Annual precipitation cycle in regional climate models: the influence of horizontal resolution

The influence of increased horizontal resolution on regional climate models simulations of 1961–1990 period was investigated with a focus on precipitation. The main attention was paid to the annual cycle of precipitation described by a special characteristic, precipitation half-time. Two models (RegCM3 and ALADIN-CLIMATE/CZ), both of them in two horizontal resolutions (25 and 10 km), were used. An evaluation of model simulations with 25 km resolution on the European domain is presented as well as a more detailed evaluation of both 25 and 10 km versions on the area of the Czech Republic. Generally, the effects of increased horizontal resolution vary with climate model and evaluated characteristic. For the precipitation amount and the dependence of precipitation amount on altitude, the increase in horizontal resolution decreases the accuracy of results in both models. For the simulation of annual precipitation cycle and the precipitation half-time, RegCM3 results improved with the increased horizontal resolution, whereas ALADIN-CLIMATE/CZ results worsened.     

Probabilistic prediction of Indian summer monsoon rainfall using global climate models

Probabilistic seasonal predictions of rainfall that incorporate proper uncertainties are essential for climate risk management. In this study, three different multi-model ensemble (MME) approaches are used to generate probabilistic seasonal hindcasts of the Indian summer monsoon rainfall based on a set of eight global climate models for the 1982–2009 period. The three MME approaches differ in their calculation of spread of the forecast distribution, treated as a Gaussian, while all three use the simple multi-model subdivision average to define the mean of the forecast distribution. The first two approaches use the within-ensemble spread and error residuals of ensemble mean hindcasts, respectively, to compute the variance of the forecast distribution. The third approach makes use of the correlation between the ensemble mean hindcasts and the observations to define the spread using a signal-to-noise ratio. Hindcasts are verified against high-resolution gridded rainfall data from India Meteorological Department in terms of meteorological subdivision spatial averages. The use of correlation for calculating the spread provides better skill than the other two methods in terms of rank probability skill score. In order to further improve the skill, an additional method has been used to generate multi-model probabilistic predictions based on simple averaging of tercile category probabilities from individual models. It is also noted that when such a method is used, skill of probabilistic forecasts is improved as compared with using the multi-model ensemble mean to define the mean of the forecast distribution and then probabilities are estimated. However, skill of the probabilistic predictions of the Indian monsoon rainfall is too low.     

Zonal winds and southeast Australian rainfall in global and regional climate models

Southeast Australia is a region of high rainfall variability related to major climate drivers, with a long-term declining trend in cool-season rainfall. Projections of future rainfall trends are uncertain in this region, despite projected southward shifts in the subtropical ridge and mid-latitude westerlies. This appears to be related to a poor representation of the spatial relationships between rainfall variability and zonal wind patterns across southeast Australia in the latest Coupled Model Intercomparison Project ensemble, particularly in the areas where weather systems embedded in the mid-latitude westerlies are the main source of cool-season rainfall. Downscaling with regional climate models offers improvements in the mean rainfall climatology, and shows some ability to correct for poor modelled relationships between rainfall and zonal winds along the east coast of Australia. However, it provides only minor improvements to these relationships in southeast Australia, despite the improved representation of topographic features. These results suggest that both global and regional climate models may fail to translate projected circulation changes into their likely rainfall impacts in southeast Australia.     

Fast versus slow response in climate change: implications for the global hydrological cycle

Recent studies have shown that changes in global mean precipitation are larger for solar forcing than for CO₂ forcing of similar magnitude. In this paper, we use an atmospheric general circulation model to show that the differences originate from differing fast responses of the climate system. We estimate the adjusted radiative forcing and fast response using Hansen’s “fixed-SST forcing” method. Total climate system response is calculated using mixed layer simulations using the same model. Our analysis shows that the fast response is almost 40% of the total response for few key variables like precipitation and evaporation. We further demonstrate that the hydrologic sensitivity, defined as the change in global mean precipitation per unit warming, is the same for the two forcings when the fast responses are excluded from the definition of hydrologic sensitivity, suggesting that the slow response (feedback) of the hydrological cycle is independent of the forcing mechanism. Based on our results, we recommend that the fast and slow response be compared separately in multi-model intercomparisons to discover and understand robust responses in hydrologic cycle. The significance of this study to geoengineering is discussed.     

Global and regional coupled climate sensitivity to the parameterization of rainfall interception

A coupled land?Catmosphere model is used to explore the impact of seven commonly used canopy rainfall interception schemes on the simulated climate. Multiple 30-year simulations are conducted for each of the seven methods and results are analyzed in terms of the mean climatology and the probability density functions (PDFs) of key variables based on daily data. Results show that the method used for canopy interception strongly affects how rainfall is partitioned between canopy evaporation and throughfall. However, the impact on total evaporation is much smaller, and the impact on rainfall and air temperature is negligible. Similarly, the PDFs of canopy evaporation and transpiration for six selected regions are strongly affected by the method used for canopy interception, but the impact on total evaporation, temperature and precipitation is negligible. Our results show that the parameterization of rainfall interception is important to the surface hydrometeorology, but the seven interception parameterizations examined here do not cause a statistically significant impact on the climate of the coupled model. We suggest that broad scale climatological differences between coupled climate models are not likely the result of how interception is parameterized. This conclusion is inconsistent with inferences derived from earlier uncoupled simulations, or simulations using very simplified climate models.     

中国暖季短时强降水分布和日变化特征及其与中尺度对流系统日变化关系分析

基于湖北省地面加密自动站2010-2015年的分钟雨量数据,利用滑动累积的小时雨量识别短时强降水事件,对比分析了鄂东南、鄂东北、武汉、江汉平原、鄂西北和鄂西南等六个预报区域的短时强降水日数、频次的时空分布特征,并对极端短时强降水进行初步探讨。结果表明：（1）短时强降水年均日数有明显的局地特征,强降水中心主要集中在鄂东南、鄂东北、武汉、鄂西南等区域;月变化呈显著单峰型特征,峰值在7月。（2）短时强降水的频次分布也具有明显的月变化和日变化特征。从月变化上看,江汉平原、鄂东南呈双月峰值分布（6月和7月）,武汉和鄂东北地区的主峰在7月、次峰在6月,鄂西北和鄂西南地区的主峰在7月、次峰在8月;从日变化上看,鄂西北（04时和19时,北京时,下同）、鄂西南（01时和17时）、鄂东北（08时和16时）、鄂东南（07时和16时）呈双峰分布,江汉平原呈单峰分布（07时）,武汉呈多峰分布（07-14时）。（3）极端短时强降水阈值范围为53~124.8 mm,具有夜发性特征,峰值在午后15时到凌晨01时,空间分布较为零散,相对而言,武汉地区观测到极端短时强降水的可能性最大,鄂西南和鄂西北最小。

     

The dynamics of uncertainty: application to parameterization constants in climate models

Climate models, ranging from statistical-dynamical to the explicit-dynamical, contain a range of uncertainties related to the parameterization constants associated with the various forcing terms used therein. Quantifying the impacts of such uncertainties has heretofore received little attention. The impact of this aspect of the dynamics of uncertainty was revealed in a series of dynamical systems of increasing complexity. The inevitability of climate drift was discussed, with one aspect being revealed as the non-Gaussian nature of most forcing terms. For those dynamical systems which are chaotic in nature, it was shown how stochastic dynamic equations can be used to describe the uncertainty, even with uncertainty in the critical forcing terms. The possibility of climate transitions driven by stochastic forcing occurring on much faster time scales (i.e., weather disturbances) has been shown by numerous authors. The caution shown here is that even very small uncertainty in a forcing term occurring on the slow climate time scales can lead to such transitions more easily. Conversely, a deterministic parameterization on the slowly varying time scale may be just slightly incorrect in a particular model formulation and lead to the wrong climatic state. In view of such concerns, the framework for attacking the difficult nonlinear problem of uncertain parameterization constants in complex GCMs is outlined.The National Center for Atmospheric Research is sponsored by the National Science Foundation     

不同分辨率下全球气候模式的集合结果检验

利用参与IPCC AR4的25个全球气候模式的模拟结果与观测资料,通过分类集合检验气候模式对东亚大陆气温和降水的模拟能力.结果表明:(1)高、中、低分辨率以及所有模式的集合(分别记为Ⅰ、Ⅱ、Ⅲ、Ⅳ类)结果均能较好地再现1901-1999年温度的增温趋势,其中Ⅱ类的线性趋势与观测值最为接近,但年际变率均小于观测值;(2)Ⅰ、Ⅱ、Ⅲ、Ⅳ类均能很好地模拟出气候态温度的月变化特征以及空间分布型,但模拟值偏小,其中Ⅰ类的冷偏差最小;(3)对于降水的时间演变特征,模拟效果明显偏差、不确定性显著;(4)4种集合方式均能较好模拟出气候态降水的空间分布型,但模拟值普遍偏高,其中Ⅰ类的误差最小.可见,在温度和降水的时间变化方面,高分辨率的集合结果并没有体现出相应的优势,但在空间分布上模拟效果明显要好于其他3种方式.     

Present-day and future Amazonian precipitation in global climate models: CMIP5 versus CMIP3

The present study aims at evaluating and comparing precipitation over the Amazon in two sets of historical and future climate simulations based on phase 3 (CMIP3) and 5 (CMIP5) of the Coupled Model Intercomparison Project. Thirteen models have been selected in order to discuss (1) potential improvements in the simulation of present-day climate and (2) the potential reduction in the uncertainties of the model response to increasing concentrations of greenhouse gases. While several features of present-day precipitation—including annual cycle, spatial distribution and co variability with tropical sea surface temperature (SST)—have been improved, strong uncertainties remain in the climate projections. A closer comparison between CMIP5 and CMIP3 highlights a weaker consensus on increased precipitation during the wet season, but a stronger consensus on a drying and lengthening of the dry season. The latter response is related to a northward shift of the boreal summer intertropical convergence zone in CMIP5, in line with a more asymmetric warming between the northern and southern hemispheres. The large uncertainties that persist in the rainfall response arise from contrasted anomalies in both moisture convergence and evapotranspiration. They might be related to the diverse response of tropical SST and ENSO (El Niño Southern Oscillation) variability, as well as to spurious behaviours among the models that show the most extreme response. Model improvements of present-day climate do not necessarily translate into more reliable projections and further efforts are needed for constraining the pattern of the SST response and the soil moisture feedback in global climate scenarios.     

Seasonal variation of the diurnal cycle of rainfall in the eastern equatorial Indian Ocean

Summary The diurnal cycle of rainfall over the eastern equatorial Indian Ocean was studied for the period 23^rd October 2001 to 31^st October 2003 using hourly data from the Triton buoy positioned at 1.5° S and 90° E. An analysis of the active and weak spells of rainfall for different seasons revealed peaks in the late evening hours in Winter, Summer and Fall and in early morning hours (in Spring) in 2002. The active spell of rainfall peaked in the afternoon hours, during Winter, Spring and Summer in 2003, which agrees with the previous results of Janowiak et al. (1994). An analysis of rainfall events showed that Fall 2002 had a maximum number of rainfall events (90) and minimum (60) were observed in Spring 2003. Further it was found that the majority of rain events (>60%) were less than 3 hours in duration throughout the study period. The longer duration rainfall events (i.e. rain events greater than 6 hour duration) contributed significantly to Spring 2002 (20% of the total rainfall) and Winter 2003 (21% of the total rainfall). Harmonic analysis of the hourly rainfall data for different seasons revealed that diurnal harmonic explains more than 80% of the variance for all seasons. Furthermore, the diurnal harmonic has a maximum amplitude for all seasons except summer, where the semidiurnal and six hourly harmonics are significant.     

Intercomparison and validation of snow albedo parameterization schemes in climate models

Snow albedo is known to be crucial for heat exchange at high latitudes and high altitudes, and is also an important parameter in General Circulation Models (GCMs) because of its strong positive feedback properties. In this study, seven GCM snow albedo schemes and a multiple linear regression model were intercompared and validated against 59 years of in situ data from Svalbard, the French Alps and six stations in the former Soviet Union. For each site, the significant meteorological parameters for modeling the snow albedo were identified by constructing the 95% confidence intervals. The significant parameters were found to be: temperature, snow depth, positive degree day and a dummy of snow depth, and the multiple linear regression model was constructed to include these. Overall, the intercomparison showed that the modeled snow albedo varied more than the observed albedo for all models, and that the albedo was often underestimated. In addition, for several of the models, the snow albedo decreased at a faster rate or by a greater magnitude during the winter snow metamorphosis than the observed albedo. Both the temperature dependent schemes and the prognostic schemes showed shortcomings.     

Improving a subgrid runoff parameterization scheme for climate models by the use of high resolution data derived from satellite observations

In this study it is shown that the availability of a very high resolution dataset of land surface characteristics leads to the improvement of a surface runoff parameterization scheme. The improved parameterization scheme was developed for application in global and regional climate models and is a further development of the Arno scheme that is widely used in climate models. Here, surface runoff is computed as infiltration excess from a "bucket" type reservoir which takes the subgrid variability of soil saturation within a model gridbox into account. Instead of prescribing a distribution of subgrid scale soil water capacities as in the original Arno scheme, the array of high resolution soil water capacities taken from a global 1 km dataset of land surface parameters is used to obtain individual fractional saturation curves for each model gridbox. From each saturation curve, the three parameters (a shape parameter describing the shape of the subgrid distribution of soil water capacities, subgrid minimum and maximum soil water capacity) required in the modified formulation of the scheme are derived via optimization. As in the original Arno scheme applied in the ECHAM general circulation model and the REMO regional climate model, topography variations will influence the distribution of saturated subgrid areas within a model gridbox. At most gridboxes the net effect of these changes is such that more runoff is produced for high soil water contents and less runoff for low soil water contents. A validation of simulated discharge computed with a simplified land surface scheme applied to reanalysis data of the European Centre for Medium-Range Weather Forecasts and a hydrological discharge model has shown that these changes lead to a more realistic simulation of the annual cycle of discharge for several catchments. In particular this could be shown for the Yangtze Kiang and Amur catchments where adequate input data are available.     

Improvements in WRF simulation skills of southeastern United States summer rainfall: physical parameterization and horizontal resolution

Realistic regional climate simulations are important in understanding the mechanisms of summer rainfall in the southeastern United States (SE US) and in making seasonal predictions. In this study, skills of SE US summer rainfall simulation at a 15-km resolution are evaluated using the weather research and forecasting (WRF) model driven by climate forecast system reanalysis data. Influences of parameterization schemes and model resolution on the rainfall are investigated. It is shown that the WRF simulations for SE US summer rainfall are most sensitive to cumulus schemes, moderately sensitive to planetary boundary layer schemes, and less sensitive to microphysics schemes. Among five WRF cumulus schemes analyzed in this study, the Zhang–McFarlane scheme outperforms the other four. Further analysis suggests that the superior performance of the Zhang–McFarlane scheme is attributable primarily to its capability of representing rainfall-triggering processes over the SE US, especially the positive relationship between convective available potential energy and rainfall. In addition, simulated rainfall using the Zhang–McFarlane scheme at the 15-km resolution is compared with that at a 3-km convection-permitting resolution without cumulus scheme to test whether the increased horizontal resolution can further improve the SE US rainfall simulation. Results indicate that the simulations at the 3-km resolution do not show obvious advantages over those at the 15-km resolution with the Zhang–McFarlane scheme. In conclusion, our study suggests that in order to obtain a satisfactory simulation of SE US summer rainfall, choosing a cumulus scheme that can realistically represent the convective rainfall triggering mechanism may be more effective than solely increasing model resolution.     

Sensitivity of regional climate simulations of the summer 1998 extreme rainfall to convective parameterization schemes

In this paper, a comparison study of three cumulus parameterization schemes (CPSs), Kain-Fritsch2 (KF2), Grell (GR) and Anthes-Kuo (AK), is carried out using the Pennsylvania State University-National Center for Atmospheric Research mesoscale model (i.e., MM5). The performances of three CPSs are examined in simulations of the long-term heavy Meiyu-frontal rainfall events over the middle to lower reaches of the Yangtze River Basin (YRB-ML) during the summer of 1998. The initial and lateral boundary atmosphere conditions are taken from the National Centers for Environmental Prediction/Department of Energy Reanalysis-2 (R-2) data. The experiment with KF2 scheme (EX_KF2) reproduces reasonably well the major rainfall events, especially the heavy rainfall over YRB-ML during the later stage, and the middle and lower troposphere circulation patterns. In contrast, the experiments with both GR and AK schemes (EX_GR and EX_AK) only simulate the heavy rainfall during the first Meiyu rainy phase with weak intensity, and almost miss the rainfall along YRB-ML during the second phase. The analyses show that the location of 500?hPa western Pacific subtropical high during the first rainy phase, the northward advance during the transition period and the retreat during the second rainy phase, observed from the R-2 data, are successfully captured by EX_KF2, compared to the poor performance of EX_GR and EX_AK. A reasonable proportion of the subgrid-scale rainfall and smaller biases of temperature and moisture from lower to middle troposphere in EX_KF2 decide its good rainfall simulations, in contrast with the absolutely high proportions and the cold and dry biases caused by the decreased vertically convective transportation and the weak southwesterly wind in EX_GR and EX_AK. Overall, the three CPSs show substantial intersimulation differences in rainfall as well as in three-dimensional atmospheric structures, and KF2 shows superior performances. The results suggest that the realistic subgrid-scale CPS is still highly required for the high-resolution regional climate models to simulate the heavy rainfall events.     

Quantitative forecast experiment of a heavy rainfall event over Korea in a global model: horizontal resolution versus lead time issues

In this study, we examine the deterministic predictability of heavy rainfall over the Korean peninsula using a global model, the Global/Regional Integrated Model system, by focusing on the effects of horizontal resolution and lead time prior to the onset of the target event. The control run reproduces locally concentrated heavy rainfall over the mid-western part of the Korean peninsula on 27–29 July 2011, with a model setup of about 25 km grid spacing and 24 h in advance of the onset of heavy rainfall. We found that small-scale features are represented well at higher resolution, but without significant change in the distribution of rainfall. Increase of lead time reduces the predictability of large-scale features, accompanying a northward shift of major rainfall. At lower resolution, the accuracy of the heavy rainfall prediction decreases more rapidly as lead time increases. We concluded that the increase in predictability of heavy rainfall achieved by enhancing horizontal resolution is promising, but an additional set of experiments also indicates that efforts should be made to improve the physics packages in models.     

A simple parameterization of sub-grid scale open water for climate models

The effects of small fractions ( < 30%) of open water covering a grid element are currently neglected even in atmospheric general circulation models (AGCMs) which incorporate complex land surface parameterization schemes. Here, a method for simulating sub-grid scale open water is proposed which permits any existing land surface model to be modified to account for open water. This new parameterization is tested as an addition to an advanced land surface scheme and, as expected, is shown to produce general increases in the surface latent heat flux at the expense of the surface sensible heat flux. Small changes in temperature are associated with this change in the partitioning of available energy which is driven by an increase in the wetness of the grid element. The sensitivity of the land surface to increasing amounts of open water is dependent upon the type of vegetation represented. Dense vegetation (with a high leaf area index) is shown to complicate the apparently simple model sensitivity and indicates that more advanced methods of incorporating open water into AGCMs need to be considered and compared against the parameterization suggested here. However, the sensitivity of one land surface model to incorporating open water is large enough to warrant consideration of its incorporation into climate models.