排序方式： 共有16条查询结果，搜索用时 125 毫秒
1.
Single-Column Model Intercomparison for a Stably Stratified Atmospheric Boundary Layer 总被引：2，自引：15，他引：2
J. Cuxart A. A. M. Holtslag R. J. Beare E. Bazile A. Beljaars A. Cheng L. Conangla M. Ek F. Freedman R. Hamdi A. Kerstein H. Kitagawa G. Lenderink D. Lewellen J. Mailhot T. Mauritsen V. Perov G. Schayes G-J. Steeneveld G. Svensson P. Taylor W. Weng S. Wunsch K-M. Xu 《Boundary-Layer Meteorology》2006,118(2):273-303
The parameterization of the stably stratified atmospheric boundary layer is a difficult issue, having a significant impact on medium-range weather forecasts and climate integrations. To pursue this further, a moderately stratified Arctic case is simulated by nineteen single-column turbulence schemes. Statistics from a large-eddy simulation intercomparison made for the same case by eleven different models are used as a guiding reference. The single-column parameterizations include research and operational schemes from major forecast and climate research centres. Results from first-order schemes, a large number of turbulence kinetic energy closures, and other models were used. There is a large spread in the results; in general, the operational schemes mix over a deeper layer than the research schemes, and the turbulence kinetic energy and other higher-order closures give results closer to the statistics obtained from the large-eddy simulations. The sensitivities of the schemes to the parameters of their turbulence closures are partially explored. 相似文献
2.
Li Xiao-Feng Blenkinsop Stephen Barbero Renaud Yu Jingjing Lewis Elizabeth Lenderink Geert Guerreiro Selma Chan Steven Li Yafei Ali Haider Villalobos Herrera Roberto Kendon Elizabeth Fowler Hayley J. 《Climate Dynamics》2020,54(11):4823-4839
Climate Dynamics - We investigate the global distribution of hourly precipitation and its connections with the El Niño–Southern Oscillation (ENSO) using both satellite precipitation... 相似文献
3.
The Scaling Behaviour of a Turbulent Kinetic Energy Closure Model for Stably Stratified Conditions 总被引：2，自引：1，他引：1
We investigate the scaling behaviour of a turbulent kinetic energy (TKE) closure model for stably stratified conditions. The mixing length scale for stable stratification is proportional to the ratio of the square root of the TKE and the local Brunt–Väisälä frequency, which is a commonly applied formulation. We analyze the scaling behaviour of our model in terms of traditional Monin–Obukov Similarity Theory and local scaling. From the model equations, we derive expressions for the stable limit behaviour of the flux–gradient relations and other scaling quantities. It turns out that the scaling behaviour depends on only a few model parameters and that the results obey local scaling theory. The analytical findings are illustrated with model simulations for the second GABLS intercomparison study. We also investigate solutions for the case in which an empirical correction function is used to express the eddy diffusivity for momentum as a function of the Richardson number (i.e. an increasing turbulent Prandtl number with stability). In this case, it seems that for certain parameter combinations the model cannot generate a steady-state solution. At the same time, its scaling behaviour becomes unrealistic. This shows that the inclusion of empirical correction functions may have large and undesired consequences for the model behaviour. 相似文献
4.
Summary Structures in atmospheric Integrated Water Vapor (IWV) have been studied for the three successive cyclones, Kerstin, Liane
and Monika, which controlled the meteorological conditions in the Baltic Sea catchment region in the period from 28 August
to 5 September 1995 (part of the PIDCAP observational campaign defined within BALTEX). Several model predictions of these
cyclones have been performed with a regional atmospheric general circulation model (RACMO). The impact of two different versions
of the model physics package (standard ECHAM4 and a revised version with modifications in the cloud and turbulence scheme)
has been investigated. Model predicted IWV has been evaluated with GPS station data from several stations in Sweden and Finland.
For the most strongly developed cyclone Monika, the revised scheme generates more pronounced IWV structures, with well defined
bands of high and low values of IWV curving into the center of the cyclone. In particular, the shape of the minima are in
better agreement with the GPS station data, and the consistency between two subsequent model forecasts is also larger with
the revised physics package. For the weaker systems, Kerstin and Liane, results from both model versions are very similar.
Received August 11, 2000 Revised February 13, 2001 相似文献
5.
Climate scenarios for the Netherlands are constructed by combining information from global and regional climate models employing
a simplified, conceptual framework of three sources (levels) of uncertainty impacting on predictions of the local climate.
In this framework, the first level of uncertainty is determined by the global radiation balance, resulting in a range of the
projected changes in the global mean temperature. On the regional (1,000–5,000 km) scale, the response of the atmospheric
circulation determines the second important level of uncertainty. The third level of uncertainty, acting mainly on a local
scale of 10 (and less) to 1,000 km, is related to the small-scale processes, like for example those acting in atmospheric
convection, clouds and atmospheric meso-scale circulations—processes that play an important role in extreme events which are
highly relevant for society. Global climate models (GCMs) are the main tools to quantify the first two levels of uncertainty,
while high resolution regional climate models (RCMs) are more suitable to quantify the third level.
Along these lines, results of an ensemble of RCMs, driven by only two GCM boundaries and therefore spanning only a rather
narrow range in future climate predictions, are rescaled to obtain a broader uncertainty range. The rescaling is done by first
disentangling the climate change response in the RCM simulations into a part related to the circulation, and a residual part
which is related to the global temperature rise. Second, these responses are rescaled using the range of the predictions of
global temperature change and circulation change from five GCMs. These GCMs have been selected on their ability to simulate
the present-day circulation, in particular over Europe. For the seasonal means, the rescaled RCM results obey the range in
the GCM ensemble using a high and low emission scenario. Thus, the rescaled RCM results are consistent with the GCM results
for the means, while adding information on the small scales and the extremes. The method can be interpreted as a combined
statistical–dynamical downscaling approach, with the statistical relations based on regional model output. 相似文献
6.
Aad van Ulden Geert Lenderink Bart van den Hurk Erik van Meijgaard 《Climatic change》2007,81(1):179-192
PRUDENCE simulations of the climate in Central Europe are analysed with respect to mean temperature, mean precipitation and three monthly mean geostrophic circulation indices. The three global models show important circulation biases in the control climate, in particular in the strength of the west-circulations in winter and summer. The nine regional models inherit much of the circulation biases from their host model, especially in winter. In summer, the regional models show a larger spread in circulation statistics, depending on nesting procedures and other model characteristics. Simulated circulation biases appear to have a significant inluence on simulated temperature and precipitation. The PRUDENCE ensemble appears to be biased towards warmer and wetter than observed circulations in winter, and towards warmer and dryer circulations in summer. A2-scenario simulations show important circulation changes, which have a significant impact on changes in the distributions of monthly mean temperature and precipitation. It is likely that interactions between land–surface processes and atmospheric circulation play an important role in the simulated changes in the summer climate in Central Europe. 相似文献
7.
8.
The inter-annual variability in monthly mean summer temperatures derived from nine different regional climate model (RCM) integrations is investigated for both the control climate (1961–1990) and a future climate (2071–2100) based on A2 emissions. All regional model integrations, carried out in the PRUDENCE project, use the same boundaries of the HadAM3H global atmospheric model. Compared to the CRU TS 2.0 observational data set most RCMs (but not all) overpredict the temperature variability significantly in their control simulation. The behaviour of the different regional climate models is analysed in terms of the surface energy budget, and the contributions of the different terms in the surface energy budget to the temperature variability are estimated. This analysis shows a clear relation in the model ensemble between temperature variability and the combined effects of downward long wave, net short wave radiation and evaporation (defined as F). However, it appears that the overestimation of the temperature variability has no unique cause. The effect of short-wave radiation dominates in some RCMs, whereas in others the effect of evaporation dominates. In all models the temperature variability and F increase when imposing future climate boundary conditions, with particularly high values in central Europe. 相似文献
9.
The spread amongst ENSEMBLES regional scenarios: regional climate models, driving general circulation models and interannual variability 总被引：4，自引：1，他引：3
M. Déqué S. Somot E. Sanchez-Gomez C. M. Goodess D. Jacob G. Lenderink O. B. Christensen 《Climate Dynamics》2012,38(5-6):951-964
Various combinations of thirteen regional climate models (RCM) and six general circulation models (GCM) were used in FP6-ENSEMBLES. The response to the SRES-A1B greenhouse gas concentration scenario over Europe, calculated as the difference between the 2021–2050 and the 1961–1990 means can be viewed as an expected value about which various uncertainties exist. Uncertainties are measured here by variance explained for temperature and precipitation changes over eight European sub-areas. Three sources of uncertainty can be evaluated from the ENSEMBLES database. Sampling uncertainty is due to the fact that the model climate is estimated as an average over a finite number of years (30) despite a non-negligible interannual variability. Regional model uncertainty is due to the fact that the RCMs use different techniques to discretize the equations and to represent sub-grid effects. Global model uncertainty is due to the fact that the RCMs have been driven by different GCMs. Two methods are presented to fill the many empty cells of the ENSEMBLES RCM?×?GCM matrix. The first one is based on the same approach as in FP5-PRUDENCE. The second one uses the concept of weather regimes to attempt to separate the contribution of the GCM and the RCM. The variance of the climate response is analyzed with respect to the contribution of the GCM and the RCM. The two filling methods agree that the main contributor to the spread is the choice of the GCM, except for summer precipitation where the choice of the RCM dominates the uncertainty. Of course the implication of the GCM to the spread varies with the region, being maximum in the South-western part of Europe, whereas the continental parts are more sensitive to the choice of the RCM. The third cause of spread is systematically the interannual variability. The total uncertainty about temperature is not large enough to mask the 2021–2050 response which shows a similar pattern to the one obtained for 2071–2100 in PRUDENCE. The uncertainty about precipitation prevents any quantitative assessment on the response at grid point level for the 2021–2050 period. One can however see, as in PRUDENCE, a positive response in winter (more rain in the scenario than in the reference) in northern Europe and a negative summer response in southern Europe. 相似文献
10.
Erik Kjellström Lars Bärring Daniela Jacob Richard Jones Geert Lenderink Christoph Schär 《Climatic change》2007,81(1):249-265
Probability distributions of daily maximum and minimum temperatures in a suite of ten RCMs are investigated for (1) biases compared to observations in the present day climate and (2) climate change signals compared to the simulated present day climate. The simulated inter-model differences and climate changes are also compared to the observed natural variability as reflected in some very long instrumental records. All models have been forced with driving conditions from the same global model and run for both a control period and a future scenario period following the A2 emission scenario from IPCC. We find that the bias in the fifth percentile of daily minimum temperatures in winter and at the 95th percentile of daily maximum temperature during summer is smaller than 3 (±5°C) when averaged over most (all) European sub-regions. The simulated changes in extreme temperatures both in summer and winter are larger than changes in the median for large areas. Differences between models are larger for the extremes than for mean temperatures. A comparison with historical data shows that the spread in model predicted changes in extreme temperatures is larger than the natural variability during the last centuries. 相似文献