Climate Feedback Response Analysis Method Research Articles

Highly inhomogeneous interactions between background climate and urban warming across typical local climate zones in heatwave and non-heatwave days

Abstract Urban heat island (UHI) in conjunction with heatwave (HW) leads to exacerbation of thermal stress in urban areas. Prior research on UHI and HW has predominantly concentrated on examining the thermal conditions at the surface and near-surface, with few investigations extending to the radiative and dynamical interactions of UHI and HW, particularly with a focus on the inhomogeneities across local climate zones (LCZs). Here, we analyse the temperature disparity between HW and non-HW conditions across LCZs in the Sydney area by quantifying the contributions of individual radiative and dynamical processes using the coupled surface-atmosphere climate feedback-response analysis method (CFRAM). Three moist HW events in 2017, 2019, and 2020 are simulated using the Weather Research and Forecasting (WRF) model coupled with the single-layer urban canopy model (SLUCM). It is found that the maximum surface and 900 hPa temperature difference between HW and non-HW days may reach up to 10 K, with the increased net solar radiation during HWs being comparable to the typical level of anthropogenic heat flux in urban areas. It is also found that the reduction of clouds, the presence of vapour, and the increase of sensible heat contribute to the warming effect to various degrees, with the contribution of clouds being the most dominant. Conversely, the generation of dry convection and the increase of latent heat flux lead to cooling effects, with the latter being more dominant and capable of causing up to 10 K surface temperature difference between LCZ1 (compact high-rise) and LCZ9 (sparsely built). The differences in the contributions of climate feedback processes across different LCZs become more evident during more severe and humid HWs. These findings underscore the necessity of implementing LCZ-tailored heat mitigation strategies.

Quantifying the dynamical and radiative processes of the drastically weak South Asian summer monsoon circulation in 2015

The South Asian summer monsoon (SASM) circulation in 2015 is the weakest since 2000s, which results in severe drought over broad regions of the Indian peninsula. The 2015 SASM is closely related to the weakened summer meridional thermal contrast between southern Eurasia (SE) and the tropical Indian Ocean (TIO) at the mid–upper troposphere. Based on an updated climate feedback-response analysis method, this study conducts a quantitative attribution analysis of the thermal contrast anomalies associated with the 2015 SASM to multiple dynamical and radiative processes, particular for aerosol process. Result shows that the 2015 weak SASM is mainly attributed to the effect of water vapor (58%), followed by the effects of atmospheric dynamics (18%), clouds (15%), and aerosols (15%), respectively. These positive effects are partially offset by the negative contribution from surface dynamic process (-14%). As the most pronounced factor, the water vapor process weakens the SASM circulation via inducing SE cooling and TIO warming, which is closely linked to the decreased (increased) specific humidity over SE (TIO). Further analysis indicates that the total effect of aerosols is dominated by the changes in black carbon and sea salt. As two important components, the SE cooling and TIO warming separately account for about 51% and 49% to the 2015 SASM. The former is mainly attributed to the cooling effect of clouds, while the latter is mainly induced by the warming effect of atmospheric dynamics. Our result provides a new insight into the 2015 weak SASM from a quantitative perspective.

Asymmetric Arctic and Antarctic Warming and Its Intermodel Spread in CMIP6

Abstract Under the background of global warming, the Arctic region has warmed faster than the Antarctic, which is referred to as asymmetric Arctic and Antarctic warming. The new generation of model simulations from the CMIP6 offers an opportunity to identify the major factors contributing to the asymmetric warming and its intermodel spread. In this study, the preindustrial and abrupt-4 × CO2 experiments from 18 CMIP6 models are examined to extract the asymmetric warming and its intermodel spread. A climate feedback-response analysis method is applied to reveal the contributions of external and internal feedback processes to the asymmetric warming and its intermodel spread, by decomposing total warming into the partial temperature changes caused by individual factors. It is found that a seasonal energy transfer mechanism (SETM) dominates in both polar warmings. The direct consequence of the sea ice declining in response to the anthropogenic forcing is an increase in the effective heat capacity of the ocean surface layer. Such an increase in the effective heat capacity temporally withholds most of the extra solar energy absorbed during summer and then releases it during winter, contributing to stronger warming in winter. However, the background oceanic circulation in the Southern Ocean, namely, the Antarctic Circumpolar Current, continually transports energy equatorward, resulting in a suppressed SETM and surface warming in the Antarctic. The key factor that accounts for intermodel spread in the asymmetric warming is the difference in their strengths of SETM. The poleward atmospheric transport and water vapor feedback also contribute to the intermodel spread. Significance Statement The asymmetric Arctic and Antarctic warming, as a response to the increase in CO2, can regulate global atmospheric and oceanic circulations via meridional temperature gradient. Previous studies have all ascribed the key role of the ocean in the asymmetric warming over the two poles with a lack of comprehensive understanding of the roles of other feedback processes. This study emphasizes that oceanic circulation is the root of the asymmetric warming via suppressing sea ice retreat and the associated SETM in the Antarctic, instead of increasing ocean heat uptake and equatorward transport only. For the intermodel spread in the asymmetric warming over two poles, the differences in the strength of all processes involving the SETM among models are the prominent issue.

Quantitative attribution of the temperature associated with winter extreme cold events in China

Extreme cold events exert enormous impacts on the ecosystems and human health. A quantitative attribution analysis of the surface temperature anomalies associated with extreme cold events in China is conducted using an updated version of the coupled atmosphere-surface climate feedback response analysis method. For both extreme warm and cold years, the effects of anomalous surface albedo, water vapor, atmospheric dynamics, and aerosols are the major positive contributors, and the processes associated with surface dynamics provide a major negative effect. Specifically, the effect of surface albedo (water vapor) is directly linked to the change in local snow cover (precipitable water) over China. More local snow cover (precipitable water) provides a cooling (warming) effect and vice versa. The process associated with atmospheric dynamics exhibits an asymmetric contribution for the extreme warm and cold years. It provides a warming effect over most of China in the extreme warm years, which is possibly related to the nation-wide warm air advection. On the other hand, the effect of atmospheric dynamics displays large regional and year-to-year variations for the cold cases. In addition, a considerable impact of anthropogenic aerosols is detected over central-southern China, which is possibly related to the emission reduction policies in China since 2013. Although clouds show only a moderate impact on the national-averaged temperature anomalies, they provide a considerable effect over southern China.

Disentangling physical and dynamical drivers of the 2016/17 record-breaking warm winter in China

Understanding the physical and dynamical origin of regional climate extremes remains a major challenge in our effort to anticipate the occurrences and mitigate the adverse impacts of these extremes. China was hit by a record-breaking hot winter in 2016/17 with remarkable surface warming over the northern and southeastern regions. Here we made a quantitative attribution of this 2016/17 winter’s surface temperature anomalies utilizing an updated version of the coupled atmosphere-surface climate feedback response analysis method (CFRAM), that recently incorporates the effect of aerosols and more species of trace gases (CFRAM-A). The CFRAM-A analysis reveals that the overall warming pattern may be largely attributed to the effects of anomalous water vapor, atmospheric dynamics, and aerosols, followed by anomalies of surface albedo, clouds, solar irradiance, ozone, and carbon dioxide. The effect of methane turns out to be negligible. Anomalies in surface dynamics provides an overall cooling effect, compensating the warming associated with other processes to some extent. Among the three major positive contributors, effects of water vapor and atmospheric dynamics prevail over both northern and southeastern China while the impact of anthropogenic aerosols appears much more pronounced over southeastern China, likely due to the implementation of highly effective emission reduction policies in China since 2013. The CFRAM-A thus provides an efficient, model-free approach for quantitatively understanding sources of regional temperature extremes and for assessing the impacts of environmental policies regulating anthropogenic emissions of aerosols and atmospheric trace gases.

Uncertainty in projections of the South Asian summer monsoon under global warming by CMIP6 models: Role of tropospheric meridional thermal contrast

Driven by the increase in CO 2 concentration, climate models reach a consensus that the large-scale circulation of the South Asian summer monsoon (SASM) becomes weakened but with different magnitudes. This study investigates the major uncertainty sources of the SASM response to an abrupt quadrupling of CO 2 (abrupt-4×CO2) in 18 models of phase 6 of the Coupled Model Intercomparison Project. The projected weakening of the SASM indicated by both zonal and meridional monsoon circulation indices is closely linked to decreases in the meridional gradient of upper-tropospheric temperature between Eurasia and the Indian Ocean (EUTT-IUTT). A climate feedback–response analysis method is applied to linearly decompose the uncertainty of changes in EUTT-IUTT into the partial changes due to external forcing and internal processes of the earth–atmosphere column. Results show that the uncertainty of changes in EUTT-IUTT is contributed positively by the dominant atmospheric dynamic process, followed by the cloud shortwave radiative effect, and negatively by the surface latent heat flux and cloud longwave radiative effect. Contributions from CO 2 forcing and other internal processes including albedo and water vapor feedbacks, oceanic heat storage, and sensible heat flux are found to be minor. 摘要 本文基于第六次国际耦合模式比较计划共18个模式的工业革命前实验和CO 2 浓度突然四倍实验, 发现在CO 2 四倍强迫下, 南亚夏季风环流呈显著减弱趋势, 但减弱强度存在较大模式间差异. 利用Webster-Yang指数和经向哈得莱环流指数的下降趋势表征SASM减弱强度, 发现该下降趋势与欧亚大陆-印度洋之间对流层上层经向温度梯度的变化值(EUTT-IUTT)高度相关. 进一步利用气候反馈-响应分析方法进行分析, 发现EUTT-IUTT变化的模式间差异主要来自于大气动力过程, 其次是云的短波辐射效应的贡献. 地表潜热通量和云的长波辐射效应缩小了EUTT-IUTT变化的模式间差异.

Understanding the Differences Between TOA and Surface Energy Budget Attributions of Surface Warming

Energy budget decompositions have widely been used to evaluate individual process contributions to surface warming. Conventionally, the top-of-atmosphere (TOA) energy budget has been used to carry out such attribution, while other studies use the surface energy budget instead. However, the two perspectives do not provide the same interpretation of process contributions to surface warming, particularly when executing a spatial analysis. These differences cloud our understanding and inhibit our ability to shrink the inter-model spread. Changes to the TOA energy budget are equivalent to the sum of the changes in the atmospheric and surface energy budgets. Therefore, we show that the major discrepancies between the surface and TOA perspectives are due to non-negligible changes in the atmospheric energy budget that differ from their counterparts at the surface. The TOA lapse-rate feedback is the manifestation of multiple processes that produce a vertically non-uniform warming response such that it accounts for the asymmetry between the changes in the atmospheric and surface energy budgets. Using the climate feedback-response analysis method, we are able to decompose the lapse-rate feedback into contributions by individual processes. Combining the process contributions that are hidden within the lapse-rate feedback with their respective direct impacts on the TOA energy budget allows for a very consistent picture of process contributions to surface warming and its inter-model spread as that given by the surface energy budget approach.

Feedback attribution to dry heatwaves over East Asia

Summer heatwave events have exhibited increasing trends, with sudden increases occurring since the early 2000s over northeastern China and along the northern boundary of Mongolia. However, the mechanism behind heatwaves remains unexplored. To quantitatively examine the feedback attribution of concurrent events related to surface temperature anomalies, the coupled atmosphere–surface climate feedback-response analysis method based on the total energy balance within the atmosphere–surface column was applied. The results demonstrate that the contributions of the latent heat flux and surface dynamic processes served as positive feedback for surface warming by reducing the heat release from the surface to the atmosphere because of deficient soil moisture based on dry conditions. Cloud feedback also led to warm temperature anomalies through increasing solar insolation caused by decreasing cloud amounts associated with anomalous high-pressure systems. In contrast, the sensible heat flux played a role in reducing the warm temperature anomalies by the emission of heat from the surface. Atmospheric dynamic feedback led to cold anomalies. The influence of ozone, surface albedo, and water vapor processes is very weak. This study provides a better understanding of combined extreme climate events in the context of radiative and dynamic feedback processes.

Process-based analysis of relative contributions to the multi-model warming projection over East Asia

Climate models predict that East Asia (EA) will be substantially warmer than the present despite large inter-model uncertainty. This study investigated the major sources of the climate projections and the inter-model uncertainty. Particularly, we decomposed the differences in surface temperatures between the historical and RCP8.5 runs from 26 CMIP5 into partial surface temperature changes due to individual radiative and non-radiative processes through the climate feedback-response analysis method. Results show that anthropogenic greenhouse forcing and subsequent water vapor feedback processes are primarily responsible for the surface warming over EA. Relatively more rapid warming over the snow/ice-covered area and southern China is due to feedback processes associated with surface albedo and cloud, respectively. The regional warming is, however, compensated by the surface non-radiative (sensible and latent heat) cooling. The inter-model projection uncertainty is substantially large over high latitudes and the Tibetan Plateau mainly due to surface albedo feedback. Again, this large uncertainty is partly suppressed by surface non-radiative cooling. Water vapor and cloud feedbacks are the secondary important sources of the projection uncertainty. Moreover, the contributions of greenhouse forcing and atmospheric dynamics to the projection uncertainty are found to be minor.

Using the climate feedback response analysis method to quantify climate feedbacks in the middle atmosphere

Abstract. Over recent decades it has become clear that the middle atmosphere has a significant impact on surface and tropospheric climate. A better understanding of the middle atmosphere and how it reacts to the current increase in the concentration of carbon dioxide (CO2) is therefore necessary. In this study, we investigate the response of the middle atmosphere to a doubling of the CO2 concentration, and the associated changes in sea surface temperatures (SSTs), using the Whole Atmosphere Community Climate Model (WACCM). We use the climate feedback response analysis method (CFRAM) to calculate the partial temperature changes due to an external forcing and climate feedbacks in the atmosphere. As this method has the unique feature of additivity, these partial temperature changes are linearly addable. In this study, we discuss the direct forcing of CO2 and the effects of the ozone, water vapour, cloud, albedo and dynamical feedbacks. As expected, our results show that the direct forcing of CO2 cools the middle atmosphere. This cooling becomes stronger with increasing height; the cooling in the upper stratosphere is about three times as strong as the cooling in the lower stratosphere. The ozone feedback yields a radiative feedback that mitigates this cooling in most regions of the middle atmosphere. However, in the tropical lower stratosphere, and in some regions of the mesosphere, the ozone feedback has a cooling effect. The increase in the CO2 concentration causes the dynamics to change. The temperature response due to this dynamical feedback is small in terms of the global average, although there are large temperature changes due to this feedback locally. The temperature change in the lower stratosphere is influenced by the water vapour feedback and, to a lesser degree, by the cloud and albedo feedback. These feedbacks play no role in the upper stratosphere and the mesosphere. We find that the effects of the changed SSTs on the middle atmosphere are relatively small compared to the effects of changing the CO2. However, the changes in SSTs are responsible for dynamical feedbacks that cause large temperature changes. Moreover, the temperature response to the water vapour feedback in the lower stratosphere is almost solely due to changes in the SSTs. As CFRAM has not been applied to the middle atmosphere in this way before, this study also serves to investigate the applicability and the limitations of this method. This work shows that CFRAM is a very powerful tool for studying climate feedbacks in the middle atmosphere. However, it should be noted that there is a relatively large error term associated with the current method in the middle atmosphere, which can, to a large extent, be explained by the linearization in the method.

Comparative Analysis of the Mechanisms of Intensified Summer Warming over Europe-West Asia and Northeast Asia since the Mid-1990s through a Process-based Decomposition Method

Previous studies have found amplified warming over Europe-West Asia and Northeast Asia in summer since the mid-1990s relative to elsewhere on the Eurasian continent, but the cause of the amplification in these two regions remains unclear. In this study, we compared the individual contributions of influential factors for amplified warming over these two regions through a quantitative diagnostic analysis based on CFRAM (climate feedback-response analysis method). The changes in surface air temperature are decomposed into the partial changes due to radiative processes (including CO2 concentration, incident solar radiation at the top of the atmosphere, surface albedo, water vapor content, ozone concentration, and clouds) and non-radiative processes (including surface sensible heat flux, surface latent heat flux, and dynamical processes). Our results suggest that the enhanced warming over these two regions is primarily attributable to changes in the radiative processes, which contributed 0.62 and 0.98 K to the region-averaged warming over Europe-West Asia (1.00 K) and Northeast Asia (1.02 K), respectively. Among the radiative processes, the main drivers were clouds, CO2 concentration, and water vapor content. The cloud term alone contributed to the mean amplitude of warming by 0.40 and 0.85 K in Europe-West Asia and Northeast Asia, respectively. In comparison, the non-radiative processes made a much weaker contribution due to the combined impact of surface sensible heat flux, surface latent heat flux, and dynamical processes, accounting for only 0.38 K for the warming in Europe-West Asia and 0.05 K for the warming in Northeast Asia. The resemblance between the influential factors for the amplified warming in these two separate regions implies a common dynamical origin. Thus, this validates the possibility that they originate from the Silk Road pattern.

The Dominant Role of Snow/Ice Albedo Feedback Strengthened by Black Carbon in the Enhanced Warming over the Himalayas

AbstractAn obvious warming trend in winter over the Tibetan Plateau (TP) in the recent decades has been widely discussed, with studies emphasizing the dominant effects of local radiative factors, including those due to black carbon (BC). The Himalayas are one of the largest snowpack- and ice-covered regions in the TP, and an ideal area to investigate local radiative effects on climate change. In this study, the coupled climate feedback response analysis method (CFRAM) is applied to quantify the magnitude of warming over the Himalayas induced by different external forcing factors and climate feedback processes. The results show that snow/ice albedo feedback (SAF) resulted in a warming of approximately 2.6°C and was the primary contributor to enhanced warming over the Himalayas in recent decades. This warming was much greater than the warming induced by dynamic and other radiative factors. In particular, the strong radiative effects of BC on the warming over the Himalayas are identified by comparing control and BC-perturbed experiments of the Community Earth System Model (CESM). As a result of strong BC effects on the Himalayas, evaporation and reduced precipitation were strengthened, accounting for local drying and land degradation, which intensified warming. These results suggest that more investigations on the local radiative effects on the climate and ecosystem are needed, especially in the high-altitude cryosphere.

A Process-Based Assessment of Decadal-Scale Surface Temperature Evolutions in the NCAR CCSM4’s 25-Year Hindcast Experiments

This study represents an initial effort in the context of the coupled atmosphere–surface climate feedback-response analysis method (CFRAM) to partition the temporal evolution of the global surface temperature from 1981 to 2005 into components associated with individual radiative and nonradiative (dynamical) processes in the NCAR CCSM4’s decadal hindcasts. When compared with the observation (ERA-Interim), CCSM4 is able to predict an overall warming trend as well as the transient cooling occurring during the period 1989–94. However, while the model captures fairly well the positive contributions of the CO2 and surface albedo change to the temperature evolution, it has an overly strong water vapor effect that dictates the temperature evolution in the hindcast. This is in contrast with ERA-Interim, where changes in surface dynamics (mainly ocean circulation and heat content change) dominate the actual temperature evolution. Atmospheric dynamics in both ERA-Interim and the model work against the surface temperature tendency through turbulent and convective heat transport, leading to an overall negative contribution to the evolution of the surface temperature. Impacts of solar forcing and ozone change on the surface temperature change are relatively weak during this period. The magnitude of cloud effect is considerably smaller compared to that in ERA-Interim and the spatial distribution of the cloud effect is also significantly different between the two, especially over the equatorial Pacific. The value and limitations of this process-based temperature decomposition are discussed.

A process-based decomposition of decadal-scale surface temperature evolutions over East Asia

This study partitions the observed decadal evolution of surface temperature and surface temperature differences between two decades (early 2000s and early 1980s) over the East Asian continent into components associated with individual radiative and non-radiative (dynamical) processes in the context of the coupled atmosphere-surface climate feedback-response analysis method (CFRAM). Rapid warming in this region occurred in late 1980s and early 2000s with a transient pause of warming between the two periods. The rising CO2 concentration provides a sustained, region-wide warming contribution and surface albedo effect, largely related to snow cover change, is important for warming/cooling over high-latitude and high-elevation regions. Sensible hear flux and surface dynamics dominates the evolution of surface temperature, with latent heat flux and atmospheric dynamics working against them mostly through large-scale and convective/turbulent heat transport. Cloud via its shortwave effect provides positive contributions to warming over southern Siberia and South China. The longwave effect associated with water vapor change contributes significant warming over northern India, Tibetan Plateau, and central Siberia. Impacts of solar irradiance and ozone changes are relatively small. The strongest year-to-year temperature fluctuation occurred at a rapid warming (1987–1988) and a rapid cooling (1995–1996) period. The pattern of the rapid warming receives major positive contributions from sensible heat flux with changes in atmospheric dynamics, water vapor, clouds, and albedo providing secondary positive contributions, while surface dynamics and latent heat flux providing negative contributions. The signs of the contributions from individual processes to the rapid cooling are almost opposite to those to the rapid warming.

Feedback Attributions to the Dominant Modes of East Asian Winter Monsoon Variations

Abstract This study investigates the variations and feedback attributions of changes in surface temperature between strong and weak East Asian winter monsoons. The variations of winter-mean surface air temperature are dominated by two distinct principal modes that account for 70.9% of the total variance. The first mode features high correlation with the high-latitude atmospheric circulation, including a correlation coefficient of −0.53 with the Arctic Oscillation in January, and the second mode is significantly linked to El Niño–Southern Oscillation, with a correlation coefficient of −0.37. The surface temperature anomalies of each mode are decomposed into partial temperature anomalies resulting from radiative and nonradiative feedback processes by applying a coupled climate feedback–response analysis method to quantify contributions from thermodynamic and dynamic processes. Results indicate that the surface cooling associated with both modes is mainly attributed to the nonradiative feedback processes of atmospheric dynamics and surface sensible heating and to the radiative feedback processes of water vapor and clouds. The first mode exhibits a deep barotropic anomalous high that weakens the high-latitude westerly jet stream but strengthens the midlatitude westerly jet stream. This circulation feature traps cold and dry air over northern East Asia. For the second mode, the ocean and land heat storage processes induce a large thermal gradient over eastern China and the northwestern Pacific, resulting in a large pressure gradient. Northerly anomalies further reinforce the pressure gradient, which favors cold air intruding southward into the tropics.

On the contrasting decadal changes of diurnal surface temperature range between the Tibetan Plateau and southeastern China during the 1980s–2000s

The diurnal surface temperature range (DTR) has become significantly smaller over the Tibetan Plateau (TP) but larger in southeastern China, despite the daily mean surface temperature having increased steadily in both areas during recent decades. Based on ERA-Interim reanalysis data covering 1979–2012, this study shows that the weakened DTR over TP is caused by stronger warming of daily minimum surface temperature (Tmin) and a weak cooling of the daily maximum surface temperature (Tmax); meanwhile, the enhanced DTR over southeastern China is mainly associated with a relatively stronger/weaker warming of Tmax/Tmin. A further quantitative analysis of DTR changes through a process-based decomposition method—the Coupled Surface–Atmosphere Climate Feedback Response Analysis Method (CFRAM)—indicates that changes in radiative processes are mainly responsible for the decreased DTR over the TP. In particular, the increased low-level cloud cover tends to induce the radiative cooling/warming during daytime/nighttime, and the increased water vapor helps to decrease the DTR through the stronger radiative warming during nighttime than daytime. Contributions from the changes in all radiative processes (over −2°C) are compensated for by those from the stronger decreased surface sensible heat flux during daytime than during nighttime (approximately 2.5°C), but are co-contributed by the changes in atmospheric dynamics (approximately −0.4°C) and the stronger increased latent heat flux during daytime (approximately −0.8°C). In contrast, the increased DTR over southeastern China is mainly contributed by the changes in cloud, water vapor and atmospheric dynamics. The changes in surface heat fluxes have resulted in a decrease in DTR over southeastern China.

Towards a physical understanding of stratospheric cooling under global warming through a process-based decomposition method

The stratosphere has been cooling under global warming, the causes of which are not yet well understood. This study applied a process-based decomposition method (CFRAM; Coupled Surface–Atmosphere Climate Feedback Response Analysis Method) to the simulation results of a Coupled Model Intercomparison Project, phase 5 (CMIP5) model (CCSM4; Community Climate System Model, version 4), to demonstrate the responsible radiative and non-radiative processes involved in the stratospheric cooling. By focusing on the long-term stratospheric temperature changes between the “historical run” and the 8.5 W m−2 Representative Concentration Pathway (RCP8.5) scenario, this study demonstrates that the changes of radiative radiation due to CO2, ozone and water vapor are the main divers of stratospheric cooling in both winter and summer. They contribute to the cooling changes by reducing the net radiative energy (mainly downward radiation) received by the stratospheric layer. In terms of the global average, their contributions are around −5, −1.5, and −1 K, respectively. However, the observed stratospheric cooling is much weaker than the cooling by radiative processes. It is because changes in atmospheric dynamic processes act to strongly mitigate the radiative cooling by yielding a roughly 4 K warming on the global average base. In particular, the much stronger/weaker dynamic warming in the northern/southern winter extratropics is associated with an increase of the planetary-wave activity in the northern winter, but a slight decrease in the southern winter hemisphere, under global warming. More importantly, although radiative processes dominate the stratospheric cooling, the spatial patterns are largely determined by the non-radiative effects of dynamic processes.

Contrasting the eastern Pacific El Niño and the central Pacific El Niño: process-based feedback attribution

This paper examines the roles of radiative and non-radiative air–sea coupled thermodynamic processes in modifying sea surface temperature (SST) anomalies driven by (air–sea coupled) oceanic dynamic processes, focusing on their contributions to the key differences between the eastern Pacific (EP) El Niño and the central Pacific (CP) El Niño. The attribution is achieved by decomposing SST anomalies into partial temperature anomalies due to individual processes using a coupled atmosphere-surface climate feedback-response analysis method. Oceanic processes induce warming from the central to the eastern equatorial Pacific and cooling over the western basin with a maximum warming center in the central Pacific for both types of El Niño. The processes that act to oppose the oceanic process-induced SST anomalies are surface latent heat flux, sensible heat flux, cloud, and atmospheric dynamic feedbacks, referred to as negative-feedback processes. The cooling due to each of the four negative-feedback processes is the strongest in the region where the initial warming due to oceanic processes is the largest. Water–vapor feedback is the sole process that acts to enhance the initial warming induced by oceanic processes. The increase in atmospheric water vapor over the eastern Pacific is much stronger for the EP El Niño than for the CP El Niño. It is the strong water–vapor feedback over the eastern Pacific and the strong negative feedbacks over the central equatorial Pacific that help to relocate the maximum warming center from the central Pacific to the eastern basin for the EP El Niño.

Diagnosis of Middle-Atmosphere Climate Sensitivity by the Climate Feedback–Response Analysis Method

Abstract The authors present a new method to diagnose the middle-atmosphere climate sensitivity by extending the climate feedback–response analysis method (CFRAM) for the coupled atmosphere–surface system to the middle atmosphere. The middle-atmosphere CFRAM (MCFRAM) is built on the atmospheric energy equation per unit mass with radiative heating and cooling rates as its major thermal energy sources. MCFRAM preserves CFRAM’s unique feature of additivity, such that partial temperature changes due to variations in external forcing and feedback processes can be added to give a total temperature change for direct comparison with the observed temperature change. In addition, MCFRAM establishes a physical relationship of radiative damping between the energy perturbations associated with various feedback processes and temperature perturbations associated with thermal responses. In this study, MCFRAM is applied to both observations and model output fields to diagnose the middle-atmosphere climate sensitivity. The authors found that the largest component of the middle-atmosphere temperature response to the 11-yr solar cycle (solar maximum vs solar minimum) is the partial temperature change due to the variation of the solar flux. Increasing CO2 cools the middle atmosphere, whereas the partial temperature change due to changes in O3 can be either positive or negative. The application of MCFRAM to model dynamical fields reconfirms the advantage of introducing the residual circulation to characterize middle-atmosphere dynamics in terms of the partial temperature changes. The radiatively driven globally averaged partial temperature change is approximately equal to the observed temperature change, ranging from −0.5 K near 25 km to −1.0 K near 70 km between solar maximum and solar minimum.

Quantifying contributions of model processes to the surface temperature bias in FGOALS‐g2

AbstractTo quantify the annual mean surface temperature bias due to various processes in Flexible Global Ocean‐Atmosphere‐Land‐System model, Grid point version 2 (FGOALS‐g2), the climate feedback‐response analysis method (CFRAM) is used to isolate contributions from both radiative and nonradiative processes in the model by comparing the model simulation with ERA‐Interim reanalysis. The observed surface temperature bias is decomposed into seven partial temperature biases associated with surface albedo, water vapor, cloud, both surface sensible and latent heat fluxes, land/ocean heat transport processes, and atmospheric transport processes. The global mean cold bias (−1.39 K) is mostly attributed to surface albedo and land/ocean heat transport processes while surface latent heat fluxes tend to weaken this bias. Cloud‐induced bias is dominated by shortwave cloud radiative effect (SWCRE) over low‐latitudes and longwave cloud radiative effect (LWCRE) over high latitudes. The mixed layer depth (MLD) bias is consistent with the bias due to ocean heat transport over North Pacific, North Atlantic, and the Southern Ocean. On global scale, contributions of radiative processes and nonradiative processes to the total observed cold bias are comparable, but tend to compensate each other over most regions except for the northern high latitudes. We suggest that the improvements in tropical clouds in the model may significantly decrease the global temperature bias through the interaction between clouds and circulation.