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Xuebin Zhang, Francis W. Zwiers, and Guilong Li

Abstract

Using Monte Carlo simulations, several methods for detecting a trend in the magnitude of extreme values are compared. Ordinary least squares regression is found to be the least reliable method. A Kendall's tau–based method provides some improvement. The advantage of this method over that of least squares diminishes when the sample size is moderate to small. Explicit consideration of the extreme value distribution when computing trend always outperforms the above two methods. The use of the r largest values as extremes enhances the power of detection for moderate values of r; the use of larger values of r may lead to bias in the magnitude of the estimated trend.

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Lijuan Li, Bin Wang, and Guang J. Zhang

Abstract

The weak response of surface shortwave cloud radiative forcing (SWCF) to El Niño over the equatorial Pacific remains a common problem in many contemporary climate models. This study shows that two versions of the Grid-Point Atmospheric Model of the Institute of Atmospheric Physics (IAP)/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG) (GAMIL) produce distinctly different surface SWCF response to El Niño. The earlier version, GAMIL1, underestimates this response, whereas the latest version, GAMIL2, simulates it well. To understand the causes for the different SWCF responses between the two simulations, the authors analyze the underlying physical mechanisms. Results indicate the enhanced stratiform condensation and evaporation in GAMIL2 play a key role in improving the simulations of multiyear annual mean water vapor (or relative humidity), cloud fraction, and in-cloud liquid water path (ICLWP) and hence in reducing the biases of SWCF and rainfall responses to El Niño due to all of the improved dynamical (vertical velocity at 500 hPa), cloud amount, and liquid water path (LWP) responses. The largest contribution to the SWCF response improvement in GAMIL2 is from LWP in the Niño-4 region and from low-cloud cover and LWP in the Niño-3 region. Furthermore, as a crucial factor in the low-cloud response, the atmospheric stability change in the lower layers is significantly influenced by the nonconvective heating variation during La Niña.

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Peng Lu, Hua Zhang, and Jiangnan Li

Abstract

A new scheme of water cloud optical properties is proposed for correlated k-distribution (CKD) models, in which the correlation in spectral distributions between the gaseous absorption coefficient and cloud optical properties is maintained. This is an extension of the CKD method from gas to cloud by dealing with the gas absorption coefficient and cloud optical properties in the same way.

Compared to the results of line-by-line benchmark calculations, the band-mean cloud optical property scheme can overestimate cloud solar heating rate, with a relative error over 30% in general. Also, the error in the flux at the top of the atmosphere can be up to 20 W m−2 at a solar zenith angle of 0°. However, the error is considerably reduced by applying the new proposed CKD cloud scheme. The physical explanation of the large error for the band-mean cloud scheme is the absence of a spectral correlation between the gaseous absorption coefficient and the cloud optical properties. The overestimation of the solar heating rate at the cloud-top layer could affect the moisture circulation and limit the growth of cloud. It is found that the error in the longwave cooling rate caused by the band-mean cloud scheme is very small. In the infrared, the local thermal emission strongly affects the spectral distribution of the radiative flux, which makes the correlation between the gaseous absorption coefficient and cloud optical properties very weak. Therefore, there is no obvious advantage in emphasizing the spectral correlation between gas and cloud.

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Dawei Li, Rong Zhang, and Thomas Knutson

Abstract

In this study the mechanisms for low-frequency variability of summer Arctic sea ice are analyzed using long control simulations from three coupled models (GFDL CM2.1, GFDL CM3, and NCAR CESM). Despite different Arctic sea ice mean states, there are many robust features in the response of low-frequency summer Arctic sea ice variability to the three key predictors (Atlantic and Pacific oceanic heat transport into the Arctic and the Arctic dipole) across all three models. In all three models, an enhanced Atlantic (Pacific) heat transport into the Arctic induces summer Arctic sea ice decline and surface warming, especially over the Atlantic (Pacific) sector of the Arctic. A positive phase of the Arctic dipole induces summer Arctic sea ice decline and surface warming on the Pacific side, and opposite changes on the Atlantic side. There is robust Bjerknes compensation at low frequency, so the northward atmospheric heat transport provides a negative feedback to summer Arctic sea ice variations. The influence of the Arctic dipole on summer Arctic sea ice extent is more (less) effective in simulations with less (excessive) climatological summer sea ice in the Atlantic sector. The response of Arctic sea ice thickness to the three key predictors is stronger in models that have thicker climatological Arctic sea ice.

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Guoyu Ren, Hongbin Liu, Ziying Chu, Li Zhang, Xiang Li, Weijing Li, Yu Chen, Ge Gao, and Yan Zhang
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Guoyu Ren, Hongbin Liu, Ziying Chu, Li Zhang, Xiang Li, Weijing Li, Yu Chen, Ge Gao, and Yan Zhang

Abstract

Middle and eastern routes of the South–North Water Diversion Project (SNWDP) of China, which are approximately located within the area 28°–42°N and 110°–122°E, are being constructed. This paper investigates the past climatic variations on various time scales using instrumental and proxy data. It is found that annual mean surface air temperature has increased significantly during the past 50–100 years, and winter and spring temperatures in the northern part of the region have undergone the most significant changes. A much more significant increase occurs for annual mean minimum temperature and extreme low temperature than for annual mean maximum temperature and extreme high temperature. No significant trend in annual precipitation is found for the region as a whole for the last 50 and 100 years, although obvious decadal and spatial variation is detectable. A seesaw pattern of annual and summer precipitation variability between the north and the south of the region is evident. Over the last 100 years, the Haihe River basin has witnessed a significant negative trend of annual precipitation, but no similar trend is detected for the Yangtze and Huaihe River basins. Pan evaporation has significantly decreased since the mid-1960s in the region in spite of the fact that the trend appears to have ended in the early 1990s. The negative trend of pan evaporation is very significant in the plain area between the Yangtze and Yellow Rivers. There was a notable series of dry intervals lasting decades in the north of the region. The northern drought of the past 30 years is not the most severe in view of the past 500 years; however, the southern drought during the period from the 1960s to the 1980s may have been unprecedented. The dryness–wetness index (DWI) shows significant oscillations with periodicities of 9.5 and 20 years in the south and 10.5 and 25 years in the north. Longer periodicities in the DWI series include 160–170- and 70–80-yr oscillations in the north, and 100–150-yr oscillations in the south. The observed climate change could have implications for the construction and management of the SNWDP. The official approval and start of the hydro project was catalyzed by the severe multiyear drought of 1997–2003 in the north, and the operation and management of the project in the future will also be influenced by climate change—in particular by precipitation variability. This paper provides a preliminary discussion of the potential implications of observed climate change for the SNWDP.

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Jianping Duan, Qi-bin Zhang, and Li-Xin Lv

Abstract

The recent increase in the frequency of winter cold extremes has received particular attention in light of the climate's warming. Knowledge about changes in the frequency of winter cold extremes requires long-term climate data over large spatial scale. In this study, a temperature-sensitive tree-ring network consisting of 31 sampling sites collected from seven provinces in subtropical China was used to investigate the characteristics of cold-season temperature extremes during the past two centuries. The results show that the percentage of trees in a year that experienced an abnormal decrease in radial growth relative to the previous year can serve as an indicator of interannual change in January–March temperature in subtropical China. The frequency of extreme interannual decreases in cold-season temperature has increased since the 1930s. The change in cold-season temperature was significantly correlated with the intensity of the Siberian high, yet the correlation was much weaker in the period preceding the 1930s. The findings provide evidence of a frequency change in the occurrence of interannual cold-season temperature extremes in the past two centuries for subtropical China. Particularly, the pattern in the variation of cold-season temperature suggests a change in climate systems around the 1930s.

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Xinrong Wu, Wei Li, Guijun Han, Shaoqing Zhang, and Xidong Wang

Abstract

While fixed covariance localization can greatly increase the reliability of the background error covariance in filtering by suppressing the long-distance spurious correlations evaluated by a finite ensemble, it may degrade the assimilation quality in an ensemble Kalman filter (EnKF) as a result of restricted longwave information. Tuning an optimal cutoff distance is usually very expensive and time consuming, especially for a general circulation model (GCM). Here the authors present an approach to compensate the demerit in fixed localization. At each analysis step, after the standard EnKF is done, a multiple-scale analysis technique is used to extract longwave information from the observational residual (referred to the EnKF ensemble mean). Within a biased twin-experiment framework consisting of a global barotropical spectral model and an idealized observing system, the performance of the new method is examined. Compared to a standard EnKF, the hybrid method is superior when an overly small/large cutoff distance is used, and it has less dependence on cutoff distance. The new scheme is also able to improve short-term weather forecasts, especially when an overly large cutoff distance is used. Sensitivity studies show that caution should be taken when the new scheme is applied to a dense observing system with an overly small cutoff distance in filtering. In addition, the new scheme has a nearly equivalent computational cost to the standard EnKF; thus, it is particularly suitable for GCM applications.

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Peng Zhao, Xiaotao Zhang, Sien Li, and Shaozhong Kang

Abstract

For sparse planting crops, soil surface plays an important role in energy balance processes within the soil–canopy–atmosphere continuum; thus, it is necessary to partition field energy fluxes into soil surface and canopy to provide useful information to reduce agricultural water use and to develop evapotranspiration models. Field experiments were conducted in vineyards during four growing seasons to examine the energy partitioning among soil surface, canopy, and field separately. Vineyard energy fluxes including latent heat (LE) were measured by eddy covariance system and canopy latent heat LEc was obtained from sap flow. Then, soil surface latent heat LEs was calculated as the difference between LE and LEc. The Bowen ratio and the ratio of latent heat to available energy were used to examine energy partitioning. Results indicate daily and hourly LEs obtained from LE and LEc overestimated microlysimeter-derived values by 13.0% and 10.8%, respectively. Seasonal-average latent heat accounted for 59.0%–64.3%, 65.8%–77.8%, and 56.6%–62.5% of corresponding available energy for vineyard, canopy, and soil surface, respectively. Soil water content and canopy were the main controlling factors on energy partitioning. Surface soil moisture explained 32%, 11%, and 52% of the seasonal variability in energy partitioning at field, canopy, and soil surface, respectively. Leaf area index explained 41% and 26% of the seasonal variability in energy partitioning at field and soil surface. Air temperature was related to canopy and field energy partitioning. During wet periods, soil can absorb sensible heat from the canopy and LEs may exceed soil surface available energy, while during dry periods, the canopy may absorb sensible heat from the soil and LEc may exceed canopy available energy.

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Tim Li, Bin Wang, C-P. Chang, and Yongsheng Zhang

Abstract

Four fundamental differences of air–sea interactions between the tropical Pacific and Indian Oceans are identified based on observational analyses and physical reasoning. The first difference is represented by the strong contrast of a zonal cloud–SST phase relationship between the warm and cool oceans. The in-phase cloud–SST relationship in the warm oceans leads to a strong negative feedback, while a significant phase difference in the cold tongue leads to a much weaker thermodynamic damping. The second difference arises from the reversal of the basic-state zonal wind and the tilting of the ocean thermocline, which leads to distinctive effects of ocean waves. The third difference lies in the existence of the Asian monsoon and its interaction with the adjacent oceans. The fourth difference is that the southeast Indian Ocean is a region where a positive atmosphere–ocean thermodynamic feedback exists in boreal summer.

A conceptual coupled atmosphere–ocean model was constructed aimed to understand the origin of the Indian Ocean dipole–zonal mode (IODM). In the model, various positive and negative air–sea feedback processes were considered. Among them were the cloud–radiation–SST feedback, the evaporation–SST–wind feedback, the thermocline–SST feedback, and the monsoon–ocean feedback. Numerical results indicate that the IODM is a dynamically coupled atmosphere–ocean mode whose instability depends on the annual cycle of the basic state. It tends to develop rapidly in boreal summer but decay in boreal winter. As a result, the IODM has a distinctive evolution characteristic compared to the El Niño. Sensitivity experiments suggest that the IODM is a weakly damped oscillator in the absence of external forcing, owing to a strong negative cloud–SST feedback and a deep mean thermocline in the equatorial Indian Ocean.

A thermodynamic air–sea (TAS) feedback arises from the interaction between an anomalous atmospheric anticyclone and a cold SST anomaly (SSTA) off Sumatra. Because of its dependence on the basic-state wind, the nature of this TAS feedback is season dependent. A positive feedback occurs only in northern summer when the southeasterly flow is pronounced. It becomes a negative feedback in northern winter when the northwesterly wind is pronounced. The phase locking of the IODM can be, to a large extent, explained by this seasonal-dependent TAS feedback. The biennial tendency of the IODM is attributed to the monsoon–ocean feedback and the remote El Niño forcing that has a quasi-biennial component.

In the presence of realistic Niño-3 SSTA forcing, the model is capable of simulating IODM events during the last 50 yr that are associated with the El Niño, indicating that ENSO is one of triggering mechanisms. The failure of simulation of the 1961 and 1994 events suggests that other types of climate forcings in addition to the ENSO must play a role in triggering an IODM event.

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