2050年前中国雾日变化趋势的预估

 利用1971-2005年中国591个气象台站的雾日资料以及逐日最低气温、相对湿度、平均风速资料,分析了35 a来中国各区域年雾日数与这些因子的相关关系,并利用IPCC第四次评估报告所提供的模式数据资料,针对3种不同的排放情景,对21世纪上半叶各区域年平均雾日进行预估。结果表明：对划分的9个雾区的年雾日数的回归方程的拟合效果较好,可以用来进行预估;未来50 a中国大部分地区雾日呈明显减少的变化趋势,在A1B,A2和B1情景下,雾日减少的平均幅度分别为16.2%,13.4%和12.9%。未来50 a中国雾日预估结果的空间分布显示：3种情景下未来中国大部分雾区雾日数都将减少,个别地区雾日数有增加趋势,其中A1B情景下雾日减少区的减少趋势最明显,而B1情景下雾日增加区的增加趋势最明显。     

Investigating the impact of climate change on New York City’s primary water supply

Future climate scenarios projected by three different General Circulation Models and a delta-change methodology are used as input to the Generalized Watershed Loading Functions – Variable Source Area (GWLF-VSA) watershed model to simulate future inflows to reservoirs that are part of the New York City water supply system (NYCWSS). These inflows are in turn used as part of the NYC OASIS model designed to simulate operations for the NYCWSS. In this study future demands and operation rules are assumed stationary and future climate variability is based on historical data to which change factors were applied in order to develop the future scenarios. Our results for the West of Hudson portion of the NYCWSS suggest that future climate change will impact regional hydrology on a seasonal basis. The combined effect of projected increases in winter air temperatures, increased winter rain, and earlier snowmelt results in more runoff occurring during winter and slightly less runoff in early spring, increased spring and summer evapotranspiration, and reduction in number of days the system is under drought conditions. At subsystem level reservoir storages, water releases and spills appear to be higher and less variable during the winter months and are slightly reduced during summer. Under the projected future climate and assumptions in this study the NYC reservoir system continues to show high resilience, high annual reliability and relatively low vulnerability.     

Future climate resources for tourism in Europe based on the daily Tourism Climatic Index

Climate is an important resource for many types of tourism. One of several metrics for the suitability of climate for sightseeing is Mieczkowski’s “Tourism Climatic Index” (TCI), which summarizes and combines seven climate variables. By means of the TCI, we analyse the present climate resources for tourism in Europe and projected changes under future climate change. We use daily data from five regional climate models and compare the reference period 1961–1990 to the A2 scenario in 2071–2100. A comparison of the TCI based on reanalysis data and model simulations for the reference period shows that current regional climate models capture the important climatic patterns. Currently, climate resources are best in Southern Europe and deteriorate with increasing latitude and altitude. With climate change the latitudinal band of favourable climate is projected to shift northward improving climate resources in Northern and Central Europe in most seasons. Southern Europe’s suitability for sightseeing tourism drops strikingly in the summer holiday months but is partially compensated by considerable improvements between October and April.     

Regional climate change patterns identified by cluster analysis

Climate change caused by anthropogenic greenhouse emissions leads to impacts on a global and a regional scale. A quantitative picture of the projected changes on a regional scale can help to decide on appropriate mitigation and adaptation measures. In the past, regional climate change results have often been presented on rectangular areas. But climate is not bound to a rectangular shape and each climate variable shows a distinct pattern of change. Therefore, the regions over which the simulated climate change results are aggregated should be based on the variable(s) of interest, on current mean climate as well as on the projected future changes. A cluster analysis algorithm is used here to define regions encompassing a similar mean climate and similar projected changes. The number and the size of the regions depend on the variable(s) of interest, the local climate pattern and on the uncertainty introduced by model disagreement. The new regions defined by the cluster analysis algorithm include information about regional climatic features which can be of a rather small scale. Comparing the regions used so far for large scale regional climate change studies and the new regions it can be shown that the spacial uncertainty of the projected changes of different climate variables is reduced significantly, i.e. both the mean climate and the expected changes are more consistent within one region and therefore more representative for local impacts.     

The role of the simulation setup in a long-term high-resolution climate change projection for the southern African region

High-resolution regional climate change simulations have proven to offer an added value compared to available global climate model simulations. However, over many regions of the globe, long-term high-resolution climate change projections are rather sparse. We present a transient high-resolution climate change projection with the regional climate model with the regional climate model REMO over the southern African region, following the SRES A1B emission scenario. The simulation was conducted at 18?km grid spacing for the period from 1960 to 2100, making it to the longest available climate change projection at such a high resolution for the region. In the first part of the study, we focus on the impact of the model setup on the simulated rainfall over the southern African region. In the standard setup, we used the output of the global climate model ECHAM5/MPIOM directly to force REMO. This setup led to a very strong wet bias over the region. Changing it to the double-nesting setup significantly reduced this bias, but a substantial wet bias still persists. The remaining bias could partly be attributed to a warm bias in the SST forcing over the southern Atlantic Ocean. Thus, we applied an SST correction based on the anomaly approach to the data, which led to a further improvement of the rainfall simulation. As the SST bias in the southern Atlantic is a common feature of all global climate models assessed by the IPCC, we recommend the chosen model setup, including the SST correction, as general procedure for dynamical downscaling studies over the southern African region. In the second part, we present the projected spatial and temporal changes of temperature and precipitation, including several rainfall characteristics, over the southern African region. Herby we compare the projections of the high-resolution REMO simulation to those of the forcing regional and global models. We generally find that for temperature the magnitude of the projected changes of the regional model only slightly differs from the GCM projection; however, the spatial patterns are much better resolved in the RCM projections. For precipitation, REMO shows a more intense drying toward the end of the twenty-first century than it is simulated by the global model. This can have a major influence when investigating the impacts of future climate change on a regional or even local scale. In combination with the improved spatial patterns, the application of high-resolution climate change information could therefore improve the results of such applications.     

甘肃省高等级公路沿线大雾天气气候特征及其预报服务

利用甘肃省高等级公路沿线20个气象站1971~2004年气候资料,分析了大雾天气的地域分布及其天气气候特征,得出甘肃省高等级公路沿线的大雾天气不仅具有明显的地域差异,而且具有明显的年际、季节、昼夜和局地性的变化特征,并在此基础上将不同路段的大雾天气划分为不同的预报服务期,为高等级公路沿线的大雾预报服务提供依据。     

Multidecadal simulation of coastal fog with a regional climate model

In order to model stratocumulus clouds and coastal fog, we have coupled the University of Washington boundary layer model to the regional climate model, RegCM (RegCM-UW). By comparing fog occurrences observed at various coastal airports in the western United States, we show that RegCM-UW has success at modeling the spatial and temporal (diurnal, seasonal, and interannual) climatology of northern California coastal fog. The quality of the modeled fog estimate depends on whether coast-adjacent ocean or land grid cells are used; for the model runs shown here, the oceanic grid cells seem to be most appropriate. The interannual variability of oceanic northern California summertime fog, from a multi-decadal simulation, has a high and statistically significant correlation with the observed interannual variability (r = 0.72), which indicates that RegCM-UW is capable of investigating the response of fog to long-term climatological forcing. While RegCM-UW has a number of aspects that would benefit from further investigation and development, RegCM-UW is a new tool for investigating the climatology of coastal fog and the physical processes that govern it. We expect that with appropriate physical parameterizations and moderate horizontal resolution, other climate models should be capable of simulating coastal fog. The source code for RegCM-UW is publicly available, under the GNU license, through the International Centre for Theoretical Physics.     

A regional climate model downscaling projection of China future climate change

Climate changes over China from the present (1990–1999) to future (2046–2055) under the A1FI (fossil fuel intensive) and A1B (balanced) emission scenarios are projected using the Regional Climate Model version 3 (RegCM3) nests with the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM). For the present climate, RegCM3 downscaling corrects several major deficiencies in the driving CCSM, especially the wet and cold biases over the Sichuan Basin. As compared with CCSM, RegCM3 produces systematic higher spatial pattern correlation coefficients with observations for precipitation and surface air temperature except during winter. The projected future precipitation changes differ largely between CCSM and RegCM3, with strong regional and seasonal dependence. The RegCM3 downscaling produces larger regional precipitation trends (both decreases and increases) than the driving CCSM. Contrast to substantial trend differences projected by CCSM, RegCM3 produces similar precipitation spatial patterns under different scenarios except autumn. Surface air temperature is projected to consistently increase by both CCSM and RegCM3, with greater warming under A1FI than A1B. The result demonstrates that different scenarios can induce large uncertainties even with the same RCM-GCM nesting system. Largest temperature increases are projected in the Tibetan Plateau during winter and high-latitude areas in the northern China during summer under both scenarios. This indicates that high elevation and northern regions are more vulnerable to climate change. Notable discrepancies for precipitation and surface air temperature simulated by RegCM3 with the driving conditions of CCSM versus the model for interdisciplinary research on climate under the same A1B scenario further complicated the uncertainty issue. The geographic distributions for precipitation difference among various simulations are very similar between the present and future climate with very high spatial pattern correlation coefficients. The result suggests that the model present climate biases are systematically propagate into the future climate projections. The impacts of the model present biases on projected future trends are, however, highly nonlinear and regional specific, and thus cannot be simply removed by a linear method. A model with more realistic present climate simulations is anticipated to yield future climate projections with higher credibility.     

Modeling the impacts of reforestation on future climate in West Africa

This study investigates the potential impacts of reforestation in West Africa on the projected regional climate in the near two decades (2031–2050) under the SRES A1B scenario. A regional climate model (RegCM3) forced with a global circulation model (ECHAM5) simulations was used for the study. The study evaluates the capability of the regional model in simulating the present-day climate over West Africa, projects the future climate over the region and investigates impacts of seven hypothetical reforestation options on the projected future climate. Three of these reforestation options assume zonal reforestation over West Africa (i.e., over the Sahel, Savanna and Guinea), while the other four assume random reforestation over Nigeria. With the elevated GHGs (A1B scenario), a warmer and drier climate is projected over West Africa in 2031–2050. The maximum warming (+2.5°C) and drying (?2?mm?day^?1) occur in the western part of the Sahel because the West Africa Monsoon (WAM) flow is stronger and deflects the cool moist air more eastward, thereby lowering the warming and drying in the eastern part. In the simulations, reforestation reduces the projected warming and drying over the reforested zones but increases them outside the zones because it influences the northward progression of WAM in summer. It reduces the speed of the flow by weakening the temperature gradient that drives the flow and by increasing the surface drag on the flow over the reforested zone. Hence, in summer, the reforestation delays the onset of monsoon flow in transporting cool moist air over the area located downwind of the reforested zone, consequently enhancing the projected warming and drying over the area. The impact of reforesting Nigeria is not limited to the country; while it lowers the warming over part of the country (and over Togo), it increases the warming over Chad and Cameroon. This study, therefore, suggests that using reforestation to mitigate the projected future climate change in West Africa could have both positive and negative impacts on the regional climate, reducing temperature in some places and increasing it in others. Hence, reforestation in West Africa requires a mutual agreement among the West African nations because the impacts of reforestation do not recognize political boundaries.     

Sediment related impacts of climate change and reservoir development in the Lower Mekong River Basin: a case study of the Nam Ou Basin,Lao PDR

This study applies the soil and water assessment tool (SWAT), with climate (precipitation and temperature) outputs from four general circulation models (GCMs) and a regional circulation model (PRECIS), to evaluate (1) the impacts of climate change on reservoir sedimentation and (2) the impacts of climate change and reservoir development on sediment outflow in the Nam Ou River Basin located in northern Laos. Three reservoir–density scenarios, namely one reservoir (1R), three reservoirs in series (3R), and five reservoirs in series (5R), were evaluated for both no climate change and climate change conditions. The results show that under no climate change conditions, by 2070, around 17, 14, and 15% of the existing reservoir storage volume in the basin will be lost for 1R, 3R, and 5R scenarios, respectively. Notably, under climate change scenario with highest changes in erosion and sediment outflux from the basin, the additional reduction in reservoir storage capacity due to sedimentation is estimated to be nearly 26% for 1R, 21% for 3R, and 23% for 5R. Climate change alone is projected to change annual sediment outflux from the basin by ?20 to 151%. In contrast, the development of reservoirs in the basin will reduce the annual sediment outflux from the basin varying from 44 to 80% for 1R, 44–81% for 3R, and 66–89% for 5R, considering climate change. In conclusion, climate change is expected to increase the sediment yield of the Nam Ou Basin, resulting in faster reduction of the reservoir’s storage capacity. Sediment yield from the Nam Ou River Basin is likely to decrease significantly due to the trapping of sediment by planned reservoirs. The impact of reservoirs is much more significant than the impact of climate change on the sediment outflow of the basin. Hence, it is necessary to investigate appropriate reservoir sediment management strategies.     

A double-resolution transient RCM climate change simulation experiment for near-coastal eastern zone of the Eastern Mediterranean region

A double-resolution regional experiment on hydrodynamic simulation of climate over the eastern Mediterranean (EM) region was performed using an International Center for Theoretical Physics, Trieste RegCM3 model. The RegCM3 was driven from the lateral boundaries by the data from the ECHAM5/MPI-OM global climate simulation performed at the MPI-M, Hamburg and based on the A1B IPCC scenario of greenhouse gases emission. Two simulation runs for the time period 1960-2060, employing spatial resolutions of 50?km/14?L and 25?km/18?L, are realized. Time variations of the differences in the space distributions of simulated climate parameters are analyzed to evaluate the role of smaller scale effects. Both least-square linear and non-linear trends of several characteristics of the EM climate are evaluated in the study. One of the key findings with regard to linear trends is a notable and statistically significant precipitation drop over the near coastal EM zone during December-February and September-November. Statistically significant positive air temperature trends are projected over the entire EM region during the four seasons. Also projected are increases in air temperature extremes and the relative contribution of convective processes in the Southern Mediterranean coastal zone (ECM) region. A notable sensitivity of projected larger-scale climate change signals to smaller-scale effects is also demonstrated.     

Climate-model induced differences in the 21st century global and regional glacier contributions to sea-level rise

The large uncertainty in future global glacier volume projections partly results from a substantial range in future climate conditions projected by global climate models. This study addresses the effect of global and regional differences in climate input data on the projected twenty-first century glacier contribution to sea-level rise. Glacier volume changes are calculated with a surface mass balance model combined with volume-area scaling, applied to 89 glaciers in different climatic regions. The mass balance model is based on a simplified energy balance approach, with separated contributions by net solar radiation and the combined other fluxes. Future mass balance is calculated from anomalies in air temperature, precipitation and atmospheric transmissivity, taken from eight global climate models forced with the A1B emission scenario. Regional and global sea-level contributions are obtained by scaling the volume changes at the modelled glaciers to all glaciers larger than 0.1 km² outside the Greenland and Antarctic ice sheets. This results in a global value of 0.102 ± 0.028 m (multi-model mean and standard deviation) relative sea-level equivalent for the period 2012–2099, corresponding to 18 ± 5 % of the estimated total volume of glaciers. Glaciers in the Antarctic, Alaska, Central Asia and Greenland together account for 65 ± 4 % of the total multi-model mean projected sea-level rise. The projected sea-level contribution is 35 ± 17 % larger when only anomalies in air temperature are taken into account, demonstrating an important compensating effect by increased precipitation and possibly reduced atmospheric transmissivity. The variability in projected precipitation and atmospheric transmissivity changes is especially large in the Arctic regions, making the sea-level contribution for these regions particularly sensitive to the climate model used. Including additional uncertainties in the modelling procedure and the input data, the total uncertainty estimate for the future projections becomes ±0.063 m.     

A linear projection for the timing of unprecedented climate in Korea

Recently we have had abnormal weather events worldwide that are attributed by climate scientists to the global warming induced by human activities. If the global warming continues in the future and such events occur more frequently and someday become normal, we will have an unprecedented climate. This study intends to answer when we will have an unprecedented warm climate, focusing more on the regional characteristics of the timing of unprecedented climate. Using an in-situ observational data from weather stations of annual-mean surface air temperature in Korea from 1973 to 2015, we estimate a timing of unprecedented climate with a linear regression method. Based on the in-situ data with statistically significant warming trends at 95% confidence level, an unprecedented climate in Korea is projected to occur first in Cheongju by 2043 and last in Haenam by 2168. This 125-year gap in the timing indicates that a regional difference in timing of unprecedented climate is considerably large in Korea. Despite the high sensitivity of linear estimation to the data period and resolution, our findings on the large regional difference in timing of unprecedented climate can give an insight into making policies for climate change mitigation and adaptation, not only for the central government but for provincial governments.     

Competition of NAO regime changes and increasing greenhouse gases and aerosols with respect to Arctic climate projections

Regional magnitudes and patterns of Arctic winter climate changes in consequence of regime changes of the North Atlantic Oscillation (NAO) are analyzed using a regional atmospheric climate model. The regional model has been driven with data of positive and negative NAO phases from a control simulation as well as from a time-dependent greenhouse gas and aerosol scenario simulation. Both global model simulations include a quite realistic interannual variability of the NAO with pronounced decadal regime changes and no or rather weak long-term NAO trends. The results indicate that the effects of NAO regime changes on Arctic winter temperatures and precipitation are regionally significant over most of northwestern Eurasia and parts of Greenland. In this regard, mean winter temperature variations of up to 6 K may occur over northern Europe. Precipitation and synoptic variability are also regionally modified by NAO regime changes, but not as significantly as temperatures. However, the climate changes associated with the NAO are in some regions clearly stronger than those attributed to enhanced greenhouse gases and aerosols, indicating that projected global changes of the atmospheric composition and internal circulation changes are competing with each other in their importance for the Arctic climate evolution in the near future. The knowledge of the future NAO trend on decadal and longer time scales appears to be vitally important in terms of a regional assessment of climate scenarios for the Arctic.     

CSIRO Mk3.6.0模式及其驱动下RegCM4.4模式对中国气候变化的预估

使用区域气候模式RegCM4.4,对全球模式CSIRO-Mk3.6.0在RCP4.5情景下的气候变化试验结果（1950-2100年）在东亚地区进行25 km动力降尺度试验,比较了CSIRO-Mk3.6.0和RegCM4.4预估中国地区的21世纪气候变化。结果表明,两个模式预估未来中国地区气温持续升高,升温幅度具有区域性特征,RegCM4.4预估区域平均升温幅度低于CSIRO-Mk3.6.0,但二者年际波动基本一致。两个模式预估未来降水在中国西部以持续增加为主,东部则表现出较大的不一致性,预估区域平均年降水量变化不大,呈现冬季明显增加,夏季微弱减少的特点。此外,为了解区域气候模式对中国降水预估的不确定性,对本研究和以往RegCM3使用相同分辨率模拟得到的未来降水预估进行了对比,两个区域模式预估中国西部大部分地区未来降水一致性增加,东部存在明显不一致（冬季中、高纬除外）。     

生态环境变化夺雾的影响

西双版纳地区是的著名的热带雨林多雾区,但７０年代末以来,雾日明显减少,德层明显减弱。１９９７年１１月２３－３０日,实施了一项雾的外场试验计划,本文利用景洪（生态环境变化较大）和勐养９生态环境变化不大）的宏、微观观测资料,对比分析了雾的宏、微观结构和物理过程,并结合气候资料,讨论了生态环境变化对雾的影响。     

Development of an airmass-based regional climate change scenario

Summary In middle latitudes, regional climates are largely determined by the frequency and character of different airmasses advected across the region. Airmass characteristics and frequencies are expected to be different in a warmer world. General circulation models are, for example, unanimous in projecting large temperature changes for high latitudes, the source region for polar airmasses. Conventional approaches to the construction of regional climate change scenarios are not able to capture such differences between airmasses. Here we present a new approach that assigns each day in the observed and model-produced records to one of three classes based on the upper-level flow, the steering current for airmasses. This approach permits an evaluation of a model's ability to reproduce the observed regional climate in terms of airmasses which is more insightful than a comparison of monthly means. The model used here, the CCM0 version of the NCAR model, was found to reproduce many of the observed December airflow features (the month chosen to demonstrate the approach) for the Lake Superior basin. The approach also permits a more insightful analysis of the projected changes under 2*CO₂ conditions. The CCM0 projects a significant warming and moistening only for the northerly airflows. The northerly flows are also projected to become more frequent. To illustrate the significance of these results, daily scenarios of climate change were constructed from these projections and used in a lake evaporation model. It is found that the changes in the northerly flows projected by this model translate into a 19% reduction in the evaporative power of the air over Lake Superior (wind speeds held at present level).With 3 Figures     

Changes to the drivers of fire weather with a warming climate – a case study of southeast Tasmania

Projected changes to the global climate system have great implications for the incidence of large infrequent fires in many regions. Here we examine the synoptic-scale and local-scale influences on the incidence of extreme fire weather days and consider projections of the large-scale mean climate to explore future fire weather projections. We focus on a case study region with periodic extreme fire dangers; southeast Tasmania, Australia. We compare the performance of a dynamically downscaled regional climate model with Global Climate Model outputs as a tool for examining the local-scale influences while accounting for high regional variability. Many of the worst fires in Tasmania and the southeast Australian region are associated with deep cold fronts and strong prefrontal winds. The downscaled simulations reproduce this synoptic type with greater fidelity than a typical global climate model. The incidence of systems in this category is projected to increase through the century under a high emission scenario, driven mainly by an increase in the temperature of air masses, with little change in the strength of the systems. The regional climate model projected increase in frequency is smaller than for the global climate models used as input, with a large model range and natural variability. We also demonstrate how a blocking Foehn effect and topographic channelling contributed to the extreme conditions during an extreme fire weather day in Tasmania in January 2013. Effects such as these are likely to contribute to high fire danger throughout the century. Regional climate models are useful tools that enable various meteorological drivers of fire danger to be considered in projections of future fire danger.     

Contrasting regional and global climate simulations over South Asia

Climate Dynamics - Two ensembles of climate simulations, one global and one regional, are used to investigate model errors and projected climate change in seasonal mean temperature and...     

Probabilistic forecasting of seasonal drought behaviors in the Huai River basin,China

Results from high resolution 7-km WRF regional climate model (RCM) simulations are used to analyse changes in the occurrence frequencies of heat waves, of precipitation extremes and of the duration of the winter time freezing period for highly populated urban areas in Central Europe. The projected climate change impact is assessed for 11 urban areas based on climate indices for a future period (2021–2050) compared to a reference period (1971–2000) using the IPCC AR4 A1B Scenario as boundary conditions. These climate indices are calculated from daily maximum, minimum and mean temperatures as well as precipitation amounts. By this, the vulnerability of these areas to future climate conditions is to be investigated. The number of heat waves, as well as the number of single hot days, tropical nights and heavy precipitation events is projected to increase in the near future. In addition, the number of frost days is significantly decreased. Probability density functions of monthly mean summer time temperatures show an increase of the 95th percentile of about 1–3 °C for the future compared with the reference period. The projected increase of cooling and decrease of heating degree days indicate the possible impact on urban energy consumption under future climate conditions.