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

AbstractClimate 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.

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Assessing Snow Phenology over the Large Part of Eurasia Using Satellite Observations from 2000 to 2016

Remote Sensing ◽

10.3390/rs12122060 ◽

2020 ◽

Vol 12 (12) ◽

pp. 2060

Author(s):

Yanhua Sun ◽

Tingjun Zhang ◽

Yijing Liu ◽

Wenyu Zhao ◽

Xiaodong Huang

Keyword(s):

Snow Cover ◽

Southern China ◽

Climate Feedback ◽

Onset Date ◽

West Siberian Plain ◽

Positive Trend ◽

The Tibetan Plateau ◽

Ecological Processes ◽

Mountain Areas ◽

Snow Cover Extent

Snow plays an important role in meteorological, hydrological and ecological processes, and snow phenology variation is critical for improved understanding of climate feedback on snow cover. The main purpose of the study is to explore spatial-temporal changes and variabilities of the extent, timing and duration, as well as phenology of seasonal snow cover across the large part of Eurasia from 2000 through 2016 using a Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-free snow product produced in this study. The results indicate that there are no significant positive or negative interannual trends of snow cover extent (SCE) from 2000 to 2016, but there are large seasonal differences. SCE shows a significant negative trend in spring (p = 0.01) and a positive trend in winter. The stable snow cover areas accounting for 78.8% of the large part of Eurasia, are mainly located north of latitude 45° N and in the mountainous areas. In this stable area, the number of snow-covered days is significantly increasing (p < 0.05) in 6.4% of the region and decreasing in 9.1% of the region, with the decreasing areas being mainly located in high altitude mountain areas and the increasing area occurring mainly in the ephemeral snow cover areas of northeastern and southern China. In central Siberia, Pamir and the Tibetan Plateau, the snow onset date tends to be delayed while the end date is becoming earlier from 2000 to 2016. While in the relatively low altitude plain areas, such as the West Siberian Plain and the Eastern European Plain region, the snow onset date is tending to advance, the end date tends to be delayed, but the increase is not significant.

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Robustness of Dynamical Feedbacks from Radiative Forcing: 2% Solar versus 2 × CO2 Experiments in an Idealized GCM

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-11-0117.1 ◽

2012 ◽

Vol 69 (7) ◽

pp. 2256-2271 ◽

Cited By ~ 32

Author(s):

Ming Cai ◽

Ka-Kit Tung

Keyword(s):

Water Vapor ◽

Radiative Forcing ◽

Lower Troposphere ◽

Radiative Heating ◽

Climate Feedback ◽

Response Analysis ◽

High Latitudes ◽

Water Vapor Feedback ◽

The Tropics ◽

Heating Profile

Abstract Despite the differences in the spatial patterns of the external forcing associated with a doubling CO2 and with a 2% solar variability, the final responses in the troposphere and at the surface in a three-dimensional general circulation model appear remarkably similar. Various feedback processes are diagnosed and compared using the climate feedback–response analysis method (CFRAM) to understand the mechanisms responsible. At the surface, solar radiative forcing is stronger in the tropics than at the high latitudes, whereas greenhouse radiative forcing is stronger at high latitudes compared with the tropics. Also solar forcing is positive everywhere in the troposphere and greenhouse radiative forcing is positive mainly in the lower troposphere. The water vapor feedback strengthens the upward-decreasing radiative heating profile in the tropics and the poleward-decreasing radiative heating profile in the lower troposphere. The “evaporative” and convective feedbacks play an important role only in the tropics where they act to reduce the warming at the surface and lower troposphere in favor of upper-troposphere warming. Both water vapor feedback and enhancement of convection in the tropics further strengthen the initial poleward-decreasing profile of energy flux convergence perturbations throughout the troposphere. As a result, the large-scale dynamical poleward energy transport, which acts on the negative temperature gradient, is enhanced in both cases, contributing to a polar amplification of warming aloft and a warming reduction in the tropics. The dynamical amplification of polar atmospheric warming also contributes additional warming to the surface below via downward thermal radiation.

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High-resolution ensemble projections and uncertainty assessment of regional climate change over China in CORDEX East Asia

Hydrology and Earth System Sciences ◽

10.5194/hess-22-3087-2018 ◽

2018 ◽

Vol 22 (5) ◽

pp. 3087-3103 ◽

Cited By ~ 12

Author(s):

Huanghe Gu ◽

Zhongbo Yu ◽

Chuanguo Yang ◽

Qin Ju ◽

Tao Yang ◽

...

Keyword(s):

Climate Change ◽

Tibetan Plateau ◽

Model Uncertainty ◽

Climate Models ◽

Southern China ◽

Regional Climate ◽

Regional Climate Change ◽

Internal Variability ◽

Northeastern China ◽

The Tibetan Plateau

Abstract. An ensemble simulation of five regional climate models (RCMs) from the coordinated regional downscaling experiment in East Asia is evaluated and used to project future regional climate change in China. The influences of model uncertainty and internal variability on projections are also identified. The RCMs simulate the historical (1980–2005) climate and future (2006–2049) climate projections under the Representative Concentration Pathway (RCP) RCP4.5 scenario. The simulations for five subregions in China, including northeastern China, northern China, southern China, northwestern China, and the Tibetan Plateau, are highlighted in this study. Results show that (1) RCMs can capture the climatology, annual cycle, and interannual variability of temperature and precipitation and that a multi-model ensemble (MME) outperforms that of an individual RCM. The added values for RCMs are confirmed by comparing the performance of RCMs and global climate models (GCMs) in reproducing annual and seasonal mean precipitation and temperature during the historical period. (2) For future (2030–2049) climate, the MME indicates consistent warming trends at around 1 ∘C in the entire domain and projects pronounced warming in northern and western China. The annual precipitation is likely to increase in most of the simulation region, except for the Tibetan Plateau. (3) Generally, the future projected change in annual and seasonal mean temperature by RCMs is nearly consistent with the results from the driving GCM. However, changes in annual and seasonal mean precipitation exhibit significant inter-RCM differences and possess a larger magnitude and variability than the driving GCM. Even opposite signals for projected changes in average precipitation between the MME and the driving GCM are shown over southern China, northeastern China, and the Tibetan Plateau. (4) The uncertainty in projected mean temperature mainly arises from the internal variability over northern and southern China and the model uncertainty over the other three subregions. For the projected mean precipitation, the dominant uncertainty source is the internal variability over most regions, except for the Tibetan Plateau, where the model uncertainty reaches up to 60 %. Moreover, the model uncertainty increases with prediction lead time across all subregions.

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

Journal of Climate ◽

10.1175/jcli-d-18-0720.1 ◽

2019 ◽

Vol 32 (18) ◽

pp. 5883-5899 ◽

Cited By ~ 3

Author(s):

Jieru Ma ◽

Tinghan Zhang ◽

Xiaodan Guan ◽

Xiaoming Hu ◽

Anmin Duan ◽

...

Keyword(s):

Black Carbon ◽

Dominant Role ◽

Warming Trend ◽

Climate Feedback ◽

Response Analysis ◽

The Tibetan Plateau ◽

Radiative Effects ◽

Albedo Feedback ◽

Community Earth System Model

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.

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Using the Radiative Kernel Technique to Calculate Climate Feedbacks in NCAR’s Community Atmospheric Model

Journal of Climate ◽

10.1175/2007jcli2044.1 ◽

2008 ◽

Vol 21 (10) ◽

pp. 2269-2282 ◽

Cited By ~ 201

Author(s):

Karen M. Shell ◽

Jeffrey T. Kiehl ◽

Christine A. Shields

Keyword(s):

Water Vapor ◽

Radiative Forcing ◽

Surface Albedo ◽

Atmospheric Model ◽

Cloud Feedback ◽

Climate Feedback ◽

Time Step ◽

Global Average ◽

Clear Sky ◽

Vapor Temperature

Abstract Climate models differ in their responses to imposed forcings, such as increased greenhouse gas concentrations, due to different climate feedback strengths. Feedbacks in NCAR’s Community Atmospheric Model (CAM) are separated into two components: the change in climate components in response to an imposed forcing and the “radiative kernel,” the effect that climate changes have on the top-of-the-atmosphere (TOA) radiative budget. This technique’s usefulness depends on the linearity of the feedback processes. For the case of CO2 doubling, the sum of the effects of water vapor, temperature, and surface albedo changes on the TOA clear-sky flux is similar to the clear-sky flux changes directly calculated by CAM. When monthly averages are used rather than values from every time step, the global-average TOA shortwave change is underestimated by a quarter, partially as a result of intramonth correlations of surface albedo with the radiative kernel. The TOA longwave flux changes do not depend on the averaging period. The longwave zonal averages are within 10% of the model-calculated values, while the global average differs by only 2%. Cloud radiative forcing (ΔCRF) is often used as a diagnostic of cloud feedback strength. The net effect of the water vapor, temperature, and surface albedo changes on ΔCRF is −1.6 W m−2, based on the kernel technique, while the total ΔCRF from CAM is −1.3 W m−2, indicating these components contribute significantly to ΔCRF and make it more negative. Assuming linearity of the ΔCRF contributions, these results indicate that the net cloud feedback in CAM is positive.

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Physical Mechanisms of Tropical Climate Feedbacks Investigated Using Temperature and Moisture Trends*

Journal of Climate ◽

10.1175/jcli-d-15-0253.1 ◽

2015 ◽

Vol 28 (22) ◽

pp. 8968-8987 ◽

Cited By ~ 6

Author(s):

A. J. Ferraro ◽

F. H. Lambert ◽

M. Collins ◽

G. M. Miles

Keyword(s):

Water Vapor ◽

Climate Models ◽

Tropical Climate ◽

Lapse Rate ◽

Climate Feedback ◽

Climate Projections ◽

Tropospheric Temperature ◽

Regional Pattern ◽

Rate Feedback ◽

Water Vapor Feedback

Abstract Tropical climate feedback mechanisms are assessed using satellite-observed and model-simulated trends in tropical tropospheric temperature from the MSU/AMSU instruments and upper-tropospheric humidity from the HIRS instruments. Despite discrepancies in the rates of tropospheric warming between observations and models, both are consistent with constant relative humidity over the period 1979–2008. Because uncertainties in satellite-observed tropical-mean trends preclude a constraint on tropical-mean trends in models regional features of the feedbacks are also explored. The regional pattern of the lapse rate feedback is primarily determined by the regional pattern of surface temperature changes, as tropical atmospheric warming is relatively horizontally uniform. The regional pattern of the water vapor feedback is influenced by the regional pattern of precipitation changes, with variations of 1–2 W m−2 K−1 across the tropics (compared to a tropical-mean feedback magnitude of 3.3–4 W m−2 K−1). Thus the geographical patterns of water vapor and lapse rate feedbacks are not correlated, but when the feedbacks are calculated in precipitation percentiles rather than in geographical space they are anticorrelated, with strong positive water vapor feedback associated with strong negative lapse rate feedback. The regional structure of the feedbacks is not related to the strength of the tropical-mean feedback in a subset of the climate models from the CMIP5 archive. Nevertheless the approach constitutes a useful process-based test of climate models and has the potential to be extended to constrain regional climate projections.

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High-resolution ensemble projections and uncertainty assessment of regional climate change over China in CORDEX East Asia

10.5194/hess-2017-407 ◽

2017 ◽

Cited By ~ 1

Author(s):

Huanghe Gu ◽

Zhongbo Yu ◽

Chuanguo Yang ◽

Qin Ju ◽

Tao Yang

Keyword(s):

Tibetan Plateau ◽

East Asia ◽

Model Uncertainty ◽

Regional Climate ◽

Regional Climate Change ◽

Internal Variability ◽

Northwest China ◽

The Tibetan Plateau ◽

Model Ensemble ◽

Cordex East Asia

Abstract. An ensemble simulation of 5 regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment in East Asia (CORDEX-East Asia) was evaluated and used for future regional climate change projection in China. Meanwhile, the contributions of model uncertainty and internal variability are identified. The RCMs simulated both the historical climate (1989–2008) and future climate projection (2030–2049) under the Representative Concentration Pathway (RCP) RCP4.5 scenario. We highlighted 5 subregions in China, viz. Northeast China, North China, South China, Northwest China, and Tibetan Plateau. Our results showed that the capability of RCMs to capture the climatology, annual cycle and inter-annual variability of temperature and precipitation and multi-model ensemble outperforms the individual RCM. For the future climate, consistent warming trends around 1 °C were indicated by multi-model ensemble over the whole domain and more pronounced warming was projected in northern and western China. The annual precipitation is likely to increase in most of the simulation region, except the Tibetan Plateau which decreases −7.8 %. Compare with the similar seasonal temperature changes with the driving global climate model (GCM), the seasonal precipitation change shows significant inter-RCM difference and has larger magnitude and variability than driving GCM. The model uncertainty for future temperature projection is clearly dominant over the northeast, northwest China and Tibetan Plateau, reaching up to 70 %, and it contribute about 40 % of the total uncertainty over north and south China. For precipitation, the internal variability is dominant over most regions except for the Tibetan Plateau which the model uncertainties reach up to 60 %. In addition, the model uncertainty increases with prediction lead time over all subregions.

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Comparison of regional characteristics of land precipitation climatology projected by an MRI-AGCM multi-cumulus scheme and multi-SST ensemble with CMIP5 multi-model ensemble projections

Progress in Earth and Planetary Science ◽

10.1186/s40645-020-00394-4 ◽

2020 ◽

Vol 7 (1) ◽

Author(s):

Rui Ito ◽

Tosiyuki Nakaegawa ◽

Izuru Takayabu

Keyword(s):

Climate Change ◽

High Resolution ◽

General Circulation ◽

Annual Precipitation ◽

Cmip5 Models ◽

Climate Projections ◽

The Tibetan Plateau ◽

Model Ensemble ◽

Uncertainty Range ◽

High Performing

AbstractEnsembles of climate change projections created by general circulation models (GCMs) with high resolution are increasingly needed to develop adaptation strategies for regional climate change. The Meteorological Research Institute atmospheric GCM version 3.2 (MRI-AGCM3.2), which is listed in the Coupled Model Intercomparison Project phase 5 (CMIP5), has been typically run with resolutions of 60 km and 20 km. Ensembles of MRI-AGCM3.2 consist of members with multiple cumulus convection schemes and different patterns of future sea surface temperature, and are utilized together with their downscaled data; however, the limited size of the high-resolution ensemble may lead to undesirable biases and uncertainty in future climate projections that will limit its appropriateness and effectiveness for studies on climate change and impact assessments. In this study, to develop a comprehensive understanding of the regional precipitation simulated with MRI-AGCM3.2, we investigate how well MRI-AGCM3.2 simulates the present-day regional precipitation around the globe and compare the uncertainty in future precipitation changes and the change projection itself between MRI-AGCM3.2 and the CMIP5 multiple atmosphere–ocean coupled GCM (AOGCM) ensemble. MRI-AGCM3.2 reduces the bias of the regional mean precipitation obtained with the high-performing CMIP5 models, with a reduction of approximately 20% in the bias over the Tibetan Plateau through East Asia and Australia. When 26 global land regions are considered, MRI-AGCM3.2 simulates the spatial pattern and the regional mean realistically in more regions than the individual CMIP5 models. As for the future projections, in 20 of the 26 regions, the sign of annual precipitation change is identical between the 50th percentiles of the MRI-AGCM3.2 ensemble and the CMIP5 multi-model ensemble. In the other six regions around the tropical South Pacific, the differences in modeling with and without atmosphere–ocean coupling may affect the projections. The uncertainty in future changes in annual precipitation from MRI-AGCM3.2 partially overlaps the maximum–minimum uncertainty range from the full ensemble of the CMIP5 models in all regions. Moreover, on average over individual regions, the projections from MRI-AGCM3.2 spread over roughly 0.8 of the uncertainty range from the high-performing CMIP5 models compared to 0.4 of the range of the full ensemble.

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Impacts of Ozone Changes in the Tropopause Layer on Stratospheric Water Vapor

Atmosphere ◽

10.3390/atmos12030291 ◽

2021 ◽

Vol 12 (3) ◽

pp. 291

Author(s):

Jinpeng Lu ◽

Fei Xie ◽

Hongying Tian ◽

Jiali Luo

Keyword(s):

Water Vapor ◽

Ozone Depletion ◽

Climate Model ◽

Global Climate ◽

Stratospheric Water Vapor ◽

Radiative Processes ◽

Low Latitudes ◽

Cold Point ◽

The Impact ◽

Tropopause Temperature

Stratospheric water vapor (SWV) changes play an important role in regulating global climate change, and its variations are controlled by tropopause temperature. This study estimates the impacts of tropopause layer ozone changes on tropopause temperature by radiative process and further influences on lower stratospheric water vapor (LSWV) using the Whole Atmosphere Community Climate Model (WACCM4). It is found that a 10% depletion in global (mid-low and polar latitudes) tropopause layer ozone causes a significant cooling of the tropical cold-point tropopause with a maximum cooling of 0.3 K, and a corresponding reduction in LSWV with a maximum value of 0.06 ppmv. The depletion of tropopause layer ozone at mid-low latitudes results in cooling of the tropical cold-point tropopause by radiative processes and a corresponding LSWV reduction. However, the effect of polar tropopause layer ozone depletion on tropical cold-point tropopause temperature and LSWV is opposite to and weaker than the effect of tropopause layer ozone depletion at mid-low latitudes. Finally, the joint effect of tropopause layer ozone depletion (at mid-low and polar latitudes) causes a negative cold-point tropopause temperature and a decreased tropical LSWV. Conversely, the impact of a 10% increase in global tropopause layer ozone on LSWV is exactly the opposite of the impact of ozone depletion. After 2000, tropopause layer ozone decreased at mid-low latitudes and increased at high latitudes. These tropopause layer ozone changes at different latitudes cause joint cooling in the tropical cold-point tropopause and a reduction in LSWV. Clarifying the impacts of tropopause layer ozone changes on LSWV clearly is important for understanding and predicting SWV changes in the context of future global ozone recovery.

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