Long-term change, interannual and intra-seasonal variability in climate and glacier mass balance in the Central Greater Caucasus, Russia

Long-term trends, interannual and intra-seasonal variability in the mass-balance record from Djankuat glacier, central Greater Caucasus, Russia, are related to local climate change, synoptic and large-scale anomalies in atmospheric circulation. A clear warming signal emerged in the central Greater Caucasus in the early 1990s, leading to a strong increase in ablation. In the absence of a compensating change in winter accumulation, the net mass balance of Djankuat has declined. The highest value of seasonal ablation on record was registered in the summer of 2000. At the beginning of the 21st century these trends reversed. Ablation was below average even in the summer of 2003, which was unusually warm in western Europe. Precipitation and winter accumulation were high, allowing for a partial recovery of net mass balance. The interannual variability in the components of mass balance is weakly related to the North Atlantic Oscillation (NAO) and the Scandinavian teleconnection patterns, but there is a clear link with the large-scale circulation anomalies represented by the Rossby pattern. Five synoptic categories have been identified for the ablation season of 2005, revealing a strong separation between components of radiation budget, air temperature and daily melt. Air temperature is the main control over melt. The highest values of daily ablation are related to the strongly positive NAO which forces high net radiation, and to the warm and moist advection from the Black Sea.

Describing seasonal variability in the distribution of daily effective temperatures for 1985-2009 compared to 1904-1984 for De Bilt, Holland

This paper proposes a method for describing the distribution of observed temperatures on any day of the year such that the distribution and summary statistics of interest derived from the distribution vary smoothly through the year. The method removes the noise inherent in calculating summary statistics directly from the data thus easing comparisons of distributions and summary statistics between different periods. The method is demonstrated using daily effective temperatures (DET) derived from observations of temperature and wind speed at De Bilt, Holland. Distributions and summary statistics are obtained from 1985 to 2009 and compared to the period 1904–1984. A two-stage process first obtains parameters of a theoretical probability distribution, in this case the generalized extreme value (GEV) distribution, which describes the distribution of DET on any day of the year. Second, linear models describe seasonal variation in the parameters. Model predictions provide parameters of the GEV distribution, and therefore summary statistics, that vary smoothly through the year. There is evidence of an increasing mean temperature, a decrease in the variability in temperatures mainly in the winter and more positive skew, more warm days, in the summer. In the winter, the 2% point, the value below which 2% of observations are expected to fall, has risen by 1.2 °C, in the summer the 98% point has risen by 0.8 °C. Medians have risen by 1.1 and 0.9 °C in winter and summer, respectively. The method can be used to describe distributions of future climate projections and other climate variables. Further extensions to the methodology are suggested.

Collaboration of the weather and climate communities to advance subseasonal-to-seasonal prediction

The World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP) have identified collaborations and scientific priorities to accelerate advances in analysis and prediction at subseasonal-to-seasonal time scales, which include i) advancing knowledge of mesoscale–planetary-scale interactions and their prediction; ii) developing high-resolution global–regional climate simulations, with advanced representation of physical processes, to improve the predictive skill of subseasonal and seasonal variability of high-impact events, such as seasonal droughts and floods, blocking, and tropical and extratropical cyclones; iii) contributing to the improvement of data assimilation methods for monitoring and predicting used in coupled ocean–atmosphere–land and Earth system models; and iv) developing and transferring diagnostic and prognostic information tailored to socioeconomic decision making. The document puts forward specific underpinning research, linkage, and requirements necessary to achieve the goals of the proposed collaboration.

West African storm tracks and their relationship to Atlantic tropical cyclones

The automatic tracking technique used by Thorncroft and Hodges (2001) has been used to identify coherent vorticity structures at 850hPa over West Africa and the tropical Atlantic in the ECMWF 40-year reanalysis. The presence of two dominant source regions, north and south of 15ºN over West Africa, for storm tracks over the Atlantic was confirmed. Results show that the southern storm track provides most of the storms that reach the main development region where most tropical cyclones develop. There exists marked seasonal variability in location and intensity of the storms leaving the West African coast, which may influence the likelihood of downstream intensification and longevity. There exists considerable year-to-year variability in the number of West African storm tracks, both in numbers over the land and continuing out over the tropical Atlantic Ocean. While the low-frequency variability is well correlated with Atlantic tropical cyclone activity, West African rainfall and SSTs, the interannual variability is found to be uncorrelated with these. In contrast, variance of the 2-6-day-filtered meridional wind, which provides a synoptic-scale measure of African Easterly Wave activity, shows a significant, positive correlation with tropical cyclone activity at interannual timescales.

Evaluation of reanalysis rainfall estimates over Ethiopia

There is a pressing need for good rainfall data for the African continent both for humanitarian and climatological purposes. Given the sparseness of ground-based observations, one source of rainfall information is Numerical Weather Prediction (NWP) model outputs. The aim of this article is to investigate the quality of two NWP products using Ethiopia as a test case. The two products evaluated are the ERA-40 and NCEP reanalysis rainfall products. Spatial, seasonal and interannual variability of rainfall have been evaluated for Kiremt (JJAS) and Belg (FMAM) seasons at a spatial scale that reflects the local variability of the rainfall climate using a method which makes optimum use of sparse gauge validation data. We found that the spatial pattern of the rainfall climatology is captured well by both models especially for the main rainy season Kiremt. However, both models tend to overestimate the mean rainfall in the northwest, west and central regions but underestimate in the south and east. The overestimation is greater for NCEP in Belg season and greater for ERA-40 in Kiremt Season. ERA-40 captures the annual cycle over most of the country better than NCEP, but strongly exaggerates the Kiremt peak in the northwest and west. The overestimation in Kiremt appears to have been reduced since the assimilation of satellite data increased around 1990. For both models the interannual variability is less well captured than the spatial and seasonal variability. Copyright © 2008 Royal Meteorological Society

Modelling seasonally varying data: A case study for sudden infant death syndrome (SIDS)

Many time series are measured monthly, either as averages or totals, and such data often exhibit seasonal variability-the values of the series are consistently larger for some months of the year than for others. A typical series of this type is the number of deaths each month attributed to SIDS (Sudden Infant Death Syndrome). Seasonality can be modelled in a number of ways. This paper describes and discusses various methods for modelling seasonality in SIDS data, though much of the discussion is relevant to other seasonally varying data. There are two main approaches, either fitting a circular probability distribution to the data, or using regression-based techniques to model the mean seasonal behaviour. Both are discussed in this paper.

Impact of hydrographic data assimilation on the modelled Atlantic meridional overturning circulation

Here we make an initial step toward the development of an ocean assimilation system that can constrain the modelled Atlantic Meridional Overturning Circulation (AMOC) to support climate predictions. A detailed comparison is presented of 1° and 1/4° resolution global model simulations with and without sequential data assimilation, to the observations and transport estimates from the RAPID mooring array across 26.5° N in the Atlantic. Comparisons of modelled water properties with the observations from the merged RAPID boundary arrays demonstrate the ability of in situ data assimilation to accurately constrain the east-west density gradient between these mooring arrays. However, the presence of an unconstrained "western boundary wedge" between Abaco Island and the RAPID mooring site WB2 (16 km offshore) leads to the intensification of an erroneous southwards flow in this region when in situ data are assimilated. The result is an overly intense southward upper mid-ocean transport (0–1100 m) as compared to the estimates derived from the RAPID array. Correction of upper layer zonal density gradients is found to compensate mostly for a weak subtropical gyre circulation in the free model run (i.e. with no assimilation). Despite the important changes to the density structure and transports in the upper layer imposed by the assimilation, very little change is found in the amplitude and sub-seasonal variability of the AMOC. This shows that assimilation of upper layer density information projects mainly on the gyre circulation with little effect on the AMOC at 26° N due to the absence of corrections to density gradients below 2000 m (the maximum depth of Argo). The sensitivity to initial conditions was explored through two additional experiments using a climatological initial condition. These experiments showed that the weak bias in gyre intensity in the control simulation (without data assimilation) develops over a period of about 6 months, but does so independently from the overturning, with no change to the AMOC. However, differences in the properties and volume transport of North Atlantic Deep Water (NADW) persisted throughout the 3 year simulations resulting in a difference of 3 Sv in AMOC intensity. The persistence of these dense water anomalies and their influence on the AMOC is promising for the development of decadal forecasting capabilities. The results suggest that the deeper waters must be accurately reproduced in order to constrain the AMOC.

The effect of environment on endosperm cell-wall development in Triticum aestivum during grain filling: an infrared spectroscopic imaging study

One of the major factors contributing to the failure of new wheat varieties is seasonal variability in end-use quality. Consequently, it is important to produce varieties which are robust and stable over a range of environmental conditions. Recently developed sample preparation methods have allowed the application of FT-IR spectroscopic imaging methods to the analysis of wheat endosperm cell wall composition, allowing the spatial distribution of structural components to be determined without the limitations of conventional chemical analysis. The advantages of the methods, described in this paper, are that they determine the composition of endosperm cell walls in situ and with minimal modification during preparation. Two bread-making wheat cultivars, Spark and Rialto, were selected to determine the impact of environmental conditions on the cell-wall composition of the starchy endosperm of the developing and mature grain, focusing on the period of grain filling (starting at about 14 days after anthesis). Studies carried out over two successive seasons show that the structure of the arabinoxylans in the endosperm cell walls changes from a highly branched form to a less branched form. Furthermore, during development the rate of restructuring was faster when the plants were grown at higher temperature with restricted water availability from 14 days after anthesis with differences in the rate of restructuring occurring between the two cultivars.

Controls of carbon dioxide concentrations and fluxes above central London

Eddy-covariance measurements of carbon dioxide fluxes were taken semi-continuously between October 2006 and May 2008 at 190 m height in central London (UK) to quantify emissions and study their controls. Inner London, with a population of 8.2 million (~5000 inhabitants per km2) is heavily built up with 8% vegetation cover within the central boroughs. CO2 emissions were found to be mainly controlled by fossil fuel combustion (e.g. traffic, commercial and domestic heating). The measurement period allowed investigation of both diurnal patterns and seasonal trends. Diurnal averages of CO2 fluxes were found to be highly correlated to traffic. However changes in heating-related natural gas consumption and, to a lesser extent, photosynthetic activity that controlled the seasonal variability. Despite measurements being taken at ca. 22 times the mean building height, coupling with street level was adequate, especially during daytime. Night-time saw a higher occurrence of stable or neutral stratification, especially in autumn and winter, which resulted in data loss in post-processing. No significant difference was found between the annual estimate of net exchange of CO2 for the expected measurement footprint and the values derived from the National Atmospheric Emissions Inventory (NAEI), with daytime fluxes differing by only 3%. This agreement with NAEI data also supported the use of the simple flux footprint model which was applied to the London site; this also suggests that individual roughness elements did not significantly affect the measurements due to the large ratio of measurement height to mean building height.

The impact of finer-resolution air-sea coupling on the intraseasonal oscillation of the Indian monsoon

The new HadKPP atmosphere–ocean coupled model is described and then used to determine the effects of sub-daily air–sea coupling and fine near-surface ocean vertical resolution on the representation of the Northern Hemisphere summer intra-seasonal oscillation. HadKPP comprises the Hadley Centre atmospheric model coupled to the K Profile Parameterization ocean-boundary-layer model. Four 30-member ensembles were performed that varied in oceanic vertical resolution between 1 m and 10 m and in coupling frequency between 3 h and 24 h. The 10 m, 24 h ensemble exhibited roughly 60% of the observed 30–50 day variability in sea-surface temperatures and rainfall and very weak northward propagation. Enhancing either only the vertical resolution or only the coupling frequency produced modest improvements in variability and only a standing intra-seasonal oscillation. Only the 1 m, 3 h configuration generated organized, northward-propagating convection similar to observations. Sub-daily surface forcing produced stronger upper-ocean temperature anomalies in quadrature with anomalous convection, which likely affected lower-atmospheric stability ahead of the convection, causing propagation. Well-resolved air–sea coupling did not improve the eastward propagation of the boreal summer intra-seasonal oscillation in this model. Upper-ocean vertical mixing and diurnal variability in coupled models must be improved to accurately resolve and simulate tropical sub-seasonal variability. In HadKPP, the mere presence of air–sea coupling was not sufficient to generate an intra-seasonal oscillation resembling observations.

Retrieval of mesospheric electron densities using an optimal estimation inverse method

We present a new method to determine mesospheric electron densities from partially reflected medium frequency radar pulses. The technique uses an optimal estimation inverse method and retrieves both an electron density profile and a gradient electron density profile. As well as accounting for the absorption of the two magnetoionic modes formed by ionospheric birefringence of each radar pulse, the forward model of the retrieval parameterises possible Fresnel scatter of each mode by fine electronic structure, phase changes of each mode due to Faraday rotation and the dependence of the amplitudes of the backscattered modes upon pulse width. Validation results indicate that known profiles can be retrieved and that χ2 tests upon retrieval parameters satisfy validity criteria. Application to measurements shows that retrieved electron density profiles are consistent with accepted ideas about seasonal variability of electron densities and their dependence upon nitric oxide production and transport.

Development and validation of a qPCR-based method for quantifying Shiga toxin-encoding and other lambdoid bacteriophages

P>To address whether seasonal variability exists among Shiga toxin-encoding bacteriophage (Stx phage) numbers on a cattle farm, conventional plaque assay was performed on water samples collected over a 17 month period. Distinct seasonal variation in bacteriophage numbers was evident, peaking between June and August. Removal of cattle from the pasture precipitated a reduction in bacteriophage numbers, and during the winter months, no bacteriophage infecting Escherichia coli were detected, a surprising occurrence considering that 1031 tailed-bacteriophages are estimated to populate the globe. To address this discrepancy a culture-independent method based on quantitative PCR was developed. Primers targeting the Q gene and stx genes were designed that accurately and discriminately quantified artificial mixed lambdoid bacteriophage populations. Application of these primer sets to water samples possessing no detectable phages by plaque assay, demonstrated that the number of lambdoid bacteriophage ranged from 4.7 x 104 to 6.5 x 106 ml-1, with one in 103 free lambdoid bacteriophages carrying a Shiga toxin operon (stx). Specific molecular biological tools and discriminatory gene targets have enabled virus populations in the natural environment to be enumerated and similar strategies could replace existing propagation-dependent techniques, which grossly underestimate the abundance of viral entities.

Will greenhouse gas-induced warming over the next 50 years lead to higher frequency and greater intensity of hurricanes?

The use of a high resolution atmospheric model at T106 resolution, for studying the influence of greenhouse warming on tropical storm climatology, is investigated. The same method for identifying the storms has been used as in a previous study by Bengtsson et al. The sea surface temperature anomalies have been taken from a previous transient climate change experiment, obtained with a low resolution ocean-atmosphere coupled model. The global distribution of the storms, at the time when the CO2 concentration in the atmosphere had doubled, agrees in geographical position and seasonal variability with that of the present climate, but the number of storms is significantly reduced, particularly at the Southern Hemisphere. The main reason to this, appear to be connected to changes in the large scale circulation, such as a weaker Hadley circulation and stronger upper air westerlies. The low level vorticity in the hurricane genesis regions is generally reduced compared to the present climate, while the vertical tropospheric wind shear is somewhat increased. Most tropical storm regions indicate reduced surface windspeeds and a slightly weaker hydrological cycle.

Wave activity in the tropical tropopause layer in seven reanalysis and four chemistry climate model data sets

Sub-seasonal variability including equatorial waves significantly influence the dehydration and transport processes in the tropical tropopause layer (TTL). This study investigates the wave activity in the TTL in 7 reanalysis data sets (RAs; NCEP1, NCEP2, ERA40, ERA-Interim, JRA25, MERRA, and CFSR) and 4 chemistry climate models (CCMs; CCSRNIES, CMAM, MRI, and WACCM) using the zonal wave number-frequency spectral analysis method with equatorially symmetric-antisymmetric decomposition. Analyses are made for temperature and horizontal winds at 100 hPa in the RAs and CCMs and for outgoing longwave radiation (OLR), which is a proxy for convective activity that generates tropopause-level disturbances, in satellite data and the CCMs. Particular focus is placed on equatorial Kelvin waves, mixed Rossby-gravity (MRG) waves, and the Madden-Julian Oscillation (MJO). The wave activity is defined as the variance, i.e., the power spectral density integrated in a particular zonal wave number-frequency region. It is found that the TTL wave activities show significant difference among the RAs, ranging from ∼0.7 (for NCEP1 and NCEP2) to ∼1.4 (for ERA-Interim, MERRA, and CFSR) with respect to the averages from the RAs. The TTL activities in the CCMs lie generally within the range of those in the RAs, with a few exceptions. However, the spectral features in OLR for all the CCMs are very different from those in the observations, and the OLR wave activities are too low for CCSRNIES, CMAM, and MRI. It is concluded that the broad range of wave activity found in the different RAs decreases our confidence in their validity and in particular their value for validation of CCM performance in the TTL, thereby limiting our quantitative understanding of the dehydration and transport processes in the TTL.