scholarly journals Variability and trends in low cloud cover over India during 1961-2010

MAUSAM ◽  
2021 ◽  
Vol 68 (2) ◽  
pp. 235-252
Author(s):  
A. K. JASWAL ◽  
P. A. KORE ◽  
VIRENDRA SINGH
Keyword(s):  
Cloud Cover ◽  
Winter Season ◽  
Central India ◽  
Northeast India ◽  
Maximum Temperature ◽  
Strong Positive Correlation ◽  
Strong Negative Correlation ◽  
Annual Variations ◽  
Low Cloud ◽  
Low Cloud Cover

Annual and seasonal variability and trends in low cloud cover over India were analyzed for the period 1961-2010. Taking all period into account, there is a general decrease in mean low cloud cover over most regions of India, but an increase in the Indo-Gangetic plains and northeast India. Long term mean low cloud cover over India has inter-annual variations with highest cloud cover (39.4%) in monsoon and lowest cloud cover (10.5%) in winter season. The annual mean low cloud cover shows significant decreasing trend of -0.45% per decade, mainly contributed by monsoon where declining rate is -1.22% per decade. Out of the total numbers of stations showing decreasing trends, 65%, 47%, 53%, 71% and 37% of the stations show significant decrease in low cloud cover for annual, winter, summer, monsoon and post monsoon respectively, with large trend magnitudes occurring in central India. Spatially, the seasonal patterns of trends in low cloud cover confirm the annual patterns in most cases. Data analyses show that low cloud cover is having a strong negative correlation with maximum temperature and diurnal temperature range and a strong positive correlation with numbers of rainy days during the period of study.

scholarly journals Synoptic-scale controls of fog and low-cloud variability in the Namib Desert

2020 ◽  
Vol 20 (6) ◽  
pp. 3415-3438 ◽  
Author(s):  
Hendrik Andersen ◽  
Jan Cermak ◽  
Julia Fuchs ◽  
Peter Knippertz ◽  
Marco Gaetani ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Cloud Cover ◽  
Large Scale ◽  
Marine Boundary Layer ◽  
Synoptic Scale ◽  
Namib Desert ◽  
Data Set ◽  
Air Masses ◽  
Low Cloud ◽  
Low Cloud Cover

Abstract. Fog is a defining characteristic of the climate of the Namib Desert, and its water and nutrient input are important for local ecosystems. In part due to sparse observation data, the local mechanisms that lead to fog occurrence in the Namib are not yet fully understood, and to date, potential synoptic-scale controls have not been investigated. In this study, a recently established 14-year data set of satellite observations of fog and low clouds in the central Namib is analyzed in conjunction with reanalysis data in order to identify synoptic-scale patterns associated with fog and low-cloud variability in the central Namib during two seasons with different spatial fog occurrence patterns. It is found that during both seasons, mean sea level pressure and geopotential height at 500 hPa differ markedly between fog/low-cloud and clear days, with patterns indicating the presence of synoptic-scale disturbances on fog and low-cloud days. These regularly occurring disturbances increase the probability of fog and low-cloud occurrence in the central Namib in two main ways: (1) an anomalously dry free troposphere in the coastal region of the Namib leads to stronger longwave cooling of the marine boundary layer, increasing low-cloud cover, especially over the ocean where the anomaly is strongest; (2) local wind systems are modulated, leading to an onshore anomaly of marine boundary-layer air masses. This is consistent with air mass back trajectories and a principal component analysis of spatial wind patterns that point to advected marine boundary-layer air masses on fog and low-cloud days, whereas subsiding continental air masses dominate on clear days. Large-scale free-tropospheric moisture transport into southern Africa seems to be a key factor modulating the onshore advection of marine boundary-layer air masses during April, May, and June, as the associated increase in greenhouse gas warming and thus surface heating are observed to contribute to a continental heat low anomaly. A statistical model is trained to discriminate between fog/low-cloud and clear days based on information on large-scale dynamics. The model accurately predicts fog and low-cloud days, illustrating the importance of large-scale pressure modulation and advective processes. It can be concluded that regional fog in the Namib is predominantly of an advective nature and that fog and low-cloud cover is effectively maintained by increased cloud-top radiative cooling. Seasonally different manifestations of synoptic-scale disturbances act to modify its day-to-day variability and the balance of mechanisms leading to its formation and maintenance. The results are the basis for a new conceptual model of the synoptic-scale mechanisms that control fog and low-cloud variability in the Namib Desert and will guide future studies of coastal fog regimes.

Low Cloud Cover Sensitivity to Biomass-Burning Aerosols and Meteorology over the Southeast Atlantic

2018 ◽  
Vol 31 (11) ◽  
pp. 4329-4346 ◽  
Author(s):  
Adeyemi A. Adebiyi ◽  
Paquita Zuidema
Keyword(s):  
Biomass Burning ◽  
Cloud Cover ◽  
Longwave Radiation ◽  
Cloud Fraction ◽  
Specific Humidity ◽  
Aerosol Layer ◽  
Stratocumulus Clouds ◽  
Low Cloud ◽  
Low Cloud Cover ◽  
Absorbing Aerosols

Abstract Shortwave-absorbing aerosols seasonally cover and interact with an expansive low-level cloud deck over the southeast Atlantic. Daily anomalies of the MODIS low cloud fraction, fine-mode aerosol optical depth (AODf), and six ERA-Interim meteorological parameters (lower-tropospheric stability, 800-hPa subsidence, 600-hPa specific humidity, 1000- and 800-hPa horizontal temperature advection, and 1000-hPa geopotential height) are constructed spanning July–October (2001–12). A standardized multiple linear regression, whereby the change in the low cloud fraction to each component’s variability is normalized by one standard deviation, facilitates comparison between the different variables. Most cloud–meteorology relationships follow expected behavior for stratocumulus clouds. Of interest is the low cloud–subsidence relationship, whereby increasing subsidence increases low cloud cover between 10° and 20°S but decreases it elsewhere. Increases in AODf increase cloudiness everywhere, independent of other meteorological predictors. The cloud–AODf effect is partially compensated by accompanying increases in the midtropospheric moisture, which is associated with decreases in low cloud cover. This suggests that the free-tropospheric moisture affects the low cloud deck primarily through longwave radiation rather than mixing. The low cloud cover is also more sensitive to aerosol when the vertical distance between the cloud and aerosol layer is relatively small, which is more likely to occur early in the biomass burning season and farther offshore. A parallel statistical analysis that does not include AODf finds altered relationships between the low cloud cover changes and meteorology that can be understood through the aerosol cross-correlations with the meteorological predictors. For example, the low cloud–stability relationship appears stronger if aerosols are not explicitly included.

scholarly journals The Strength of Low-Cloud Feedbacks and Tropical Climate: A CESM Sensitivity Study

2019 ◽  
Vol 32 (9) ◽  
pp. 2497-2516 ◽  
Author(s):  
Ehsan Erfani ◽  
Natalie J. Burls
Keyword(s):  
Climate Sensitivity ◽  
Cloud Cover ◽  
Hydrological Cycle ◽  
Tropical Climate ◽  
Cloud Feedback ◽  
Cloud Feedbacks ◽  
Feedback Strength ◽  
Low Cloud ◽  
Low Cloud Cover ◽  
The Impact

Abstract Variability in the strength of low-cloud feedbacks across climate models is the primary contributor to the spread in their estimates of equilibrium climate sensitivity (ECS). This raises the question: What are the regional implications for key features of tropical climate of globally weak versus strong low-cloud feedbacks in response to greenhouse gas–induced warming? To address this question and formalize our understanding of cloud controls on tropical climate, we perform a suite of idealized fully coupled and slab-ocean climate simulations across which we systematically scale the strength of the low-cloud-cover feedback under abrupt 2 × CO2 forcing within a single model, thereby isolating the impact of low-cloud feedback strength. The feedback strength is varied by modifying the stratus cloud fraction so that it is a function of not only local conditions but also global temperature in a series of abrupt 2 × CO2 sensitivity experiments. The unperturbed decrease in low cloud cover (LCC) under 2 × CO2 is greatest in the mid- and high-latitude oceans, and the subtropical eastern Pacific and Atlantic, a pattern that is magnified as the feedback strength is scaled. Consequently, sea surface temperature (SST) increases more in these regions as well as the Pacific cold tongue. As the strength of the low-cloud feedback increases this results in not only increased ECS, but also an enhanced reduction of the large-scale zonal and meridional SST gradients (structural climate sensitivity), with implications for the atmospheric Hadley and Walker circulations, as well as the hydrological cycle. The relevance of our results to simulating past warm climate is also discussed.

On the Relationship between Stratiform Low Cloud Cover and Lower-Tropospheric Stability

2006 ◽  
Vol 19 (24) ◽  
pp. 6425-6432 ◽  
Author(s):  
Robert Wood ◽  
Christopher S. Bretherton
Keyword(s):  
Boundary Layer ◽  
Temperature Profile ◽  
Cloud Cover ◽  
Cloud Amount ◽  
Lapse Rate ◽  
Stratus Cloud ◽  
Low Clouds ◽  
Wide Range ◽  
Low Cloud ◽  
Low Cloud Cover

Abstract Observations in subtropical regions show that stratiform low cloud cover is well correlated with the lower-troposphere stability (LTS), defined as the difference in potential temperature θ between the 700-hPa level and the surface. The LTS can be regarded as a measure of the strength of the inversion that caps the planetary boundary layer (PBL). A stronger inversion is more effective at trapping moisture within the marine boundary layer (MBL), permitting greater cloud cover. This paper presents a new formulation, called the estimated inversion strength (EIS), to estimate the strength of the PBL inversion given the temperatures at 700 hPa and at the surface. The EIS accounts for the general observation that the free-tropospheric temperature profile is often close to a moist adiabat and its lapse rate is strongly temperature dependent. Therefore, for a given LTS, the EIS is greater at colder temperatures. It is demonstrated that while the seasonal cycles of LTS and low cloud cover fraction (CF) are strongly correlated in many regions, no single relationship between LTS and CF can be found that encompasses the wide range of temperatures occurring in the Tropics, subtropics, and midlatitudes. However, a single linear relationship between CF and EIS explains 83% of the regional/seasonal variance in stratus cloud amount, suggesting that EIS is a more regime-independent predictor of stratus cloud amount than is LTS under a wide range of climatological conditions. The result has some potentially important implications for how low clouds might behave in a changed climate. In contrast to Miller’s thermostat hypothesis that a reduction in the lapse rate (Clausius–Clapeyron) will lead to increased LTS and increased tropical low cloud cover in a warmer climate, the results here suggest that low clouds may be much less sensitive to changes in the temperature profile if the vertical profile of tropospheric warming follows a moist adiabat.

scholarly journals Sensitivity analysis of WOFOST for yield simulation of cassava over the major growing areas of India

2021 ◽  
Vol 23 (4) ◽  
pp. 375-380
Author(s):  
RAJI PUSHPALATHA ◽  
GOVINDAN KUTTY ◽  
BYJU GANGADHARAN
Keyword(s):  
Crop Production ◽  
Monsoon Season ◽  
Meteorological Data ◽  
Winter Season ◽  
Northeast India ◽  
Crop Model ◽  
Significant Trend ◽  
Maximum Temperature ◽  
Yield Variation ◽  
Cassava Production

A study was conducted to assess the meteorological sensitivity of the WOFOST crop model in simulating the yield of cassava. The sensitivity was designed by changing the present meteorological data by ±1 to ±5 %. The results has shown the minimum temperature influencing the yield of cassava (variation: 4.94 to -7.65 %) followed by the maximum temperature (yield variation: 6.39 to -6.03 %) and solar radiation (yield variation: -2.41 to 2.07 %). The trends of these meteorological variables have been further analyzed over the major cassava growing regions in India to link its variations with cassava production. A significant trend has been detected during the monsoon season in northeast India, with a decadal change of 0.63ºC. At the same time, a significant trend was detected in the peninsular region during the winter season, with a value of 0.74ºC/decade. The rate of solar dimming in northeast India during the monsoon season was -0.53 hour/decade and during the autumn season, it was -0.25 hour/decade, respectively. The meteorological sensitivity of crop model on its yield and trends may assist the decision-makers in developing appropriate plans mitigations strategies to enhance crop production to ensure food security.

scholarly journals Cloud climatology of the Indian Ocean based on ship observations

MAUSAM ◽  
2022 ◽  
Vol 52 (3) ◽  
pp. 527-540
Author(s):  
M. RAJEEVAN ◽  
R. K. PRASAD ◽  
U. S. DE
Keyword(s):  
Indian Ocean ◽  
Bay Of Bengal ◽  
Cloud Cover ◽  
Monsoon Season ◽  
Equatorial Indian Ocean ◽  
Enso Events ◽  
Decadal Scale ◽  
Low Cloud ◽  
The Indian Ocean ◽  
Low Cloud Cover

Surface cloud data based on synoptic observations made by Voluntary Observing Ships (VOS) during the period 1951-98 were used to prepare the seasonal and annual cloud climatology of the Indian Ocean. The analysis has been carried out by separating the long-term trends, decadal and inter-annual components from the monthly cloud anomaly time series at each 5° × 5° grids.   Maximum zone of total and low cloud cover shifts from equator to northern parts of India during the monsoon season. During the monsoon season (June-September), maximum total cloud cover exceeding 70% and low cloud cover exceeding 50% are observed over north Bay of Bengal. Maximum standard deviation of total and low cloud cover is observed near the equator and in the southern hemisphere. Both total and low cloud cover over Arabian Sea and the equatorial Indian Ocean are observed to decrease during the ENSO events. However, cloud cover over Bay of Bengal is not modulated by the ENSO events. On inter-decadal scale, low cloud cover shifted from a "low regime" to a "high regime" after 1980 which may be associated with the corresponding inter-decadal changes of sea surface temperatures over north Indian Ocean observed during the late 1970s.

scholarly journals Classification of Crops, Pastures, and Tree Plantations along the Season with Multi-Sensor Image Time Series in a Subtropical Agricultural Region

2019 ◽  
Vol 11 (3) ◽  
pp. 334 ◽  
Author(s):  
Cecília Lira Melo de Oliveira Santos ◽  
Rubens Augusto Camargo Lamparelli ◽  
Gleyce Kelly Dantas Araújo Figueiredo ◽  
Stéphane Dupuy ◽  
Julie Boury ◽  
...  
Keyword(s):  
Time Series ◽  
Cloud Cover ◽  
Radar Data ◽  
Agricultural Landscapes ◽  
Gap Filling ◽  
Use Of Time ◽  
High Quality Image ◽  
Low Cloud ◽  
Low Cloud Cover ◽  
Heterogeneous Region

Timely and efficient land-cover mapping is of high interest, especially in agricultural landscapes. Classification based on satellite images over the season, while important for cropland monitoring, remains challenging in subtropical agricultural areas due to the high diversity of management systems and seasonal cloud cover variations. This work presents supervised object-based classifications over the year at 2-month time-steps in a heterogeneous region of 12,000 km2 in the Sao Paulo region of Brazil. Different methods and remote-sensing datasets were tested with the random forest algorithm, including optical and radar data, time series of images, and cloud gap-filling methods. The final selected method demonstrated an overall accuracy of approximately 0.84, which was stable throughout the year, at the more detailed level of classification; confusion mainly occurred among annual crop classes and soil classes. We showed in this study that the use of time series was useful in this context, mainly by including a small number of highly discriminant images. Such important images were eventually distant in time from the prediction date, and they corresponded to a high-quality image with low cloud cover. Consequently, the final classification accuracy was not sensitive to the cloud gap-filling method, and simple median gap-filling or linear interpolations with time were sufficient. Sentinel-1 images did not improve the classification results in this context. For within-season dynamic classes, such as annual crops, which were more difficult to classify, field measurement efforts should be densified and planned during the most discriminant window, which may not occur during the crop vegetation peak.

scholarly journals Interpretation of Factors Controlling Low Cloud Cover and Low Cloud Feedback Using a Unified Predictive Index

2017 ◽  
Vol 30 (22) ◽  
pp. 9119-9131 ◽  
Author(s):  
Hideaki Kawai ◽  
Tsuyoshi Koshiro ◽  
Mark J. Webb
Keyword(s):  
Cloud Cover ◽  
Vertical Gradient ◽  
Sea Surface ◽  
Observation Data ◽  
Strongly Correlated ◽  
Predictive Index ◽  
Low Cloud ◽  
Inversion Strength ◽  
Low Cloud Cover ◽  
Static Energy

This paper reports on a new index for low cloud cover (LCC), the estimated cloud-top entrainment index (ECTEI), which is a modification of estimated inversion strength (EIS) and takes into account a cloud-top entrainment (CTE) criterion. Shipboard cloud observation data confirm that the index is strongly correlated with LCC. It is argued here that changes in LCC cannot be fully determined from changes in EIS only, but can be better determined from changes in both EIS and sea surface temperature (SST) based on the ECTEI. Furthermore, it is argued that various proposed predictors of LCC change, including the moist static energy vertical gradient, SST, and midlevel clouds, can be better understood from the perspective of the ECTEI.

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