SCIENCE CHINA Earth Sciences. The role of cloud height and warming in the decadal weakening of atmospheric heat source over the Tibetan Plateau

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1 SCIENCE CHINA Earth Sciences ESEACH PAPE March 2015 Vol.58 No.3: doi: /s The role of cloud height and warming in the decadal weakening of atmospheric heat source over the Tibetan Plateau WU Hui 1,2, YANG Kun 1*, NIU XiaoLei 1 & CHEN YingYing 1 1 Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau esearch, Chinese Academy of Sciences, Beijing , China; 2 University of Chinese Academy of Sciences, Beijing , China eceived April 6, 2014; accepted August 26, 2014; published online December 17, 2014 The warming over the Tibetan Plateau (TP) is very significant during last 30 years, but the thermal forcing has been weakened. The thermal weakening is attributed mainly to the enhancement of the TOA (top of atmosphere) outgoing radiation. This enhancement is opposite to the greenhouse-gas-induced weakening of the global mean TOA outgoing radiation and is also unable to be explained by the observed decrease of total cloud cover. This study presents the importance of cloud height change and the warming over the TP in modulating the TOA radiation budget and thus the thermal forcing during spring and summer. On the basis of surface observations and satellite radiation data, we found that both the TOA outgoing shortwave radiation and longwave radiation were enhanced during this period. The former enhancement is due mainly to the increase of low-level cloud cover, which has a strong reflection to shortwave radiation, especially in summer. The latter enhancement is caused mainly by the planetary warming, and it is further enhanced by the decrease of total cloud cover in spring, as clouds extinguish outgoing longwave radiation emitted from the land surface. Therefore, the radiative cooling enhancement and thus the thermal weakening over the TP is a response of the earth-atmosphere system to the unique change of cloud cover configuration and the rapid warming of the land surface. However, these trends in cloud cover and TOA outgoing radiation are not well represented in four reanalyses. heat source, radiative cooling, trend, Tibetan Plateau, cloud cover Citation: Wu H, Yang K, Niu X L, et al The role of cloud height and warming in the decadal weakening of atmospheric heat source over the Tibetan Plateau. Science China: Earth Sciences, 58: , doi: /s The vast Tibetan Plateau (TP), with an average elevation of > 4000 m above sea level, influences the atmospheric circulation through its significant thermal and dynamical forcings (Charney and Eliassen, 1949; Flohn, 1957; Ye and Gao, 1979). Aside from the annual land-sea thermal contrast cycle, it has been recognized that the formation and evolution of the Asian summer monsoon are closely related to the atmospheric heating and cooling processes over the TP, due to its effective heating to the atmosphere (Ye and Gao, 1979; Yanai et al., 1992). As a huge heat source in summer, the *Corresponding author ( yangk@itpcas.ac.cn) thermal forcing over the TP intensifies the convergence flow toward the TP from surroundings and pushes the rain belt northward (Wu et al., 2007). Many efforts have been made to determine the intensity of heat sources and have revealed many important thermal features on the regional scale (e.g., He et al., 1987; Duan and Wu, 2005). However, a recent debate on the formation of South Asian summer monsoon (Boos and Kuang, 2010; Wu et al., 2012) highlights our inadequate understanding of the mechanism between the TP thermal forcing and the monsoon and the deficiency of climate modeling for the high-elevation region. There are growing concerns on the decadal change of the Science China Press and Springer-Verlag Berlin Heidelberg 2014 earth.scichina.com link.springer.com

2 396 Wu H, et al. Sci China Earth Sci March (2015) Vol.58 No.3 heat source over the TP and its possible connection with the regional atmospheric circulation, especially with the Asian monsoon. Zhu et al. (2008) found a decline trend of the heat source over the TP in NCEP reanalysis. The weakening of the atmospheric heating over the TP is possibly responsible for the inter-decadal variation of the summer precipitation in East China (Ding et al., 2009; Liu et al., 2012; Xu et al., 2013). On the basis of surface observations and satellite data, Duan and Wu (2008) and Yang et al. (2011) clarified that the weakening heat source is attributed to both the weakening in sensible heat flux (SH) and radiative cooling enhancement over last 30 years, and the TOA outgoing radiation enhancement dominates the thermal weakening. The TOA outgoing radiation enhancement over the TP is opposite to the weakening trend in the global mean TOA outgoing radiation. The latter causes the global warming and is commonly attributed to the greenhouse-gas effect. The situation over the TP seems more complex, and this enhancement of TOA outgoing radiation may imply an increase in cloud-radiative forcing. However, both station data and satellite product indicate that total cloud cover (TCC) has decreased over the past decades (Yang et al., 2012). Thus, it seems a paradox between the enhancement of radiative cooling and the decrease in TCC over the TP remains. Here we attempt to understand the causes of the radiative cooling enhancement and to explain the paradox. We further evaluate the performance of four reanalysis datasets in representing the TOA radiation cooling enhancement. Considering the importance of the heat source to the onset and maintenance of the Asian summer monsoon, we focus mainly on the summer-half-year. 1 Data The surface observations include daily cloud cover and ground temperature at 78 CMA (China Meteorological Administration) stations. The distribution of the stations is shown in Figure 1, and all stations are above 2000 m. The cloud cover records include the TCC and low-level cloud cover (LCC). Both TCC and LCC vary from 0 to 100 percent of sky cover. A decreasing trend in TCC and an increasing trend in LCC have been reported on an annual timescale (Duan and Wu, 2006), and the LCC plays a more important role in controlling the surface radiation variability over the TP (Yang et al., 2012). The TOA radiative budget data are obtained from satellite observations. We employed two satellite radiation products, the GEWEX (Global Energy and Water Cycle Experiments) Surface adiation Budget (GEWEX-SB; Stackhouse et al., 2004) and the International Satellite Cloud Climatology Project-Flux Data (ISCCP-FD; Zhang et al., 2004), to estimate TOA outgoing shortwave and longwave radiative fluxes from 1984 to The former was estimated with the cloud cover and radiances from the ISCCP-DX nominal 30 km pixels within each 1 1 cell. The latter was estimated with the ISCCP-D1 cloud cover, cloud top temperature, optical thickness, and cloud phase based on 15 cloud types in a 280-km (2.5 degree) equal-area grid with climatologies for the cloud particle size and vertical structure (See Table 4 in Zhang et al., 2004). The GEWEX-SB product used in this study is Version 3.0 for shortwave radiation and Version 2.0 for longwave radiation. The complete spatial and temporal coverage of the products provides an opportunity to investigate the variability of the earth radiation budget. In order to reduce uncertainty in the estimate of variability, we averaged the two datasets to generate the least error-prone TOA outgoing radiation components. Four relatively new reanalyses concerned are shown in Table 1. eanalysis datasets are typically used in climate monitoring and research applications at regional and global Figure 1 Spatial distribution of CMA stations over the TP. The shaded background is the topography above 2000 m.

3 Wu H, et al. Sci China Earth Sci March (2015) Vol.58 No Table 1 Summary of the reanalysis datasets used, including their spatial resolutions, production centers and the references describing the datasets Name esolution Center eference MEA (Modern-Era etrospective Analysis for esearch and Application) JA-25 (Japanese 25-year eanalysis) EA-Interim (European Centre for Medium-ange Weather Forecasts Interim e-analysis) NCEP-2 (NCEP/DOE AMIP-II eanalysis) 2/3 1/2 Gaussian grid, ~1.125 Gaussian grid, ~0.7 Gaussian grid, ~1.875 NASA (National Aeronautics and Space Administration) JMA (Japan Meteorological Agency) and CIEPI (Central esearch Institute of Electric Power Industry) ECMWF (European Centre for Medium-ange Weather Forecasts) NCEP-DOE (National Centers for Environmental Prediction-Department of Energy) ienecker et al. (2011) Onogi et al. (2007) Dee et al. (2011) Kanamitsu et al. (2002) scales, but few studies have addressed the TOA energy budget and its relationship with clouds in reanalysis. This study discussed their performance in representing the interaction between cloud covers and outgoing radiations using the aforementioned independent observations that were not employed in their assimilation systems. 2 Cross check of cloud and radiation data quality To some extent, the visual classification of cloud type and cloud amount is influenced inevitably by the subjective judgment of observer at the surface. So, the ISCCP cloud cover is introduced to understand the accuracy of the trend in CMA cloud cover. Notably, the ISCCP cloud data are derived from satellite observation according to cloud top pressure whereas the CMA observed one is defined by the height of cloud base. Therefore, the two types of low cloud cover denote different meanings and their values are not comparable. Following Yang et al. (2012), we use the deep cloud cover in ISCCP as a proxy of LCC defined by the CMA observations, as the latter tends to develop into deep cloud over the TP. Figure 2 shows the annual mean anomaly of TCC and LCC between CMA and ISCCP, as our concern in this study is the inter-annual variability and decadal change of clouds and radiation budget. It is clear that both TCC and LCC from CMA show consistent inter-annual variability and linear trend with them in ISCCP. This cross-check suggests that the CMA cloud data may be used for our purpose. The two radiation products (GEWEX-SB and ISCCP-FD) used in the study are the major global data sets of the radiation budget. They are produced with different radiative transfer models. Due to the limitation of cloud retrievals, their surface radiation budgets show large discrepancies, but their net radiation at the TOA is quite comparable, as has been demonstrated in Yang et al. (2011). 3 Decadal change in TOA outgoing radiation To facilitate the analysis of the relationship between the Figure 2 Comparison of annual mean anomaly of cloud covers between CMA and ISCCP for TCC (a) and LCC (b) from 1984 to 2006 over the TP. β is the slope of the linear trend given in per decade, pval is the significance level. gridded TOA outgoing radiation and the cloud cover observed at CMA stations, we averaged the radiation data of the grids collocated around a station to represent the station-averaged TOA outgoing radiation. Although the station-averaged TOA radiation value is different from the all-grid-averaged one over the TP owing to the inhomogeneous distribution of CMA stations (Figure 1), they give quite similar temporal variations (not shown), so the station-averaged satellite radiation data can be used to investigate the inter-annual variability and the decadal change of TOA outgoing radiation over the entire TP. As shown in Figure 3(a), the outgoing shortwave radiation (OS) has a significant positive trend (significance level of p-value < 0.05) over the TP in the summer-half-year (March-August),

4 398 Wu H, et al. Sci China Earth Sci March (2015) Vol.58 No.3 which is up to 10.3 W m 2 per decade in summer. Meanwhile, the outgoing longwave radiation (OL) also increases persistently in spring and summer (Figure 3(b)), and the slopes are weaker than the ones in OS. At the TOA, the incoming radiation is only the input downward shortwave radiation from sun to the earth, which changes little at annual scale. Thus, the TOA net radiation is estimated by subtracting outgoing radiations (OS and OL) from TOA downward shortwave radiation. As a result, Figure 3(c) shows that the TOA net radiation exhibits considerable decreasing trends over the TP in spring (MAM) and summer (JJA) (relative decreasing as much as of 16.9% per decade and 18.9% per decade, respectively). In a word, the strengthened atmospheric radiative cooling over the TP reported in previous studies is resulted from the enhancement of both OS and OL during spring and summer. This positive trend seems conflicting to the decrease of TCC that was reported by Duan and Wu (2006). 4 Causes of TOA outgoing radiation enhancement The cloud-radiative forcing plays an important role in climate change. Usually, increasing cloud cover results in increasing OS due to its strong reflection of the shortwave radiation back to the space but decreasing OL due to greenhouse effect of clouds (amanathan et al., 1989). Smith and Shi (1995) concluded that the cloud-induced heating and cooling effects to atmosphere over the TP are much greater than over low-elevation regions. Moreover, the vertical position of a cloud and its optical depth can alter vertical structure of radiative cooling (Stuhlman and Smith, 1988). Thus, it is necessary to discriminate cloud covers at different heights for exploring the causes of TOA outgoing radiation enhancement. 4.1 Causes of OS enhancement As shown in Figure 4(a), TCC over the TP exhibits a significant negative trend in spring but a slightly positive trend in summer, whereas LCC (Figure 4(b)) shows significant increasing trends in both seasons due to the increase in convective available potential energy (Yang et al., 2012). Figure 4 also gives the correlation coefficients () between OS and cloud covers (including TCC, LCC), which present significant correlations between OS and LCC in both spring and summer. Meanwhile, Figure 4(b) shows the temporal variations and linear trends of OS and LCC during spring and summer. It is obvious that the enhanced OS over the TP is highly correlated with the increasing LCC. As an explanation, the optical thickness of LCC is much larger than higher clouds and so the LCC can reflect more shortwave radiation. The increasing of LCC is more significant in summer than in spring, so the change of OS correlates more closely with LCC in summer (=0.87). Such a close cause-and-effect relationship between OS and LCC is caused by the fact that the observed LCC is usually dominated by deep convective clouds in summer (Wu et al., 2007; Yang et al., 2012) that have strong reflection effects. It is worthwhile to note that the negative correlation between OS and TCC is supposed to be unphysical, because less cloud cover basically weakens the reflected shortwave radiation (i.e., less OS). In short, the LCC plays an important role in determining the trend and the inter-annual variability of OS. Figure 3 Inter-annual variation of OS (a), OL (b) and TOA net radiation (c) averaged over two satellite radiation budgets (GEWEX-SB and ISCCP-FD) in spring and summer from 1984 to 2006 over the TP. β is the slope of the linear trend in W m 2 (10 yr) 1, pval is the significance level. 4.2 Causes of OL enhancement The TP has been experiencing more warming than lowland regions along the latitude belt (Liu and Chen, 2000; Qin et

5 Wu H, et al. Sci China Earth Sci March (2015) Vol.58 No al., 2009), and the strong planetary warming over the TP can excite more upward longwave radiation; thus, the inter-annual variability of OL is significantly related to the increasing ground temperature (Table 2). Contrast to the impact on the shortwave radiation, more clouds extinguish more outgoing longwave radiation from the land surface, due to the lower temperature at the top of the cloud than the surface, so the observed temporal variation of OL correlates well with TCC instead of LCC, as shown in Table 2. As both the TCC decreasing and the rapid warming may contribute to the OL enhancement, we separate their contribution by defining the mean planetary emissivity: 4 OL / Tg (where is the Stefan-Boltzmann constant, and T g is the ground temperature). The emissivity mainly represents the land surface and atmospheric states and eliminates the planetary warming effect. Figure 5 shows that the mean planetary emissivity is highly correlated with the observed temporal variation of OL (=0.91 in Table 2). Therefore, besides the planetary warming, the increasing ε further leads to the enhancement of OL. We calculated the correlation coefficient between ε and TCC and Table 2 shows that the correlation is high in both spring (= 0.70) and summer (= 0.86). The individual contributions of warming and TCC change may be quantified. In summer, the ground temperature is about 290 K, the warming is 0.56 K (10 yr) 1, and the ε value is about The estimated OL enhancement due to the warming is 1.7 W m 2 (10 yr) 1, which is comparable to the observed OL trend (2.3 W m 2 (10 yr) 1 ), so the OL trend is determined mainly by the warming. Similarly, the springtime OL enhancement Figure 4 Temporal variation and linear trend of OS from satellite datasets and cloud covers from observations at the CMA stations over the TP in spring and summer from 1984 to (a) for TCC and (b) for LCC. β is the slope of the linear trend given in per decade, is the correlation coefficients between OS and cloud covers, the values with * indicate passing student s t-test of P<0.05. Table 2 Slope of linear trend (β) of surface ground temperature, mean planetary emissivity and OL given in per decade, and correlation coefficients () between OL and surface ground temperature, cloud covers and mean planetary emissivity a) β (T g ) β (ε) β (OL) (OL, T g ) (OL, TCC) (OL, LCC) (OL, ε) (TCC, ε) Spring Summer a) The values are obtained for spring and summer in , respectively. Bold values indicate passing student s t-test of P<0.05.

6 400 Wu H, et al. Sci China Earth Sci March (2015) Vol.58 No.3 Figure 5 Temporal variation and linear trend of OL from satellite datasets and mean planetary emissivity over the TP in spring and summer from 1984 to due to the warming can only explain half of the observed OL enhancement (3.8 W m 2 (10 yr) 1 ), and the remaining part is attributed to the positive trend of ε that is physically consistent with the negative trend of TCC. Overall, the enhancement of OL is caused primarily by the planetary warming and further enhanced by the decreasing TCC over the TP. 5 Evaluation TOA radiation cooling in reanalysis data The basic idea of reanalysis is to merge the observations with a fixed operational forecast system to produce the best estimate of the state of the global atmosphere and land surface. By taking advantage of the self-consistent assimilation system, the reanalysis provides the globally complete spatial and temporal coverage and information of some unobserved parameters in a physically meaningful way. It is also valuable to obtain the estimate of total heat source based on the reanalysis at global and regional scales (Trenberth and Caron, 2001; Yanai et al., 1992). However, the quality of the reanalysis is subject to the uncertainties of available observations, forecast model, and assimilation technique. Wang et al. (2012) indicated that some reanalyses are difficult to reproduce the weakening of total heat source over the TP. Moreover, reanalyses from different centers may perform differently because of different configurations, especially in a regional scale. For example, two recent investigations (Wang and Zeng, 2012; Bao and Zhang, 2013) demonstrated that no reanalysis product outweighs others and the quality of each reanalysis varies from variable to variable over the TP. Given the fundamental role of energy budget in determining the climate and its variability, the assessment of the reanalyses (MEA, JA-25, and EA-Interim, NCEP-2) benefits the identification of the strengths and weaknesses of each reanalysis (Allan et al., 2004). Based on the distribution of the CMA stations, the TOA radiation and cloud cover over grids above 2000 m from the four reanalyses are area-weight averaged to compare with observation. Figure 6 shows that the inter-annual variation of OS in almost all reanalysis data sets positively correlates with the LCC, particularly for summer, and the OL negatively correlates with the TCC. These high correlations are in accordance with the observation. However, the reanalyses have some obvious deficiencies: (1) EA-Interim reproduces the cloud covers better than other three reanalyses do, but all reanalyses underestimate the cloud covers (including LCC and TCC); particularly, the NCEP-2 reanalysis yields much less LCC compared with observation. (2) All the four reanalyses produce weaker OS due to less LCC forecasted, and more OL due to less TCC. Table 3 gives the linear trends of the cloud covers and outgoing radiation components for spring and summer. The reanalyses generally produce positive trends in both LCC and OS, which are similar to the observed ones, but the magnitudes of the trends are much weaker than the observed ones. TCC in the reanalyses has strong positive trends, which are opposite to the observed negative trend. OL in the reanalyses has negative trends or slightly positive trends, which are also different from the observed positive trend. As a total, the TOA outgoing radiation in the reanalyses has no significant trend because of the cancelation between OS and OL. Therefore, the reanalyses fail to reproduce the enhancement of the TOA outgoing radiations over the TP.

7 Wu H, et al. Sci China Earth Sci March (2015) Vol.58 No Figure 6 Inter-annual variation of OS and LCC (left panels) and OL and TCC (right panels) from four reanalysis datasets over the TP in spring and summer from 1984 to Table 3 Slope of linear trend (β) of cloud covers, OS and OL in four reanalyses and observation for spring and summer in a) Spring Summer Data β (TCC) β (LCC) β (OS) β (OL) MEA JA EA-Interim NCEP Observation MEA JA EA-Interim NCEP Observation a) Bold values indicate passing student s t-test of P<0.05.

8 402 Wu H, et al. Sci China Earth Sci March (2015) Vol.58 No.3 6 Summary The significant enhancement of radiative cooling at TOA has weakened the atmospheric heat source over the TP during last three decades. In this study, we found that both the enhanced OS and OL contribute to the weakened TOA net radiation during spring and summer. This seems contradicting the decrease of TCC. In order to understand the paradox, it is necessary to discriminate LCC and TCC. We found that the OS enhancement is mainly due to the increase of LCC, which can strongly reflect the shortwave radiation to the space. The increase of OL over the TP is caused primarily by the planetary warming and further enhanced by the increasing mean planetary emissivity. The latter is highly related with the decrease of TCC. This study does not investigate the cause of cloud changes, which may be related to changes in regional circulation and microphysical processes. For instance, the semi-direct effect of dust aerosols can introduce changes in cloud properties (Huang et al., 2006), and satellite observations could facilitate this aerosol effect study (Huang et al., 2007). Nevertheless, no sufficient microphysical and aerosol information can support the study on the long-term trend of interest. In addition, Duan and Wu (2006) found a diurnal change in the LCC trend but not in the TCC trend. How the diurnal change affects the thermal forcing is also worthy of further studies. In summary, the enhancement of the radiative cooling since the 1980s over the TP is the consequence of the climate warming and the unique change in cloud height. However, current reanalyses generally fail to represent the decadal change of the cloud covers and TOA outgoing radiation fluxes over the TP. 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