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.     

Sensitivity of a coupled climate model to canopy interception capacity

The canopy interception capacity is a small but key part of the surface hydrology, which affects the amount of water intercepted by vegetation and therefore the partitioning of evaporation and transpiration. However, little research with climate models has been done to understand the effects of a range of possible canopy interception capacity parameter values. This is in part due to the assumption that it does not significantly affect climate. Near global evapotranspiration products now make evaluation of canopy interception capacity parameterisations possible. We use a range of canopy water interception capacity values from the literature to investigate the effect on climate within the climate model HadCM3. We find that the global mean temperature is affected by up to ?0.64 K globally and ?1.9 K regionally. These temperature impacts are predominantly due to changes in the evaporative fraction and top of atmosphere albedo. In the tropics, the variations in evapotranspiration affect precipitation, significantly enhancing rainfall. Comparing the model output to measurements, we find that the default canopy interception capacity parameterisation overestimates canopy interception loss (i.e. canopy evaporation) and underestimates transpiration. Overall, decreasing canopy interception capacity improves the evapotranspiration partitioning in HadCM3, though the measurement literature more strongly supports an increase. The high sensitivity of climate to the parameterisation of canopy interception capacity is partially due to the high number of light rain-days in the climate model that means that interception is overestimated. This work highlights the hitherto underestimated importance of canopy interception capacity in climate model hydroclimatology and the need to acknowledge the role of precipitation representation limitations in determining parameterisations.     

CO2 climate sensitivity and snow-sea-ice albedo parameterization in an atmospheric GCM coupled to a mixed-layer ocean model

The snow-sea-ice albedo parameterization in an atmospheric general circulation model (GCM), coupled to a simple mixed-layer ocean and run with an annual cycle of solar forcing, is altered from a version of the same model described by Washington and Meehl (1984). The model with the revised formulation is run to equilibrium for 1 × CO₂ and 2 × CO₂ experiments. The 1 ×CO₂ (control) simulation produces a global mean climate about 1° warmer than the original version, and sea-ice extent is reduced. The model with the altered parameterization displays heightened sensitivity in the global means, but the geographical patterns of climate change due to increased carbon dioxide (CO₂) are qualitatively similar. The magnitude of the climate change is affected, not only in areas directly influenced by snow and ice changes but also in other regions of the globe, including the tropics where sea-surface temperature, evaporation, and precipitation over the oceans are greater. With the less-sensitive formulation, the global mean surface air temperature increase is 3.5 °C, and the increase of global mean precipitation is 7.12%. The revised formulation produces a globally averaged surface air temperature increase of 4.04 °C and a precipitation increase of 7.25%, as well as greater warming of the upper tropical troposphere. Sensitivity of surface hydrology is qualitatively similar between the two cases with the larger-magnitude changes in the revised snow and ice-albedo scheme experiment. Variability of surface air temperature in the model is comparable to observations in most areas except at high latitudes during winter. In those regions, temporal variation of the sea-ice margin and fluctuations of snow cover dependent on the snow-ice-albedo formulation contribute to larger-than-observed temperature variability. This study highlights an uncertainty associated with results from current climate GCMs that use highly parameterized snow-sea-ice albedo schemes with simple mixed-layer ocean models.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Global comparison of the regional rainfall results of enhanced greenhouse coupled and mixed layer ocean experiments: Implications for climate change scenario development

The extent of agreement amongst current global climate models (GCMs) on the global pattern of rainfall change simulated under enhanced greenhouse conditions is assessed. We consider the results of five experiments which use a simple mixed layer ocean formulation and five which use a fully dynamic ocean model (coupled experiments). For many regions of the northern hemisphere there is strong agreement amongst both mixed layer and coupled experiments on the sign of simulated rainfall change. However, in the southern hemisphere there are large, and apparently systematic, differences between the coupled and mixed layer experiments. In particular, whereas the mixed layer experiments agree on simulated rainfall increase in summer in the tropics and subtropics of the Australian sector, the coupled experiments agree (although more weakly) on rainfall decreases. These differences appear to relate to the much reduced warming simulated by the coupled experiments in the high latitudes of the southern hemisphere. However, recent oceanographie evidence suggests that this suppressed warming may be considerably overestimated. We conclude therefore that despite the in-principle advantages of coupled models, it may be too soon to base some regionally specific climate change scenarios solely on the results of coupled experiments.     

Global and regional ocean carbon uptake and climate change: sensitivity to a substantial mitigation scenario

Under future scenarios of business-as-usual emissions, the ocean storage of anthropogenic carbon is anticipated to decrease because of ocean chemistry constraints and positive feedbacks in the carbon-climate dynamics, whereas it is still unknown how the oceanic carbon cycle will respond to more substantial mitigation scenarios. To evaluate the natural system response to prescribed atmospheric ??target?? concentrations and assess the response of the ocean carbon pool to these values, 2 centennial projection simulations have been performed with an Earth System Model that includes a fully coupled carbon cycle, forced in one case with a mitigation scenario and the other with the SRES A1B scenario. End of century ocean uptake with the mitigation scenario is projected to return to the same magnitude of carbon fluxes as simulated in 1960 in the Pacific Ocean and to lower values in the Atlantic. With A1B, the major ocean basins are instead projected to decrease the capacity for carbon uptake globally as found with simpler carbon cycle models, while at the regional level the response is contrasting. The model indicates that the equatorial Pacific may increase the carbon uptake rates in both scenarios, owing to enhancement of the biological carbon pump evidenced by an increase in Net Community Production (NCP) following changes in the subsurface equatorial circulation and enhanced iron availability from extratropical regions. NCP is a proxy of the bulk organic carbon made available to the higher trophic levels and potentially exportable from the surface layers. The model results indicate that, besides the localized increase in the equatorial Pacific, the NCP of lower trophic levels in the northern Pacific and Atlantic oceans is projected to be halved with respect to the current climate under a substantial mitigation scenario at the end of the twenty-first century. It is thus suggested that changes due to cumulative carbon emissions up to present and the projected concentration pathways of aerosol in the next decades control the evolution of surface ocean biogeochemistry in the second half of this century more than the specific pathways of atmospheric CO₂ concentrations.     

Modelling Indonesian rainfall with a coupled regional model

Long-term high-resolution coupled climate model simulations using the Max Planck Institute Regional Climate Model and the Max Planck Institute Ocean Model have been performed with boundary forcings from two reanalyses: firstly from the European Centre for Medium-Range Weather Forecasts, and secondly from the joint reanalysis of the National Centers for Environmental Prediction and the National Center for Atmospheric Research. This study employs a special coupling setup using a regional atmospheric model and a global ocean model. The latter model applies a special conformal grid from a bipolar orthogonal spherical coordinate system, which allows irregular positions of the poles and focuses on the detail over the Maritime Continent. The coupled model was able to simulate stable and realistic rainfall variabilities without flux correction and at two different ocean resolutions. The coupled system is integrated for a period between 1979 and 1993 and the results are then compared to those from uncoupled runs and from observation. The results show improved performance after coupling: a remarkable reduction of overestimated rainfall over the sea for the atmospheric model and of warm SST biases for the ocean model. There is no significant change in rainfall variability at higher ocean model resolution, but the ocean circulation shows less transport variability within the Makassar Strait in comparison to observations. This paper has not been published or considered by any other journal in any language.     

Simulating the diurnal cycle of rainfall in global climate models: resolution versus parameterization

The effects of horizontal resolution and the treatment of convection on simulation of the diurnal cycle of precipitation during boreal summer are analyzed in several innovative weather and climate model integrations. The simulations include: season-long integrations of the Non-hydrostatic Icosahedral Atmospheric Model (NICAM) with explicit clouds and convection; year-long integrations of the operational Integrated Forecast System (IFS) from the European Centre for Medium-range Weather Forecasts at three resolutions (125, 39 and 16 km); seasonal simulations of the same model at 10 km resolution; and seasonal simulations of the National Center for Atmospheric Research (NCAR) low-resolution climate model with and without an embedded two-dimensional cloud-resolving model in each grid box. NICAM with explicit convection simulates best the phase of the diurnal cycle, as well as many regional features such as rainfall triggered by advancing sea breezes or high topography. However, NICAM greatly overestimates mean rainfall and the magnitude of the diurnal cycle. Introduction of an embedded cloud model within the NCAR model significantly improves global statistics of the seasonal mean and diurnal cycle of rainfall, as well as many regional features. However, errors often remain larger than for the other higher-resolution models. Increasing resolution alone has little impact on the timing of daily rainfall in IFS with parameterized convection, yet the amplitude of the diurnal cycle does improve along with the representation of mean rainfall. Variations during the day in atmospheric prognostic fields appear quite similar among models, suggesting that the distinctive treatments of model physics account for the differences in representing the diurnal cycle of precipitation.     

Global and regional variability in a coupled AOGCM

 The variability of near surface temperature on global and regional spatial scales and interannual time scales from a 1000 year control integration of the Hadley Centre coupled model (HADCM2-CTL) are compared with the observational record of surface temperature. The model succeeds in reproducing the observed patterns of natural variability, with high variability over the northern continents and low variability over much of the tropics. The model global mean variability has similar strength to observed global mean variability on time scales less than 20 years. The warming seen in the historical record is outside the range of natural variability as simulated in HADCM2-CTL. The model has El-Ni?o/Southern Oscillation (ENSO)-like behaviour with a central Pacific, peak to peak, strength of approximately 3 K. Changes in near surface temperature in the central Pacific are strongly correlated with changes in near surface temperature over most of the tropics, large regions of the extra-tropics and changes in tropical ocean upper 250 m heat content. Tropospheric temperature changes and tropical surface pressure changes are also strongly correlated with changes in the central Pacific surface temperature. Oceanic regions show significant departures from an AR1 or first order Markov behaviour in the Northwest Atlantic, Northwest Pacific and Arctic oceans. The Northwest Atlantic region has large amounts of variability over periods greater than 50 years. This variability is associated with a jump in the strength of North Atlantic meridional stream function. The spectra of the Western European and Continental US land regions are not significantly different from an AR1 process. The flow through the Drake Passage has an interannual standard deviation of approximately 2.5 Sv with significant departures from an AR1 process at time scales greater than 40 years. Winter northern hemispheric 500 hPa geopotential height shows some evidence of multiple regimes but no year to year persistence of these regimes. Received: 31 January 1996/Accepted: 22 July 1996     

未来极端降水对气候平均变暖敏感性的蒙特卡罗模拟试验

利用Weibull分布拟合逐日降水的原始分布模式,并基于统计降尺度和蒙特卡罗随机模拟方法,对中国东部区域各站逐日极端降水量在未来气候变暖条件下的响应特征进行统计数值试验.结果表明,在全球变暖背景下,区域平均温度的改变即可导致区域极端降水概率分布特征的变动.从两个典型代表区域的预估结果中可见,长江中下游南部平均降水量对平均温度升高有正响应,模拟得到的区域极端降水概率分布曲线有明显的向右平移,导致大量级的极端降水的再现期缩短即概率增大.山东及渤海湾区域平均降水量对平均温度升高有负响应,模拟得到的区域极端降水概率密度分布尺度参数变小更明显,即方差增大,表现为左右两侧概率密度增加,同样导致大量级的极端降水再现期缩短即概率增大.本文仅考察了气候均值改变条件下,未来区域气候极端值的概率预估的可行性方案.对于未来气候方差的变化并未作试验,但理论上已经证明,未来气候极端值的概率对于气候方差变化的敏感性可能更大.由于目前尚未整卵出考察方差变化的较为完整的实际观测资料,该问题还有待进一步深入研究.     

Potential decadal predictability and its sensitivity to sea ice albedo parameterization in a global coupled model

Decadal prediction is one focus of the upcoming 5th IPCC Assessment report. To be able to interpret the results and to further improve the decadal predictions it is important to investigate the potential predictability in the participating climate models. This study analyzes the upper limit of climate predictability on decadal time scales and its dependency on sea ice albedo parameterization by performing two perfect ensemble experiments with the global coupled climate model EC-Earth. In the first experiment, the standard albedo formulation of EC-Earth is used, in the second experiment sea ice albedo is reduced. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric parameters. The decadal predictability of the atmospheric circulation is small. The highest potential predictability was found in air temperature at 2?m height over the northern North Atlantic and the southern South Atlantic. Over land, only a few areas are significantly predictable. The predictability for continental size averages of air temperature is relatively good in all northern hemisphere regions. Sea ice thickness is highly predictable along the ice edges in the North Atlantic Arctic Sector. The meridional overturning circulation is highly predictable in both experiments and governs most of the decadal climate predictability in the northern hemisphere. The experiments using reduced sea ice albedo show some important differences like a generally higher predictability of atmospheric variables in the Arctic or higher predictability of air temperature in Europe. Furthermore, decadal variations are substantially smaller in the simulations with reduced ice albedo, which can be explained by reduced sea ice thickness in these simulations.     

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.     

Quantifying Arctic contributions to climate predictability in a regional coupled ocean-ice-atmosphere model

The relative importance of regional processes inside the Arctic climate system and the large scale atmospheric circulation for Arctic interannual climate variability has been estimated with the help of a regional Arctic coupled ocean-ice-atmosphere model. The study focuses on sea ice and surface climate during the 1980s and 1990s. Simulations agree reasonably well with observations. Correlations between the winter North Atlantic Oscillation index and the summer Arctic sea ice thickness and summer sea ice extent are found. Spread of sea ice extent within an ensemble of model runs can be associated with a surface pressure gradient between the Nordic Seas and the Kara Sea. Trends in the sea ice thickness field are widely significant and can formally be attributed to large scale forcing outside the Arctic model domain. Concerning predictability, results indicate that the variability generated by the external forcing is more important in most regions than the internally generated variability. However, both are in the same order of magnitude. Local areas such as the Northern Greenland coast together with Fram Straits and parts of the Greenland Sea show a strong importance of internally generated variability, which is associated with wind direction variability due to interaction with atmospheric dynamics on the Greenland ice sheet. High predictability of sea ice extent is supported by north-easterly winds from the Arctic Ocean to Scandinavia.     

Modeling the tropical Pacific Ocean using a regional coupled climate model

A high-resolution tropical Pacific general circulation model (GCM) coupled to a global atmospheric GCM is described in this paper. The atmosphere component is the 5°×4°global general circulation model of the Institute of Atmospheric Physics (IAP) with 9 levels in the vertical direction. The ocean component with a horizontal resolution of 0.5°, is based on a low-resolution model (2°×1°in longitude-latitude).Simulations of the ocean component are first compared with its previous version. Results show that the enhanced ocean horizontal resolution allows an improved ocean state to be simulated; this involves (1) an apparent decrease in errors in the tropical Pacific cold tongue region, which exists in many ocean models,(2) more realistic large-scale flows, and (3) an improved ability to simulate the interannual variability and a reduced root mean square error (RMSE) in a long time integration. In coupling these component models, a monthly "linear-regression" method is employed to correct the model's exchanged flux between the sea and the atmosphere. A 100-year integration conducted with the coupled GCM (CGCM) shows the effectiveness of such a method in reducing climate drift. Results from years 70 to 100 are described.The model produces a reasonably realistic annual cycle of equatorial SST. The large SSTA is confined to the eastern equatorial Pacific with little propagation. Irregular warm and cold events alternate with a broad spectrum of periods between 24 and 50 months, which is very realistic. But the simulated variability is weaker than the observed and is also asymmetric in the sense of the amplitude of the warm and cold events.     

降水气候强迫下非均匀地表区域平均径流的一种参数化方案

将任一中尺度区域的平均瞬间径流率考虑为区域平均降水量和地表土壤层水分渗透垦的余项.根据降水量在地理空间上分布的实测资料拟合其空间概率密度函数(PDF),并结合土壤入渗物理过程的数学描述及其经验公式,精确估计出地表土壤渗透率及其空间分布,由此建立区域地表径流率的统计-动力学估计方案.换言之,区域内地表产流率可视为区域平均降水量与区域平均的土壤下渗量之差值,而区域内土壤的平均下渗量又町分为非饱和区和饱和区两部分的下渗量来分别计算.就陆面水分循环的物理过程而言,地表入渗现象是在一定的下垫面特性基础上,由一定的水分供应源而形成的.根据大气降水向地表层输送水分的物理过程,在满足植被表层覆盖需水(截流水)和地表层土壤人渗水基础上,多余的降水量才会形成地表径流.凶此,推求地表产流率的主要关键在于地表土壤层需水量.为此奉文根据土壤水分通量方程推导出水分入渗公式.又从描述土壤水分和降水的空间PDF出发,推导出非均匀土壤含水量及降水气候强迫所形成的次网格尺度区域平均径流率计算公式.利用长江三角洲地区1996年降水量和土壤特性等实测资料建立区域平均地表径流率的估计公式,并对其影响凶素进行敏感性试验.结果表明,该方法与用Mosaic方法计算的区域径流率(或产流率)结果十分接近.由此可见,该文提出的降水气候强迫下非均匀地表区域平均径流的这种统计-动力参数化方案,具有相当的可靠性与可行性.     

Simulation of rainfall anomalies leading to the 2005 drought in Amazonia using the CLARIS LPB regional climate models

The meteorological characteristics of the drought of 2005 in Amazonia, one of the most severe in the last 100 years were assessed using a suite of seven regional models obtained from the CLARIS LPB project. The models were forced with the ERA-Interim reanalyses as boundary conditions. We used a combination of rainfall and temperature observations and the low-level circulation and evaporation fields from the reanalyses to determine the climatic and meteorological characteristics of this particular drought. The models reproduce in some degree the observed annual cycle of precipitation and the geographical distribution of negative rainfall anomalies during the summer months of 2005. With respect to the evolution of rainfall during 2004–2006, some of the models were able to simulate the negative rainfall departures during early summer of 2005 (December 2004 to February 2005). The interannual variability of rainfall anomalies for both austral summer and fall over northern and southern Amazonia show a large spread among models, with some of them capable of reproducing the 2005 observed negative rainfall departures (four out of seven models in southern Amazonia during DJF). In comparison, all models simulated the observed southern Amazonia negative rainfall and positive air temperature anomalies during the El Nino-related drought in 1998. The spatial structure of the simulated rainfall and temperature anomalies in DJF and MAM 2005 shows biases that are different among models. While some models simulated the observed negative rainfall anomalies over parts of western and southern Amazonia during DJF, others simulated positive rainfall departures over central Amazonia. The simulated circulation patterns indicate a weaker northeasterly flow from the tropical North Atlantic into Amazonia, and reduced flows from southern Amazonia into the La Plata basin in DJF, which is consistent with observations. In general, we can say that in some degree the regional models are able to capture the response to the forcing from the tropical Atlantic during the drought of 2005 in Amazonia. Moreover, extreme climatic conditions in response to anomalous low-level circulation features are also well captured, since the boundary conditions come from reanalysis and the models are largely constrained by the information provided at the boundaries. The analysis of the 2005 drought suggests that when the forcing leading to extreme anomalous conditions is associated with both local and non-local mechanisms (soil moisture feedbacks and remote SST anomalies, respectively) the models are not fully capable of representing these feedbacks and hence, the associated anomalies. The reason may be a deficient reproduction of the land–atmosphere interactions.