Impact of the LMDZ atmospheric grid configuration on the climate and sensitivity of the IPSL-CM5A coupled model

The IPSL-CM5A climate model was used to perform a large number of control, historical and climate change simulations in the frame of CMIP5. The refined horizontal and vertical grid of the atmospheric component, LMDZ, constitutes a major difference compared to the previous IPSL-CM4 version used for CMIP3. From imposed-SST (Sea Surface Temperature) and coupled numerical experiments, we systematically analyze the impact of the horizontal and vertical grid resolution on the simulated climate. The refinement of the horizontal grid results in a systematic reduction of major biases in the mean tropospheric structures and SST. The mid-latitude jets, located too close to the equator with the coarsest grids, move poleward. This robust feature, is accompanied by a drying at mid-latitudes and a reduction of cold biases in mid-latitudes relative to the equator. The model was also extended to the stratosphere by increasing the number of layers on the vertical from 19 to 39 (15 in the stratosphere) and adding relevant parameterizations. The 39-layer version captures the dominant modes of the stratospheric variability and exhibits stratospheric sudden warmings. Changing either the vertical or horizontal resolution modifies the global energy balance in imposed-SST simulations by typically several W/m² which translates in the coupled atmosphere-ocean simulations into a different global-mean SST. The sensitivity is of about 1.2 K per 1 W/m² when varying the horizontal grid. A re-tuning of model parameters was thus required to restore this energy balance in the imposed-SST simulations and reduce the biases in the simulated mean surface temperature and, to some extent, latitudinal SST variations in the coupled experiments for the modern climate. The tuning hardly compensates, however, for robust biases of the coupled model. Despite the wide range of grid configurations explored and their significant impact on the present-day climate, the climate sensitivity remains essentially unchanged.     

A NUMERICAL SIMULATION OF THE EFFECT ON CHINESE REGIONAL CLIMATE DUE TO SEASONAL VARIATION OF LAND SURFACE PARAMETERS(PART I)

Sensitivity experiment is an important method to study the effect on regional climate due toseasonal variation of land surface parameters.Using China Regional Climate Model(CRCM)nested in CCM1.we first simulate Chinese regional climate,then two numerical sensitivityexperiments on the effect of vegetation and roughness length are made.The results show that:(1)If the vegetation is replaced with the monthly data of 1997.precipitation and land-surfacetemperature are both changed clearly,precipitation decreases and land surface temperatureincreases,but there is no regional correspondence between these changes.And the results aremuch better than the results when climate average vegetation was used in the CRCM.(2)If theroughness length is replaced with the monthly data of 1997,there is significant change on landsurface temperature,and there is very good regional correspondence between these changes.Butthe effect on precipitation is very small.     

The effect of land surface changes on Eemian climate

Transient experiments for the Eemian (128–113 ky BP) were performed with a complex, coupled earth system model, including atmosphere, ocean, terrestrial biosphere and marine biogeochemistry. In order to investigate the effect of land surface parameters (background albedo, vegetation and tree fraction and roughness length) on the simulated changes during the Eemian, simulations with interactive coupling between climate and vegetation were compared with additional experiments in which these feedbacks were suppressed. The experiments show that the influence of land surface on climate is mainly caused by changes in the albedo. For the northern hemisphere high latitudes, land surface albedo is changed partially due to the direct albedo effect of the conversion of grasses into forest, but the indirect effect of forests on snow albedo appears to be the major factor influencing the total absorption of solar radiation. The Western Sahara region experiences large changes in land surface albedo due to the appearance of vegetation between 128 and 120 ky BP. These local land surface albedo changes can be as much as 20%, thereby affecting the local as well as the global energy balance. On a global scale, latent heat loss over land increases more than 10% for 126 ky BP compared to present-day.     

Mid-Holocene greening of the Sahara: first results of the GAIM 6000 year BP Experiment with two asynchronously coupled atmosphere/biome models

 The mid-Holocene `green' Sahara represents the largest anomaly of the atmosphere-biosphere system during the last 12 000 years. Although this anomaly is attributed to precessional forcing leading to a strong enhancement of the African monsoon, no climate model so far has been able to simulate the full extent of vegetation in the Sahara region 6000 years ago. Here two atmospheric general circulation models (LMD 5.3 and ECHAM 3) are asynchronously coupled to an equilibrium biogeography model to give steady-state simulations of climate and vegetation 6000 years ago, including biogeophysical feedback. The two model results are surprisingly different, and neither is fully realistic. ECHAM shows a large northward extension of vegetation in the western part of the Sahara only. LMD shows a much smaller and more zonal vegetation shift. These results are unaffected by the choice of `green' or modern initial conditions. The inability of LMD to sustain a `green' Sahara 6000 years ago is linked to the simulated strength of the tropical summer circulation. During the northern summer monsoon season, the meridional gradient of sea-level pressure and subsidence over the western part of northern Africa are both much weaker in ECHAM than in LMD in the present as well as the mid-Holocene. These features allow the surface moist air flux to penetrate further into northern Africa in ECHAM than in LMD. This comparison illustrates the importance of correct simulation of atmospheric circulation features for the sensitivity of climate models to changes in radiative forcing, particularly for regional climates where atmospheric changes are amplified by biosphere-atmosphere feedbacks. Received: 20 April 1999 / Accepted: 20 January 2000     

CCM3模式中LSM积雪方案的改进研究(Ⅰ):修改方案介绍及其单点试验

为了改进美国NCARCCM3全球模式中LSM陆面模型中的积雪方案的模拟效果,在Sun等[1]SAST积雪模型的基础上,作了部分修改后,加进CCM3模式LSM模型中.该方案根据格点区域平均积雪深度的不同,把地面雪盖划分为1到3层不等,能在积雪表层和中间层更好地描述温度的日变化和季节变化;较详细地考虑了雪的热传导、太阳辐射的穿透吸收、雪的融化、液态水的储存、渗透和再冻结等积雪内部的主要物理过程;根据Nimbus-7卫星实测雪深资料修改了积雪覆盖度和雪面反照率的计算方案.利用前苏联6个台站1978-1983年的实测积雪资料和大气强迫数据,进行了单点模拟试验,结果表明,新的积雪参数化方案能够较好地再现积雪深度和雪水当量的逐日和季节变化特征,部分提高了积雪参数化方案对积雪的模拟能力.     

中国西部植被覆盖变化对北方夏季气候影响的数值模拟

植被覆盖的变化是气候变化的成因之一,植被改变对气候的反馈可能会加强或者减缓气候的变化.文中利用CCM3全球气候模式以及20世纪70年代和90年代中国西部的植被覆盖资料进行数值模拟试验,研究了这两个时期植被变化对北方夏季区域气候的影响.模拟结果表明:植被增加的地方,地面吸收的辐射通量增加;植被减少的地方,地面吸收的辐射通量减少.地面辐射平衡的变化造成局地大气热量异常,并引起周边大气热量的调整,从而导致东亚地区夏季大气环流异常.相对于70年代的植被状况,用90年代植被模拟的北方地区对流层上层为异常气旋性环流,而中、低层为异常反气旋环流,东北亚到中国东部盛行异常北风,同时西太平洋副热带高压强度偏弱、位置偏南.这种异常环流特征说明模拟的90年代中国东部夏季风明显减弱,异常的环流形势造成华北和东北地区夏季水汽输送减少,水汽辐合减弱,年降水量减少了40 mm,呈现减少的特征,这是和观测事实是比较吻合的.降水和环流的异常还造成华北和东北夏季平均地面气温降低了0.4-0.8℃.因此近30年来中国西部植被变化可能是东亚夏季风年代际变化以及北方夏季降水减少的一个重要因素.     

Modeling the hydroclimatology of the midwestern United States. Part 1: current climate

An ensemble of six 22-year numerical experiments was conducted to evaluate the ability of Regional Climate Model version 3 (RegCM3) to simulate the energy and water budgets of the midwestern United States. RegCM3 was run using two surface physics schemes: Integrated Biosphere Simulator (IBIS) and Biosphere-Atmosphere Transfer Scheme 1e (BATS1e), and two convective closure assumptions: Fritsch & Chappell (FC80) and Arakawa & Schubert (AS74). Boundary conditions were provided by the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 dataset and the ECHAM5 general circulation model. A companion paper examines the American Midwest under future climate scenarios. Overall, the model that reproduces the observed seasonal cycles of the midwestern United States climate system best is RegCM3 using IBIS and the AS74 convective closure assumption. IBIS simulates shortwave radiation more accurately, while BATS1e simulates longwave radiation more accurately. Summer two-meter air temperature is overestimated by the combination of IBIS and the FC80 convective closure assumption. All models contain a wet bias and overestimate evapotranspiration during the spring. Total runoff, surface runoff, groundwater runoff, and root zone soil moisture are best simulated by RegCM3 using IBIS and the AS74 convective closure assumption. While BATS1e does capture the seasonal cycle of total runoff, gross errors in the partitioning of total runoff between surface runoff and groundwater runoff exist. The seasonal cycle of root zone soil moisture simulated by RegCM3 using IBIS and the AS74 convective closure assumption is dry, but agrees with observations during the summer. The rest of the models underestimate root zone soil moisture.     

Examining climate variability over West Africa during the 1979–1993 period: observations and CCM3 comparisons

The Community Climate Model Version 3.6 is used to simulate the mean climate of West Africa during the Northern Hemisphere summer season (June-August). The climate model uses prescribed climatological sea surface temperatures (SSTs) and observed SSTs during the 1979-1993 period. Two important circulation features, the African Easterly Jet (AEJ) and the Tropical Easterly Jet (TEJ), are found in the simulations but a westerly wind bias is found with respect to 700 hPa winds. Consequently, easterly waves and rain rates are poorly simulated. The primary cause of the poorly simulated AEJ is the advection of cold air from Europe producing a cold bias over northern Africa and a weaker than observed meridional temperature gradient. The cold bias is caused by an eastward displacement of the simulated Azores surface high into Western Europe creating a stronger than observed meridional sea level pressure gradient over northern Africa. This bias systematically occurs in simulations using both climatological and observed SSTs. The biases in sea level pressure, temperature and zonal winds have the potential to produce poor regional climate model results for West Africa if the meteorological output from the CCM3 is used as lateral boundaries. Moreover, these biases introduce uncertainties to West African GCM sensitivity studies associated with interannual variability, land-use change and elevated anthropogenic greenhouse gases.     

Climate Change in Northern Africa: The Past is Not the Future

By using a climate system model of intermediate complexity, we have simulated long-term natural climate changes occurring over the last 9000 years. The paleo-simulations in which the model is driven by orbital forcing only, i.e., by changes in insolation caused by changes in the Earth's orbit, are compared with sensitivity simulations in which various scenarios of increasing atmospheric CO₂ concentration are prescribed. Focussing on climate and vegetation change in northern Africa, we recapture the strong greening of the Sahara in the early and mid-Holocene (some 9000–6000 years ago), and we show that some expansion of grasslandinto the Sahara is theoretically possible, if the atmospheric CO₂ concentration increases well above pre-industrial values and if vegetation growth is not disturbed. Depending on the rate of CO₂ increase, vegetation migration into the Sahara can be rapid, up to 1/10th of the Saharan area per decade, but could not exceed a coverage of 45%. In ourmodel, vegetation expansion into today's Sahara is triggered by an increase in summer precipitation which is amplified by a positive feedback between vegetation and precipitation. This is valid for simulations with orbital forcing and greenhouse-gas forcing. However, we argue that the mid-Holocene climate optimum some 9000 to 6000 years ago with its marked reduction of deserts in northern Africa is not a direct analogue for future greenhouse-gas induced climate change, as previously hypothesized. Not only does the global pattern of climate change differ between the mid-Holocene model experiments and the greenhouse-gas sensitivity experiments, but the relative role of mechanisms which lead to a reduction of the Sahara also changes. Moreover, the amplitude of simulated vegetation cover changes in northern Africa is less than is estimated for mid-Holocene climate.     

Evaluating the influence of different vegetation biomes on the global climate

The participation of different vegetation types within the physical climate system is investigated using a coupled atmosphere-biosphere model, CCM3-IBIS. We analyze the effects that six different vegetation biomes (tropical, boreal, and temperate forests, savanna, grassland and steppe, and shrubland/tundra) have on the climate through their role in modulating the biophysical exchanges of energy, water, and momentum between the land-surface and the atmosphere. Using CCM3-IBIS we completely remove the vegetation cover of a particular biome and compare it to a control simulation where the biome is present, thereby isolating the climatic effects of each biome. Results from the tropical and boreal forest removal simulations are in agreement with previous studies while the other simulations provide new evidence as to their contribution in forcing the climate. Removal of the temperate forest vegetation exhibits behavior characteristic of both the tropical and boreal simulations with cooling during winter and spring due to an increase in the surface albedo and warming during the summer caused by a reduction in latent cooling. Removal of the savanna vegetation exhibits behavior much like the tropical forest simulation while removal of the grassland and steppe vegetation has the largest effect over the central United States with warming and drying of the atmosphere in summer. The largest climatic effect of shrubland and tundra vegetation removal occurs in DJF in Australia and central Siberia and is due to reduced latent cooling and enhanced cold air advection, respectively. Our results show that removal of the boreal forest yields the largest temperature signal globally when either including or excluding the areas of forest removal. Globally, precipitation is most affected by removal of the savanna vegetation when including the areas of vegetation removal, while removal of the tropical forest most influences the global precipitation excluding the areas of vegetation removal.     

Climate sensitivity to wetlands and wetland vegetation in mid-Holocene North Africa

 Wetland regions are important components of the local climate, with their own characteristic surface energy and moisture budgets. Realistic representation of wetlands, including the important vegetation component, may therefore be necessary for more accurate simulations of climate and climate change. However, many land-atmosphere coupled models either ignore wetlands or treat wetlands as bare, water-saturated soil, neglecting the vegetation present within wetland environments. This study investigates the possible response of the mid-Holocene climate of North Africa to changes in orbital forcing, both with and without the presence of wetlands. The location of these wetlands is guided by analysis of paleovegetation and wetland distribution. In this study, the wetland regime in the land surface component of a climate model was modified to incorporate vegetation. Field measurements have shown that vegetation affects water loss associated with evaporation (including transpiration) within a wetland area. Comparisons between non-vegetated wetland and vegetated wetland revealed an increase in local albedo that produced an associated decrease in net radiation, evaporation and precipitation in the vicinity of the wetlands regions. Based on an analysis of the model surface water balance, the calculated area of mid-Holocene wetland coverage for North Africa closely matches the observed. For the North African region as a whole, the effects of adding vegetation to the wetland produced relatively small changes in climate, but local recycling of water may have served to help maintain paleo wetland communities. Received: 16 March 1999 / Accepted: 17 May 2000     

CCM3模式中LSM积雪方案的改进研究(Ⅱ):全球模拟试验分析

为了进一步检验新LSM积雪方案的气候模拟性能,经文献[1]单站模拟检验后,在本文中又进一步将其加入CCM3模式中,分别积分近两年。模拟结果表明：原LSM和新LSM积雪方案虽然都能再现全球气候的主要平均特征,但经改进后的新积雪方案对全球积雪气候、降水等要素场及环流等的气候模拟性能比原LSM积雪方案更好些。     

Sensitivity of ecosystem models to the spatial resolution of the NCAR Community Climate Model CCM2

 This study evaluates the sensitivity of ecosystem models to changes in the horizontal resolution of version 2 of the National Centre for Atmospheric Research Community Climate Model (CCM2). A previous study has shown that the distributions of natural ecosystems predicted by vegetation models using coarse resolution present-day climate simulations are poorly simulated. It is usually assumed that increasing the spatial resolution of general circulation models (GCMs) will improve the simulation of climate, and hence will increase our level of confidence in the use of GCM output for impacts studies. The principal goals of this study is to investigate this hypothesis and to identify which biomes are more affected by the changes in spatial resolution of the forcing climate. The ecosystem models used are the BIOME-1 model and a version of the Holdridge scheme. The climate simulations come from a set of experiments in which CCM2 was run with increasing horizontal resolutions. The biome distributions predicted using CCM2 climates are compared against biome distributions predicted using observed climate datasets. Results show that increasing the resolution of CCM2 produces a significant improvement of the global-scale vegetation prediction, indicating that a higher level of confidence can be vested in the global-scale prediction of natural ecosystems using medium and high resolution GCMs. However, not all biomes are equally affected by the increased spatial resolution, and although certain biome distributions are improved (e.g. hot desert, tropical seasonal forest), others remain globally poorly predicted even at high resolution (e.g. grasses and xerophytic woods). In addition, these results show that some climatic biases are enhanced with increasing resolution (e.g. in mountain ranges), resulting in the inadequate prediction of biomes. Received: 4 March 1997 / Accepted: 10 December 1997     

Influence of SST biases on future climate change projections

We use a quantile-based bias correction technique and a multi-member ensemble of the atmospheric component of NCAR CCSM3 (CAM3) simulations to investigate the influence of sea surface temperature (SST) biases on future climate change projections. The simulations, which cover 1977?C1999 in the historical period and 2077?C2099 in the future (A1B) period, use the CCSM3-generated SSTs as prescribed boundary conditions. Bias correction is applied to the monthly time-series of SSTs so that the simulated changes in SST mean and variability are preserved. Our comparison of CAM3 simulations with and without SST correction shows that the SST biases affect the precipitation distribution in CAM3 over many regions by introducing errors in atmospheric moisture content and upper-level (lower-level) divergence (convergence). Also, bias correction leads to significantly different precipitation and surface temperature changes over many oceanic and terrestrial regions (predominantly in the tropics) in response to the future anthropogenic increases in greenhouse forcing. The differences in the precipitation response from SST bias correction occur both in the mean and the percent change, and are independent of the ocean?Catmosphere coupling. Many of these differences are comparable to or larger than the spread of future precipitation changes across the CMIP3 ensemble. Such biases can affect the simulated terrestrial feedbacks and thermohaline circulations in coupled climate model integrations through changes in the hydrological cycle and ocean salinity. Moreover, biases in CCSM3-generated SSTs are generally similar to the biases in CMIP3 ensemble mean SSTs, suggesting that other GCMs may display a similar sensitivity of projected climate change to SST errors. These results help to quantify the influence of climate model biases on the simulated climate change, and therefore should inform the effort to further develop approaches for reliable climate change projection.     

A regional climate model simulation over West Africa: parameterization tests and analysis of land-surface fields

The West African Monsoon has been simulated with the regional climate model PROMES, coupled to the land-surface model ORCHIDEE and nested in ECMWF analysis, within AMMA-EU project. Three different runs are presented to address the influence of changes in two parameterizations (moist convection and radiation) on the simulated West African Monsoon. Another aim of the study is to get an insight into the relationship of simulated precipitation and 2-m temperature with land-surface fluxes. To this effect, data from the AMMA land-surface model intercomparison project (ALMIP) have been used. In ALMIP, offline simulations have been made using the same land-surface model than in the coupled simulation presented here, which makes ALMIP data particularly relevant for the present study, as it enables us to analyse the simulated soil and land-surface fields. The simulation of the monsoon depends clearly on the two analysed parameterizations. The inclusion of shallow convection parametrization affects the intensity of the simulated monsoon precipitation and modifies some dynamical aspects of the monsoon. The use of a fractional cloud-cover parameterization and a more complex radiation scheme is important for better reproducing the amplitude of the latitudinal displacement of the precipitation band. This is associated to an improved simulation of the surface temperature field and the easterly jets. However, the parameterization changes do not affect the timing of the main rainy and break periods of the monsoon. A better representation of downward solar radiation is associated with a smaller bias in the surface heat fluxes. The comparison with ALMIP land-surface and soil fields shows that precipitation and temperature biases in the regional climate model simulation are associated to certain biases in land-surface fluxes. The biases in soil moisture seem to be driven by atmospheric biases as they are strongly affected by the parameterization changes in atmospheric processes.     

Continental vegetation as a dynamic component of a global climate model: a preliminary assessment

A simplified vegetation distribution prediction scheme is used in combination with the Biosphere-Atmosphere Transfer Scheme (BATS) and coupled to a version of the NCAR Community Climate Model (CCM1) which includes a mixed-layer ocean. Employed in an off-line mode as a diagnostic tool, the scheme predicts a slightly darker and slightly rougher continental surface than when BATS' prescribed vegetation classes are used. The impact of tropical deforestation on regional climates, and hence on diagnosed vegetation, differs between South America and S.E. Asia. In the Amazon, the climatic effects of removing all the tropical forest are so marked that in only one of the 18 deforested grid elements could the new climate sustain tropical forest vegetation whereas in S.E. Asia in seven of the 9 deforested elements the climate could continue to support tropical forest. Following these off-line tests, the simple vegetation scheme has been coupled to the GCM as an interactive (or two-way) submodel for a test integration lasting 5.6 yr. It is found to be a stable component of the global climate system, producing only ~ 3% (absolute) interannual changes in the predicted percentages of continental vegetation, together with globally-averaged continental temperature increases of up to + 1.5 °C and evaporation increases of 0 to 5 W m^–2 and no discernible trends over the 67 months of integration. On the other hand, this interactive land biosphere causes regional-scale temperature differences of ± 10 °C and commensurate disturbances in other climatic parameters. Tuning, similar to the q-flux schemes used for ocean models, could improve the simulation of the present-day surface climate but, in the longer term, it will be important to focus on predicting the characteristics of the continental surface rather than simple vegetation classes. The coupling scheme will also have to allow for vegetation responses occurring over longer timescales so that the coupled system is buffered from sudden shocks.     

FGOALS-g3模拟的南亚夏季风:气候态和年际变率

南亚夏季风的变化决定着印度半岛的旱涝状况,气候系统模式则是研究南亚夏季风变化规律的重要工具。本文基于观测和JRA55再分析资料,系统评估了FGOALS-g3模式模拟的南亚夏季风气候态和年际变率,并重点关注FGOALS-g3与FGOALS-g2以及是否考虑海气相互作用的模拟差异。结果表明,由于局地海温模拟的变化,相比于FGOALS-g2,FGOALS-g3模拟的南亚夏季风在气候态热带印度洋信风和El Ni?o期间沃克环流下沉支上有明显改进。同时,由于对流层系统性冷偏差持续存在并且中心位于副热带300 hPa附近,造成气候态上经向温度梯度减弱,使季风环流减弱,导致FGOALS-g3中陆地季风槽的水汽辐散偏差和降水干偏差仍然存在;在年际变率上,FGOALS-g3模拟的El Ni?o期间赤道西太平洋海温冷异常偏弱,印度洋偶极子偏强,导致印度半岛下沉运动减弱,FGOALS-g3中ENSO—印度降水负相关关系也依然偏弱。研究表明,耦合过程导致的气候态海温偏差通过改变环流和水汽输送,有效补偿了大气模式中印度半岛中部和中南半岛的降水湿偏差;在年际变率上,耦合模式由于考虑了海温—降水—云短波辐射的负反馈过程,能够减小大气模式模拟偏差的强度,但印太暖池区海温模拟偏差导致沃克环流下沉支偏西,使得印度半岛的降水响应出现更大的湿偏差。     

The interactive climate and vegetation along the Pole-Equator belts simulated by a global coupled model

The interaction between climate and vegetation along four Pole-Equator-Pole （PEP） belts were explored using a global two-way coupled model, AVIM-GOALS, which links the ecophysiological processes at the land surface with the general circulation model （GCM）. The PEP belts are important in linking the climate change with the variation of sea and land, including terrestrial ecosystems. Previous PEP belts studies have mainly focused on the paleoclimate variation and its reconstruction. This study analyzes and discusses the interaction between modern climate and vegetation represented by leaf area index （LAI） and net primary production （NPP）. The results show that the simulated LAI variation, corresponding to the observed LAI variation, agrees with the peak-valley variation of precipitation in these belts. The annual mean NPP simulated by the coupled model is also consistent with PIK NPP data in its overall variation trend along the four belts, which is a good example to promote global ecological studies by coupling the climate and vegetation models. A large discrepancy between the simulated and estimated LAI emerges to the south of 15°N along PEP 3 and to the south of 18°S in PEP 1S, and the discrepancy for the simulated NPP and PIK data in the two regions is relatively smaller in contrast to the LAI difference. Precipitation is a key factor affecting vegetation variation, and the overall trend of LAI and NPP corresponds more obviously to precipitation variation than temperature change along most parts of these PEP belts.