Midlatitude Cirrus Clouds at the SACOL Site: Macrophysical Properties and Large‐Scale Atmospheric States

Ge, Jinming; Zheng, Chuang; Xie, Haichao; Xin, Yue; Huang, Jianping; Fu, Qiang

doi:10.1002/2017jd027724

Cited by 23 publications

(9 citation statements)

References 60 publications

(77 reference statements)

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“…This net cloud radiative flux is expected to change as clouds response to the global warming (Su et al ., 2014; Ceppi and Hartmann, 2015; Ceppi et al ., 2017), which is so‐called the cloud feedback that constitutes by far the largest source of uncertainty in the future climate prediction. To better constrain the cloud feedback processes in climate models, it is crucial to improve the understanding of the interactions between clouds and dynamical and thermal dynamical conditions of the atmosphere (Bony et al ., 2004; Yuan et al ., 2008; Ge et al ., 2018; Ge et al ., 2019). Traditional studies simply assume that cloud feedback processes scale with the global‐mean surface temperature (Henderson‐Sellers, 1986; Tselioudis et al ., 1993), independent of the spatial pattern of surface warming.…”

Section: Introductionmentioning

confidence: 99%

Pairwise‐rotated EOFs of global cloud cover and their linkages to sea surface temperature

Dong

et al. 2020

Intl Journal of Climatology

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Sea surface temperature (SST) could significantly affect the dynamic and thermodynamic conditions of the atmospheric circulation and consequently the cloud variations. Here we use several different satellite records to extract the spatial‐time modes of total cloud cover (TCC) by employing a pairwise rotation of Empirical Orthogonal Function analysis. The results show that the first two principal oscillation modes of TCC are closely associated with the Central Pacific El Niño Southern Oscillation (CP ENSO) and Eastern Pacific (EP) ENSO during the 1980s–2000s, while the ENSO‐like mode of TCC can provide an evident contribution to the TCC change during the 2000s–2010s. In CP El Niño, the cloud vertical structure decomposed from CloudSat observations shows an increase of cloud occurrence frequency near the equator and around 40°, and a decrease around 10° in both hemispheres, suggesting a symmetric tightening of Hadley cell (HC). In addition, cloud occurrence frequency increases around 180°, which is accompanied by an eastward shift of Walker circulation (WC). In EP El Niño, TCC increases (decreases) over the Equatorial Eastern Pacific (Western Pacific warm pool), and decreases asymmetrically over the subtropical Pacific Ocean, indicating a weakening of WC and an asymmetric tightening of HC, respectively. The different responses of circulation and clouds to CP and EP El Niño highlight the nonlinearity of El Niño SST forcing. We also construct a trend mode of TCC to investigate cloud long‐term responses to SST warming by transferring the linear trends of the rest modes to a specific mode. The principal components (PCs) of TCC trend modes are strongly correlated with global‐mean SST (GSST) with correlation a coefficient of about 0.60 during the 1980s–2000s and 0.45 during the 2000s–2010s, suggesting a continued influence of global SST warming on TCC. The global TCC change is mainly influenced by the combined effects of Atlantic Multi‐decadal Oscillation (AMO), Pacific Decadal Oscillation (PDO) and Indian Ocean Dipole (IOD). The variation about the trend mode of TCC is closely associated with PDO and IOD.

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Section: Introductionmentioning

confidence: 99%

Pairwise‐rotated EOFs of global cloud cover and their linkages to sea surface temperature

Dong

et al. 2020

Intl Journal of Climatology

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“…Thus, the maximum assumption minimizes the total cloud cover, while minimum assumption produces minimal overlap between cloud layers and results in maximum total cloud cover (Weger et al, 1992). The total cloud cover predicted by the random assumption will fall somewhere between the maximum and minimum assumptions (Geleyn and Hollingsworth, 1979). Studies have shown that these different overlap assumptions result in obviously different total cloud covers and will significantly affect the calculated radiative budgets and heating/cooling rate profiles (Morcrette and Fouquart, 1986;Barker et al, 1999;Barker and Fu, 2000;Chen et al, 2000;Pincus et al, 2005;Jing, 2010, 2016;Zhang et al, 2013;Jing et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

The impact of atmospheric stability and wind shear on vertical cloud overlap over the Tibetan Plateau

Jian

et al. 2018

Atmos. Chem. Phys.

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Abstract. Studies have shown that changes in cloud cover are responsible for the rapid climate warming over the Tibetan Plateau (TP) in the past 3 decades. To simulate the total cloud cover, atmospheric models have to reasonably represent the characteristics of vertical overlap between cloud layers. Until now, however, this subject has received little attention due to the limited availability of observations, especially over the TP. Based on the above information, the main aim of this study is to examine the properties of cloud overlaps over the TP region and to build an empirical relationship between cloud overlap properties and large-scale atmospheric dynamics using 4 years (2007–2010) of data from the CloudSat cloud product and collocated ERA-Interim reanalysis data. To do this, the cloud overlap parameter α, which is an inverse exponential function of the cloud layer separation D and decorrelation length scale L, is calculated using CloudSat and is discussed. The parameters α and L are both widely used to characterize the transition from the maximum to random overlap assumption with increasing layer separations. For those non-adjacent layers without clear sky between them (that is, contiguous cloud layers), it is found that the overlap parameter α is sensitive to the unique thermodynamic and dynamic environment over the TP, i.e., the unstable atmospheric stratification and corresponding weak wind shear, which leads to maximum overlap (that is, greater α values). This finding agrees well with the previous studies. Finally, we parameterize the decorrelation length scale L as a function of the wind shear and atmospheric stability based on a multiple linear regression. Compared with previous parameterizations, this new scheme can improve the simulation of total cloud cover over the TP when the separations between cloud layers are greater than 1 km. This study thus suggests that the effects of both wind shear and atmospheric stability on cloud overlap should be taken into account in the parameterization of decorrelation length scale L in order to further improve the calculation of the radiative budget and the prediction of climate change over the TP in the atmospheric models.

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“…Their short wavelengths allow the radars to detect clouds with small droplets and infer the microphysical and dynamical cloud processes (Kollias et al, 2007a). A Kaband zenith radar (KAZR) has been continuously running at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) since 2013 (Ge et al, 2018(Ge et al, , 2019Huang et al, 2008b) to investigate cloud properties over the site. SACOL is located in the downwind dust transport path about 2000 km to the east of the Taklimakan Desert (i.e., one of the most important global sources of atmospheric dust) (Ge et al, 2014;Huang et al, 2007;Jing Su et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar

et al. 2021

Atmos. Meas. Tech.

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Abstract. Low-level clouds play a key role in the energy budget and hydrological cycle of the climate system. The accurate long-term observation of low-level clouds is essential for understanding their climate effect and model constraints. Both ground-based and spaceborne millimeter-wavelength cloud radars can penetrate clouds but the detected low-level clouds are always contaminated by clutter, which needs to be removed. In this study, we develop an algorithm to accurately separate low-level clouds from clutter for ground-based cloud radar using multi-dimensional probability distribution functions along with the Bayesian method. The radar reflectivity, linear depolarization ratio, spectral width, and their dependence on the time of the day, height, and season are used as the discriminants. A low-pass spatial filter is applied to the Bayesian undecided classification mask by considering the spatial correlation difference between clouds and clutter. The final feature mask result has a good agreement with lidar detection, showing a high probability of detection rate (98.45 %) and a low false alarm rate (0.37 %). This algorithm will be used to reliably detect low-level clouds at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) site for the study of their climate effect and the interaction with local abundant dust aerosol in semi-arid regions.

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Midlatitude Cirrus Clouds at the SACOL Site: Macrophysical Properties and Large‐Scale Atmospheric States

Cited by 23 publications

References 60 publications

Pairwise‐rotated EOFs of global cloud cover and their linkages to sea surface temperature

Pairwise‐rotated EOFs of global cloud cover and their linkages to sea surface temperature

The impact of atmospheric stability and wind shear on vertical cloud overlap over the Tibetan Plateau

A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar

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