Heat budget of the south-central equatorial Pacific in CMIP3 models

ABSTRACT Using data from 17 coupled models and nine sets of corresponding Atmospheric Model Intercomparison Project （AMIP） results, we investigated annual and seasonal variation biases in the upper 50 m of the south-central equatorial Pacific, with a focus on the double-ITCZ bias, and examined the causes for the amplitude biases by using heat budget analysis. The results showed that, in the research region, most of the models simulate SSTs that are higher than or similar to observed. The simulated seasonal phase is close to that observed, but the amplitudes of more than half of the model results are larger than or equal to observations. Heat budget analysis demonstrated that strong shortwave radiation in individual atmospheric models is the main factor that leads to high SST values and that weak southward cold advection is an important mechanism for maintaining a high SST. For seasonal circulation, large surface shortwave radiation amplitudes cause large SST amplitudes.     

Parallel comparison of the northern winter stratospheric circulation in reanalysis and in CMIP5 models

A parallel comparison is made of the circulation climatology and the leading oscillation mode of the northern winter stratosphere among six reanalysis products and 24 CMIP5(Coupled Model Intercomparison Project Phase 5) models. The results reveal that the NCEP/NCAR, NECP/DOE, ERA40, ERA-Interim and JRA25 reanalyses are quite consistent in describing the climatology and annual cycle of the stratospheric circulation. The 20 CR reanalysis, however, exhibits a remarkable"cold pole" bias accompanied by a much stronger stratospheric polar jet, similar as in some CMIP5 models. Compared to the1–2 month seasonal drift in most coupled general circulation models(GCMs), the seasonal cycle of the stratospheric zonal wind in most earth system models(ESMs) agrees very well with reanalysis. Similar to the climatology, the amplitude of Polar Vortex Oscillation(PVO) events also varies among CMIP5 models. The PVO amplitude in most GCMs is relatively weaker than in reanalysis, while that in most of the ESMs is more realistic. In relation to the "cold pole" bias and the weaker oscillation in some CMIP5 GCMs, the frequency of PVO events is significantly underestimated by CMIP5 GCMs; while in most ESMs, it is comparable to that in reanalysis. The PVO events in reanalysis(except in 20CR) mainly occur from mid-winter to early spring(January–March); but in some of the CMIP5 models, a 1–2 month delay exists, especially in most of the CMIP5 GCMs. The long-term trend of the PVO time series does not correspond to long-term changes in the frequency of PVO events in most of the CMIP5 models.     

Changes in Wind Speed and Extremes in Beijing during 1960--2008 Based on Homogenized Observations

Daily observations of wind speed at 12 stations in the Greater Beijing Area during 1960–2008 were homogenized using the Multiple Analysis of Series for Homogenization method. The linear trends in the regional mean annual and seasonal (winter, spring, summer and autumn) wind speed series were-0.26,-0.39,-0.30,-0.12 and-0.22 m s-1 (10 yr)-1 , respectively. Winter showed the greatest magnitude in declining wind speed, followed by spring, autumn and summer. The annual and seasonal frequencies of wind speed extremes (days) also decreased, more prominently for winter than for the other seasons. The declining trends in wind speed and extremes were formed mainly by some rapid declines during the 1970s and 1980s. The maximum declining trend in wind speed occurred at Chaoyang (CY), a station within the central business district (CBD) of Beijing with the highest level of urbanization. The declining trends were in general smaller in magnitude away from the city center, except for the winter case in which the maximum declining trend shifted northeastward to rural Miyun (MY). The influence of urbanization on the annual wind speed was estimated to be about-0.05 m s-1 (10 yr)-1 during 1960–2008, accounting for around one fifth of the regional mean declining trend. The annual and seasonal geostrophic wind speeds around Beijing, based on daily mean sea level pressure (MSLP) from the ERA-40 reanalysis dataset, also exhibited decreasing trends, coincident with the results from site observations. A comparative analysis of the MSLP fields between 1966–1975 and 1992–2001 suggested that the influences of both the winter and summer monsoons on Beijing were weaker in the more recent of the two decades. It is suggested that the bulk of wind in Beijing is influenced considerably by urbanization, while changes in strong winds or wind speed extremes are prone to large-scale climate change in the region.     

The Arctic Sea Ice Thickness Change in CMIP6's Historical Simulations

This study assesses sea ice thickness(SIT) from the historical run of the Coupled Model Inter-comparison Project Phase 6(CMIP6). The SIT reanalysis from the Pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS)product is chosen as the validation reference data. Results show that most models can adequately reproduce the climatological mean, seasonal cycle, and long-term trend of Arctic Ocean SIT during 1979–2014, but significant intermodel spread exists. Differences in simulated SIT patte...     

Differences between CMIP6 and CMIP5 Models in Simulating Climate over China and the East Asian Monsoon

We compare the ability of coupled global climate models from the phases 5 and 6 of the Coupled Model Intercomparison Project(CMIP5 and CMIP6, respectively) in simulating the temperature and precipitation climatology and interannual variability over China for the period 1961–2005 and the climatological East Asian monsoon for the period1979–2005. All 92 models are able to simulate the geographical distribution of the above variables reasonably well.Compared with earlier CMIP5 models, current CMIP6 models have nationally weaker cold biases, a similar nationwide overestimation of precipitation and a weaker underestimation of the southeast–northwest precipitation gradient, a comparable overestimation of the spatial variability of the interannual variability, and a similar underestimation of the strength of winter monsoon over northern Asia. Pairwise comparison indicates that models have improved from CMIP5 to CMIP6 for climatological temperature and precipitation and winter monsoon but display little improvement for the interannual temperature and precipitation variability and summer monsoon. The ability of models relates to their horizontal resolutions in certain aspects. Both the multi-model arithmetic mean and median display similar skills and outperform most of the individual models in all considered aspects.     

Weak ENSO Asymmetry Due to Weak Nonlinear Air–Sea Interaction in CMIP5 Climate Models

State-of-the-art climate models have long-standing intrinsic biases that limit their simulation and projection capabilities.Significantly weak ENSO asymmetry and weakly nonlinear air–sea interaction over the tropical Pacific was found in CMIP5(Coupled Model Intercomparison Project, Phase 5) climate models compared with observation. The results suggest that a weak nonlinear air–sea interaction may play a role in the weak ENSO asymmetry. Moreover, a weak nonlinearity in air–sea interaction in the models may be associated with the biases in the mean climate—the cold biases in the equatorial central Pacific. The excessive cold tongue bias pushes the deep convection far west to the western Pacific warm pool region and suppresses its development in the central equatorial Pacific. The deep convection has difficulties in further moving to the eastern equatorial Pacific, especially during extreme El Ni o events, which confines the westerly wind anomaly to the western Pacific. This weakens the eastern Pacific El Ni o events, especially the extreme El Ni o events, and thus leads to the weakened ENSO asymmetry in climate models. An accurate mean state structure(especially a realistic cold tongue and deep convection) is critical to reproducing ENSO events in climate models. Our evaluation also revealed that ENSO statistics in CMIP5 climate models are slightly improved compared with those of CMIP3. The weak ENSO asymmetry in CMIP5 is closer to the observation. It is more evident in CMIP5 that strong ENSO activities are usually accompanied by strong ENSO asymmetry, and the diversity of ENSO amplitude is reduced.     

Does CMIP6 Inspire More Confidence in Simulating Climate Extremes over China?

Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during1961–2005, the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),and 30 models from phase 5 of CMIP(CMIP5), are assessed in terms of spatial distribution and interannual variability. The CMIP6 multi-model ensemble mean(CMIP6-MME) can simulate well the spatial pattern of annual mean temperature,maximum daily maximum temperature, and minimum daily minimum temperature. However, CMIP6-MME has difficulties in reproducing cold nights and warm days, and has large cold biases over the Tibetan Plateau. Its performance in simulating extreme precipitation indices is generally lower than in simulating temperature indices. Compared to CMIP5, CMIP6 models show improvements in the simulation of climate indices over China. This is particularly true for precipitation indices for both the climatological pattern and the interannual variation, except for the consecutive dry days. The arealmean bias for total precipitation has been reduced from 127%(CMIP5-MME) to 79%(CMIP6-MME). The most striking feature is that the dry biases in southern China, very persistent and general in CMIP5-MME, are largely reduced in CMIP6-MME. Stronger ascent together with more abundant moisture can explain this reduction in dry biases. Wet biases for total precipitation, heavy precipitation, and precipitation intensity in the eastern Tibetan Plateau are still present in CMIP6-MME, but smaller, compared to CMIP5-MME.     

The Role of the Aerosol Indirect Effect in the Northern Indian Ocean Warming Simulated by CMIP5 Models

The northern Indian Ocean （NIO） experienced a decadal-scale persistent warming from 1950 to 2000, which has influenced both regional and global climate. Because the NIO is a region susceptible to aerosols emis- sion changes, and there are still large uncertainties in the representation of the aerosol indirect effect （ALE） in CMIP5 （Coupled Model Intercomparison Project Phase 5） models, it is necessary to investigate the role of the AIE in the NIO warming simulated by these models. In this study, the authors select seven CMIP5 models with both the aerosol direct and indirect effects to investigate their performance in simulating the basin-wide decadal-scale NIO warming. The results show that the decreasing trend of the downwelling shortwave flux （FSDS） at the surface has the major damping effect on the SST increasing trend, which counteracts the warming effect of greenhouse gases （GHGs）. The FSDS decreasing trend is mostly contrib- uted by the decreasing trend of cloudy-sky surface downwelling shortwave flux （FSDSCL）, a metric used to measure the strength of the AIE, and partly by the clear-sky surface downwelling shortwave flux （FSDSC）. Models with a relatively weaker AIE can simulate well the SST increasing trend, as compared to observation. In contrast, models with a relatively stronger AIE produce a much smaller magnitude of the increasing trend, indicat- ing that the strength of the AIE in these models may be overestimated in the NIO.     

Contrasting Trend of Wintertime Wind Speed Between Near-surface and Upper Air in China During 1979–2021

The long-term height-resolved wind trend in China under global warming still needs to be discovered. To fill this gap, in this paper we examined the climatology and long-term(1979–2021) trends of the wintertime wind speed at the near-surface and upper atmosphere in China based on long-term radiosonde measurements. At 700, 500, and 400 hPa,much higher wind speed was found over eastern China, compared with western China. At 300, 200, and 100 hPa,maximum wind speed was observed in the latitude zone...     

Simulation and Projection of the Western Pacific Subtropical High in CMIP5 Models

This work examined the performance of 26 coupled climate models participating in the Coupled Model Intercomparison Project Phase 5 （CMIP5） in the simulation of the present-day temporal variability and spatial pattern of the western Pacifi c subtropical high （WPSH）. The results show that most models are able to capture the spatial distribution and variability of the 500-hPa geopotential height and zonal wind fi elds in the western subtropical Pacifi c, but with underestimated mean intensity of the WPSH. The underestimation may be associated with the cold bias of sea surface temperature in the tropical Indian and western Pacifi c oceans in the models. To eliminate the impact of the climatology biases, the climatology of these models is replaced by that of the NCEP/NCAR reanalysis in the verifi cation, and the models reproduce the WPSH’s enhancement and westward extension after the late 1970s. According to assessment of the simulated WPSH indices, it is found that some models （CNRM-CM5, FGOALS-g2, FIO-ESM, MIROC-ESM, and MPI-ESM-P） are better than others in simulating WPSH. Then, the ensemble mean of these better models is used to pro ject the future changes of WPSH under three representative concentration pathway scenarios （RCP8.5, RCP4.5, and RCP2.6）. The WPSH enlarges, strengthens, and extends westward under all the scenarios, with the largest linear growth trend projected in RCP8.5, smallest in RCP2.6, and in between in RCP4.5;while the ridge line of WPSH shows no obvious long-term trend. These results may have implications for the attribution and prediction of climate variations and changes in East Asia.     

Historical Trends in Surface Air Temperature Estimated by Ensemble Empirical Mode Decomposition and Least Squares Linear Fitting

Ensemble empirical mode decomposition(EEMD) and least squares linear fitting(LSLF) are applied to estimate the historical trends of surface air temperature(SAT) from observations and Coupled Model Intercomparison Project Phase 5(CMIP5) simulations during the period 1901–2005. The magnitudes of trends estimated by the two approaches are comparable. The trend calculated by the EEMD approach is larger than that by the LSLF approach in most(23/27) of the models during 1901–2005. During the slow warming period, the EEMD trend is smaller than the LSLF trend. The rootmean-square errors(RMSEs) between the raw and reconstructed times series by the LSLF approach are larger than those by the EEMD trend component and multi-decadal variability components during 1901–2005 in most of the models and observations. During 1901–70(or 1971–2005), the RMSEs between the raw and reconstructed times series by LSLF are larger than those by the EEMD trend component. In this sense, the EEMD trend is a better choice to obtain the climate trends in observations and CMIP5 models, especially for short time periods. This is because the trend estimated by LSLF cannot capture the internal variability and the cooling in some years. The estimated global warming rates(trend) are consistently larger(smaller) than those from observations in 11 of 27 CMIP5 models during 1901–2005 in the slow and rapid warming periods. This implies these 11 models have consistent responses to greenhouse gases for any period.     

Future Precipitation Extremes in China under Climate Change and Their Physical Quantification Based on a Regional Climate Model and CMIP5 Model Simulations

The atmospheric water holding capacity will increase with temperature according to Clausius-Clapeyron scaling and affects precipitation.The rates of change in future precipitation extremes are quantified with changes in surface air temperature.Precipitation extremes in China are determined for the 21st century in six simulations using a regional climate model,RegCM4,and 17 global climate models that participated in CMIP5.First,we assess the performance of the CMIP5 models and RCM runs in their simulation of extreme precipitation for the current period(RF:1982-2001).The CMIP5 models and RCM results can capture the spatial variations of precipitation extremes,as well as those based on observations:OBS and XPP.Precipitation extremes over four subregions in China are predicted to increase in the mid-future(MF:2039-58)and far-future(FF:2079-98)relative to those for the RF period based on both the CMIP5 ensemble mean and RCM ensemble mean.The secular trends in the extremes of the CMIP5 models are predicted to increase from 2008 to 2058,and the RCM results show higher interannual variability relative to that of the CMIP5 models.Then,we quantify the increasing rates of change in precipitation extremes in the MF and FF periods in the subregions of China with the changes in surface air temperature.Finally,based on the water vapor equation,changes in precipitation extremes in China for the MF and FF periods are found to correlate positively with changes in the atmospheric vertical wind multiplied by changes in surface specific humidity(significant at the p<0.1 level).     

Simulated Relationship between Wintertime ENSO and East Asian Summer Rainfall: From CMIP3 to CMIP6

El Ni?o-Southern Oscillation(ENSO)events have a strong influence on East Asian summer rainfall(EASR).This paper investigates the simulated ENSO-EASR relationship in CMIP6 models and compares the results with those in CMIP3 and CMIP5 models.In general,the CMIP6 models show almost no appreciable progress in representing the ENSO-EASR relationship compared with the CMIP5 models.The correlation coefficients in the CMIP6 models are relatively smaller and exhibit a slightly greater intermodel diversity than those in the CMIP5 models.Three physical processes related to the delayed effect of ENSO on EASR are further analyzed.Results show that,firstly,the relationships between ENSO and the tropical Indian Ocean(TIO)sea surface temperature(SST)in the CMIP6 models are more realistic,stronger,and have less intermodel diversity than those in the CMIP3 and CMIP5 models.Secondly,the teleconnections between the TIO SST and Philippine Sea convection(PSC)in the CMIP6 models are almost the same as those in the CMIP5 models,and stronger than those in the CMIP3 models.Finally,the CMIP3,CMIP5,and CMIP6 models exhibit essentially identical capabilities in representing the PSC-EASR relationship.Almost all the three generations of models underestimate the ENSO-EASR,TIO SST-PSC,and PSC-EASR relationships.Moreover,almost all the CMIP6 models that successfully capture the significant TIO SST-PSC relationship realistically simulate the ENSO-EASR relationship and vice versa,which is,however,not the case in the CMIP5 models.     

Maximum Wind Speed Changes over China

In this study,the maximum wind speed（WSmax） changes across China from 1956 to 2004 were analyzed based on observed station data,and the changes of WS max for 2046-2065 and 2080-2099 are projected using three global climate models（GFDL_CM2₀,CCCMA_CGCM3,and MRI_CGCM2） that have participated in the IPCC Fourth Assessment Report（AR4）.The observed annual and seasonal WS max and the frequency of gale days showed obvious declining trends.The annual WS max decreased by approximately 1.46 m s-1 per decade,and the number of gale days decreased by 3.0 days per decade from 1956 to 2004.The amplitudes of the annual and seasonal WS max decreases are larger than those of the annual and seasonal average wind speeds（WSavg）.The weakening of the East Asian winter and summer monsoons is the cause for the distinct decreases of both WS max and WS avg over the whole China.The decrease of WS max in the southeast coastal areas of China is related to the reduced intensity of cold waves in China and the decreasing number（and decreasing intensity） of land-falling typhoons originated in the Northwest Pacific Ocean.The global climate models GFDL_CM2₀,MRI_CGCM2,and EBGCM（the ensemble of above mentioned three global climate models） consistently suggest that the annual and seasonal WS max values will decrease during 2046-2065 and 2080-2099 relative to 1981-2000.The models also suggest that decreases in WS max for whole China during 2046-2065 and 2080-2099 are related to both the reduced intensity of cold waves and the reduced intensity of the winter monsoon,and the decrease in WS max in the southeast coastal areas of China is corresponding to the decreasing number of tropical cyclones over the Northwest Pacific Ocean in the summer during the same periods.     

Evaluation of Arctic Sea Ice Drift and its Relationship with Near-surface Wind and Ocean Current in Nine CMIP6 Models from China

The simulated Arctic sea ice drift and its relationship with the near-surface wind and surface ocean current during 1979-2014 in nine models from China that participated in the sixth phase of the Coupled Model Intercomparison Project(CMIP6)are examined by comparison with observational and reanalysis datasets.Most of the models reasonably represent the Beaufort Gyre(BG)and Transpolar Drift Stream(TDS)in the spatial patterns of their long-term mean sea ice drift,while the detailed location,extent,and strength of the BG and TDS vary among the models.About two-thirds of the models agree with the observation/reanalysis in the sense that the sea ice drift pattern is consistent with the near-surface wind pattern.About the same proportion of models shows that the sea ice drift pattern is consistent with the surface ocean current pattern.In the observation/reanalysis,however,the sea ice drift pattern does not match well with the surface ocean current pattern.All nine models missed the observational widespread sea ice drift speed acceleration across the Arctic.For the Arctic basin-wide spatial average,five of the nine models overestimate the Arctic long-term(1979-2014)mean sea ice drift speed in all months.Only FGOALS-g3 captures a significant sea ice drift speed increase from 1979 to 2014 both in spring and autumn.The increases are weaker than those in the observation.This evaluation helps assess the performance of the Arctic sea ice drift simulations in these CMIP6 models from China.     

CMIP5/AMIP GCM simulations of East Asian summer monsoon

The East Asian summer monsoon （EASM） is a distinctive component of the Asian climate system and critically influences the economy and society of the region.To understand the ability of AGCMs in capturing the major features of EASM,10 models that participated in Coupled Model Intercomparison Project/Atmospheric Model Intercomparison Project （CMIP5/AMIP）,which used observational SST and sea ice to drive AGCMs during the period 1979-2008,were evaluated by comparing with observations and AMIP Ⅱ simulations.The results indicated that the multi-model ensemble （MME） of CMIP5/AMIP captures the main characteristics of precipitation and monsoon circulation,and shows the best skill in EASM simulation,better than the AMIP Ⅱ MME.As for the Meiyu/Changma/Baiyu rainbelt,the intensity of rainfall is underestimated in all the models.The biases are caused by a weak western Pacific subtropical high （WPSH） and accompanying eastward southwesterly winds in group Ⅰ models,and by a too strong and west-extended WPSH as well as westerly winds in group Ⅱ models.Considerable systematic errors exist in the simulated seasonal migration of rainfall,and the notable northward jumps and rainfall persistence remain a challenge for all the models.However,the CMIP5/AMIP MME is skillful in simulating the western North Pacific monsoon index （WNPMI）.     

Chinese Contribution to CMIP5：An Overview of Five Chinese Models’Performances

An overview of Chinese contribution to Coupled Model Intercomparison Project-Phase 5 （CMIP5） is presented. The performances of five Chinese Climate/Earth System Models that participated in the CMIP5 pro ject are assessed in the context of climate mean states, seasonal cycle, intraseasonal oscillation, interan-nual variability, interdecadal variability, global monsoon, Asian-Australian monsoon, 20th-century historical climate simulation, climate change pro jection, and climate sensitivity. Both the strengths and weaknesses of the models are evaluated. The models generally show reasonable performances in simulating sea surface tem-perature （SST） mean state, seasonal cycle, spatial patterns of Madden-Julian oscillation （MJO） amplitude and tropical cyclone Genesis Potential Index （GPI）, global monsoon precipitation pattern, El Ni-no-Southern Oscillation （ENSO）, and Pacific Decadal Oscillation （PDO） related SST anomalies. However, the perfor-mances of the models in simulating the time periods, amplitude, and phase locking of ENSO, PDO time periods, GPI magnitude, MJO propagation, magnitude of SST seasonal cycle, northwestern Pacific mon-soon and North American monsoon domains, as well as the skill of large-scale Asian monsoon precipitation need to be improved. The model performances in simulating the time evolution and spatial pattern of the 20th-century global warming and the future change under representative concentration pathways pro jection are compared to the multimodel ensemble of CMIP5 models. The model discrepancies in terms of climate sensitivity are also discussed.     

Tropical cyclone genesis potential index over the western North Pacific simulated by CMIP5 models

Tropical cyclone(TC) genesis over the western North Pacific(WNP) is analyzed using 23 CMIP5(Coupled Model Intercomparison Project Phase 5) models and reanalysis datasets. The models are evaluated according to TC genesis potential index(GPI). The spatial and temporal variations of the GPI are first calculated using three atmospheric reanalysis datasets(ERA-Interim, NCEP/NCAR Reanalysis-1, and NCEP/DOE Reanalysis-2). Spatial distributions of July–October-mean TC frequency based on the GPI from ERA-interim are more consistent with observed ones derived from IBTr ACS global TC data. So, the ERA-interim reanalysis dataset is used to examine the CMIP5 models in terms of reproducing GPI during the period 1982–2005. Although most models possess deficiencies in reproducing the spatial distribution of the GPI, their multimodel ensemble(MME) mean shows a reasonable climatological GPI pattern characterized by a high GPI zone along 20?N in the WNP. There was an upward trend of TC genesis frequency during 1982 to 1998, followed by a downward trend. Both MME results and reanalysis data can represent a robust increasing trend during 1982–1998, but the models cannot simulate the downward trend after 2000. Analysis based on future projection experiments shows that the GPI exhibits no significant change in the first half of the 21 st century, and then starts to decrease at the end of the 21 st century under the representative concentration pathway(RCP) 2.6 scenario. Under the RCP8.5 scenario, the GPI shows an increasing trend in the vicinity of20?N, indicating more TCs could possibly be expected over the WNP under future global warming.     

Response of Atmospheric Energy to Historical Climate Change in CMIP5

Three forms of atmospheric energy, i.e., internal, potential, and latent, are analyzed based on the historical simulations of 32 Coupled Model Intercomparison Project Phase 5(CMIP5) models and two reanalysis datasets(NCEP/NCAR and ERA-40). The spatial pattern of climatological mean atmospheric energy is well reproduced by all CMIP5 models. The variation of globally averaged atmospheric energy is similar to that of surface air temperature(SAT) for most models. The atmospheric energy from both simulation and reanalysis decreases following the volcanic eruption in low-latitude zones. Generally, the climatological mean of simulated atmospheric energy from most models is close to that obtained from NCEP/NCAR, while the simulated atmospheric energy trend is close to that obtained from ERA-40. Under a certain variation of SAT, the simulated global latent energy has the largest increase ratio, and the increase ratio of potential energy is the smallest.