Coupling Terrestrial and Atmospheric Water Dynamics to Improve Prediction in a Changing Environment
Coupling Terrestrial and Atmospheric Water Dynamics to Improve Prediction in a Changing Environment
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耦合陆地和大气水动力学以改进不断变化的环境中的预测
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
M. Walter
中科院分区：
文献类型：
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作者：
S. Lyon;F. Dominguez;D. Gochis;N. Brunsell;C. Castro;F. Chow;Ying Fan;D. Fuka;Y. Hong;P. Kucera;S. Nesbitt;N. Salzmann;J. Schmidli;P. K. Snyder;A. Teuling;T. Twine;S. Levis;J. Lundquist;G. Salvucci;A. Sealy;M. Walter
人类已经深刻地影响了他们的环境。据估计，近三分之一的全球土地覆盖已经被改造，而大约40%的光合作用已经被占用。由于地下和大气之间的界面发生了变化，我们必须了解这种变化对区域和全球气候变化的影响。陆地表面异质性有时是局部和区域气候的主要调节器，因此，当陆地表面在一系列尺度上发生变化时，存在从土壤孔隙到大气环流等尺度上的潜在聚集和遥相关效应。人类对陆地表面过程的影响是至关重要的，在陆地-大气耦合的讨论中也必须考虑到这一点，因为它与气候和全球变化以及蒸散发和水流等局部过程有关。在这个关键的界面上，水文学家、大气科学家和生态学家必须了解他们的学科是如何相互作用和影响的。陆地表面的通量直接影响生态过程、大气动力学和陆地水文的预测。然而，在从大气和反之的角度考虑陆地水文时，数值模式作了许多简化。虽然这在当前用于预测的操作模型中可能是必要的，但它可能会对过程理解的进步造成障碍。这些简化可能会限制数值预测水如何在水循环的所有阶段中自我分配的能力。陆地和大气水动力学之间的反馈没有得到很好的理解，也没有被当前一代的陆地表面和大气模式所代表。这可能导致陆地-大气交换和大气水循环预测中的错误空间格局和异常时间持续性。需要跨学科的努力，不仅要确定，而且要量化在适当的时空尺度上陆地和大气水之间的反馈。这一点尤其正确，因为今天的年轻科学家将目光投向了通过研究和用于描述此类关联系统的操作模型来提高过程理解和预测技能。为了认识到这些挑战，最近在科罗拉多州博尔德的国家大气研究中心（NCAR）举行了一个初级教师和早期职业科学家论坛，旨在确定和描述反馈相互作用及其随之而来的空间和时间尺度，这对陆地和大气水动力学的耦合很重要。这个论坛的主要焦点是改进的过程理解，而不是操作产品，因为将更现实的物理结合到操作模型的可能性在计算上是禁止的。我们通过关注下面描述和讨论的三个框架问题，通过更好地理解过程来改进可预测性。
Humans have profoundly influenced their environment. It has been estimated that nearly one-third of the global land cover has been modified while approximately 40% of the photosynthesis has been appropriated. As the interface between the subsurface and the atmosphere is altered, it is imperative that we understand the influence this alteration has in terms of changing regional and global climates. Land surface heterogeneity is sometimes a principal modulator of local and regional climates and, as such, there are potential aggregation and teleconnection effects ranging in scales from soil pores to the general atmospheric circulation when the land surface is altered across a range of scales. The human fingerprint on land surface processes is critical and must also be accounted for in the discourse on land-atmosphere coupling as it pertains to climate and global change as well as local processes such as evapotranspiration and streamflow. It is at this pivotal interface where hydrologists, atmospheric scientists and ecologists must understand how their disciplines interact and influence each other.Fluxes across the land-surface directly influence predictions of ecological processes, atmospheric dynamics, and terrestrial hydrology. However, many simplifications are made in numerical models when considering terrestrial hydrology from the view point of the atmosphere and visa-versa. While this may be a necessity in the current generation of operational models used for forecasting, it can create obstacles to the advancement of process understanding. These simplifications can limit the numerical prediction capabilities on how water partitions itself throughout all phases of the water cycle. The feedbacks between terrestrial and atmospheric water dynamics are not well understood or represented by the current generation of operational land-surface and atmospheric models. This can lead to erroneous spatial patterns and anomalous temporal persistence in land-atmosphere exchanges and atmospheric water cycle predictions. Cross-disciplinary efforts are needed not only to identify but also to quantify feedbacks between terrestrial and atmospheric water at appropriate spatiotemporal scales. This is especially true as today’s young scientists set their sights on improving process understanding and prediction skill from both research and operational models used to describe such linked systems.In recognition of these challenges, a junior faculty and early career scientist forum was recently held at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado with the intent of identifying and characterizing feedback interactions, and their attendant spatial and temporal scales, important for coupling terrestrial and atmospheric water dynamics. The primary focus of this forum is on improved process understanding, rather than operational products, as the possibility of incorporating more realistic physics into operational models is computationally prohibitive. We approached the subject of improved predictability through better process understanding by focusing on the following three framework questions described and discussed below.