Home About us Contact
|
Home About us Contact | ||
|
|
||
Temperature Variance (temperature + variance)
Selected AbstractsAssessment of non-Fickian subgrid-scale models for passive scalar in a channel flowINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 1 2005E. Montreuil Abstract In order to assess new subgrid-scale (SGS) models for a passive scalar, several large eddy simulations of a turbulent channel flow with passive scalar, for various Prandtl numbers ranging from 0.1 to 2.0 are carried out. These models are not based on the classical Fickian approximation and do not necessarily induce an alignment between the SGS heat flux vector and the gradient of the resolved temperature. Five SGS models are investigated on two grids. To validate the simulations, statistical quantities such as mean temperature, temperature variance and turbulent heat flux are compared with available data obtained by direct numerical simulation (DNS). The SGS dissipation is computed for different models in order to analyse its behaviour. The turbulence structures based on instantaneous velocity and temperature are described to study the correlations between these two fields. Among the assessed models, those consisting in Fickian and non-Fickian parts seem to be full of promise. Copyright © 2005 John Wiley & Sons, Ltd. [source] Annual temperature history in Southwest Tibet during the last 400 years recorded by tree ringsINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 7 2010Bao Yang Abstract We present a tree ring-width record from the southern Tibetan Plateau (TP) which spans from 1612,1998 AD (387 years). The series was developed from Tibetan juniper (Juniperus tibetica Kom) growing at sites near the western distribution limit of the species. Two versions of the chronology, a traditionally standardized chronology (TSC) and a regional curve standardization (RCS)chronology were developed. Linear regression models between ring width and mean annual temperature account for 41% (TSC) and 43% (RCS) of the annual (July,June) temperature variance for the period 1957,1998. According to the TSC reconstruction, warm periods occurred during the 1620s, 1650,1675, 1720s, 1740,1790, 1810s, 1850s,1890s, 1935,1950, and 1957,1964 and since 1980. Cold conditions prevailed during the 1630s,1640s, 1680s,1710s, 1730s, 1820,1840s, 1900s,1920s and the 1970s. Within the last 400 years, the late-20th century warming is distinctive but still within the range of natural climatic variability of this region. Comparison of our TSC reconstruction with proxy temperature records from other parts of the TP shows that the cold conditions during the 1730s, 1900s,1920s, and 1970s, and the warm periods during the 1770,1800, 1850s,1890s, 1935,1950, and 1957,1964 and since 1980 were synchronously occurring broad-scale climate anomalies on the whole TP. Differences between the reconstructions are found during the 17th century and around 1760, which were probably caused by local differences in temperature change and different sensitivity in seasonality. The RCS series portrays low-frequency variations such as warm periods during 1620,1640, 1650,1690, 1715,1790, and 1845,1875, and cold conditions during 1640,1650, 1690,1715, and 1875,1995. These long-term trends need to be verified by developing other proxy records that target to capture low-frequency signals in the future. Copyright © 2009 Royal Meteorological Society [source] Signals of anthropogenic influence on European warming as seen in the trend patterns of daily temperature varianceINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 1 2005A. M. G. Klein Tank Abstract Signals of anthropogenic warming over Europe are searched for in the spatial trend patterns for the variance and skewness (expressed by the 10th and 90th percentiles) of the distribution of daily mean temperature. Comparisons are made between these patterns in the station records of the European Climate Assessment dataset for the 1976,99 period, the patterns associated with natural variability in the observations (which were empirically derived from the observations in the 1946,75 period), and the patterns of future warming and natural variability as simulated by the National Center for Atmospheric Research Community Climate System Model in the Challenge ensemble experiment. The results indicate that, on the basis of the patterns for the variance, a distinction can be made between temperature change due to natural variability and temperature change due to changes in external forcing. The observed variance trend patterns for the spring (March,May) and summer (June,August) warming 1976,99 are clearly different from the patterns for the change in variance associated with a warming due to natural variability in the observations. This led us to conclude that a change in an external forcing has to be invoked to explain the observed spring and summer warming. From the evaluation of the greenhouse and natural variability patterns in the climate model simulations, we infer that the observed spring and summer variance trend patterns contain imprints consistent with anthropogenic warming. The analysis of the variance trend patterns for the winter (December,February) season is inconclusive about identifying causes of the observed warming for that season. Unlike the other three seasons, the autumn (September,November) is for Europe a period of cooling in recent decades. The observed variance trend pattern for this season closely resembles the estimated pattern for the change in variance associated with a cooling due to natural variability, indicating that the observed autumn cooling can be ascribed to random weather variations in the period under consideration. Copyright © 2005 Royal Meteorological Society [source] Intra-seasonal variability of wintertime temperature over East AsiaINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 2 2004Dao-Yi Gong Abstract There has been a profound warming over East Asia during the winter months (November through to March) over the past few decades. The goal of this study is to address the question of whether the daily temperature has become more variable in conjunction with this warming by using observed temperature data obtained from 155 Chinese and Korean stations. Prior to the analysis, the annual cycle is removed to obtain daily temperature anomalies for each winter for each station. Results show that the intra-seasonal variance generally decreases, implying that the daily temperatures are becoming less variable. Considering all stations as a whole, the rate of change is ,0.49°C2 per decade (equivalent to ,3.59% per decade). The changes are more robust in the northeastern portion of China. In contrast, there are no dominant trends for the skewness coefficients, except for clear negatively skewed trends in northeastern China. These results are consistent with an increase in the number of extremely cold events. Over the region, the frequency of low-temperature extremes (as low as below minus two standard deviations) increases at a rate of change of 0.26 days per decade, significant at the 95% confidence level. Both the Siberian high and Arctic oscillation (AO) exert a notable influence on the temperature variance. Intra-seasonal variance of the Siberian high and AO are significantly correlated with the temperature variance, whereas the seasonal mean state of the AO affects the temperature variance by modulating the high-frequency components of the Siberian high. The intra-seasonal variance of the Siberian high tends to decline at a rate of change of ,10.7% per decade, significant at the 99% level; meanwhile, the mean wintertime AOs have strengthened in the last few decades. These two climate features together make a considerable contribution to the changes in intra-seasonal temperature variance in East Asia. Copyright © 2004 Royal Meteorological Society [source] Dendroclimatic signals in long tree-ring chronologies from the Himalayas of NepalINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 7 2003Edward R. Cook Abstract We describe the development of a tree-ring chronology network in Nepal that is suitable for reconstructing temperature-related climate forcing over the past few hundred years. The network is composed of 32 tree-ring chronologies and is represented by five indigenous tree species. An empirical orthogonal function analysis of the chronologies over the common interval 1796,92 indicates the existence of coherent large-scale signals among the tree-ring chronologies that are hypothesized to reflect, in part, broad-scale climate forcing related to temperatures. A long monthly temperature record for Kathmandu is developed and used to test this hypothesis. In so doing, significant monthly and seasonal temperature responses are identified that provide guidance for the formal reconstruction of two temperature seasons: February,June (1546,91) and October,February (1605,91). Each reconstruction indicates the occurrence of unusually cold temperatures in 1815,22, which coincides with the eruption of Tambora in Indonesia. A novel method is also used to add probable missing multi-centennial temperature variance to each reconstruction. The resulting ,adjusted' reconstructions strongly reflect patterns of temperature variability associated with Little Ice Age cooling and warming into the 20th century, with the October,February season exhibiting the strongest increase in temperature over the past ,400 years. Only the October,February season shows any evidence for late- 20th century warming, whereas February,June temperatures have actually cooled since 1960 (as with the observational series). Copyright © 2003 Royal Meteorological Society [source] Factors governing the interannual variation and the long-term trend of the 850 hPa temperature over IsraelTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 647 2010H. Saaroni Abstract This study examines the ability of the interannual variability in the occurrence of synoptic types, intensity of large-scale circulations and global temperature to explain that of the 850 hPa temperature in Israel for the summer and the winter. The synoptic factor was represented by 19 types defined by Alpert et al(2004b). For the summer, the deep and the weak Persian Trough explained 35% of the interannual temperature variance. For the winter, the lows to the east and to the north explained 44% of the interannual temperature variance. Two additional factors were incorporated: large-scale circulations, the North Atlantic Oscillation for the summer and the Arctic Oscillation for the winter; and global radiative forcing, represented by the global temperature. Both of them were found to be significant, and the variance explained by all of them is 56% for the summer and 64% for the winter. In the summer the variation is dominated by warm and cool types whereas in the winter the cold systems dominate. The individual contribution of each factor to the long-term temperature trend was estimated. While the global radiative forcing contribution was positive and large in both seasons, the synoptic contribution was positive, four times larger in the summer. The large-scale contribution was negative, three times larger in the winter. The considerable warming in the summer results from a rapid increase in the occurrence of the weak Persian Trough, which is a warm type. The study approach may be useful for predicting future temperature regimes, based on predicted synoptic features in climatic models. Copyright © 2010 Royal Meteorological Society [source] DNS of turbulent heat transfer in a channel flow with a varying streamwise thermal boundary conditionHEAT TRANSFER - ASIAN RESEARCH (FORMERLY HEAT TRANSFER-JAPANESE RESEARCH), Issue 4 2006Yohji Seki Abstract Direct numerical simulation (DNS) was performed for the turbulent heat transfer in a channel flow. In the present study, the effect of the thermal boundary condition was examined. DNS was carried out for varying streamwise thermal boundary conditions (Re, = 180) with Pr = 0.71 to obtain statistical mean temperatures, temperature variances, budget terms, and time scale ratios. The results obtained indicate that the time scale ratio varies along the stream direction. © 2006 Wiley Periodicals, Inc. Heat Trans Asian Res, 35(4): 265,278, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/htj.20114 [source] | |||||||||||||