Intraseasonal Variability of Cloud Cover in Midlatitudes during Boreal Winter

2021 ◽  
Author(s):  
Reona Satoh ◽  
Noriyuki Nishi ◽  
Hitoshi Mukougawa
Keyword(s):  
Vertical Velocity ◽  
Cloud Cover ◽  
Rossby Waves ◽  
Correlation Coefficients ◽  
Condensation Process ◽  
Upward Motion ◽  
Total Cloud Cover ◽  
High Cloud ◽  
Short Period ◽  
Low Cloud

<p>We investigated the spatial structure of the intraseasonal variation (15-30 day) in cloud cover in the mid-latitudes during winter. We attempted to interpret the spatial pattern of clouds in　the context of Rossby waves.</p><p> </p><p>We used the total cloud cover in H-series dataset (1984-2016) by the International Satellite Cloud Climatology Project (ISCCP) based on the satellite observations, and ERA-Interim re-analysis data (1980-2016) including high, medium, and low cloud covers defined by σ coordinate.</p><p> </p><p>We calculated correlation coefficients between the geopotential height at 300hPa (Z300) at a certain position and the cloud covers, meridional wind, and vertical velocity in the surrounding area. The positions of the maximum of high (0.45≧σ) and medium cloud cover (0.8≧σ＞0.45) relative to Z300 are longitudinally constant for all longitudes except the region from east Asia to western part of the Pacific. The position of the maximum of the high cloud cover is located just west of the ridge and just east of the maximum positions of the upward motions of re-analysis vertical velocity and its adiabatic component. These results suggest that the adiabatic upward motion in the southerly wind region west of the ridge contributes to the generation of high cloud cover. In contrast, the position of the maximum of medium cloud cover is located just east of the trough. The position of the maximum of diabatic upward motion, which is consider to be due to condensation process is located near the maximum of medium cloud cover. These results suggest that Rossby waves modulate activity of short-period disturbances with precipitation. Apart from high and medium cloud covers, the position of the maximum of low cloud cover (σ＞0.8) has large longitudinal dependency. While the position of the maximum is located at almost the same as that of medium cloud cover mainly over the continent, the position of the maximum is located just east of the ridge mainly over the ocean.</p><p> </p><p>The correlation coefficients between ISCCP total cloud cover and Z300 are statistically significant only over the continent, where the positions of the maximum of high, medium, and low cloud covers are all located east of the trough and west of the ridge.</p>

scholarly journals Investigating the Diurnal Evolution of the Cloud Size Distribution of Continental Cumulus Convection Using Multiday LES

2019 ◽  
Vol 76 (3) ◽  
pp. 729-747 ◽  
Author(s):  
Thirza W. van Laar ◽  
Vera Schemann ◽  
Roel A. J. Neggers
Keyword(s):  
Power Law ◽  
Cloud Cover ◽  
Large Scale ◽  
Correlation Coefficients ◽  
Scale Model ◽  
Cloud Base ◽  
Size Distributions ◽  
Total Cloud Cover ◽  
Surface Precipitation ◽  
Shallow Cumulus

Abstract The diurnal dependence of cumulus cloud size distributions over land is investigated by means of an ensemble of large-eddy simulations (LESs). A total of 146 days of transient continental shallow cumulus are selected and simulated, reflecting a low midday maximum of total cloud cover, weak synoptic forcing, and the absence of strong surface precipitation. The LESs are semi-idealized, forced by large-scale model output but using an interactive surface. This multitude of cases covers a large parameter space of environmental conditions, which is necessary for identifying any diurnal dependencies in cloud size distributions. A power-law exponential function is found to describe the shape of the cloud size distributions for these days well, with the exponential component capturing the departure from power-law scaling at the larger cloud sizes. To assess what controls the largest cloud size in the distribution, the correlation coefficients between the maximum cloud size and various candidate variables reflecting the boundary layer state are computed. The strongest correlation is found between total cloud cover and maximum cloud size. Studying the size density of the cloud area revealed that larger clouds contribute most to a larger total cloud cover, and not the smaller ones. Besides cloud cover, cloud-base and cloud-top height are also found to weakly correlate with the maximum cloud size, suggesting that the classic idea of deeper boundary layers accommodating larger convective thermals still holds for shallow cumulus. Sensitivity tests reveal that the results are only minimally affected by the representation of microphysics and the output resolution.

scholarly journals ROLLING MOSAIC METHOD TO SUPPORT THE DEVELOPMENT OF POTENTIAL FISHING ZONE FORECASTING FOR COASTAL AREAS

2020 ◽  
Vol 16 (2) ◽  
pp. 107
Author(s):  
Komang Iwan Suniada ◽  
Eko Susilo ◽  
Wingking Era Rintaka Siwi ◽  
Nuryani Widagti
Keyword(s):  
Rainy Season ◽  
Cloud Cover ◽  
Correlation Coefficients ◽  
Strong Relationship ◽  
Dry Season ◽  
Time Range ◽  
Marine Research ◽  
Low Cloud ◽  
Seasurface Temperature ◽  
Potential Fishing Zone

The production of the Indonesian Institute for Marine Research and Observation’s mapping of forecast fishing areas (peta prakiraan daerah penangkapan ikan or PPDPI) based on passive satellite imagery is often constrained by high-cloud-cover issues, which lead to sub-optimal results. This study examines the use of the rolling mosaic method for providing geophysical variables, in particular, seasurface temperature (STT) together with minimum cloud cover, to enable clearer identification of oceanographic conditions. The analysis was carried out in contrasting seasons: dry season in July 2018 and rainy season in December 2018. In general, the rolling mosaic method is able to reduce cloud cover for sea-surface temperature (SST) data. A longer time range will increase the coverage percentage (CP) of SST data. In July, the CP of SST data increased significantly, from 15.3 % to 30.29% for the reference 1D mosaic and up to 84.19 % to 89.07% for the 14D mosaic. In contrast, the CP of SST data in December tended to be lower, from 4.93 % to 13.03% in the 1D mosaic to 41.48 % to 51.60% in the14D mosaic. However, the longer time range decreases the relationship between the reference SST data and rolling mosaic method data. A strong relationship lies between the 1D mosaic and 3D mosaics, with correlation coefficients of 0.984 for July and 0.945 for December. Furthermore, a longer time range will decrease root mean square error (RMSE) values. In July, RMSE decreased from 0.288°C (3D mosaic) to 0.471°C (14D mosaic). The RMSE value in December decreased from 0.387°C (3D mosaic) to 0.477°C (14D mosaic). Based on scoring analysis of CP, correlation coefficient and RMSE value, results indicate that the 7D mosaic method is useful for providing low-cloud-coverage SST data for PPDPI production in the dry season, while the 14D mosaic method is suitable for the rainy season.

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

2018 ◽  
Vol 18 (10) ◽  
pp. 7329-7343 ◽  
Author(s):  
Jiming Li ◽  
Qiaoyi Lv ◽  
Bida Jian ◽  
Min Zhang ◽  
Chuanfeng Zhao ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Wind Shear ◽  
Cloud Cover ◽  
Atmospheric Stability ◽  
Length Scale ◽  
The Tibetan Plateau ◽  
Total Cloud Cover ◽  
Atmospheric Models ◽  
The Impact ◽  
Overlap Parameter

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.

Common summertime total cloud cover and aerosol optical depth weekly variabilities over Europe: Sign of the aerosol indirect effects?

2015 ◽  
Vol 153 ◽  
pp. 59-73 ◽  
Author(s):  
A.K. Georgoulias ◽  
K.A. Kourtidis ◽  
G. Alexandri ◽  
S. Rapsomanikis ◽  
A. Sanchez-Lorenzo
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Indirect Effects ◽  
Cloud Cover ◽  
Total Cloud Cover ◽  
Aerosol Indirect Effects

Assessment of Arctic Cloud Cover Anomalies in Atmospheric Reanalysis Products Using Satellite Data

2016 ◽  
Vol 29 (17) ◽  
pp. 6065-6083 ◽  
Author(s):  
Yinghui Liu ◽  
Jeffrey R. Key
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Global Climate ◽  
Correlation Coefficients ◽  
Cloud Amount ◽  
Satellite Observation ◽  
Skill Score ◽  
Global Climate Models ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Cloud cover is one of the largest uncertainties in model predictions of the future Arctic climate. Previous studies have shown that cloud amounts in global climate models and atmospheric reanalyses vary widely and may have large biases. However, many climate studies are based on anomalies rather than absolute values, for which biases are less important. This study examines the performance of five atmospheric reanalysis products—ERA-Interim, MERRA, MERRA-2, NCEP R1, and NCEP R2—in depicting monthly mean Arctic cloud amount anomalies against Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations from 2000 to 2014 and against Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) observations from 2006 to 2014. All five reanalysis products exhibit biases in the mean cloud amount, especially in winter. The Gerrity skill score (GSS) and correlation analysis are used to quantify their performance in terms of interannual variations. Results show that ERA-Interim, MERRA, MERRA-2, and NCEP R2 perform similarly, with annual mean GSSs of 0.36/0.22, 0.31/0.24, 0.32/0.23, and 0.32/0.23 and annual mean correlation coefficients of 0.50/0.51, 0.43/0.54, 0.44/0.53, and 0.50/0.52 against MODIS/CALIPSO, indicating that the reanalysis datasets do exhibit some capability for depicting the monthly mean cloud amount anomalies. There are no significant differences in the overall performance of reanalysis products. They all perform best in July, August, and September and worst in November, December, and January. All reanalysis datasets have better performance over land than over ocean. This study identifies the magnitudes of errors in Arctic mean cloud amounts and anomalies and provides a useful tool for evaluating future improvements in the cloud schemes of reanalysis products.

scholarly journals The lunar and solar diurnal variations of water-level in a well at Kew observatory, Richmond

1918 ◽  
Vol 94 (663) ◽  
pp. 476-478
Keyword(s):  
Water Level ◽  
Royal Society ◽  
Correlation Coefficients ◽  
Barometric Pressure ◽  
Diurnal Variations ◽  
Range Of Movement ◽  
Nearest Point ◽  
Similar Relation ◽  
Short Period ◽  
The Mean

In a paper communicated to the Royal Meteorological Society, it was shown that the experimental well at Kew Observatory responded to the lunar fortnightly oscillation of mean level in the River Thames, which is 300 yards from the Observatory at its nearest point. The sensitiveness of the water-level to barometric pressure has also been investigated, and the results have been given in a paper recently read before the Royal Society. The present paper deals with the effects of the short-period tides in the solar and lunar series, S 1 , S 2 , S 3 , S 4 , and M 1 , M 2 , M 3 , M 4 . Two-hourly measurements, both in lunar and solar time, were made on the traces obtained during the first two years, August, 1914-August, 1916, omitting days of very irregular movement. Monthly mean inequalities were then computed. Well marked solar and lunar diurnal variations were found in each month, taking the form of double oscillations with two maxima and two minima during the 24 hours. The range of movement was in each case found to be highly associated with the mean height of the water in the well, the correlation coefficients being 0·89 (lunar) and 0·90 (solar). A similar relation had been previously found to exist in the case of barometric pressure.

The effect of cloud cover on the development of habitat quality indices for juvenile Atlantic salmon (Salmo salar)

2003 ◽  
Vol 60 (11) ◽  
pp. 1386-1397 ◽  
Author(s):  
Philippe Girard ◽  
Daniel Boisclair ◽  
Michel Leclerc
Keyword(s):  
Grain Size ◽  
Atlantic Salmon ◽  
Water Temperature ◽  
Salmo Salar ◽  
Cloud Cover ◽  
Predictive Power ◽  
Fish Distribution ◽  
Quality Indices ◽  
High Cloud ◽  
Physical Conditions

We tested the validity of the predictions made by a habitat probabilistic index (HPI) developed using a description of the physical conditions (depth, flow velocity, grain size) used and avoided by parrs during days of different cloudiness. Thirteen surveys were designed to estimate the number and the distribution of parrs actively foraging within a 300-m reach of a river. During these surveys, the number of parrs actively foraging ranged from 12 to 118, cloud cover ranged from 5% to 100%, and water temperature ranged from 16.5 °C to 21.7 °C. The number of parrs actively foraging was negatively related to cloud cover (r2 = 0.44 to 0.88) but was independent of water temperature. HPI models developed under low (<33%) and intermediate (34–67%) cloud cover explained 82% to 98% of the local variations of fish density. The HPI model developed under high cloud cover (67–100%) was unable to predict fish distribution observed during cloudy days. Our results suggest that HPI models developed when cloudiness is >67% may have a limited predictive power.

scholarly journals The impact of atmospheric dynamics on vertical cloud overlap over the Tibetan Plateau

2017 ◽  
Author(s):  
Jiming Li ◽  
Qiaoyi Lv ◽  
Bida Jian ◽  
Min Zhang ◽  
Chuanfeng Zhao ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Wind Shear ◽  
Cloud Cover ◽  
Atmospheric Stability ◽  
Separation Distance ◽  
Atmospheric Dynamics ◽  
The Tibetan Plateau ◽  
Total Cloud Cover ◽  
The Impact ◽  
Overlap Parameter

Abstract. The accurate representation of cloud vertical overlap in atmospheric models is particularly significant for predicting the total cloud cover and for the calculations related to the radiative budget in these models. However, it has received too little attention due to the limited observation, especially over the Tibetan Plateau (TP). In this study, 4 years (2007–2010) of data from the CloudSat cloud product and collocated ERA-Interim reanalysis product were analyzed to examine the seasonal and zonal variations of cloud overlap properties over the TP region, and evaluate the effect of atmospheric dynamics on cloud overlap. Unique characteristics of cloud overlap over the TP have been found. The statistical results show that the random overlap assumption slightly underestimates the total cloud coverage for discontinuous cloud layers over the TP, whereas the overlap parameter α for continuous cloud sharply decrease from maximum to random overlap with an increase of layer distance, eventually trending towards a minimal overlap (e.g., negative α values) as the cloud layer separation distance exceeds 1.5 km. Compared with the global averaged cloud overlap characteristics, the proportion of minimal overlap over the TP is significant high (about 41 %). It may be associated with the unique topographical forcing and thermos-dynamical environment of the TP. As a result, we propose a valid scheme for quantifying the degree of cloud overlap over the TP through a linear combination of the maximum and minimum overlap, and further parameterize decorrelation length scale L as a function of wind shear and atmospheric stability. Compared with other parameterizations, the new scheme reduces the bias between predicted and observed cloud covers. These results thus indicate that effects of wind shear and atmospheric stability on cloud overlap should both be taken into account in the parameterization of overlap parameter to improve the simulation of total cloud cover in models.

scholarly journals Characterisation and surface radiative impact of Arctic low clouds from the IAOOS field experiment

2020 ◽  
Author(s):  
Julia Maillard ◽  
François Ravetta ◽  
Jean-Christophe Raut ◽  
Vincent Mariage ◽  
Jacques Pelon
Keyword(s):  
Field Experiment ◽  
Arctic Ocean ◽  
Cloud Cover ◽  
Great Majority ◽  
The North ◽  
Low Clouds ◽  
Radiative Impact ◽  
Low Cloud ◽  
Ocean Observing ◽  
Layer Cloud

Abstract. The Ice, Atmosphere, Arctic Ocean Observing System (IAOOS) field experiment took place from 2014 to 2019. Over this period, more than 20 instrumented buoys were deployed at the North Pole. Once locked into the ice, the buoys drifted for periods of a month to more than a year. Some of these buoys were equipped with 808 nm wavelength lidars which acquired a total of 1805 profiles over the course of the campaign. This IAOOS lidar dataset is exploited to establish a novel statistic of cloud cover and of the geometrical and optical characteristics of the lowest cloud layer. Cloud frequency is globally at 75 %, and above 85 % from May to October. Single layers are thickest in October/November and thinnest in the summer. Meanwhile, their optical depth is maximum in October. On the whole, the cloud cover is very low, with the great majority of first layer bases beneath 120 m. In the shoulder seasons, surface temperatures are markedly warmer when the IAOOS profile contains at least one low cloud than when it does not. This temperature difference is statistically insignificant in the summer months. Indeed, summer clouds have a shortwave cooling effect which can reach −60 W m−2 and balance out their longwave warming effect.

scholarly journals Characterisation and surface radiative impact of Arctic low clouds from the IAOOS field experiment

2021 ◽  
Vol 21 (5) ◽  
pp. 4079-4101
Author(s):  
Julia Maillard ◽  
François Ravetta ◽  
Jean-Christophe Raut ◽  
Vincent Mariage ◽  
Jacques Pelon
Keyword(s):  
Field Experiment ◽  
Cloud Cover ◽  
Great Majority ◽  
Cloud Base ◽  
The North ◽  
Low Clouds ◽  
Radiative Impact ◽  
Low Cloud ◽  
Ocean Observing ◽  
Cloud Base Height

Abstract. The Ice, Atmosphere, Arctic Ocean Observing System (IAOOS) field experiment took place from 2014 to 2019. Over this period, more than 20 instrumented buoys were deployed at the North Pole. Once locked into the ice, the buoys drifted for periods of a month to more than a year. Some of these buoys were equipped with 808 nm wavelength lidars which acquired a total of 1777 profiles over the course of the campaign. This IAOOS lidar dataset is exploited to establish a novel statistic of cloud cover and of the geometrical and optical characteristics of the lowest cloud layer. The average cloud frequency from April to December over the course of the campaign was 75 %. Cloud occurrence frequencies were above 85 % from May to October. Single layers are thickest in October/November and thinnest in the summer. Meanwhile, their optical depth is maximum in October. On the whole, the cloud base height is very low, with the great majority of first layer bases beneath 120 m. In April and October, surface temperatures are markedly warmer when the IAOOS profile contains at least one low cloud than when it does not. This temperature difference is statistically insignificant in the summer months. Indeed, summer clouds have a shortwave cooling effect which can reach −60 W m−2 and balance out their longwave warming effect.

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