Vertical Structures of Anvil Clouds of Tropical Mesoscale Convective Systems Observed by CloudSat

Yuan, Jing; Houze, Robert A.; Heymsfield, Andrew J.

doi:10.1175/2011jas3687.1

Cited by 64 publications

(63 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This classification is, strictly speaking, based on arbitrary τ and p c thresholds, and clouds assigned to each pair of bin boundaries will only loosely represent cloud types originally defined from morphological features seen by surface observers. Previously we noted that continental MCSs often include thick anvils (Cetrone and Houze, 2009;Yuan et al, 2011), but we can not identify whether those anvils are classified as Cs show that similar MODIS joint histograms can have a variety of cloud vertical structures (Oreopoulos et al 2017, submitted to J. Geophys. Res.…”

Section: Uncertainty Of Cloud Type Classificationmentioning

confidence: 91%

Contrasting the Co-variability of Daytime Cloud and Precipitation over Tropical Land and Ocean

Jin¹,

Oreopoulos²,

Lee³

et al. 2017

Preprint

View full text Add to dashboard Cite

Abstract. The co-variability of cloud and precipitation in the extended tropics (35°N−35°S) is investigated using contemporaneous datasets for a 13-year period. The goal is to quantify the relationship between cloud types and precipitation events of particular strength. Particular attention is paid to whether the relationship exhibits different characteristics over 15It is found that the strongest coupling (positive correlation) between clouds and precipitation occurs for cumulonimbus clouds and heaviest rainfall over ocean. While the same cloud type and rainfall bin are also best correlated over land compared to other combinations, the correlation magnitude over land is weaker than over ocean. The difference is attributed to the greater size of convective systems over ocean. It is also found both over ocean and land that the anti-correlation of strong precipitation with "weak" (i.e., thin and/or low) cloud types is of greater absolute strength than positive correlations 20 between weak cloud types and weak precipitation. Cloud type co-occurrence relationships explain some of the cloudprecipitation anti-correlations. Couplings between weaker rainfall and clouds are also distinct in ocean vs. land, with precipitation predictability when cloud type is known being quite poor in general, particularly over land.

show abstract

Section: Uncertainty Of Cloud Type Classificationmentioning

confidence: 91%

Contrasting the Co-variability of Daytime Cloud and Precipitation over Tropical Land and Ocean

Jin¹,

Oreopoulos²,

Lee³

et al. 2017

Preprint

View full text Add to dashboard Cite

show abstract

“…12 bottom). Yuan et al (2011) regarded MCS anvils near the rain core as young anvils. They found these young anvils to have a broader distribution of reflectivity compared to the ones located far away from the raining area (old anvils), which is consistent with our results when comparing the anvils in the developing-mature stages (associated with younger anvils) and dissipating stage (associated with older anvils).…”

Section: Microphysical Propertiesmentioning

confidence: 99%

“…Satellite-based radar data is very useful for regions that have limited groundbased radar network such as the Maritime Continent of Indonesia. Yuan et al (2011) studied the vertical structure of MCSs by using data from the Cloud Profiling Radar onboard CloudSat in the A-train constellation to investigate the microphysics of cloud anvils in MCSs. As the distance from the rain core was used as the proxy of the age of anvil, the study only captured the MCS life stage for the mature stage.…”

Section: Introductionmentioning

confidence: 99%

The Properties of Mesoscale Convective Systems in Indonesia Detected Using the Grab ‘Em Tag ‘Em Graph ‘Em (GTG) Algorithm

Putri

Hayasaka

Whitehall

2017

Journal of the Meteorological Society of Japan

View full text Add to dashboard Cite

A mesoscale convective system (MCS) is organized thunderstorms with connected anvils, which has a significant impact on the global climate. By focusing on MCSs over the Maritime Continent of Indonesia, this study aims to gain a better understanding on the properties of the MCSs over the study area. The "Grab 'em Tag 'em Graph 'em" (GTG) tracking algorithm is applied to hourly Multi-functional Transport Satellite-1R data for two years to observe the distribution of MCSs and the evolution of MCSs along their lifetime. The results of MCS identification by using GTG are combined with CloudSat data products to study the vertical structure of the MCSs at various MCS life stages: developing, mature, and dissipating.The distribution of MCSs over Indonesia has a seasonal variation and distinct diurnal cycle. The life stages of the observed MCSs are characterized by distinct cloud microphysics at each stage. In the developing stage, the upper level of the MCS raining region shows the presence of precipitating ice particles. As the MCS progresses to the mature stage, the proportion of the raining area becomes small and the intensity of rain is reduced, accompanied by increasing occurrence of small-sized ice particles at the upper level. In the dissipating stage, large hydrometeors no longer exist at the upper part of the raining region. Within the MCS anvils, the dissipating stage shows a more uniform distribution of ice-particle effective radius compared to that shown by the developing and mature stages.MCS characteristics over the land and ocean differ on the basis of the minimum brightness temperature, the equivalent radius, the maximum rain rate, and the rain fraction that varies along the MCS evolution.

show abstract

“…It can be an indicator of the meteorological conditions, (thermo-)dynamical and micro-physical processes, in which a cloud forms (e.g., Yin et al, 2013;Yuan et al, 2011;Luo et al, 2009). Further, the cloud vertical distribution affects radiative and latent heating fluxes, which in turn, affect the largescale atmospheric circulation and precipitation processes (e.g., Wang and Rossow, 1998;Li et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

Henken¹,

Doppler

Lindstrot

et al. 2015

Atmos. Meas. Tech.

View full text Add to dashboard Cite

Abstract. This work presents a study on the sensitivity of two satellite cloud height retrievals to cloud vertical distribution. The difference in sensitivity is exploited by relating the difference in the retrieved cloud heights to cloud vertical extent. The two cloud height retrievals, performed within the Freie Universität Berlin AATSR MERIS Cloud (FAME-C) algorithm, are based on independent measurements and different retrieval techniques. First, cloud-top temperature (CTT) is retrieved from Advanced Along Track Scanning Radiometer (AATSR) measurements in the thermal infrared. Second, cloud-top pressure (CTP) is retrieved from Medium Resolution Imaging Spectrometer (MERIS) measurements in the oxygen-A absorption band and a nearby window channel. Both CTT and CTP are converted to cloud-top height (CTH) using atmospheric profiles from a numerical weather prediction model. First, a sensitivity study using radiative transfer simulations in the near-infrared and thermal infrared was performed to demonstrate, in a quantitative manner, the larger impact of the assumed cloud vertical extinction profile, described in terms of shape and vertical extent, on MERIS than on AATSR top-of-atmosphere measurements. Consequently, cloud vertical extinction profiles will have a larger influence on the MERIS than on the AATSR cloud height retrievals for most cloud types.Second, the difference in retrieved CTH ( CTH) from AATSR and MERIS are related to cloud vertical extent (CVE), as observed by ground-based lidar and radar at three ARM sites. To increase the impact of the cloud vertical extinction profile on the MERIS-CTP retrievals, single-layer and geometrically thin clouds are assumed in the forward model. Similarly to previous findings, the MERIS-CTP retrievals appear to be close to pressure levels in the middle of the cloud. Assuming a linear relationship, the CTH multiplied by 2.5 gives an estimate on the CVE for single-layer clouds. The relationship is stronger for single-layer clouds than for multi-layer clouds. Due to large variations of cloud vertical extinction profiles occurring in nature, a quantitative estimate of the cloud vertical extent is accompanied with large uncertainties.Yet, estimates of the CVE provide an additional parameter, next to CTH, that can be obtained from passive imager measurements and can be used to further describe cloud vertical distribution, thus contributing to the characterization of a cloudy scene.To further demonstrate the plausibility of the approach, an estimate of the CVE was applied to a case study. In light of the follow-up mission Sentinel-3 with AATSR and MERIS like instruments, Sea and Land Surface Temperature Radiometer (SLSTR) and (Ocean and Land Colour Instrument) OLCI, respectively, for which the FAME-C algorithm can be easily adapted, a more accurate estimate of the CVE can be expected. OLCI will have three channels in the oxygen-A absorption band, possibly providing enhanced information on cloud vertical distributions.

show abstract

Vertical Structures of Anvil Clouds of Tropical Mesoscale Convective Systems Observed by CloudSat

Cited by 64 publications

References 64 publications

Contrasting the Co-variability of Daytime Cloud and Precipitation over Tropical Land and Ocean

Contrasting the Co-variability of Daytime Cloud and Precipitation over Tropical Land and Ocean

The Properties of Mesoscale Convective Systems in Indonesia Detected Using the Grab ‘Em Tag ‘Em Graph ‘Em (GTG) Algorithm

Exploiting the sensitivity of two satellite cloud height retrievals to cloud vertical distribution

Contact Info

Product

Resources

About