Linkages between mid-latitude cirrus cloud properties and large-scale meteorology at the SACOL site

Ge, Jinming; Wang, Zhenquan; Liu, Yuanyong; Jing, Su; Wang, Chen; Dong, Zixiang

doi:10.1007/s00382-019-04843-9

Cited by 16 publications

(9 citation statements)

References 36 publications

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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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“…In the cloud classification algorithm developed for the Cloud Profiling Radar onboard the CloudSat satellite, the average temperature at the largest radar equivalent reflectivity factor (Ze), the average largest Ze, the average height of the maximum Ze, the cloud-base height, etc., are combined to determine cirrus cloud (Wang and Sassen 2001b). Ge et al (2019) used two temperature criteria to identify cirrus cloud: the temperature of the cloud top should be less than −30°C and the temperature at the maximum Ze layer and at the cloud base should be less than 0°C.…”

Section: Cirrus Identificationmentioning

confidence: 99%

“…The physical and optical properties of cirrus clouds, such as ice crystal size, ice shape, particle concentration, cloud-top height, and optical depth, are heterogeneously and diversely distributed over the globe (Adhikari et al 2012;Cotton et al 2013;Ge et al 2019;Heymsfield et al 2013;Jensen et al 1996;Luebke et al 2016;Mace et al 2006;Yang and Fu 2009). Recent studies show that cirrus clouds remain one of the largest uncertainty sources in global climate models (GCMs), due to the deficiencies in representing their observed spatial and temporal variability (Joos et al 2014;Muhlbauer et al 2014;Zelinka et al 2012).…”

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confidence: 99%

Properties of mid-latitude cirrus cloud from surface Ka-band radar observations during 2014–2017

Huo

Tian

et al. 2020

Preprint

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Abstract. The physical properties and radiative role of cirrus clouds remain one of the uncertainties in the Earth–atmosphere system. In this study, we present a detailed analysis of cirrus properties based on four years of surface millimetre wavelength radar measurements in Beijing, China, where summer monsoon from the ocean and winter monsoon from the continent prevails alternately, resulting in various cirrus clouds. More than 6600 cirrus clusters were studied to quantify the properties of cirrus clouds, such as the height, optical depth and horizontal extent, which can serve as a reference for parameterization and characterization in global climate models. In addition, comparison between cirrus clusters formed under summer monsoon and winter monsoon indicates the different formation and evolution mechanisms of cirrus. Statistically, the temperature of more than 90 % of cirrus bins are below −15 °C. The dependence of the radar reflectivity of cirrus particles on the height and temperature was also observed in this study, indicating that the reflectivity of cirrus bins increases (decreases) as the temperature (height) increases. In addition, it was found that there is a strong linear relationship between the mean reflectivity and the cirrus cloud depth. Due to various synoptic circumstances, the cirrus clouds in summer are warmer, higher, and thicker, with larger reflectivity than that in winter; in particular, the mean cloud-top height of cirrus clouds in summer is 2.5 km higher than that in winter. It was found that most cirrus clusters in winter are likely to be the in situ origin type cirrus but some cirrus clusters in summer are the in situ origin cirrus and others are the liquid origin type cirrus.

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“…Independently, Ge et al (), hereafter G17, proposed an improved hydrometeor detection algorithm by adopting a bilateral filter, which is initially used in images process (Tomasi & Manduchi, ) to improve the weak signal detection. It has demonstrated good performance when applied to ground‐based Ka‐band cloud radar data collected at Semi‐Arid Climate and Environment Observatory of Lanzhou University (Ge et al, , ; Huang et al, ; Zhu et al, ), which can reduce radar noise while preserving cloud edges. In this study, we modified and applied this bilateral filter scheme to CloudSat hydrometeor detection algorithm in order to decrease the false detection rate of weak signals but preserve the detected real signals in the cloud mask.…”

Section: Introductionmentioning

confidence: 99%

Improved Hydrometeor Detection Method: An Application to CloudSat

et al. 2020

Earth and Space Science

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Clouds play an important role in the climate system and are a principal source of uncertainty in climate projections. CloudSat has provided an unprecedented opportunity to study the vertical structure of clouds, and its observations are being widely used in scientific studies. However, some clouds are not detected or are only weakly detected by CloudSat. In most studies, the weakest detections, specifically those detected by the so‐called along‐track integration scheme, are typically ignored due to the high rate of false detections, namely, a significant probability that a detected cloud is actually a region of increased measurement noise, rather than a true cloud signal. False detections have been reduced in the latest version (called R05 for release 5) of the CloudSat cloud mask product but at a cost of a significant loss in the true weak signals (i.e., a higher false omission rate). In this study, the CloudSat hydrometeor detection algorithm used in R05 is modified by adding a bilateral filter scheme to improve the detection of weak signals. By comparing with the CALIPSO lidar vertical feature mask, it is shown that the new scheme largely reduces the false detection rate compared to the R04 version, while retaining a large fraction of the true weak signals that have been lost in the R05 version. Implementing this scheme in future CloudSat data processing is expected to lead to a better detection of thin clouds.

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Linkages between mid-latitude cirrus cloud properties and large-scale meteorology at the SACOL site

Cited by 16 publications

References 36 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

Properties of mid-latitude cirrus cloud from surface Ka-band radar observations during 2014–2017

Improved Hydrometeor Detection Method: An Application to CloudSat

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