Climatic variations of general atmospheric circulation, precipitation and river flow of the territory of Kazakhstan

Methods of calculating the basic hydrological characteristics of a water resource assessment, as well as the planning and management of their long-term use are based upon the concept of stationarity of long-term flow fluctuations. However, data of researches by hydrologists and climatologists clearly indicate that there are long-period changes in the characteristics of precipitation and river flow. This article discusses the variations of annual precipitation and river flow in the Ishim River Basin in Kazakhstan, based on the W, C and E classification developed by G.Y. Vangengeim who analyzed the long-term variability of anomalies by the number of days with some form of atmospheric circulation. From this study, the largest anomaly of the macro-circulation processes was revealed, and a comparative analysis of the number of days with various forms of atmospheric circulation and precipitation anomalies was made. It was demonstrated that the nature of atmospheric circulation depends on the distribution of precipitation; however, precipitation is also highly dependent on local physiographic conditions. The analysis of anomalous precipitation during the maximum number of days of positive anomalies with various forms of atmospheric circulation was also carried out. This study presents some results from the preliminary analysis of annual river flow linked with forms of atmospheric circulation.     

An Intercomparison of Large-Eddy Simulations of the Stable Boundary Layer

Results are presented from the first intercomparison of large-eddy simulation (LES) models for the stable boundary layer (SBL), as part of the Global Energy and Water Cycle Experiment Atmospheric Boundary Layer Study initiative. A moderately stable case is used, based on Arctic observations. All models produce successful simulations, in as much as they generate resolved turbulence and reflect many of the results from local scaling theory and observations. Simulations performed at 1-m and 2-m resolution show only small changes in the mean profiles compared to coarser resolutions. Also, sensitivity to subgrid models for individual models highlights their importance in SBL simulation at moderate resolution (6.25 m). Stability functions are derived from the LES using typical mixing lengths used in numerical weather prediction (NWP) and climate models. The functions have smaller values than those used in NWP. There is also support for the use of K-profile similarity in parametrizations. Thus, the results provide improved understanding and motivate future developments of the parametrization of the SBL.     

Localised Uniform Conditioning (LUC): A New Approach for Direct Modelling of Small Blocks

Recoverable mineralisation at a given mining selectivity is traditionally modelled from sparse data grids by non-linear geostatistical techniques such as Uniform Conditioning. This method estimates the tonnage and grade of mineralisation which can be extracted as small selective minable blocks from large blocks (panels), whose grade is modelled by Ordinary Kriging. Uniform Conditioning technique estimates the proportions of recoverable mineralisation in each panel without specifying the actual locations of the economically extractable blocks. This inability to predict a spatial location of the recoverable mineralisation is a major disadvantage of the conventional Uniform Conditioning method. A new approach, called Localised Uniform Conditioning, has been developed to overcome this limitation. This method applies the grade–tonnage relationships modelled by the Uniform Conditioning technique to the spatial grade distribution patterns approximated by direct kriging of the small blocks from the sparse data grid. This approach estimates localised selective mining units grades conforming to the proper grade–tonnage curves obtained by the Uniform Conditioning method as well as maintaining the relative spatial grade distribution pattern indicated by the directly kriged small block grades. The advantage of this approach is essentially dependent upon the data available for ranking the small blocks within a panel in increasing order of their grade. Ordinary Kriging of the small blocks can be used for their ranking providing the kriged estimates produce a meaningful indication of the relative grade pattern. Where the data is sparse and not close to a panel, or their distribution is characterised by a strong short-range variability, the advantages of using the Localised Uniform Conditioning approach are more limited.     

Extension of sea surface temperature unpredictability

Ocean Dynamics - The sea surface temperature (SST) variability is clearly affected by global climate patterns, which involve large-scale ocean-atmosphere fluctuations similar to the El...     

Simulation of Indian summer monsoon intraseasonal oscillations in a superparameterized coupled climate model: need to improve the embedded cloud resolving model

The characteristic features of Indian summer monsoon (ISM) and monsoon intraseasonal oscillations (MISO) are analyzed in the 25 year simulation by the superparameterized Community Climate System Model (SP-CCSM). The observations indicate the low frequency oscillation with a period of 30–60 day to have the highest power with a dominant northward propagation, while the faster mode of MISO with a period of 10–20 day shows a stationary pattern with no northward propagation. SP-CCSM simulates two dominant quasi-periodic oscillations with periods 15–30 day and 40–70 day indicating a systematic low frequency bias in simulating the observed modes. Further, contrary to the observation, the SP-CCSM 15–30 day mode has a significant northward propagation; while the 40–70 day mode does not show prominent northward propagation. The inability of the SP-CCSM to reproduce the observed modes correctly is shown to be linked with inability of the cloud resolving model (CRM) to reproduce the characteristic heating associated with the barotropic and baroclinic vertical structures of the high-frequency and the low-frequency modes. It appears that the superparameterization in the General Circulation Model (GCM) certainly improves seasonal mean model bias significantly. There is a need to improve the CRM through which the barotropic and baroclinic modes are simulated with proper space and time distribution.     

Effects of model resolution and subgrid-scale physics on the simulation of precipitation in the continental United States

We analyze simulations of the global climate performed at a range of spatial resolutions to assess the effects of horizontal spatial resolution on the ability to simulate precipitation in the continental United States. The model investigated is the CCM3 general circulation model. We also preliminarily assess the effect of replacing cloud and convective parameterizations in a coarse-resolution (T42) model with an embedded cloud-system resolving model (CSRM). We examine both spatial patterns of seasonal-mean precipitation and daily time scale temporal variability of precipitation in the continental United States. For DJF and SON, high-resolution simulations produce spatial patterns of seasonal-mean precipitation that agree more closely with observed precipitation patterns than do results from the same model (CCM3) at coarse resolution. However, in JJA and MAM, there is little improvement in spatial patterns of seasonal-mean precipitation with increasing resolution, particularly in the southeast USA. This is because of the dominance of convective (i.e., parameterized) precipitation in these two seasons. We further find that higher-resolution simulations have more realistic daily precipitation statistics. In particular, the well-known tendency at coarse resolution to have too many days with weak precipitation and not enough intense precipitation is partially eliminated in higher-resolution simulations. However, even at the highest resolution examined here (T239), the simulated intensity of the mean and of high-percentile daily precipitation amounts is too low. This is especially true in the southeast USA, where the most extreme events occur. A new GCM, in which a cloud-resolving model (CSRM) is embedded in each grid cell and replaces convective and stratiform cloud parameterizations, solves this problem, and actually produces too much precipitation in the form of extreme events. However, in contrast to high-resolution versions of CCM3, this model produces little improvement in spatial patterns of seasonal-mean precipitation compared to models at the same resolution using traditional parameterizations.     

FUV and NIR size of the HI selected low surface brightness galaxies

How low surface brightness galaxies(LSBGs)form stars and assemble stellar mass is one of the most important questions related to understanding the LSBG population.We select a sample of 381 HI bright LSBGs with both far ultraviolet(FUV)and near infrared(NIR)observations to investigate the star formation rate(SFR)and stellar mass scales,and the growth mode.We measure the FUV and NIR radii of our sample,which represent the star-forming and stellar mass distribution scales respectively.We also compare the FUV and H band radius-stellar mass relation with archival data,to identify the SFR and stellar mass structure difference between the LSBG population and other galaxies.Since galaxy HI mass has a tight correlation with the HI radius,we can also compare the HI and FUV radii to understand the distribution of HI gas and star formation activities.Our results show that most of the HI selected LSBGs have extended star formation structure.The stellar mass distribution of LSBGs may have a similar structure to disk galaxies at the same stellar mass bins,but the star-forming activity of LSBGs happens at a larger radius than the high surface density galaxies,which may help to identify the LSBG sample from the wide-field deep u band image survey.The HI is also distributed at larger radii,implying a steeper(or not)Kennicutt-Schmidt relation for LSBGs.