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Jiafeng Wang
and
Xuebin Zhang

Abstract

Large-scale atmospheric variables have been statistically downscaled to derive winter (December–March) maximum daily precipitation at stations over North America using the generalized extreme value distribution (GEV). Here, the leading principal components of the sea level pressure field and local specific humidity are covariates of the distribution parameters. The GEV parameters are estimated using data from 1949 to 1999 and the r-largest method. This statistical downscaling procedure is found to yield skill over the southern and northern West Coast, central United States, and areas of western and eastern Canada when tested with independent data.

The projected changes in covariates or predictors are obtained from transient climate change simulations conducted with the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled General Circulation Model, version 3.1 (CGCM3.1) forced by the Intergovernmental Panel on Climate Change (IPCC) A2 forcing scenario. They are then used to derive the GEV distribution parameters for the period 2050–99. The projected frequency of the current 20-yr return maximum daily precipitation for that period suggests that extreme precipitation risk will increase heavily over the south and central United States but decrease over the Canadian prairies. The difference between the statistical downscaling results and those estimated using GCM simulation is also discussed.

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Cheng Qian
and
Xuebin Zhang

Abstract

Temperature seasonality, the difference between summer and winter temperatures in mid–high latitudes, is an important component of the climate. Whether humans have had detectable influences on changing surface temperature seasonality at scales smaller than the subcontinental scale, where humans are directly impacted, is not clear. In this study, the first detection and attribution analysis of changes in temperature seasonality in China has been carried out. Detection and attribution of both summer and winter temperatures were also conducted, with careful consideration of observational uncertainty and the inconsistency between observation and model simulations induced by the long coastline and country border in China. The results show that the response to external forcings is robustly detectable in the spatiotemporal pattern of weakening seasonality and in that of warming winter temperature, although models may have underestimated the observed changes. The response to external forcings is detectable and consistent with the observed change in summer temperature averaged over China. Human influences are detectable in changes in seasonality and summer and winter temperatures, most robustly in winter, and these influences can be separated from those of natural forcing when averaged over China. The recent increase in summer temperature was found to be due to external forcings, and the warming hiatus in winter temperature from 1998 to 2013 was due to a statistically significant cooling trend induced by internal variability. These results will give insights into the understanding of the warming hiatus in China, as well as the hot summers and cold winters in recent years.

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Cheng Qian
and
Xuebin Zhang

Abstract

The annual cycle is the largest variability for many climate variables outside the tropics. Whether human activities have affected the annual cycle at the regional scale is unclear. In this study, long-term changes in the amplitude of surface air temperature annual cycle in the observations are compared with those simulated by the climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Different spatial domains ranging from hemispheric to subcontinental scales in mid- to high-latitude land areas for the period 1950–2005 are considered. Both the optimal fingerprinting and a nonoptimal detection and attribution technique are used. The results show that the space–time pattern of model-simulated responses to the combined effect of anthropogenic and natural forcings is consistent with the observed changes. In particular, models capture not only the decrease in the temperature seasonality in the northern high latitudes and East Asia, but also the increase in the Mediterranean region. A human influence on the weakening in the temperature seasonality in the Northern Hemisphere is detected, particularly in the high latitudes (50°–70°N) where the influence of the anthropogenic forcing can be separated from that of the natural forcing.

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Xuebin Zhang
and
Michael J. McPhaden

Abstract

Vertical advection of temperature is the primary mechanism by which El Niño–Southern Oscillation (ENSO) time-scale sea surface temperature (SST) anomalies are generated in the eastern equatorial Pacific. Variations in vertical advection are mediated primarily by remote wind-forced thermocline displacements, which control the temperature of water upwelled to the surface. However, during some ENSO events, large wind stress variations occur in the eastern Pacific that in principle should affect local upwelling rates, the depth of the thermocline, and SST. In this study, the impact of these wind stress variations on the eastern equatorial Pacific is addressed using multiple linear regression analysis and a linear equatorial wave model. The regression analysis indicates that a zonal wind stress anomaly of 0.01 N m−2 leads to approximately a 1°C SST anomaly over the Niño-3 region (5°N–5°S, 90°–150°W) due to changes in local upwelling rates. Wind stress variations of this magnitude occurred in the eastern Pacific during the 1982/83 and 1997/98 El Niños, accounting for about 1/3 of the maximum SST anomaly during these events. The linear equatorial wave model also indicates that depending on the period in question, zonal wind stress variations in the eastern Pacific can work either with or against remote wind stress forcing from the central and western Pacific to determine the thermocline depth in the eastern Pacific. Thus, zonal wind stress variations in the eastern Pacific contribute to the generation of interannual SST anomalies through both changes in local upwelling rates and changes in thermocline depth. Positive feedbacks between the ocean and atmosphere in the eastern Pacific are shown to influence the evolution of the surface wind field, especially during strong El Niño events, emphasizing the coupled nature of variability in the region. Implications of these results for understanding the character of event-to-event differences in El Niño and La Niña are discussed.

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Xuebin Zhang
,
Jian Sheng
, and
Amir Shabbar

Abstract

The multichannel singular spectrum analysis has been used to characterize the spatio–temporal structures of interdecadal and interannual variability of SST over the Pacific Ocean from 20°S to 58°N. Using the Comprehensive Ocean–Atmosphere Data Set from 1950 to 1993, three modes with distinctive spatio-temporal structures were found. They are an interdecadal mode, a quasi-quadrennial (QQ) oscillation with a period of 51 months, and a quasi-biennial (QB) oscillation with a period of 26 months. The interdecadal mode is a standing mode with opposite signs of SST anomalies in the North Pacific and in the tropical Pacific. The amplitude of this mode is larger in the central North Pacific than in the tropical Pacific. This mode contributes 11.4% to the total variance. It is associated with cooling in the central North Pacific and warming in the equatorial Pacific since around 1976–77. The QQ oscillation exhibits propagation of SST anomalies northeastward from the Philippine Sea and then eastward along 40°N, but behaves more like a standing wave over the tropical Pacific. It explains nearly 20% of the total variance. The QB oscillation is localized in the Tropics and is characterized by the westward propagation of SST anomalies near the equator. This mode accounts for 7.4% of the total variance. Since the interdecadal mode is apparently independent of QB and QQ oscillations, it may play an important role in configuring the state of the tropical SST anomalies, which in turn affects the strength of the El Niño–Southern Oscillation phenomenon. It seems likely that the higher phase of the interdecadal mode since 1976–77 has raised the background SST state, on which the superposition of the QQ and QB oscillations produced the strongest warm event on record in 1982–83, as well as more frequent warm events since 1976.

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Chunhui Lu
,
Ying Sun
, and
Xuebin Zhang

Abstract

The diurnal temperature range (DTR) as measured by the difference between daily maximum (Tmax) and minimum (Tmin) temperatures is of great importance to human health, ecology, and agriculture. The link of its long-term change to anthropogenic forcing is still unclear. This study shows evidence of human influence on long-term changes in DTR over the globe, five continents, and China during the past century (1901–2014). Using multiple observational datasets, we find a general decrease in the DTR over most of the global land since 1901, especially after the mid-1950s. Changes in DTR are due to different warming rates of Tmax and Tmin in response to external forcings. The climate models that participated in phase 6 of the Coupled Model Intercomparison Project Phase 6 (CMIP6) generally reproduce most of the changes in DTR, along with those in Tmax and Tmin. The models have underestimated the observed changes in DTR, however. A formal detection and attribution analysis shows that the anthropogenic forcing signal, including both greenhouse gas and aerosol emissions but dominated by the greenhouse gas emissions, is the main driver for these changes. The anthropogenic aerosol signal can be detected in Tmax and Tmin but not in DTR during the period of 1901–2014 over the globe and most continents. These indicate the observed decrease in DTR is not a simple response to anthropogenic aerosol emission. The natural signal is negligible in almost all the cases. Globally, anthropogenic influence is estimated to explain more than 90% of the observed changes in the three variables. In China, human influence is also clearly detected, although model simulated results on the regional scale have larger deviation.

Significance Statement

The diurnal temperature range (DTR) is of great importance in many areas. We compare multiple observational datasets with the simulations by climate models that participated in the latest phase (phase 6) of the Coupled Model Intercomparison Project (CMIP6), finding evidence of human influence on long-term changes in DTR over the past century (1901–2014) and robust evidence for the period since the early 1950s. The decrease in DTR as seen in the observational dataset is caused by different warming rates of daily maximum and daily minimum temperature in response to anthropogenic forcing, including both greenhouse gases and aerosols.

Open access
Tong Li
,
Xuebin Zhang
, and
Zhihong Jiang

Abstract

Weighting models according to their performance has been used to produce multimodel climate change projections. But the added value of model weighting for future projection is not always examined. Here we apply an imperfect model framework to evaluate the added value of model weighting in projecting summer temperature changes over China. Members of large-ensemble simulations by three climate models of different climate sensitivities are used as pseudo-observations for the past and the future. Performance of the models participating in the phase 6 of the Coupled Model Intercomparison Project (CMIP6) are evaluated against the pseudo-observations based on simulated historical climatology and trends in global, regional, and local temperatures to determine the model weights for future projection. The weighted projections are then compared with the pseudo-observations in the future period. We find that regional trend as a metric of model performance yields generally better skill for future projection, while past climatology as performance metric does not lead to a significant improvement to projection. Trend at the grid-box scale is also not a good performance indicator as small-scale trend is highly uncertain. For the model weighting to be effective, the metric for evaluating the model’s performance must be relatable to future changes, with the response signal separable from internal variability. Projected summer warming based on model weighting is similar to that of unweighted projection but the 5th–95th-percentile uncertainty range of the weighted projection is 38% smaller with the reduction mainly in the upper bound, with the largest reduction appearing in southeast China.

Open access
Xuebin Zhang
and
Michael J. McPhaden

Abstract

The authors use a new and novel heat balance formalism for the upper 50 m of the Niño-3 region (5°N–5°S, 90°–150°W) to investigate the oceanographic processes underlying interannual sea surface temperature (SST) variations in the eastern equatorial Pacific. The focus is on a better understanding of the relationship between local and remote atmospheric forcing in generating SST anomalies associated with El Niño–Southern Oscillation (ENSO) events. The heat balance analysis indicates that heat advection across 50-m depth and across 150°W are the important oceanic mechanisms responsible for temperature variations with the former being dominant. On the other hand, net surface heat flux adjusted for penetrative radiation damps SST. Jointly, these processes can explain most of interannual variations in temperature tendency averaged over the Niño-3 region. Decomposition of vertical advection across the bottom indicates that the mean seasonal advection of anomalous temperature (the so-called thermocline feedback) dominates and is highly correlated with 20°C isotherm depth variations, which are mainly forced by remote winds in the western and central equatorial Pacific. Temperature advection by anomalous vertical velocity (the “Ekman feedback”), which is highly correlated with local zonal wind stress variations, is smaller with an amplitude of about 40% on average of remotely forced vertical heat advection. These results support those of recent empirical and modeling studies in which local atmospheric forcing, while not dominant, significantly affects ENSO SST variations in the eastern equatorial Pacific.

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Xuebin Zhang
,
Bruce Cornuelle
, and
Dean Roemmich

Abstract

The evolution of sea surface temperature (SST) over the eastern equatorial Pacific plays a significant role in the intense tropical air–sea interaction there and is of central importance to the El Niño–Southern Oscillation (ENSO) phenomenon. Effects of atmospheric fields (especially wind stress) and ocean state on the eastern equatorial Pacific SST variations are investigated using the Massachusetts Institute of Technology general circulation model (MITgcm) and its adjoint model, which can calculate the sensitivities of a cost function (in this case the averaged 0–30-m temperature in the Niño-3 region during an ENSO event peak) to previous atmospheric forcing fields and ocean state going backward in time. The sensitivity of the Niño-3 surface temperature to monthly zonal wind stress in preceding months can be understood by invoking mixed layer heat balance, ocean dynamics, and especially linear equatorial wave dynamics. The maximum positive sensitivity of the Niño-3 surface temperature to local wind forcing usually happens ~1–2 months before the peak of the ENSO event and is hypothesized to be associated with the Ekman pumping mechanism. In model experiments, its magnitude is closely related to the subsurface vertical temperature gradient, exhibiting strong event-to-event differences with strong (weak) positive sensitivity during La Niña (strong El Niño) events. The adjoint sensitivity to remote wind forcing in the central and western equatorial Pacific is consistent with the standard hypothesis that the remote wind forcing affects the Niño-3 surface temperature indirectly by exciting equatorial Kelvin and Rossby waves and modulating thermocline depth in the Niño-3 region. The current adjoint sensitivity study is consistent with a previous regression-based sensitivity study derived from perturbation experiments. Finally, implication for ENSO monitoring and prediction is also discussed.

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Francis W. Zwiers
and
Xuebin Zhang

Abstract

Using an optimal detection technique, the extent to which the combined effect of changes in greenhouse gases and sulfate aerosols (GS) may be detected in observed surface temperatures is assessed in six spatial domains decreasing in size from the globe to Eurasia and North America, separately. The GS signal is detected in the annual mean near-surface temperatures of the past 50 yr in all domains. It is also detected in some seasonal mean temperatures of the past 50 yr, with detection in more seasons in larger domains.

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