论文标题
背景气压如何影响3D视图中潮汐锁定行星宜居区的内边缘？
How does Background Air Pressure Influence the Inner Edge of the Habitable Zone for Tidally Locked Planets in a 3D View?
论文作者
论文摘要
我们使用三维（3D）大气通用循环模型（AGCM）Exocam检查了不同背景N2表面压力（标记为PN2）对1：1潮汐锁定行星的宜居内边缘的影响。在我们的实验中，在改变恒星通量时，旋转周期是固定的，以便更清楚地隔离PN2的作用。我们发现失控温室的恒星通量阈值是PN2的非单调函数。这是由于五个过程的竞争影响：压力扩大，热容量，失流率，相对湿度和云。这些竞争过程增加了预测可居住区内边缘位置的复杂性。对于慢速旋转轨道为60个地球天，失控的温室发作的关键恒星通量为1700--1750，1900---1950和1750---1800 W m $^{ - 2} $下的0.25、1.0和4.0 bar of PN2，这表明PN2的幅度在PN2的幅度范围内。对于快速旋转轨道，变化PN2对内边缘的影响较小，范围约为7％。此外，我们表明，由于云散射的掩盖效果以及在炎热气候下，水蒸气的强烈短波吸收，瑞利散射效果对变化的PN2不重要。需要使用具有不同云和对流方案的AGCM和具有明确云和对流的云解析模型来修改此问题的未来工作。
We examine the effect of varying background N2 surface pressure (labelled as pN2) on the inner edge of the habitable zone for 1:1 tidally locked planets around M dwarfs, using the three-dimensional (3D) atmospheric general circulation model (AGCM) ExoCAM. In our experiments, the rotation period is fixed when varying the stellar flux, in order to more clearly isolate the role of pN2. We find that the stellar flux threshold for the runaway greenhouse is a non-monotonous function of pN2. This is due to the competing effects of five processes: pressure broadening, heat capacity, lapse rate, relative humidity, and clouds. These competing processes increase the complexity in predicting the location of the inner edge of the habitable zone. For a slow rotation orbit of 60 Earth days, the critical stellar flux for the runaway greenhouse onset is 1700--1750, 1900--1950, and 1750--1800 W m$^{-2}$ under 0.25, 1.0, and 4.0 bar of pN2, respectively, suggesting that the magnitude of the effect of pN2 is within ~13%. For a rapid rotation orbit, the effect of varying pN2 on the inner edge is smaller, within a range of ~7%. Moreover, we show that Rayleigh scattering effect as varying pN2 is unimportant for the inner edge due to the masking effect of cloud scattering and to the strong shortwave absorption by water vapor under hot climates. Future work using AGCMs having different cloud and convection schemes and cloud-resolving models having explicit cloud and convection are required to revise this problem.
