IPCC Climate Change Data: ECHAM4 B2a Model: 2050 Wind Speed

The ECHAM climate model has been developed from the ECMWF atmospheric model (therefore the first part of its name: EC) and a comprehensive parameterisation package developed at Hamburg therefore the abbreviation HAM) which allows the model to be used for climate simulations. The model is a spectral transform model with 19 atmospheric layers and the results used here derive from experiments performed with spatial resolution T42 (which approximates to about 2.8 degrees longitude/latitude resolution). The model has also been used at resolutions in the range T21 to T106. ECHAM4 is the current generation in the line of ECHAM models (Roeckner, et al., 1992). A summary of developments regarding model physics in ECHAM4 and a description of the simulated climate obtained with the uncoupled ECHAM4 model is given in Roeckner et al. (1996). The initial sea surface temperature and sea-ice data is the COLA/CAC AMIP SST and sea-ice data set. The mean terrain heights are computed from high resolution US Navy data set. The fraction of grid area covered by vegetation based on the Wilson and Henderson-Sellers (1985) data set. The ocean albedo is a function of solar zenith angle and the land albedo from the satellite data of Geleyn and Preuss (1983). A diurnal cycle and gravity wave-drag is included. The time-step of the model is 24 minutes, except for radiation which uses two hours. The ocean model is an updated version of the isopycnal model (OPYC3) developed by Josef Oberhuber (Oberhuber, 1993) at the Max-Planck-Institute for Meteorology, Hamburg, Germany. The name OPYC is derived from Ocean and isoPYCnal co-ordinates. The concept to use isopycnals as the vertical co-ordinate system for an OGCM is based on the observation that the interior ocean behaves as a rather conservative fluid. Even over long distances the origin of water masses can be traced back by considering the distribution of active or passive tracers. Treating the ocean as a conservative fluid fails in areas of significant turbulence activity such as the surface boundary layer. A surface mixed-layer is therefore coupled to the interior ocean in order to represent near-surface vertical mixing and to improve the response time-scales to atmospheric forcing which is controlled by the mixed-layer thickness. Since the model is designed for studies on large scales, a sea ice model with rheology is included and serves the purpose of de-coupling the ocean from extreme high-latitude winter conditions and promotes a realistic treatment of the salinity forcing due to melting or freezing sea ice. The experiments from which results are used here are the 1000-year unforced control simulation using the coupled ECHAM4/OPYC3 model and then two climate change simulations. The greenhouse gas only forced experiment (referred to as GGa1) used historical greenhouse gas forcing from 1860 to 1990 followed by a 1 per cent annum increase in radiative forcing from 1990 to 2099. The greenhouse gas and sulphate aerosol forced experiment (referred to as GSa1) used the GGa1 forcing, plus the negative forcing due to sulphate aerosols. This was represented by means of an increase in clear-sky surface albedo proportional to the local sulphate loading. The indirect effects of aerosols were not simulated. For 1860 to 1990 the historic sulphate aerosol forcing estimate was used and for 1990 to 2049 the aerosol forcing estimated for the IS92a emissions scenario. The GSa1 experiment did not extend beyond 2049. Fuller details of the ECHAM4/OPYC3 coupled model can befound at the DDC Yellow Pages.Several papers describe results using this version of the model - see Bacher et al. (1998), Oberhuber et al. (1998), Zhang et al. (1998). The climate sensitivity of ECHAM4 is about 2.6 degrees C.The A2 world consolidates into a series of roughly continental economic regions, emphasizing local cultural roots. In some regions, increased religious participation leads many to reject a materialist path and to focus attention on contributing to the local community. Elsewhere, the trend is towards ncreased investment in education and science and growth in economic productivity. Social and political structures diversify with some regions moving towards stronger welfare systems and reduced income inequality, while others move towards "lean" government. Environmental concerns are relatively weak, although some attention is paid to bringing local pollution under control and maintaining local environmental amenities. The A2 world sees more international tensions and less cooperation than in A1 or B1. People, ideas and capital are less mobile so that technology diffuses slowly. International disparities in productivity, and hence income per capita, are maintained or increased. With the emphasis on family and community life, fertility rates decline only slowly, although they vary among regions. Hence, this scenario family has high population growth (to 15 billion by 2100) with comparatively low incomes per capita relative to the A1 andB1 worlds, at US$7,200 in 2050 and US$16,000 in 2100.Technological change is rapid in some regions and slow in others as industry adjusts to local resource endowments, culture, and education levels. Regions with abundant energy and mineral resources evolve more resource intensive economies, while those poor in resources place very high priority on minimizing import dependence through technological innovation to improve resource efficiency and make use of substitute inputs. The fuel mix in different regions is determined primarily by resource availability. And divisions among regions persist in terms of their mix of technologies, with high-income but resource-poor regions shifting toward advanced post fossil technologies (renewables in regions of large land availability, nuclear in densely populated, resource poor regions) and low-income resource-rich regions generally relying on older fossil technologies.With substantial food requirements, agricultural productivity is one of the main focus areas for innovation and RD efforts in this future. Initially high levels of soil erosion and water pollution are eventually eased through the local development of more sustainable high-yield agriculture.Although attention is given to potential local and regional environmental damage, it is not uniform across regions. For example, sulfur and particulate emissions are reduced in Asia due to impacts on human health and agricultural production but increase in Africa as a result of the intensified exploitation of coal and other mineral resources. The A2 world sees high energy and carbon intensity, and correspondingly high GHG emissions. Its CO2 emissions are the highest of all four scenario families. Data are available for the following periods: 1961-1990, 2010-2039; 2040-2069; and 2090-2099, mean and monthly change fields.ECHAM气候模式（ECHAM climate model）由欧洲中期天气预报中心（European Centre for Medium-Range Weather Forecasts, ECMWF）的大气模式发展而来（因此其名称的前半部分为EC），并搭载了汉堡研发的一套综合参数化方案包（因此缩写为HAM），使其可用于气候模拟。该模式为谱变换模式，包含19个大气分层，本文所用的模拟结果来自空间分辨率为T42的试验（该分辨率近似对应2.8度的经纬度分辨率）。该模式也曾在T21至T106的分辨率范围内运行。ECHAM4是ECHAM系列模式的当前版本（Roeckner等人，1992年）。Roeckner等人（1996年）总结了ECHAM4的模式物理过程发展情况，并描述了未耦合ECHAM4模式模拟得到的气候特征。初始海表温度与海冰数据采用COLA/CAC AMIP海表温度及海冰数据集。平均地形高度取自高分辨率美国海军数据集。植被覆盖的格点面积占比基于Wilson与Henderson-Sellers（1985年）的数据集。海洋反照率为太阳天顶角的函数，陆地反照率则取自Geleyn与Preuss（1983年）的卫星数据。模式包含日循环与重力波拖曳过程。模式的时间步长为24分钟，辐射过程的时间步长则为2小时。 海洋模式是由德国汉堡马克斯·普朗克气象研究所的Josef Oberhuber开发的等密度坐标海洋模式（isopycnal model, OPYC3）的更新版本（Oberhuber，1993年）。OPYC这一名称源自Ocean（海洋）与isoPYCnal（等密度面）。将等密度面作为海洋环流模式（Ocean General Circulation Model, OGCM）的垂直坐标系的理念，基于海洋内部近似为保守流体的观测结果：即使在长距离范围内，仍可通过追踪活性或惰性示踪剂的分布来追溯水团的起源。将海洋视为保守流体的假设在湍流活动显著的区域（如表面边界层）并不成立，因此需将表面混合层与海洋内部耦合，以表征近地表垂直混合过程，并改善受混合层厚度控制的、对大气强迫的响应时间尺度。由于该模式旨在用于大尺度研究，因此还包含了具有流变学特性的海冰模式，其作用是将海洋与高纬度冬季极端条件解耦，并更真实地处理海冰融化或冻结所导致的盐度强迫过程。 本文所用的结果来自两类试验：一是使用耦合ECHAM4/OPYC3模式开展的1000年无强迫控制模拟，二是两项气候变化模拟试验。仅受温室气体强迫的试验（记为GGa1）采用了1860年至1990年的历史温室气体强迫，随后自1990年至2099年以每年1%的速率增加辐射强迫。同时受温室气体与硫酸盐气溶胶强迫的试验（记为GSa1）在GGa1强迫的基础上，叠加了硫酸盐气溶胶产生的负强迫，该强迫通过与局地硫酸盐载荷成正比的晴空地表反照率增加来表征，未模拟气溶胶的间接效应。1860年至1990年采用历史硫酸盐气溶胶强迫估算值，1990年至2049年采用针对IS92a排放情景的气溶胶强迫估算值。GSa1试验的模拟时长未超过2049年。关于ECHAM4/OPYC3耦合模式的更多细节可参见DDC黄页。已有多篇文献使用该版本模式开展研究并发表结果，例如Bacher等人（1998年）、Oberhuber等人（1998年）以及Zhang等人（1998年）。ECHAM4的气候敏感度约为2.6摄氏度。 A2情景下，世界将整合为若干大致以大陆为界的经济区域，强调本地文化根源。部分区域内，宗教参与度的提升使得许多人摒弃物质主义路径，转而专注于为本地社区做贡献。而在其他区域，趋势则是加大对教育与科学的投入，提升经济生产率。社会与政治结构呈现多元化：部分区域建立更完善的福利体系，缩小收入差距；而另一些区域则转向“小政府”模式。环境问题相对不受重视，尽管部分区域会关注控制本地污染与维护本地环境宜居性。与A1或B1情景相比，A2情景下国际紧张局势更多，合作更少。人员、思想与资本的流动性更低，技术传播速度缓慢。国际间的生产率差异，进而人均收入差异，将维持甚至扩大。由于重视家庭与社区生活，生育率仅缓慢下降，但区域间存在差异。因此，该情景家族的人口增长较快，到2100年将达到150亿，且相对于A1与B1情景，人均收入较低：2050年为7200美元，2100年为16000美元。部分区域的技术变革迅速，另一部分则较为缓慢，工业会根据本地资源禀赋、文化与教育水平进行调整。能源与矿产资源丰富的区域会发展资源密集型经济，而资源匮乏的区域则将通过技术创新提升资源利用效率、开发替代投入品，以最大限度降低对进口的依赖，作为首要目标。不同区域的燃料结构主要由资源可获得性决定。区域间的技术结构差异持续存在：高收入但资源匮乏的区域将转向先进的后化石燃料技术（土地资源丰富的区域发展可再生能源，人口稠密、资源匮乏的区域发展核电），而低收入且资源丰富的区域通常仍依赖老旧的化石燃料技术。由于粮食需求庞大，农业生产率是该未来情景下创新与研发（Research and Development, RD）工作的核心重点之一。最初严重的土壤侵蚀与水污染问题，最终将通过本地发展可持续的高产农业得到缓解。尽管关注潜在的本地与区域环境破坏，但这种关注在各区域并不均衡。例如，由于对人类健康与农业生产的影响，亚洲的硫与颗粒物排放有所减少，而非洲则因加大煤炭与其他矿产资源的开发力度，相关排放有所增加。A2情景下的能源与碳强度较高，相应的温室气体排放量也较高，其二氧化碳排放量是四个情景家族中最高的。 可用数据涵盖以下时段：1961-1990年、2010-2039年、2040-2069年以及2090-2099年，包含均值与月变化场。