Acta Oceanol. Sin., 2011, Vol. 30, No. 2, P. 33-45 DOI: 10.1007/s13131-011-0103-x http://www.hyxb.org.cn E-mail: [email protected]

Features of aerosol optical depth and its relation to extreme temperatures in China during 1980–2001 HU Ting1,2∗ , SUN Zhaobo1,2 , LI Zhaoxin3 1

Jiangsu Key Laboratory of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044, China

2

The Department of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, China

3

Laboratoire de Meteorologie Dynamique, CNRS, France

Received 4 May 2010; accepted 2 November 2010 ©The Chinese Society of Oceanography and Springer-Verlag Berlin Heidelberg 2011

Abstract Based on Total Ozone Mapping Spectrometer (TOMS) monthly aerosol optical thickness (AOT) measurements in 1980–2001 a study is made of space/time patterns and difference between land and sea of AOT 0.50 µm thick over China, which are put into correlation analysis with synchronous extreme temperature indices (warm/cold day and night). Results suggest that 1) the long-term mean AOT over China is characterized by typical geography, with pronounced land-sea contrast. And AOT has significant seasonality and its seasonal difference is diminished as a function of latitude. 2) On the whole, the AOT displays an appreciably increasing trend, with the distinct increase in the eastern Qinghai-Tibetan plateau and SW China, North China, the mid-lower Changjiang (MiLY) valley as well as the South China Sea, but marginal decrease over western/northern Xinjiang and part of South China. 3) The AOT over land and sea is marked by conspicuous intra-seasonal and -yearly oscillations, with remarkable periods at one-, two-yr and more (as interannual periods). 4) Land AOT change is well correlated with extremely temperature indexes. Generally, the correlations of AOT to the extreme temperature indices are more significant in Eastern China with 110◦ E as the division. Their high-correlation regions are along the Southern China coastline, the Loess Plateau and the Sichuan Basin, and even higher in North China Plain and the mid-lower Changjiang River reaches. 5) Simulations of LMDZ-regional model indicate that aerosol effects may result in cooling all over China, particularly in Eastern China. The contribution of aerosol change may result in more decrease in the maximum temperature than the minimum, with decrease of 0.11/0.08 K for zonal average, respectively. Key words: aerosol optical thickness, extreme temperature index, space/time pattern, trend, correlation

1 Introduction Tropospheric aerosol particles are one of the important components of the system consisting of the globe, atmosphere and oceans, able to directly affect earth-air radiative equilibrium through absorbing and scattering solar radiation and also participating, by means of acting as cloud condensation nuclei and heterogeneous phase chemical reaction, in a range of chemical processes to impact the source/sink of greenhouse gases so that they have innegligible significance to global climate change. There are great uncertainties regarding aerosol climate effect owing to lack of complete knowledge of the changing space/time patterns, optical properties and size spectrum as the prin-

cipal parameters of the particles (Houghton et al., 2001; Loeb et al., 2005; Bates et al., 2006; Yu et al., 2006). As one of the crucial parameters in the study of aerosols, AOT represents a physical variable for characterizing atmospheric turbidity, a key factor of climate aerosol impacts as well as an important parameter of atmospheric models (Durkee, et al., 1991). Of the AOT acquisitions (broadband extinction, satellite sensing retrieval and surface observations), satellite sensing can timely detect aerosol space/time distribution over a large area, thereby acting as a reliable technique for observation and experiment on global and regional aerosol distribution, its variation, optical properties and its radiative effect (King et al., 1999).

Foundation item: Foundation of Jiangsu Key Laboratory of Meteorological Disaster under contract No. KLME05001. author, E-mail: [email protected]

∗ Corresponding

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Now, data from such transducers as NOAA/AVHRR, TOMS, MODIS, SeaWiFS, MISR and GMS/VISS are widely employed in similar studies (Torres et al., 1998, 2002; Zhang et al., 2002; Li et al., 2003, 2005; Xu et al., 2005; Hao et al., 2006). The study on AOT climate effect depends greatly on its space/time patterns and so researchers have made numerous efforts specific to AOT space/time patterns over China. For example, in their study on 1961–1990 AOT variations and yearly means distributed over China, Luo et al. (2001) discovered that high-value areas are in the Sichuan and southern Xinjiang Basins, with the annual variation keeping a rising trend. Zhang et al. (2002) made research into aerosol distribution and properties over China via the combination of photometers for ground observation with satellite probing, uncovering that in the vicinity of the mid–lower valleys of the Huanghe/Changjiang Rivers, seaboards as well as the Sichuan Basis there are maximal AOT cores throughout the year; much of the country shows the greatest AOT in spring, during which NW China suffers sandstorms or suspended dusts in the air, leading to its maximum cores therein. Li et al. (2003) owed the aerosol source in Eastern China to human activity, with bands of maximum AOT in the North-China plains, MiLY valley, the Sichuan Basis and the delta region of the Pearl River as zones of industrially-developed, densely-populated and swift economical prosperity, in addition to high-value AOT zones in NW China due to sandstorm. Also, Zong et al. (2005) undertook a study using broad-width extinction technique on 1993–2002 AOT features, indicating that its annual mean displays no longer an increasing trend, with some stations like Beijing exhibiting a markedly reducing trend. Hu et al (2008) indicated a roughly growing trend of aerosol optical thickness all over China. Wang et al. (2006) demonstrated linear forcing on radiation of sand-dust AOT. Up to date the research into AOT properties has received a particular concern of large cities, i.e., Beijing (Xu et al., 2005), Lanzhou (Zhao et al., 2005), Hong Kong (Li et al., 2005). Besides, domestic and foreign researchers have taken great interest in AOT features over seas of China (Zhao et al., 2005; Hao et al., 2006) as well as impacts of AOT above China on regional climate. Some studies emphasized the cooling effects of increasing aerosol in China (Xu, 2001; Qian et al., 2003; Zhou and Yu, 2006; Li et al., 2007). As shown by modeling from Menon et al (2002),

the surface temperature in China may drop 0.1∼1.0 k on account of AOT. Zhou et al. (1998) found a decreasing trend caused by the increase in atmospheric aerosol loadings for the ground temperature, particularly from the Sichuan Basin to the MiLY valley as well as from the north side of the Tibetan plateau to the Hetao region of north Ningxia. Li et al. (2007), with the Grid Atmospheric Model of IAP LASG, suggested a significant contribution by the sulfate aerosol to surface cooling over Eastern China, through both dynamic and thermal processes. They found that the inclusion of the sulfate aerosol induces a positive gradient of air temperature in the middle-upper troposphere, which results in a northward shift in the 200 hPa East Asian westerly jet stream and an increase of the East Asian summer monsoon, leading to less cloud cover and precipitation over the MiLY Valley, more in Eastern China therefore surface cooling over the region. Nowadays a major worry of mankind is anthropogenic climate change and its socioeconomic impacts. In line with the characteristics of global temperature rise (Jones et al., 1999; Karl et al., 2000), extreme weather and climate events have received increased attention in the last few years, several papers (Karl et al., 1999, Easterling et al, 2000; Frich et al., 2002; KleinTank and K¨ onnen, 2003) paid attention to the characteristics of extreme temperature events, with the works of Intergovernmental Panel on Climate Change (IPCC) 3rd Assessment Report (TAR, 2001) and 4th Assessment Report (AR4, 2007). Alexander et al. (2006) showed widespread significant changes in temperature extremes associated with warming, especially for those indices derived from daily minimum temperature all over the world. Extreme temperature events in China have also attracted researcher’s attentions (Karl et al., 1991; Ren and Zhai, 1998; Qian et al., 2003; Zhai and Pan, 2003; Qian et al., 2007). As investigated in recent years, great influences on the trends of extreme temperature may be caused by aerosols (Xu, 2001; Wild et al., 2004; Qian and Lin, 2004). And when increasing sulfate aerosols are considered, simulations are able to realistically capture the observed climatological large-scale patterns of extreme temperature indices (IPCC, 2007). Activities of the WMO CCl/CLIVAR Working Group on Climate Change Detection (Peterson et al., 2001) also reached similar conclusions. However, regional connections between aerosol and extreme temperature events are not clear now.

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To gain overall insight into AOT space/time patterns and its long-term evolutions over China, the authors have investigated, by means of TOMS soundings, the geographical distribution, seasonality and trends of 500 nm AOT, difference between land and sea in China in view of TOMS large-scale coverage. In addition, correlations of land AOT with extreme temperature indices, i.e., warm and cold day/night are dealt with in an attempt to explore the climate-AOT relationships on an initial basis. Then, LMDZ-regional model is used to estimate the contributions of aerosol to the extreme temperature over China. 2 Data and processing

tensive region (2◦ –55◦ N, 70◦ –140◦ E), we used it as an expedient approach. Because of presumed uncertainties of aerosol models it is necessary to assess and test TOMS data, for which AERONET sunphotometer-made AOT soundings are often used to validate satellite probed AOT, arriving at precision of 0.01–0.02 (Holben et al., 1998). Table 1. Positions of AERONET stations with their observations used for comparison to TOMS AOT station Beijing Dunhuang Yulin

2.1 AOT Observations and Validation Xianghe

Data used included TOMS-offered global monthly 500 nm AOT measurements in January 1980– December 1992 and also August 1996–December 2001(with observations missing in January 1993– July 1996), totaling 221 months, and the data were at resolution of 1◦ ×1◦ lat/long, downloaded from NASA/TOMS website. TOMS scientists have constructed tables for finding corresponding radiation values by calculating radiative transfer from aerosol models with different assumptions presumed. They investigated the relation of ratio (Iλ1 /Iλ2 ) of backscattering radiation of near ultraviolet bands (λ2 > λ1 ) to backscattering of longer wavelength radiation (Iλ ) to obtain AOT values over land and ocean. The reader is referred to Torres et al. (1998, 2002) for details. Good consistency is found between retrievals and AERONET observations over land (Torres et al., 1998; 2002) and ocean (Myhre et al., 2004). This work employed re-corrected data by Torres et al. in 2006. Consequently, results from the algorithm for corrected TOMS aerosol are the same as those of the Aura-OMI scheme due to the fact that the former draws upon the dataset of even accurate ground reflectance, thereby modifying the underestimated albedo by 0.015 from the original algorithm and thus decreasing spurious high values of AOT data (overestimated by 0.1∼0.2). Land area in 15◦ –55◦ N, 70◦ –140◦ E and ocean extent in 2◦ –42◦ N, 98◦ –138◦ E were selected for AOT study. The year was divided into spring (MarchMay), summer (June-August), autumn (SeptemberNovember) and winter (December-February). However, although it was not entirely reasonable to divide seasons in accordance with the definition for the ex-

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(◦ E)

(◦ N)

heads

116.381 39.977 Hong-Bin Chen and P. Goloub 94.794 40.038 B. Holben 109.717 38.283 B. Chatenet, Xiao-Ye Zhang, L. Gomes 116.962 39.754 Pucai Wang and Zhanqing Li 115.954 42.683 B. Holben 116.724 20.709 B. Holben 121.100 24.900 Gin-Rong Liu

Nei Mongolia Dong Sha (Island) Taiwan Central University Shirahama (Japan) 135.357 33.693 B. Holben Anmyon (Korea) 126.330 36.539 Cha Joo-Wan, B. Holben

There are nine AERONET ground-based stations inside the study domain (Table 1), of which five are in China Mainland, with the rest on islands and peninsula. We made use of high-quality data level 2.0 that had been subject to pre-/post-field calibration, automatically cloud clearing and manually inspection as a testing basis for TOMS AOT in comparison to TOMS retrievals of monthly mean AOT at 500 nm band (Fig.1). During the study the interpolation scheme was utilized to acquire related data for stations Yulin and the Taiwan Central University following the procedure described below as the two stations do not provide 500 nm AOT. AOT and wavelength satisfy the ˚ Angstr¨om relation τa (λ) = βλ−α ,

(1)

in which τa denotes the AOT relating to wavelength λ, β the ˚ Angstr¨ om turbidity coefficient and α the ˚ Angstr¨om wavelength index. To compare AOT at λ1 and λ2 , we have λ−α1 τα (λ1 ) = 1−α2 τα (λ2 ) λ2

(2)

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Thus, we employed AERONET 870 nm AOT and the ratio between ˚ Angstr¨om wavelength indexes to make interpolation for AOT at 500 nm band. Figure 1 shows quite good consistency between TOMS-sensed aerosol products and surface observations inside China, which can be used to investigate AOT distribution and behaviors in the region.

2.2 Extreme Temperature Indices 1951–2004 daily mean temperatures, maxima and minima came from 720 stations provided by the Data Division of National Meteorological Information Center China Meteorological Administration. We removed the stations thereof that had the data length short of requirement or changed in position, leading to 550 stations left for use. Using the extreme temperature indices definition released by WMOCCCL/CLIVAR (Table 2), we obtained four indices and made a preliminary study on their characteristics and relations to AOT. 3 AOT distribution over land-sea of China 3.1 Pattern of Annual Mean AOT Figure 2a is a plot of yearly mean AOT over the

Fig.1.

TOMS retrieved 500 nm AOT vs

AERONET observations, with solid line designating the linear fitting, dotted for y = x line, and r = coefficient of correlation.

mainland, showing >0.1 values in much of the land, with high cores in the Southern Xinjiang Basin, SouthChina seaboards, and the Sichuan Basin, peaking at >0.6 and lower cores (<0.1) in the eastern Tibetan Plateau, east Qinghai and Yunnan, and over the seas (Fig. 2b) the values were a lot lower compared to th-

Table 2. Extreme temperature indexes used in the work Name (code)

definition

Cold nights (TN10P) Days with TN < 10th percentile of daily min temperature Cold days(TX10P) Days with TX < 10th percentile of daily max temperature Warm nights (TN90P) Days with TN > 90th percentile of daily min temperature Warm days (TX90P) Days with TX > 90th percentile of daily max temperature TN (TX) stands for mean of daily minimum (maximum) temperature (unit: ◦ C)

Fig.2. 1980–2001 averaged yearly mean AOT distributed over land in a) and sea in b).

unit day day day day

HU Ting et al. Acta Oceanol. Sin., 2011, Vol. 30, No. 2, P. 33-45

ose over the land, with the high-valued center in the South-China Sea and annual mean exceeding 0.15. 3.2 Seasonal Distribution The seasonal mean AOT distributed along 110◦ E (figure omitted) indicates that its distribution displays strong seasonality, differing between land and sea. On the whole, the land AOT reduced from spring to autumn, with increase in winter. In spring, a thick layer of aerosol particles covered almost the whole land, with most areas having >0.2 AOT, even with >0.3 in Xinjiang, southern NE China, North China, the MiLY valley, Sichuan Basin and South China. This may be attributed to seasonal sandstorms in the north while South China was also likely to be under the affect of the south Asian brown haze (Ramanathan et al., 2002). In summer to autumn, in contrast, AOT reduced, to great degree, in the Sichuan Basin, the MiLY valley, Guangdong and Guangxi, with AOT in much of the country on the order of 0.1, due likely to frequent summer rainfall that resulted in scavenging and wet depositing for shortening AOT lifecycle in the atmosphere. In southern Xinjiang the value kept increasing in summer, peaking at >0.7, probably in association with deficient precipitation in that season which was prone to dust-raising and -floating, a condition favorable for layered aerosol formation and maintenance. When winter came, AOT dropped somewhat just in southern Xinjiang, probably in relation to the snow cover available there. In other parts, in contrast, AOT increased more or less, especially in the Sichuan Basin and South-China seaboards where AOT reached >0.3, on average, with greater increase found in north China and MiLY valley. During this period the Mongolian cyclone moved southeastward, with ensuing gales so that sandy weather may be the principal cause of AOT increase in the north. Over the seas, on the other hand, diminishing AOT was found from spring to winter. In spring off-sea AOT exceeded 0.2, decreasing as a function of increased seaward distance. This was likely to relate to land-origin aerosols. When summer set in, the oceanic AOT of China began decreasing and dropped to <0.1 except off-sea areas, where it was >0.15 throughout the year, with its relatively smaller seasonal variation over the South-China Sea, a fact that is evidently under the effect of monsoon climate. In winter, strong NE winds were responsible for land-origin aerosols transferred to the South-China Sea that covered most of it, so that a high-value zone appeared in the Sea at low latitudes. In summer, SE

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monsoon was unfavorable for transporting land-origin aerosols but for the particles from the volcanoes erupting in the Philippines or Indonesia as a distant source, leading to all its high cores close to shoreline of the South-China Sea. Seasonal mean AOTs along 110◦ E (Fig. 3) indicate appreciable land-sea contrast, with differences much smaller and the zonal variations also over a smaller range over the seas compared to those over the land. In the case of land, AOT in spring and summer reduced with increasing latitude, with a small range of its zonal variation in autumn. Besides, land AOT showed its noticeable seasonality, which decreased with latitude. The values generally range in a descending order as spring > summer > winter > autumn, the only exception being that in the MiLY valley (approximately 28∼33◦ N) wintertime AOT rose so greatly as to be almost equivalent to its spring value. Comparing long-term mean AOTs distributed over 25 and 40◦ N (representative of the south and north of the study region, respectively, cf. Fig. 4), we found that at 40◦ N within Chinese territory spring saw violent sandstorm, leading to bigger AOT, which even reached up to 0.8 in the atmosphere over the southern Xinjiang Basin, with a distinct higher-value zone in the south of China. In summer and autumn, to the east of 100◦ E AOTs showed the values higher in the south than in the north, and the reversal to the west. In winter, AOT was always higher in the north (where the climate was arid, with gales carrying dust into upper levels) than in the south. As for oceanic AOT, its zonal distribution was marked by higher values over islands both of the Bohai (in the north) and East-China Sea (in the south), with relatively high AOT over waters close to shorelines.

Fig.3. Hovmoeller diagram of Seasonal mean AOT along 110◦ E inside the scope of China.

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Fig.4. AOT distributed along 25 and 40◦ N for (a) spring, (b) summer, (c) autumn and (d) winter.

4 Time-dependent AOT 4.1 Analysis of AOT Trends The 1980–2001 linear trend of AOT annual mean over the inland of China is given in Fig. 5a, where the increase is dominant nationwide, averaging >0.001 per year, particularly in the south of NW China, the western Qinghai-Tibetan Plateau, much of NE China, and Eastern China as opposed to the trend in NW Xinjiang, Guangdong, Guangxi, and the eastern QinghaiTibetan Plateau. In terms of seasonal variations (figure omitted), they varied to great extent, indicative of prominent regionality. For the springtime mean AOT the increase prevailed in these years with the higherincrease zones in West China (to the west of 100◦ E), Nei Mongolia, North China, the Sichuan Basin and the

MiLY valley. In autumn, greater-increase zones, although available, were positioned in eastern Nei Mongolia, most of NE China, North China as well as the Sichuan Basis. Meanwhile, AOT in Guangdong and Guangxi showed its linear reduction. As regards AOT variation in winter and summer, its decrease was predominant roughly between –0.001 and –0.005 on an annual basis. Oceanic AOT yearly mean experienced the changes similar to those over land (Fig. 5b), displaying a consistent increasing trend in the main except a small-size area of the Leizhou Peninsula. Moreover, the midlatitude oceanic AOT exhibited noticeable increase in spring and autumn, with its smaller rise in winter but decrease in summer (figure not present). Variations in long-term averaged seasonal AOT show-

Fig.5. 1980–2001 500 nm yearly mean AOT linear trend with land (ΔAOT per year) in (a) and ocean (ΔAOT per Decade) in (b). The light (dark) shading denotes the decreasing (increasing) trend, with the slashed squares being statistically significant at 90% confidence level.

HU Ting et al. Acta Oceanol. Sin., 2011, Vol. 30, No. 2, P. 33-45

Fig.6. 1980–2001 trends of yearly mean AOT over land and sea in comparison to the linear trends(dots).

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Fig.7. The curves of 1980-2001 annual mean AOT cumulative anomalies for land and sea.

Fig.8. Like Fig.7 but for seasonal mean: (a) spring; (b) summer; (c) autumn; (d) winter.

ed a weak trend for the South-China Sea, which failed to pass the significance tests in most cases. Referring to Figs 6–8, we see that AOT values were bigger over land, with land-sea difference of ∼0.05 in annual mean AOT, both having comparable values of linear tendency. As given in the chart for the linear tendency of 1980∼2001 seasonal mean (figure not shown), the land-sea contrast is much bigger in spring compared to other seasons, but with similar trends of land-sea AOT values in the same season displayed in such a way that in all seasons but summer the mean increased from one year to another and except summer, the oceanic mean AOT showed greater increase (which was significant at 90% level), with the maximum linear tendency value in autumn, next being the spring

AOT. The increasing trend of land AOT passed tests at 0.1 significance level in autumn. From the cumulative anomalies of annual means (Fig. 7) we see more clearly that the land-sea AOTs have fairly consistent variation on an interannual scale. The 1980∼2001 period can be separated into two stages of higher- and one of lower-value AOT, and the 1991–1992 sudden increase in AOT may be ascribed to the eruption of Pinatubo volcano in Philippines in 1991. The seasonal AOT cumulative anomaly curve (Fig. 8) gave prominence to the seasonal difference in AOT of China, displaying a wider range of land AOT and rather consistent trends of values over land and sea. Since the end of the 1980s annual mean as well as Seasonal mean AOT except winter AOT had exhibited rising trends

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in a fluctuating way. As far as land AOT was concerned, spring AOT trend was analogous to the annual counterpart, suggestive of its bigger contribution to the yearly AOT. The summer trend was of much smaller magnitude of order although it was close to the yearly trend. As to the autumnal trend it began successive increase instead of progressive decrease, starting from 1990. The winter AOT trend was opposite to the spring counterpart around 1990, with no big difference in the other time intervals. In the case of oceanic AOT the regional mean showed the trends similar in spring, autumn and winter, all changing from drop to rise around 1990/1991. 4.2 Periodicity Wavelet analysis was undertaken of the periods of 1980–2001 0.50 μm AOT in the study region. Because wavelet variance tends to amplify the relative power of long period waves and shorten the amplitude of shorter-period components, finally leading to discriminant errors, so that Fourier power spectrum was employed for testing (Wu and Liu, 2005). The Morlet wavelet analysis shows that there are signals of intra- (<1 yr) and interannual period (∼1 yr) for land AOT and its anomaly (figure omitted), and the AOT anomalies also include stronger signals at >2 year periods, all being statistically significant at 95% level for the red-noise background spectrum. AOT interannual signals experienced no distinct turning trends in 1980–2001. Subsequent to 1991, AOT anomaly exhibited strong enough signals of 2–4-yr oscillations, with intra-yearly and quasi 1-yr signals strengthened to great extent. Comparison between wavelet analysis of primitive data and its anomaly yields that their periods were rather consistent except the significant ones that were not coincident. Features of periodicity of oceanic AOT were extremely similar to those of land counterpart, showing practically the same periodicity on a synchronous basis.

tribute to that the whole mean is unable to represent regional characteristics of the relationships. Thus, supplemented are connections of AOT spatial distributions to the extreme temperature indices’. Comparison of distributions of annual mean AOT to the indices in 1980-2001 (figure not shown) yields their analogous areas at an interannual scale. The cold-day index was in close relation to AOT in SW and South China, the Sichuan Basin and Loess tableland; cold night index changed in much the same way as AOT in the southern Xinjiang Basis and East China coastwise bands; the warm day index changed in a basically opposite way as compared to AOT in the Sichuan Basis; warm night index was intimately associated with AOT in southern and central China. Figure 9 presents the 1980–2001 monthly averaged land AOT in correlation with the warm night, showing that in the southern Xinjiang Basin, Qinghai, Gansu, Nei Mongolia and NE China the AOT is positively correlated with the warm-night index, with the coefficients statistically significant at 95% level, particularly in the east of the southern Xinjiang Basin and NE China, suggesting that the climate change there bears a close relation to AOT, but the correlativity was insignificant for the plains of North China and MiLY valley. As for the other three indices, their correlations to monthly mean AOT differed in pattern and high correlation areas (exceeding the 0.05 significance level). For instance, the cold night index values were in higher positive (negative) correlation with AOT in the west of the southern Xinjiang Basis (North China), the index being positively correlated to AOT in the main in other areas. The cold day values differed in correlation with AOT, with 110◦ N as the division, east (west) of which the coefficients were negative (positive), with

5 Features of extreme temperature index in relation to the study AOT 5.1 Relationship between AOT and extreme temperature The correlation coefficients of zonal mean land AOT to synchronous extreme temperature indices show clearly that warm day/night have positive correlations with AOT as opposed to cold indices, but neither passing the confidence test. This might at-

Fig.9. Coefficients of monthly averaged land AOT correlated with warm-night index (TN90p),with shaded areas being statistically significant at 0.05 level.

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their intimate relation in the Jiang-Huai River reaches and the west of the southern Xinjiang Basis. The AOT-warm day index relation was positive in most cases (except their insignificant negative correlation in part of SW and South China, with higher correlation areas in NE China and northern Xinjiang. Overall, all these indices had higher correlativity to AOT, with multiple higher correlation areas nationwide. Warm indices (TX10p and TX90p) bore higher positive correlation to AOT, with the rest dominantly in negative correlativity with it. Then the interannual variations (Table 3) of China land AOT and the extreme temperature indexes were obtained by the Morlet wavelet analysis and Mann-Kendall test, showing that AOT has similar interannual features as compared to the indexes. Both the extreme temperature indexes and land AOT exhibited quite intense interannual signals, dominated by 2–4-yr oscillations and an abrupt change in 1988/1989 except the warm-day index. And the linear tendency analysis yields that cold day/night indices display descending trends but the warm indices and land AOT display mainly ascending trends on an annual basis, with similar annual gradients for AOT and daytime indexes (warm/cold day), which is much smaller than the nights. It may indicate that the daily maximum temperature change slower than the minimum in the study period (Karl et al., 1991; Zhai and Ren, 1997; Manton et al., 2001; Griffiths et al., 2005). Table 3. Interannual characteristics of the extreme temperature indices and AOT

Cold night Cold day Warm night Warm day AOT

Interannual period

linear tendency (/a)

Abrupt time

2, 4 2, 4 4 4 1, 2, 4

–0.203 –0.054 0.168 0.065 0.072

1988/1989 1988/1989 1988/1989 1993/1994 1988/1989

The foregoing comparisons have indicated that the relationship between AOT to the extreme temperature indices is marked by pronounced geography, resulting in incomplete coincidence of higher correlation zones and patterns of the indices relative to AOT. The warm night/day is positively correlated with China land AOT, as opposed to the cold indexes. There are similar periods and abrupt change for AOT and the indices, as well as comparable annual gradients for AOT and daytime indexes (warm/cold days). And increase in the daily maximum is less than the minimum temperature.

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In view of the relationship of the AOT to the extreme temperature indices of warm and cold days/nights, we may reach conclusions that the aerosol loading could be one of the causes cooling extreme temperatures along with the global warming. And the aerosol may exert a more profound influence on the maximum temperature than on the minimum. 5.2 LMDZ-regional model Results To confirm the suspetion that aerosol may cool the extreme temperature and more on the maximum ones, we perform regional simulations in China. The model used in this study is the LMDZ model (Version 4) of Laboratoire de Meteorologie Dynamique (LMD), CNRS, a variable-grid atmospheric general circulation model, used as a regional climate model (Hourdin et al., 2006; Li et al., 2006, 2008). For this simulation, there are 76 and 41 grids in longitude and latitude, respectively, and 19 vertical layers with a hybrid pressure co-ordinate system. Two numerical simulations are carried out. The integrations cover the period from 1958 to 2001. In the performance of validation runs, LMDZ is forced by ERA40 forcing for the period 1958-2001 (hereinafter Model I). Results show that, as compared with the mean-time CRU data, the LMDZ model is able to simulate most characteristics of the special/temporal distributions of daily maximum and minimum temperatures, named as T2max and T2min. Then model runs taking into account only the sulfate aerosols, but not black carbon, neither dusts (hereinafter Model II). The historical estimation of sulfate, as used in IPCC runs, is imposed in our simulation. The direct and indirect effects of sulfate are both activated, as published in papers of Boucher et al (1995a; 1995b; 1998; 2003) In order to see the aerosol contribution, the differences between Model I and II are used. It is not surprising to find that the effect of aerosol induces a cooling over the whole China, with the largest decreases of 0.25K and 0.3K in the T2min and T2max, respectively (Fig. 10). Further analyses find that, on regional average, aerosol effects may result in cooling all over China, particularly in areas from the Sichuan Basin to the mid-lower the Changjiang River reaches, and the Qinghai-Tibetan Plateau. Under the influence of aerosol, daily maximum/minimum temperatures are decreased by 0.11/0.08 K (per year), respectively, to some extent indicating more effects on the T2max rela-

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Fig.10. modeled II minus I of 1958–2000 annual mean T2min (a) and T2max (b) distributions (contour interval 1 K).

tive to the T2min, which may be results of the smaller rise in the maximum temperatures as compared to that of minimum ones under the global warming. 6 Conclusions This work deals with the distribution and evolutions of 500 nm AOT over land and sea of China and preliminary analysis of its synchronous correlation to extreme temperature indices, i.e., TN10p, TN90p, TX10p and TX90p, arriving at the conclusions as follows. (1) Long-term mean AOT distribution is featured by typical geography. For the land there are two highvalued AOT areas, more extensive and longer persistent, in the southern Xinjiang Basin and North China Jiang-Huai River reaches, with its low-value bands in the east of the Qinghai-Tibetan plateau and Yunnan. The relatively higher-value band over seas is in the South China Sea. (2) AOT has its appreciable seasonality, which decreases as a function of latitude. For the majority of China AOT in spring has its maximum value. (3) AOT is featured by remarkable land-sea contrast, with its land values considerably higher and in a greater range. For the land AOT, it exhibits a decreasing trend from spring to autumn, with its increase in winter. For the oceanic AOT, on the other hand, it is thinned from spring to winter, with its seasonal difference much smaller than the land counterpart and a narrower range of its zonal variation. The land- sea difference is the greatest in spring. (4) AOT differs greatly in its meridional distribution all over the country. In spring, the northern values are higher in comparison to the southern ones except the high value zone in South China. In summer the southern values are marginally bigger than the northern ones and the reversal happens in winter. AOT in

autumn is higher in the north than in the south to the west of 110◦ N and v.v. to the east. (5) Annual mean AOT for the land and seas displays appreciably linearly increasing trends quite similar to each other. The 1980–2001 period can be divided into two stages of thicker AOT and one interval of thinner AOT. It is found that since the end of the 1980s the yearly mean and seasonal (but winter) AOT have displayed rising trends in a way that is distinctly fluctuating. The study AOT is marked by pronounced intra-seasonal and -annual oscillations interannual periods of 1-, 2- and 4-years and more are also highly pronounced. (6) Good correlations are obtained between AOT and extreme temperature indices over the land, with their change in phase for some areas. Generally, the correlations of AOT to the extreme temperature indices are more significant in Eastern China with 110◦ E as the division. Their high-correlation regions are along the South China coastline, the Loess Plateau and the Sichuan Basin, and even higher in North China Plain and the mid-lower Changjiang River reaches. (7) LMDZ regional model has the capability of simulating extreme temperature characteristics in spatial and temporal variations. Its simulations indicate that, aerosol effects may result in cooling all over China, particularly in East China for areas from the Sichuan Basin to the mid-lower Changjiang River reaches. Under the influence of aerosol, daily maximum/minimum temperatures are decreased by 0.11/0.08 K, respectively, indicating more effects on the T2max relative to the T2min. Further, we may reach conclusions that the aerosol may influence the maximum temperature more seriously than the minimum, leading to smaller rise in the maximum temperatures than minimum ones under the global warming. But this supposition needs more supports of observa-

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