Surface warming patterns dominate the uncertainty in global water vapor plus lapse rate feedback

Climate feedbacks have been usually estimated using changes in radiative effects associated with increased global-mean surface temperature. Feedback uncertainties, however, are not only functions of global-mean surface temperature increase. In projections by global climate models, it has been demonstrated that the geographical variation of sea surface temperature change brings significant uncertainties into atmospheric circulation and precipitation responses at regional scales. Here we show that the spatial pattern of surface warming is a major contributor to uncertainty in the combined water vapour-lapse rate feedback. This is demonstrated by computing the global-mean radiative effects of changes in air temperature and relative humidity simulated by 31 climate models using a methodology based on radiative kernels. Our results highlight the important contribution of regional climate change to the uncertainty in climate feedbacks, and identify the regions of the world where constraining surface warming patterns would be most effective for higher skill of climate projections.

Revisiting the Seasonal Evolution of the Indian Ocean Dipole from the Perspective of Process-Based Decomposition

The seasonal phase-locking feature of the Indian Ocean Dipole(IOD)is well documented.However,the seasonality ten-dency of sea surface temperature anomalies(SSTAs)during the development of the IOD has not been widely investigated.The SSTA tendencies over the two centers of the IOD peak in September-October-November are of different monthly amplitudes.The SSTA tendency over the west pole is small before June-July-August but dramatically increases in July-August-September.Meanwhile,the SSTA tendency over the east pole gradually increases before June-July-August and decreases since then.The growth rate attribution of the SSTAs is achieved by examining the roles of radiative and non-radiative air-sea coupled thermodynamic processes through the climate feedback-response analysis method(CFRAM).The CFRAM results indicate that oceanic dynamic processes largely contribute to the total SSTA tendency for initiating and fueling the IOD SSTAs,similar to previous studies.However,these results cannot ex-plain the monthly amplitudes of SSTA tendency.Four negative feedback processes(cloud radiative feedback,atmospheric dynamic processes,surface sensible,and latent heat flux)together play a damping role opposite to the SSTA tendency.Nevertheless,the sea surface temperature-water vapor feedback shows positive feedback.Specifically,variations in SSTAs can change water vapor con-centrations through evaporation,resulting in anomalous longwave radiation that amplifies the initial SSTAs through positive feedback.The effect of water vapor feedback is well in-phase with the monthly amplitudes of SSTA tendency,suggesting that the water vapor feedback might modulate the seasonally dependent SSTA tendency during the development of the IOD.

大气水汽变化及其反馈效应研究进展

大气水汽变化的反馈作用是影响平衡气候系统敏感性的最大反馈作用之一,能够放大其他温室气体增暖的效应,并可能导致极端天气气候事件的发生趋多趋强。因此,全面分析大气水汽的时空分布特征及其长期变化趋势,评估大气水汽反馈的区域气候效应,对于我们深入认识和理解全球变暖背景下区域气候响应的机理具有重要意义。综合国内外最新研究,已基本能够确定水汽反馈效应为一种使得全球增暖加快近一倍的强烈正反馈,并已能够估计其大致变化范围,但是此估计仍存在较大不确定性。随着卫星和探空技术的发展,目前已有的长期水汽资料日趋丰富,但资料之间也存在一些不确定性问题,同时单个资料本身也存在非均一性问题。最新的气候系统模式已能够大致模拟大气水汽的反馈效应,但近年的进展速度却并不令人乐观。我国的水汽观测和水汽反馈效应的研究也已取得长足进步,可以基本确定为水汽变化与地面温度存在正反馈关系,而与降水的关系虽然也较为密切,但因区域气候变化仍存在较大的不一致性。

水汽浓度变化对温室效应影响的定量分析

为了考察大气水汽浓度变化对温室效应的影响,以全球大气温度探空数据集RATPAC-A为基础,对流层采用固定相对湿度的假设,并根据平流层水汽的历史变化趋势,进行了定量研究。结果表明,对流层绝对湿度的增加,会造成其各处向上出射长波通量的减少,并在层顶处达到最大,且对流层顶水汽含量的变化,对于向上长波通量的影响最为显著;如果地表温度升高1 K,大气水汽浓度增加所导致的对流层顶向上长波通量的减小值为2.22 W/m2,对流层水汽含量变化与地表温升之间存在着强烈的正反馈关系,有能力使二氧化碳所造成的温室效应进一步增强50%;平流层水蒸汽体积浓度每上升1×10-6,将会使对流层顶的向下长波通量增加0.31 W/m2。

Why Does FGOALS-gl Reproduce a Weak Medieval Warm Period But a Reasonable Little Ice Age and 20th Century Warming?

To understand the strengths and limitations of a low-resolution version of Flexible Global Ocean Atmosphere-Land-Sea-ice （FGOALS-gl） to simulate the climate of the last millennium, the energy balance, climate sensitivity and absorption feedback of the model are analyzed. Simulation of last-millennium climate was carried out by driving the model with natural （solar radiation and volcanic eruptions） and anthropogenic （greenhouse gases and aerosols） forcing agents. The model feedback factors for （model sensitivity to） different forcings were calculated. The results show that the system feedback factor is about 2.5 （W m-2） K-1 in the pre-industrial period, while 1.9 （W m-2） K-1 in the industrial era. Thus, the model＇s sensitivity to natural forcing is weak, which explains why it reproduces a weak Medieval Warm Period. The relatively reasonable simulation of the Little Ice Age is caused by both the specified radiative forcing and unforced linear cold drift. The model sensitivity in the industrial era is higher than that of the pre-industrial period. A negative net cloud radiative feedback operates during whole-millennial simulation and reduces the model＇s sensitivity to specified forcing. The negative net cloud radiative forcing feedback under natural forcing in the period prior to 1850 is due to the underestimation （overestimation） of the response of cloudiness （in-cloud water path）. In the industrial era, the strong tropospheric temperature response enlarges the effective radius of ice clouds and reduces the fractional ice content within cloud, resulting in a weak negative net cloud feedback in the industrial period. The water vapor feedback in the industrial era is also stronger than that in the pre-industrial period. Both are in favor of higher model sensitivity and thus a reasonable simulation of the 20th century global warming.