Calculating the rate of Antarctic Bottom Water formation using new theory, fine-scale modelling and observations

地球的赤道地区比极地地区接收更多的太阳能。额外的热量通过大气和海洋的循环以大致相等的比例向极地输送。温暖的表面水进入极地地区，在那里释放热量。随着这些表层海水的冷却，它们可能会开始冻结形成海冰，这会向海洋中释放出稠密的盐水。地表冷却和卤水释放的结合导致地表水变得足够稠密，从而下沉。这样形成的冷底水向赤道方向流动，平衡了向极地表面的流动。底水产生的位置和机制影响海洋环流的空间分布和强度，这有助于决定天气。气候模型和观测的证据表明，南极洲周围的底水形成将受到全球变暖的影响，并将影响南半球和北半球的气候和天气。为了准确预测未来的气候变化，气候模型需要对南极洲周围的底层水形成有足够的描述，而这是目前所缺乏的。由于其有限的空间分辨率和简化的物理，气候模型不能充分反映导致底水形成的小规模过程。气候模型通常产生的底层水太少，这些水太温暖和新鲜，这被归因于没有充分反映冬季海水冻结形成海冰，从而将卤水释放到上层海洋。这项提议将使用海冰和海洋的高分辨率数值模拟，结合现场观测来提高我们对南极洲周围底水形成过程的理解。我们将重点关注罗恩冰架以北的大陆架上的特定区域，因为该地区被认为是南极洲周围形成的大约三分之一的底层水，是南极洲周围其他底水形成区域的代表，而且相对于南大洋的其他区域，我们有大量数据可以用来检验我们的模型。我们将探索由南极洲吹来的风造成的海冰覆盖中的开放水域罗恩波利尼亚和脆弱的冰层在控制该地区底层水形成方面的作用。脆冰由毫米大小的冰晶组成，当海水低于冰点时，冰晶就会形成和生长。我们将把碎冰形成的物理学纳入我们的模型。我们将使用最近获得的海洋和大气数据以及卫星观测来测试我们的模型。我们将使用我们的模型，这将是迄今为止物理上最复杂、高度校准的模型，来计算罗恩大陆架上的底层水形成速度。一旦对罗恩大陆架进行了校准，这些模型将被用来计算整个南极洲周围的海底形成总量。除了对底水形成的新估计外，我们还将开发新的模型物理，并确定海洋混合的最佳表示。

The equatorial regions of the Earth receive more solar energy than the polar regions. The extra heat is transported polewards in approximately equal parts by the circulations of the atmosphere and ocean. Warm surface waters enter the polar regions, where they release their heat. As these surface waters cool, they can begin to freeze to form sea ice and this releases dense brine into the ocean. The combination of surface cooling and brine release causes the surface waters to become sufficiently dense to sink. The cold bottom waters so formed then flow equatorward, balancing the poleward surface flow. The location and mechanism of bottom water production affects the spatial distribution and intensity of the ocean circulation, which helps determine the weather.Evidence from climate models and observations suggest that bottom water formation around Antarctica will be affected by global warming and will influence the climate and weather in both the Southern and Northern hemispheres. In order to accurately predict future climate change, climate models require an adequate representation of bottom water formation around Antarctica, which is presently lacking. As a result of their limited spatial resolution and simplified physics, climate models are unable to represent adequately the small-scale processes responsible for the formation of bottom water. Climate models typically produce too little bottom water and this water is too warm and fresh, which has been ascribed to inadequate representation of winter freezing of seawater to form sea ice, which releases brine into the upper ocean. This proposal will use high resolution numerical modelling of the sea ice and ocean, combined with field observations to improve our understanding of the processes controlling bottom water formation around Antarctica.We will focus on a particular region, over the continental shelf north of the Ronne Ice Shelf, since this region is believed to be responsible for about a third of the bottom water formed around Antarctica, is representative of other regions of bottom water formation around Antarctica, and because, relative to other areas in the Southern Ocean, we have a lot of data with which to test our model. We will explore the role of the Ronne polynya, an open water region in the sea-ice cover caused by winds blowing off Antarctica, and frazil ice formation, in controlling the bottom water formation in this region. Frazil ice consists of millimetre-sized ice crystals that form and grow when the seawater is below its freezing point. We will include the physics of frazil ice formation into our models. We will test our models with recently-acquired oceanographic and atmospheric data and satellite observations. We will use our models, which will be the most physically-sophisticated, and highly-calibrated, models to date, to calculate the rate of bottom water formation over the Ronne continental shelf. The models, once calibrated for the Ronne continental shelf, will be used to calculate total bottom formation around the whole of Antarctica. In addition to new estimates for bottom water formation, we will develop new model physics and identify the optimal representation of ocean mixing.