青藏高原极端气温的动力降尺度模拟

利用ERA-Interim再分析资料作为边界条件,基于耦合陆面模式Noah-MP的区域气候模式WRF在东亚区域进行了动力降尺度模拟(简称WRF2),对比格点观测资料,评估了动力降尺度对青藏高原极端气温指数的模拟能力,在此控制试验基础上,分别将WRF的陆面模式替换为Noah LSM,边界条件替换为CCSM4,进行了两组敏感性试验(分别是WRF1和WRF3),通过与控制试验的比较,分析了边界条件和陆面模式对极端气温指数模拟的影响。结果表明,WRF2能较好地模拟青藏高原极端气温指数气候态的空间分布,但存在一定的冷偏差;受边界条件影响WRF3模拟的极端气温指数的气候倾向率存在负偏差。同时,尽管采用不同的边界条件,耦合相同陆面过程的两次数值试验对极端气温空间分布的模拟能力相似,相比WRF2,WRF1表现出更强的冷偏差;但边界条件对极端气温指数气候倾向率的影响大于陆面模式,WRF3模拟的极端气温指数气候倾向率与观测结果更为接近。     

农田灌溉过程与土壤参数更新对中亚费尔干纳盆地WRF/Noah模拟精度的提升

通过中亚费尔干纳盆地2007～2011年气候的模拟试验,揭示了新增农田灌溉过程与更新土壤参数对WRF（Weather Research and Forecasting）/Noah模式模拟精度的提升作用。通过对比标准版本与嵌入灌溉过程参数化方案后的WRF/Noah模式的模拟结果,研究发现农业灌溉提升了土壤含水量,导致地表蒸发增强,潜热增加,感热减少,致使近地层大气降温、增湿,这一效应降低了WRF/Noah模拟的暖、干偏差,模拟2 m气温和大气比湿均方根误差分别由6.52°C降低至5.81°C,由1.66 g/kg降低至1.13 g/kg。进而针对WRF默认配置的费尔干纳盆地内土壤数据精度欠佳的问题,再利用国际土壤参比与信息中心（ISRIC）数据（主要是粉砂粘壤土和粉砂壤土）替换了WRF默认的数据（主要是粘土和壤土）,降低了土壤凋萎系数,使得有效土壤水增多,缩小了灌溉需水量的模拟误差,并使得蒸散发进一步增强,潜热增多,感热减少,导致近地层降温、增湿,进一步降低了WRF/Noah模拟的暖、干偏差,模拟温度、湿度的均方根误差分别由5.81°C降低至5.46°C,由1.13 g/kg降低至1.08 g/kg。上述结果表明:充分农业灌溉对陆面过程产生影响,以及采用高精度的土壤数据能够显著提高WRF/Noah模式在中亚费尔干纳盆地的模拟精度。     

青藏高原极端气温的动力降尺度模拟北大核心CSCD

利用ERA-Interim再分析资料作为边界条件,基于耦合陆面模式Noah-MP的区域气候模式WRF在东亚区域进行了动力降尺度模拟(简称WRF2),对比格点观测资料,评估了动力降尺度对青藏高原极端气温指数的模拟能力,在此控制试验基础上,分别将WRF的陆面模式替换为Noah LSM,边界条件替换为CCSM4,进行了两组敏感性试验(分别是WRF1和WRF3),通过与控制试验的比较,分析了边界条件和陆面模式对极端气温指数模拟的影响。结果表明,WRF2能较好地模拟青藏高原极端气温指数气候态的空间分布,但存在一定的冷偏差;受边界条件影响WRF3模拟的极端气温指数的气候倾向率存在负偏差。同时,尽管采用不同的边界条件,耦合相同陆面过程的两次数值试验对极端气温空间分布的模拟能力相似,相比WRF2,WRF1表现出更强的冷偏差;但边界条件对极端气温指数气候倾向率的影响大于陆面模式,WRF3模拟的极端气温指数气候倾向率与观测结果更为接近。     

陆面过程参数化对宁波地区雷暴过程模拟的影响

利用耦合复杂程度不同的陆面过程参数化方案(Noah、RUC)的新一代中尺度数值模式WRF,对2006年6月24日发生在宁波地区的一次典型的雷暴过程进行了数值模拟试验。结果表明:对于雷暴发生前期近地面热力、动力场的特征,Noah方案的模拟较为逼真,RUC方案没有反映出下垫面覆盖的多样性以及城市下垫面的影响,城乡之间差异不明显;Noah方案模拟的雷暴启动、发展过程与观测较为一致,RUC方案较好地描述出了演变过程中的关键阶段(3次合并过程);由于参数化所考虑的要素和物理过程存在一定差异,Noah方案在对降水的强度、降水中心位置的模拟方面具有一定优势;雷暴的持续时间对陆面过程参数化方案的选择比较敏感,两个方案所模拟的雷暴过程持续时间不同程度地长于实际雷暴持续时间;无论是哪种下垫面覆盖类型,白天Noah方案模拟的感热通量均大于RUC方案,而Noah方案模拟的潜热通量均小于RUC方案。     

太湖对周边城市热环境影响的模拟

太湖微气候条件及局地热环境的研究对于太湖周边城市地区可持续发展以及大气宏观调控具有重要意义。为了更准确模拟太湖湖-气交换,将CLM4-LISSS浅水湖泊陆面过程参数化方案耦合进入WRF中的Noah陆面过程模型。采用太湖湖上平台及岸边陆上测站观测的数据,评估了CLM4-LISSS浅水湖泊过程方案对太湖区域近地层气象条件的模拟性能。并基于耦合模型模拟研究了太湖对周边城市区域热环境的影响。结果表明,CLM4-LISSS湖泊陆面过程方案模拟的湖表面温度能反映真实温度的变化趋势。两种陆面过程方案在2 m气温的模拟值也存在一定的差异。CLM4-LISSS与Noah方案计算所得湖上2 m气温的模拟值与观测值的平均均方根误差分别为1.77和2.22℃,平均相关系数分别为0.88和0.84;模拟10 m风速的平均均方根误差分别为1.93和2.78 m/s,平均相关系数为0.72和0.68。太湖对周边城市热环境存在明显的影响。8月太湖对周边地区15时（北京时）近地层平均降温0.5-0.7℃,影响范围达60 km。06时太湖导致周边近地层平均升温达0.7-1℃,影响范围达50 km。湖风带来的冷空气抑制了城市热岛的垂直运动,在高温天气下使得苏州、无锡和常州城市地区昼间边界层下降高度可达300、400和100 m。无锡地区边界层内气温最高降幅可达0.5-0.7℃。通过选取无锡地区2015年8月28日高温小风天气作为背景条件,分析该地区湖风对城市热岛环流的影响机制。结果表明湖风能够破坏无锡地区的热岛环流结构,改变近地面热量和水汽的分布,抑制城市热岛的垂直发展,并影响至整个无锡地区。局地热力环流的变化对于局地气候以及污染物质的输送与扩散有可能产生重要影响,准确的湖泊陆面过程参数化方案对于天气预报、空气污染模拟,以及气候模拟研究等均具有重要意义。     

不同初始场及陆面方案对青藏高原中东部积雪消融过程的模拟研究

基于WRF(Weather Research and Forecasting)模式,本研究使用更为准确的气象站点及卫星遥感积雪资料替换初始场中积雪深度、雪水当量等积雪数据,对2014年2月17-27日青藏高原中东部一次积雪消融过程进行模拟研究,评估WRF模式中CLM(Community Land Model)、Noah-LSM(Noah land surface model)和Noah-MP(Noah-Multiparameterization Land Surface Model)3种陆面过程方案对该次积雪消融过程的模拟性能。结果表明：3种陆面过程方案均能较好地再现2 m气温、积雪深度和反照率的日变化趋势,但各试验模拟效果有一定差异。气象站点及卫星遥感积雪资料作为初始场时,CLM陆面过程方案模拟的2 m气温平均误差最小,为0.002℃;Noah-LSM陆面过程方案中2 m气温均方根误差（4.01℃）和平均绝对误差（3.30℃）最小,但昼夜温差较观测显著偏小;同时CLM陆面过程方案模拟的积雪深度均方根误差、平均误差和平均绝对误差均最小,分别为4.70 cm、-1.25 cm和2.75 ...     

WRF模式对西南地区干旱事件的模拟研究

2009—2010年在中国西南地区发生了严重的秋冬春三季持续性干旱,为了评估WRF模式两种陆面方案在中国西南地区干旱事件中的模拟性能,该文采用Noah陆面方案和Pleim_Xiu陆面方案两种WRF模拟方案对西南干旱事件进行模拟研究。两种陆面方案都合理的模拟出了西南地区极端干旱事件中的降水空间分布与时间序列,但与观测资料相比仍然存在一定的误差。两种陆面方案的相互比较表明,在极端干旱事件模拟中,Noah陆面方案在降水模拟中有着一定的改进作用。在对西南干旱时期的蒸发模拟当中,Noah和Px方案相比有着更低的误差,采用Noah陆面方案能更好的模拟蒸发状况。     

植被覆盖度对兰州地区气象场影响的模拟研究

利用WRF(Weather Research and Forecasting)模式耦合Noah陆面过程模式,模拟了兰州地区冬季气象场,并用观测资料对模拟结果进行了检验。利用2006年中分辨率成像分光辐射计(MODIS)植被归一化指数(NDVI)计算得到的植被覆盖度替换模式默认的植被覆盖度,研究了植被覆盖度对WRF模式模拟结果的影响。结果表明,新的植被覆盖度数据使研究区域的地表反照率减小,发射率增加,感热通量白天增加、夜间减小;还明显地改进了WRF模式对近地面温度和风速的模拟;植被覆盖度对地表蒸发有很大影响,冬季干旱半干旱地区的植被基本处于休眠状态,地表蒸发以直接蒸发为主,使用新的植被覆盖度数据后,模拟区域的植被覆盖度增加,地表蒸发减小,近地面水汽含量减少,WRF模式模拟的边界层高度增大。     

北京地区夏季边界层结构日变化的高分辨模拟对比

使用WRF中尺度数值模式, 分别选用两种不同的边界层参数化方案 (MYJ, YSU) 和3种陆面参数化方案 (SLAB, Noah, RUC), 对2004年7月1日08:00—7月4日20:00 (北京时) 北京地区夏季边界层结构进行1 km的高分辨模拟。对比分析了近地面层风场、温度场以及边界层的日变化特征, 结果发现:WRF模式基本模拟出了北京夏季边界层的日变化特征; 在边界层方案中, MYJ方案描述的边界层结构较YSU方案合理; Noah陆面模式较好地反映了城市的热岛效应; 无降水时, 风速及边界层高度对于陆面过程不敏感, 而降水发生后, 陆面过程对于边界层结构的影响增大; 各方案模拟的城区风速明显偏大, 这是因为没有充分考虑城市建筑物的阻力作用。     

陆面模式中土壤湿度影响蒸散参数化方案的评估

本文将四个常见陆面模式CLM3.5（Community Land Model Version 3.5）、Noah_LSM（The Noah Land Surface Model）、VIC（Variable Infiltration Capacity）以及SSiB（The Simplified Simple Biosphere Model）中土壤湿度影响蒸散的参数化方案进行简化,并利用实验观测资料对不同参数化方案进行评估,探究不同陆面模式对土壤湿度与蒸散关系的模拟差异,从而为提高模式的模拟能力提供依据。结果表明,（1）CLM与SSiB中计算土壤湿度影响裸土蒸发的参数化方案较Noah_LSM和VIC更接近真实的物理过程,同时CLM与SSiB模式中土壤湿度对蒸发的影响程度较Noah_LSM和VIC大;而对于下垫面有植被条件下的蒸散而言,CLM中包含了植被光合作用、呼吸作用等生物物理学过程,与实际情况更为接近,并且CLM与SSiB中土壤湿度对植被蒸散的影响程度大于VIC,Noah_LSM最低;（2）根据干旱区、半干旱区、半湿润区以及湿润区各站点的分析可知,CLM、SSiB与Noah_LSM中土壤湿度影响蒸散的参数化方案的拟合效果较VIC好,同时在部分站点CLM与SSiB的参数化方案稍优于Noah_LSM。区域之间比较说明,四个模式对干旱半干旱区的模拟效果明显较半湿润区和湿润区好。     

Improved Parameterization of Snow Albedo in WRF + Noah: Methodology Based on a Severe Snow Event on the Tibetan Plateau

Snowfall and the subsequent evolution of the snowpack have a large effect on the surface energy balance and water cycle of the Tibetan Plateau (TP). The effects of snow cover can be represented by the WRF coupled with a land surface scheme. The widely used Noah scheme is computationally efficient, but its poor representation of albedo needs considerable improvement. In this study, an improved albedo scheme is developed using a satellite-retrieved albedo that takes snow depth and age into account. Numerical experiments were then conducted to simulate a severe snow event in March 2017. The performance of the coupled WRF/Noah model, which implemented the improved albedo scheme, is compared against the model’s performance using the default Noah albedo scheme and against the coupled WRF/CLM that applied CLM albedo scheme. When the improved albedo scheme is implemented, the albedo overestimation in the southeastern TP is reduced, reducing the RMSE of the air temperature by 0.7°C. The improved albedo scheme also attains the highest correlation between the satellite-derived and the model-estimated albedo, which provides for a realistic representation of both the snow water equivalent (SWE) spatial distribution in the heavy snowbelt (SWE > 6 mm) and the maximum SWE in the eastern TP. The underestimated albedo in the coupled WRF/CLM leads to underestimating the regional maximum SWE and a consequent failure to estimate SWE in the heavy snowbelt accurately. Our study demonstrates the feasibility of improving the Noah albedo scheme and provides a theoretical reference for researchers aiming to improve albedo schemes further.     

Evaluation of the WRF Model with Different Land Surface Schemes： A Drought Event Simulation in Southwest China during 2009–10

The authors examined the performance of version 3.4.1 of the Weather Research and Forecasting Model（WRF） with various land surface schemes in simulating a severe drought event in Southwest China. Five numerical experiments were completed using the Noah land surface scheme, the Pleim-Xiu land surface scheme, the Noah-MP land surface schemes, the Noah- MP scheme with dynamic vegetation, and the Noah-MP scheme with dynamic vegetation and groundwater processes. In general, all the simulations reasonably reproduced the spatial and temporal variations in precipitation, but significant bias was also found, especially for the spatial pattern of simulated precipitation. The WRF simulations with the Noah-MP series land surface schemes performed slightly better than the WRF simulation with the Noah and Pleim-Xiu land surface schemes in reproducing the severe drought events in Southwest China. The leaf area index（LAI） simulated by the different land surface schemes showed significant deviations in Southwest China. The Pleim-Xiu scheme overestimated the value of LAI by a factor of two. The Noah-MP scheme with dynamical vegetation overestimated the magnitude of the annual cycle of the LAI, although the annual mean LAI was close to observations. The simulated LAI showed a long-term lower value from autumn 2009 to spring 2010 relative to normal years. This indicates that the LAI is a potential indictor to monitor drought events.     

Tropical land savannization: impact of global warming

This study investigates the impact of global warming on the savannization of the tropical land region and also examines the relative roles of the impact of the increase of greenhouse gas concentration and future changes in land cover on the tropical climate. For this purpose, a mechanistic–statistical–dynamical climate model with a bidirectional interaction between vegetation and climate is used. The results showed that climate change due to deforestation is more than that due to greenhouse gases in the tropical region. The warming due to deforestation corresponds to around 60% of the warming in the tropical region when the increase of CO₂ concentration is included together. However, the global warming due to deforestation is negligible. On the other hand, with the increase of CO₂ concentration projected for 2100, there is a lower decrease of evapotranspiration, precipitation and net surface radiation in the tropical region compared with the case with only deforestation. Differently from the case with only deforestation, the effect of the changes in the net surface radiation overcomes that due to the evapotranspiration, so that the warming in the tropical land region is increased. The impact of the increase of CO₂ concentration on a deforestation scenario is to increase the reduction of the areas covered by tropical forest (and a corresponding increase in the areas covered by savanna) which may reach 7.5% in future compared with the present climate. Compared with the case with only deforestation, drying may increase by 66.7%. This corroborates with the hypothesis that the process of savannization of the tropical forest can be accelerated in future due to global warming.     

Rain follows logging in the Amazon? Results from CAM3–CLM3

The impact of logging on precipitation in the Amazon region is investigated based on numerical experiments using the community atmosphere model version 3 coupled with the community land surface model version 3 (CAM3–CLM3). Three different representations of logging are examined, ranging from selective logging, to partial deforestation, to clear cut. Precipitation increases in response to modest selective logging, and decreases as the severity of logging progresses to partial deforestation and clear cut. Further experiments indicate that the increase of precipitation is mostly due to the decrease of surface albedo following selective logging, resulting from a low contrast between bare soil albedo and vegetation optical properties (i.e., leaf reflectance) in CLM3. This study demonstrates the complexity of representing land cover changes in climate models, and underlines the importance of accuracy in albedo measurement from satellite remote sensing.     

Customization of regional climate model (RegCM4) over Indian region

The regional climate model (RegCM4) is customized for 10-year climate simulation over Indian region through sensitivity studies on cumulus convection and land surface parameterization schemes. The model is configured over 30° E–120° E and 15° S–45° N at 30-km horizontal resolution with 23 vertical levels. Six 10-year (1991–2000) simulations are conducted with the combinations of two land surface schemes (BATS, CLM3.5) and three cumulus convection schemes (Kuo, Grell, MIT). The simulated annual and seasonal climatology of surface temperature and precipitation are compared with CRU observations. The interannual variability of these two parameters is also analyzed. The results indicate that the model simulated climatology is sensitive to the convection as well as land surface parameterization. The analysis of surface temperature (precipitation) climatology indicates that the model with CLM produces warmer (dryer) climatology, particularly over India. The warmer (dryer) climatology is due to the higher sensible heat flux (lower evapotranspiration) in CLM. The model with MIT convection scheme simulated wetter and warmer climatology (higher precipitation and temperature) with smaller Bowen ratio over southern India compared to that with the Grell and Kuo schemes. This indicates that a land surface scheme produces warmer but drier climatology with sensible heating contributing to warming where as a convection scheme warmer but wetter climatology with latent heat contributing to warming. The climatology of surface temperature over India is better simulated by the model with BATS land surface model in combination with MIT convection scheme while the precipitation climatology is better simulated with BATS land surface model in combination with Grell convection scheme. Overall, the modeling system with the combination of Grell convection and BATS land surface scheme provides better climate simulation over the Indian region.     

A dampened land use change climate response towards the tropics

In climate simulations we find a pronounced meridional (equator to pole) gradient of climate response to land cover change. Climate response approaches zero in the tropics, and increases towards the poles. The meridional gradient in climate response to land cover change results from damping feedbacks in the tropics, rather than from polar amplification. The main cause for the damping in the tropics is the decrease in cloud cover after deforestation, resulting in increased incoming radiation at the surface and a lower planetary albedo, both counteracting the increase in surface albedo with deforestation. In our simulations, deforestation was also associated with a decrease in sensible heat flux but not a clear signal in evaporation. Meridional differences in climate response have implications for attribution of observed climate change, as well as for climate change mitigation strategies.     

陆面过程参数化对太湖地区雷暴过程模拟的影响

以2010年8月发生在太湖地区的一次雷暴过程为例,利用WRF模式进行48 h的短期天气模拟,分析两个陆面参数化方案(Noah方案和RUC方案)对雷暴过程模拟的影响。对比模式结果与实况降水以及太湖地区两个站点的近地面要素表明:雷暴过程对陆面参数化方案的选取较为敏感,不同陆面参数化方案可影响雷暴发生的时间、地点及强度,两种方案的降水中心值差达40 mm以上,其中Noah方案所模拟的降水与实况更为接近。通过对两个方案模拟的物理量场的对比分析发现,RUC方案中对流发展滞后于Noah方案2 h;这表明陆面过程对雷暴等中尺度对流过程有显著的反馈作用,不同陆面参数化方案的使用影响雷暴发生的动力和热力作用,并改变雷暴的时空分布特征。陆面过程通过改变地面热通量输送影响边界层结构,使得水平和垂直方向上的风和温度等发生变化并产生辐合辐散,进而影响对流的启动时间和对流发展强度。由于对不同植被的参数化处理的差异,Noah方案对下垫面特征的描述能力优于RUC方案,尤其是对城市下垫面的处理,这也使得之后该方案模拟的雷暴发生时间更加接近于实况且雷暴过程更加强烈。