Effect of cirrus clouds on the diurnal cycle of tropical deep convective clouds

Hong, Gang; Heygster, Georg; Rodriguez, Carlos Augusto Morales

doi:10.1029/2005jd006208

Cited by 36 publications

(72 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Those investigations demonstrated that rain usually increases progressively as the cloud-top temperature decreases [4]. However, some studies shows that cold cloud TB does not necessarily imply precipitation due to the existence of cold cloud tops [1,5]. The relationship between cloud characteristics and their generated precipitation remains unclear and needs further detailed analysis at the pixel scale [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Analysis and Application of the Relationship between Cumulonimbus (Cb) Cloud Features and Precipitation Based on FY-2C Image

Liu

et al. 2014

Atmosphere

View full text Add to dashboard Cite

Although cumulonimbus (Cb) clouds are the main source of precipitation in south China, the relationship between Cb cloud characteristics and precipitation remains unclear. Accordingly, the primary objective of this study was to thoroughly analyze the relationship between Cb cloud features and precipitation both at the pixel and cloud patch scale, and then to apply it in precipitation estimation in the Huaihe River Basin using China's first operational geostationary meteorological satellite, FengYun-2C (FY-2C), and the hourly precipitation data of 286 gauges from 2007. First, 31 Cb parameters (14 parameters of three pixel features and 17 parameters of four cloud patch features) were extracted based on a Cb tracking method using an artificial neural network (ANN) cloud classification as a pre-processing procedure to identify homogeneous Cb patches. Then, the relationship between Cb cloud properties and precipitation was analyzed and applied in a look-up table algorithm to estimate precipitation. The results were as follows: (1) Precipitation increases first and then declines with increasing values for cold cloud and time evolution parameters, OPEN ACCESSAtmosphere 2014, 5 212 and heavy precipitation may occur not only near the convective center, but also on the front of the Cb clouds on the pixel scale. (2) As for the cloud patch scale, precipitation is typically associated with cold cloud and rough cloud surfaces, whereas the coldest and roughest cloud surfaces do not correspond to the strongest rain. Moreover, rainfall has no obvious relationship with the cloud motion features and varies significantly over different life stages. The involvement of mergers and splits of minor Cb patches is crucial for precipitation processes. (3) The correlation coefficients of the estimated rain rate and gauge rain can reach 0.62 in the cross-validation period and 0.51 in the testing period, which indicates the feasibility of the further application of the relationship in precipitation estimation.

show abstract

Section: Introductionmentioning

confidence: 99%

Analysis and Application of the Relationship between Cumulonimbus (Cb) Cloud Features and Precipitation Based on FY-2C Image

Liu

et al. 2014

Atmosphere

View full text Add to dashboard Cite

show abstract

“…deep convective clouds T 11 < 220 K, and cirrus anvils clouds 220 K < T 11 < 260 K). It has been demonstrated that a noticeable diurnal cycle of both deep convective clouds, high cold clouds, and upper tropospheric humidity (UTH) is present over land and ocean regions associated with convective activity (Hong et al, 2006;Chung et al, 2007). The UTH is observed to lag the peak of high cloud cover by several hours which, in turn, lags the peak of deep convective cloud occurrence (Horváth and Soden, 2008;Sohn et al, 2008;Zelinka and Hartmann, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…Most of these studies are based on geostationary infrared (IR) data (e.g. Soden, 2000;Tian et al, 2004;Chung et al, 2007), but also combinations of IR and radar data from the Tropical Rainfall Measuring Mission (Hong et al, 2006;Liu and Zipser, 2008a) as well as IR and passive microwave measurements (Zelinka and Hartmann, 2009) have been used. Typically, IR brightness temperatures at 6.7 µm are used to estimate the clear sky mean relative humidity between 500 and 200 hPa (Soden and Bretherton, 1993), and various thresholds of the 11 µm window channel are used to estimate occurrence frequencies of various cloud types (e.g.…”

Section: Introductionmentioning

confidence: 99%

Diurnal variations of humidity and ice water content in the tropical upper troposphere

et al. 2010

View full text Add to dashboard Cite

Abstract.Observational results of diurnal variations of humidity from Odin-SMR and AURA-MLS, and cloud ice mass from Odin-SMR and CloudSat are presented for the first time. Comparisons show that the retrievals of humidity and cloud ice from these two satellite combinations are in good agreement. The retrieved data are combined from four almost evenly distributed times of the day allowing mean values, amplitudes and phases of the diurnal variations around 200 hPa to be estimated. This analysis is applied to six climatologically distinct regions, five located in the tropics and one over the subtropical northern Pacific Ocean. The strongest diurnal cycles are found over tropical land regions, where the amplitude is ∼7% RHi for humidity and ∼50% for ice mass. The greatest ice mass for these regions is found during the afternoon, and the humidity maximum is observed to lag this peak by ∼6 h. Over tropical ocean regions the variations are smaller and the maxima in both ice mass and humidity are found during the early morning. Observed results are compared with output from three climate models (ECHAM, EC-EARTH and CAM3). Direct measurementmodel comparisons were not possible because the measured and modelled cloud ice masses represent different quantities. To make a meaningful comparison, the amount of snow had to be estimated from diagnostic parameters of the models. There is a high probability that the models underestimate the average ice mass (outside the 1-σ uncertainty). The models also show clear deficiencies when it comes to amplitude and phase of the regional variations, but to varying degrees.

show abstract

“…This is not necessarily the case for H 2 O and the influence from below would tend to increase retrieved mixing ratios at 100 hPa. This influence is more pronounced over land since convection has no strong diurnal cycle over ocean (Hong et al, 2006) and would thus explain the smaller correlation of nighttime IWC and H 2 O over land.…”

Section: Discussionmentioning

confidence: 99%

“…However, the anticorrelation is higher over Indonesia and the Pacific Ocean than over South America. Convection has a pronounced diurnal cycle over land which is absent over ocean (Hong et al, 2006). This may explain the differences in correlation over land and ocean since we only use nighttime CALIPSO measurements.…”

Section: Anticorrelation Of Water Vapor and Cirrus Cloudsmentioning

confidence: 99%

Correlation among cirrus ice content, water vapor and temperature in the TTL as observed by CALIPSO and Aura/MLS

Flury

Read

2012

Atmos. Chem. Phys.

View full text Add to dashboard Cite

Abstract. Water vapor in the tropical tropopause layer (TTL) has a local radiative cooling effect. As a source for ice in cirrus clouds, however, it can also indirectly produce infrared heating. Using NASA A-Train satellite measurements of CALIPSO and Aura/MLS we calculated the correlation of water vapor, ice water content and temperature in the TTL. We find that temperature strongly controls water vapor (correlation r = 0.94) and cirrus clouds at 100 hPa (r = −0.91). Moreover we observe that the cirrus seasonal cycle is highly (r = −0.9) anticorrelated with the water vapor variation in the TTL, showing higher cloud occurrence during December-January-February. We further investigate the anticorrelation on a regional scale and find that the strong anticorrelation occurs generally in the ITCZ (Intertropical Convergence Zone). The seasonal cycle of the cirrus ice water content is also highly anticorrelated to water vapor (r = −0.91) and our results support the hypothesis that the total water at 100 hPa is roughly constant. Temperature acts as a main regulator for balancing the partition between water vapor and cirrus clouds. Thus, to a large extent, the depleting water vapor in the TTL during DJF is a manifestation of cirrus formation.

show abstract

Effect of cirrus clouds on the diurnal cycle of tropical deep convective clouds

Cited by 36 publications

References 59 publications

Analysis and Application of the Relationship between Cumulonimbus (Cb) Cloud Features and Precipitation Based on FY-2C Image

Analysis and Application of the Relationship between Cumulonimbus (Cb) Cloud Features and Precipitation Based on FY-2C Image

Diurnal variations of humidity and ice water content in the tropical upper troposphere

Correlation among cirrus ice content, water vapor and temperature in the TTL as observed by CALIPSO and Aura/MLS

Contact Info

Product

Resources

About