The full-spectrum correlated-k method for longwave atmospheric radiative transfer using an effective Planck function

The correlated k-distribution (CKD) method is widely used in the radiative transfer schemes of atmospheric models and involves dividing the spectrum into a number of bands and then reordering the gaseous absorption coefficients within each one. The fluxes and heating rates for each band may then be computed by discretizing the reordered spectrum into of order 10 quadrature points per major gas and performing a monochromatic radiation calculation for each point. In this presentation it is shown that for clear-sky longwave calculations, sufficient accuracy for most applications can be achieved without the need for bands: reordering may be performed on the entire longwave spectrum. The resulting full-spectrum correlated k (FSCK) method requires significantly fewer monochromatic calculations than standard CKD to achieve a given accuracy. The concept is first demonstrated by comparing with line-by-line calculations for an atmosphere containing only water vapor, in which it is shown that the accuracy of heating-rate calculations improves approximately in proportion to the square of the number of quadrature points. For more than around 20 points, the root-mean-squared error flattens out at around 0.015 K/day due to the imperfect rank correlation of absorption spectra at different pressures in the profile. The spectral overlap of m different gases is treated by considering an m-dimensional hypercube where each axis corresponds to the reordered spectrum of one of the gases. This hypercube is then divided up into a number of volumes, each approximated by a single quadrature point, such that the total number of quadrature points is slightly fewer than the sum of the number that would be required to treat each of the gases separately. The gaseous absorptions for each quadrature point are optimized such that they minimize a cost function expressing the deviation of the heating rates and fluxes calculated by the FSCK method from line-by-line calculations for a number of training profiles. This approach is validated for atmospheres containing water vapor, carbon dioxide, and ozone, in which it is found that in the troposphere and most of the stratosphere, heating-rate errors of less than 0.2 K/day can be achieved using a total of 23 quadrature points, decreasing to less than 0.1 K/day for 32 quadrature points. It would be relatively straightforward to extend the method to include other gases.

The full-spectrum correlated k method for longwave atmospheric radiative transfer: treatment of gaseous overlap

The correlated k-distribution (CKD) method is widely used in the radiative transfer schemes of atmospheric models, and involves dividing the spectrum into a number of bands and then reordering the gaseous absorption coefficients within each one. The fluxes and heating rates for each band may then be computed by discretizing the reordered spectrum into of order 10 quadrature points per major gas, and performing a pseudo-monochromatic radiation calculation for each point. In this paper it is first argued that for clear-sky longwave calculations, sufficient accuracy for most applications can be achieved without the need for bands: reordering may be performed on the entire longwave spectrum. The resulting full-spectrum correlated k (FSCK) method requires significantly fewer pseudo-monochromatic calculations than standard CKD to achieve a given accuracy. The concept is first demonstrated by comparing with line-by-line calculations for an atmosphere containing only water vapor, in which it is shown that the accuracy of heating-rate calculations improves approximately in proportion to the square of the number of quadrature points. For more than around 20 points, the root-mean-squared error flattens out at around 0.015 K d−1 due to the imperfect rank correlation of absorption spectra at different pressures in the profile. The spectral overlap of m different gases is treated by considering an m-dimensional hypercube where each axis corresponds to the reordered spectrum of one of the gases. This hypercube is then divided up into a number of volumes, each approximated by a single quadrature point, such that the total number of quadrature points is slightly fewer than the sum of the number that would be required to treat each of the gases separately. The gaseous absorptions for each quadrature point are optimized such they minimize a cost function expressing the deviation of the heating rates and fluxes calculated by the FSCK method from line-by-line calculations for a number of training profiles. This approach is validated for atmospheres containing water vapor, carbon dioxide and ozone, in which it is found that in the troposphere and most of the stratosphere, heating-rate errors of less than 0.2 K d−1 can be achieved using a total of 23 quadrature points, decreasing to less than 0.1 K d−1 for 32 quadrature points. It would be relatively straightforward to extend the method to include other gases.

Distribution and statistics of African mesoscale convective weather systems based on the ISCCP Meteosat imagery

This paper provides for the first time an objective short-term (8 yr) climatology of African convective weather systems based on satellite imagery. Eight years of infrared International Satellite Cloud Climatology Project-European Space Agency's Meteorological Satellite (ISCCP-Meteosat) satellite imagery has been analyzed using objective feature identification, tracking, and statistical techniques for the July, August, and September periods and the region of Africa and the adjacent Atlantic ocean. This allows various diagnostics to be computed and used to study the distribution of mesoscale and synoptic-scale convective weather systems from mesoscale cloud clusters and squall lines to tropical cyclones. An 8-yr seasonal climatology (1983-90) and the seasonal cycle of this convective activity are presented and discussed. Also discussed is the dependence of organized convection for this region, on the orography, convective, and potential instability and vertical wind shear using European Centre for Medium-Range Weather Forecasts reanalysis data.

Effect of ENSO phase on large-scale snow water equivalent distribution in a GCM

Understanding links between the El Nino-Southern Oscillation (ENSO) and snow would be useful for seasonal forecasting, but also for understanding natural variability and interpreting climate change predictions. Here, a 545-year run of the general circulation model HadCM3, with prescribed external forcings and fixed greenhouse gas concentrations, is used to explore the impact of ENSO on snow water equivalent (SWE) anomalies. In North America, positive ENSO events reduce the mean SWE and skew the distribution towards lower values, and vice versa during negative ENSO events. This is associated with a dipole SWE anomaly structure, with anomalies of opposite sign centered in western Canada and the central United States. In Eurasia, warm episodes lead to a more positively skewed distribution and the mean SWE is raised. Again, the opposite effect is seen during cold episodes. In Eurasia the largest anomalies are concentrated in the Himalayas. These correlations with February SWE distribution are seen to exist from the previous June-July-August (JJA) ENSO index onwards, and are weakly detected in 50-year subsections of the control run, but only a shifted North American response can be detected in the anaylsis of 40 years of ERA40 reanalysis data. The ENSO signal in SWE from the long run could still contribute to regional predictions although it would be a weak indicator only

Modelling habitat selection and distribution of the critically endangered Jerdon's courser Rhinoptilus bitorquatus in scrub jungle: an application of a new tracking method

1. Jerdon's courser Rhinoptilus bitorquatus is a nocturnally active cursorial bird that is only known to occur in a small area of scrub jungle in Andhra Pradesh, India, and is listed as critically endangered by the IUCN. Information on its habitat requirements is needed urgently to underpin conservation measures. We quantified the habitat features that correlated with the use of different areas of scrub jungle by Jerdon's coursers, and developed a model to map potentially suitable habitat over large areas from satellite imagery and facilitate the design of surveys of Jerdon's courser distribution. 2. We used 11 arrays of 5-m long tracking strips consisting of smoothed fine soil to detect the footprints of Jerdon's coursers, and measured tracking rates (tracking events per strip night). We counted the number of bushes and trees, and described other attributes of vegetation and substrate in a 10-m square plot centred on each strip. We obtained reflectance data from Landsat 7 satellite imagery for the pixel within which each strip lay. 3. We used logistic regression models to describe the relationship between tracking rate by Jerdon's coursers and characteristics of the habitat around the strips, using ground-based survey data and satellite imagery. 4. Jerdon's coursers were most likely to occur where the density of large (>2 m tall) bushes was in the range 300-700 ha(-1) and where the density of smaller bushes was less than 1000 ha(-1). This habitat was detectable using satellite imagery. 5. Synthesis and applications. The occurrence of Jerdon's courser is strongly correlated with the density of bushes and trees, and is in turn affected by grazing with domestic livestock, woodcutting and mechanical clearance of bushes to create pasture, orchards and farmland. It is likely that there is an optimal level of grazing and woodcutting that would maintain or create suitable conditions for the species. Knowledge of the species' distribution is incomplete and there is considerable pressure from human use of apparently suitable habitats. Hence, distribution mapping is a high conservation priority. A two-step procedure is proposed, involving the use of ground surveys of bush density to calibrate satellite image-based mapping of potential habitat. These maps could then be used to select priority areas for Jerdon's courser surveys. The use of tracking strips to study habitat selection and distribution has potential in studies of other scarce and secretive species.

Exploring the enzymatic landscape: distribution and kinetics of hydrolytic enzymes in soil particle-size fractions

The location of extracellular enzymes within the soil architecture and their association with the various soil components affects their catalytic potential. A soil fractionation study was carried out to investigate: (a) the distribution of a range of hydrolytic enzymes involved in C, N and P transformations, (b) the effect of the location on their respective kinetics, (c) the effect of long-term N fertilizer management on enzyme distribution and kinetic parameters. Soil (silty clay loam) from grassland which had received 0 or 200 kg N ha(-1) yr(-1) was fractionated, and four particle-size fractions (> 200, 200-63, 63-2 and 0. 1-2 mum) were obtained by a combination of wet-sieving and centrifugation, after low-energy ultrasonication. All fractions were assayed for four carbohydrases (beta-cellobiohydrolase, N-acetyl-beta-glucosammidase, beta-glucosidase and beta-xylosidase), acid phosphatase and leucine-aminopeptidase using a microplate fluorimetric assay based on MUB-substrates. Enzyme kinetics (V-max and K-m) were estimated in three particle-size fractions and the unfractionated soil. The results showed that not all particle-size fractions were equally enzymatically active and that the distribution of enzymes between fractions depended on the enzyme. Carbohydrases predominated in the coarser fractions while phosphatase and leucine-aminopeptidase were predominant in the clay-size fraction. The Michaelis constant (K.) varied among fractions, indicating that the association of the same enzyme with different particle-size fractions affected its substrate affinity. The same values of Km were found in the same fractions from the soil under two contrasting fertilizer management regimes, indicating that the Michaelis constant was unaffected by soil changes caused by N fertilizer management. (C) 2004 Elsevier Ltd. All rights reserved.

Distribution of salinity in the root zone affects the yield, quality of tomato fruit

Tomato plants (Lycopersicon esculentum Mill. var. DRK) were grown with a split root system to determine the effect of an unequal distribution of salinity in the root zone on yield and quality. The roots of the plant were divided into two portions and each portion was irrigated with nutrient solutions differing in EC levels achieved by adding Na or K. The maximum yield was observed in treatments with unequal EC when one portion of the roots received only water and the lowest in the high EC treatments. The reduced yield in the high EC treatment was due to the incidence of blossom-end rot and reduced fruit size. Fruit size in the treatments receiving solutions of unequal EC was up to 12% greater than that in the control. No significant differences were found in soluble solids and acidity between control and all other unequal EC treatments. Ca concentration was significantly higher in the treatments where one portion of the root system received water. It was concluded that high salinity had positive effects on yield and quality provided that one portion of the root system were placed in low EC or only water.

Uneven distribution of nutrients in the root zone affects the incidence of blossom end rot and concentration of calcium and potassium in fruits of tomato

Tomato plants ( Lycopersicon esculentum Mill. var. DRK) were grown hydroponically to determine the effect of an uneven distribution of nutrients in the root zone on blossomend rot (BER) and Ca and K concentrations in the fruits. The plants were grown in rockwool with their root system divided into two portions. Each portion was irrigated with nutrient solutions with either the same or the different electrical conductivity (EC) in the range 0 to 6 dS m(-1). Solutions with high EC supplied to both sides of the root system significantly increased the incidence of BER. However, when only water or a solution of low EC was supplied to one portion, BER was reduced by 80%. Fruit yields were significantly higher ( P < 0.01) for plants that received solutions of the uneven EC treatments (6/0 or 4.5/0 EC treatment). Plants supplied with solutions of uneven EC generally had higher leaf and fruit concentrations of Ca but lower concentrations of K than those supplied with solutions of high EC. There was no difference in Ca concentration at the distal end of young fruits of the uneven EC treatment but it was reduced in the high EC treatments. The concentration of K in the mature fruits of the uneven EC treatments was lower than that of the high EC treatments and higher or similar that of the 3/3 or 2.5/2.5 EC treatments ( controls). A clear relationship was found between the incidence of BER and the exudation rate. High rate of xylem exudation was observed in the uneven EC treatments. Reduction of BER in the uneven EC treatments is most likely to be the effect of high exudation rate on Ca status in the young fruits. It was concluded that high EC of solution had positive effects on Ca concentration and incidence of BER provided that nutrient solution with low EC or water is supplied to the one portion of the root system.

REMOTE SENSING OF AEOLIAN DUST PRODUCTION AND DISTRIBUTION

Airborne dust is of concern due to hazards in the localities affected by erosion, transport and deposition, but it is also of global concern due to uncertainties over its role in radiative forcing of climate. In order to model the environmental impact of dust, we need a better knowledge of sources and transport processes. Satellite remote sensing has been instrumental in providing this knowledge, through long time series of observations of atmospheric dust transport. Three remote sensing methodologies have been used, and are reviewed briefly in this paper. Firstly the use of observations from the Total Ozone Mapping Spectrometer (TOMS), secondly the use of the Infrared Difference Dust Index (IDDI) from Meterosat infrared data, thirdly the use of MODIS images from the rapid response system. These data have highlighted the major global sources of dust, mist of which are associated with endoreic drainage basins in deserts, which held lakes during Quaternary humid climate phases, and identified the Bodele Depression in Tchad as the dustiest place on Earth.

Scalability of efficient parallel K-Means

Clustering is defined as the grouping of similar items in a set, and is an important process within the field of data mining. As the amount of data for various applications continues to increase, in terms of its size and dimensionality, it is necessary to have efficient clustering methods. A popular clustering algorithm is K-Means, which adopts a greedy approach to produce a set of K-clusters with associated centres of mass, and uses a squared error distortion measure to determine convergence. Methods for improving the efficiency of K-Means have been largely explored in two main directions. The amount of computation can be significantly reduced by adopting a more efficient data structure, notably a multi-dimensional binary search tree (KD-Tree) to store either centroids or data points. A second direction is parallel processing, where data and computation loads are distributed over many processing nodes. However, little work has been done to provide a parallel formulation of the efficient sequential techniques based on KD-Trees. Such approaches are expected to have an irregular distribution of computation load and can suffer from load imbalance. This issue has so far limited the adoption of these efficient K-Means techniques in parallel computational environments. In this work, we provide a parallel formulation for the KD-Tree based K-Means algorithm and address its load balancing issues.

Airborne measurements of the spatial distribution of aerosol chemical composition across Europe and evolution of the organic fraction

The spatial distribution of aerosol chemical composition and the evolution of the Organic Aerosol (OA) fraction is investigated based upon airborne measurements of aerosol chemical composition in the planetary boundary layer across Europe. Sub-micron aerosol chemical composition was measured using a compact Time-of-Flight Aerosol Mass Spectrometer (cToF-AMS). A range of sampling conditions were evaluated, including relatively clean background conditions, polluted conditions in North-Western Europe and the near-field to far-field outflow from such conditions. Ammonium nitrate and OA were found to be the dominant chemical components of the sub-micron aerosol burden, with mass fractions ranging from 20--50% each. Ammonium nitrate was found to dominate in North-Western Europe during episodes of high pollution, reflecting the enhanced NO_x and ammonia sources in this region. OA was ubiquitous across Europe and concentrations generally exceeded sulphate by 30--160%. A factor analysis of the OA burden was performed in order to probe the evolution across this large range of spatial and temporal scales. Two separate Oxygenated Organic Aerosol (OOA) components were identified; one representing an aged-OOA, termed Low Volatility-OOA and another representing fresher-OOA, termed Semi Volatile-OOA on the basis of their mass spectral similarity to previous studies. The factors derived from different flights were not chemically the same but rather reflect the range of OA composition sampled during a particular flight. Significant chemical processing of the OA was observed downwind of major sources in North-Western Europe, with the LV-OOA component becoming increasingly dominant as the distance from source and photochemical processing increased. The measurements suggest that the aging of OA can be viewed as a continuum, with a progression from a less oxidised, semi-volatile component to a highly oxidised, less-volatile component. Substantial amounts of pollution were observed far downwind of continental Europe, with OA and ammonium nitrate being the major constituents of the sub-micron aerosol burden. Such anthropogenically perturbed air masses can significantly perturb regional climate far downwind of major source regions.

Dynamic load balancing in parallel KD-tree k-means

One among the most influential and popular data mining methods is the k-Means algorithm for cluster analysis. Techniques for improving the efficiency of k-Means have been largely explored in two main directions. The amount of computation can be significantly reduced by adopting geometrical constraints and an efficient data structure, notably a multidimensional binary search tree (KD-Tree). These techniques allow to reduce the number of distance computations the algorithm performs at each iteration. A second direction is parallel processing, where data and computation loads are distributed over many processing nodes. However, little work has been done to provide a parallel formulation of the efficient sequential techniques based on KD-Trees. Such approaches are expected to have an irregular distribution of computation load and can suffer from load imbalance. This issue has so far limited the adoption of these efficient k-Means variants in parallel computing environments. In this work, we provide a parallel formulation of the KD-Tree based k-Means algorithm for distributed memory systems and address its load balancing issue. Three solutions have been developed and tested. Two approaches are based on a static partitioning of the data set and a third solution incorporates a dynamic load balancing policy.

Breeding distribution and population decline of globally threatened Grey-necked Picathartes Picathartes oreas in Mbam Minkom Mountain Forest, southern Cameroon

The Grey-necked Picathartes Picathartes oreas, considered 'Vulnerable', is an enigmatic ground-dwelling bird endemic to the central African equatorial rainforest and belongs to a family of only two species. Its distribution extends to the two Endemic Bird Areas within Cameroon (Guinea Congo forest biome and Cameroon mountain arc) and its population is thought to be in decline throughout its range due to increasing habitat fragmentation and disturbance. During March-April 2003 and June and October 2007 we surveyed Grey-necked Picathartes in the north-western region of the Mbam Minkom Mountain Forest. In January-March 2006 we surveyed the entire mountain range and found go breeding and 24 potential breeding sites, mostly located on the western slopes. From the complete survey, we estimated the population at 44 breeding individuals. Populations were highest in the north-west region but had apparently declined from 40 breeding individuals in 2003 to 20 in 2007. This region accounted for 41% of the entire population on the mountain range during the 2006 survey. The Mbam Minkom/Kala Important Bird Area was designated based on the presence of Grey-necked Picathartes but is under high pressure of imminent destruction from agricultural encroachment and illegal timber exploitation. These results have important implications for decision making in delimiting forest boundaries and core areas for protection in the development of management plans. We suggest possible remedial actions, appropriate repeatable methods for future monitoring and opportunities for community involvement in the management and conservation of the site.