Germany.

Description: The Southern Hemisphere Westerly Winds (SWW) have been suggested to exert a critical influence on global climate through the wind-driven upwelling of deep water in the Southern Ocean and the potentially resulting atmospheric CO2 variations. The investigation of the temporal and spatial evolution of the SWW along with forcings and feedbacks remains a significant challenge in climate research. In this study, the evolution of the SWW under orbital forcing from the mid-Holocene (7 kyr BP) to pre-industrial modern times (250 yr BP) is examined with transient experiments using the comprehensive coupled global climate model CCSM3. In addition, a model inter-comparison is carried out using orbitally forced Holocene transient simulations from four other coupled global climate models. Analyses and comparison of the model results suggest that the annual and seasonal mean SWW were subject to an overall strengthening and poleward shifting trend during the course of the mid-to-late Holocene under the influence of orbital forcing, except for the austral spring season, where the SWW exhibited an opposite trend of shifting towards the equator.

Description: The Southern Hemisphere Westerly Winds (SWW) have been suggested to exert a critical influence on global climate through wind-driven upwelling of deep water in the Southern Ocean and the potentially resulting atmospheric CO2 variations. The investigation of the temporal and spatial evolution of the SWW along with forcings and feedbacks remains a significant challenge in climate research. In this study, the evolution of the SWW under orbital forcing from the mid-Holocene (7 kyr BP) to pre-industrial modern times (250 yr BP) is examined with transient experiments using the comprehensive coupled global climate model CCSM3. In addition, a model inter-comparison is carried out using orbitally forced Holocene transient simulations from four other coupled global climate models. Analyses and comparison of the model results suggest that the annual and seasonal mean SWW were subject to an overall strengthening and poleward shifting trend during the course of the mid-to-late Holocene under the influence of orbital forcing, except for the austral spring season, where the SWW exhibited an opposite trend of shifting towards the equator.

Description: This paper evaluates the performance of the stratospheric ozone analyses delivered in near real time by the MACC (Monitoring Atmospheric Composition and Climate) project during the 3 year period between September 2009 and September 2012. Ozone analyses produced by four different chemistry transport models and data assimilation techniques are examined: the ECMWF Integrated Forecast System (IFS) coupled to MOZART-3 (IFS-MOZART), the BIRA-IASB Belgian Assimilation System for Chemical ObsErvations (BASCOE), the DLR/RIU Synoptic Analysis of Chemical Constituents by Advanced Data Assimilation (SACADA), and the KNMI Data Assimilation Model based on Transport Model version 3 (TM3DAM). The assimilated satellite ozone retrievals differed for each system: SACADA and TM3DAM assimilated only total ozone observations, BASCOE assimilated profiles for ozone and some related species, while IFS-MOZART assimilated both types of ozone observations. The stratospheric ozone analyses are compared to independent ozone observations from ground-based instruments, ozone sondes and the ACE-FTS (Atmospheric Chemistry Experiment – Fourier Transform Spectrometer) satellite instrument. All analyses show total column values which are generally in good agreement with groundbased observations (biases 50%) for ozone in the lower stratosphere in the Tropics and in the Antarctic, especially during ozone hole conditions. This study shows that ozone analyses with realistic total ozone column densities do not necessarily yield good agreement with the observed ozone profiles. It also shows the large benefit obtained from the assimilation of a single limb-scanning instrument (Aura MLS) with a high density of observations. Hence even state-of-the-art models of stratospheric chemistry still require the assimilation of limb observations for a correct representation of the vertical distribution of ozone in the stratosphere.

Description: Cloud microphysical processes involving the ice phase in tropospheric clouds are among the major uncertainties in cloud formation, weather and General Circulation Models (GCMs). The simultaneous detection of aerosol particles, liquid droplets, and ice crystals, especially in the small cloud-particle size range below 50 μm, remains challenging in mixed phase, often unstable ice-water phase environments. The Cloud Aerosol Spectrometer with Polarisation (CASPOL) is an airborne instrument that has the ability to detect such small cloud particles and measure their effects on the backscatter polarisation state. Here we operate the versatile Cosmics-Leaving-OUtdoor-Droplets (CLOUD) chamber facility at the European Organisation for Nuclear Research (CERN) to produce controlled mixed phase and other clouds by adiabatic expansions in an ultraclean environment, and use the CASPOL to discriminate between different aerosols, water and ice particles. In this paper, optical property measurements of mixed phase clouds and viscous Secondary Organic Aerosol (SOA) are presented. We report observations of significant liquid – viscous SOA particle polarisation transitions under dry conditions using CASPOL. Cluster analysis techniques were subsequently used to classify different types of particles according to their polarisation ratios during phase transition. A classification map is presented for water droplets, organic aerosol (e.g., SOA and oxalic acid), crystalline substances such as ammonium sulphate, and volcanic ash. Finally, we discuss the benefits and limitations of this classification approach for atmospherically relevant concentration and mixtures with respect to the CLOUD 8–9 campaigns and its potential contribution to Tropical Troposphere Layer (TTL) analysis.