Characteristics of Deep Cloud Systems under Weak and Strong Synoptic Forcing during the Indian Summer Monsoon Season

2019 ◽  
Vol 147 (10) ◽  
pp. 3741-3758 ◽  
Author(s):  
Jayesh Phadtare ◽  
G. S. Bhat
Keyword(s):  
Monsoon Season ◽  
Propagation Speed ◽  
Maximum Size ◽  
Gradient Field ◽  
Synoptic Scale ◽  
Pressure System ◽  
Cloud Systems ◽  
Convective Systems ◽  
The North ◽  
Synoptic Forcing

Abstract Synoptic-scale weather systems are often responsible for initiating mesoscale convective systems (MCSs). Here, we explore how synoptic forcing influences MCS characteristics, such as the maximum size, lifespan, cloud-top height, propagation speed, and triggering over the Indian region. We used 30-min interval infrared (IR) data of the Indian Kalpana-1 geostationary satellite. Cloud systems (CSs) in this data are identified and tracked using an object tracking algorithm. ERA-Interim 850-hPa vorticity is taken as a proxy for the synoptic forcing. The probability of CSs being larger, longer lived, and deeper is more in the presence of a synoptic-scale vorticity field; however, the influence of synoptic forcing is not evident on the westward propagation of CSs over land. There exists a linear relationship between maximum size, lifespan, and average cloud-top height of CSs regardless of the nature of synoptic forcing. Formation of CSs peaks around 1500 LST over land, which is independent of synoptic forcing. Over the north Bay of Bengal, CSs formation is predominantly nocturnal when synoptic forcing is strong, whereas, 0300 and 1200 LST are the preferred times when synoptic forcing is weak. Long-lived CSs are preferentially triggered in the western flank of the 850-hPa vorticity gradient field of a monsoon low pressure system. Once triggered, CSs propagate westward and ahead of the synoptic system and dissipate around midnight. Formation of new CSs on the next day occurs in the afternoon hours in the wake of previous day’s CSs and where vorticity gradient is also present. Formation and westward propagations of CSs on successive days move the synoptic envelope westward.

scholarly journals Evaluating Forecast Skills of Moisture from Convective-Permitting WRF-ARW Model during 2017 North American Monsoon Season

Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 694 ◽  
Author(s):  
Christoforus Bayu Risanto ◽  
Christopher L. Castro ◽  
James M. Moker ◽  
Avelino F. Arellano ◽  
David K. Adams ◽  
...  
Keyword(s):  
North American ◽  
Monsoon Season ◽  
Precipitable Water ◽  
Weather Forecast ◽  
Moisture Flux ◽  
Rain Gauge ◽  
North American Monsoon ◽  
Convective Systems ◽  
The North ◽  
Northwestern Mexico

This paper examines the ability of the Weather Research and Forecasting model forecast to simulate moisture and precipitation during the North American Monsoon GPS Hydrometeorological Network field campaign that took place in 2017. A convective-permitting model configuration performs daily weather forecast simulations for northwestern Mexico and southwestern United States. Model precipitable water vapor (PWV) exhibits wet biases greater than 0.5 mm at the initial forecast hour, and its diurnal cycle is out of phase with time, compared to observations. As a result, the model initiates and terminates precipitation earlier than the satellite and rain gauge measurements, underestimates the westward propagation of the convective systems, and exhibits relatively low forecast skills on the days where strong synoptic-scale forcing features are absent. Sensitivity analysis shows that model PWV in the domain is sensitive to changes in initial PWV at coastal sites, whereas the model precipitation and moisture flux convergence (QCONV) are sensitive to changes in initial PWV at the mountainous sites. Improving the initial physical states, such as PWV, potentially increases the forecast skills.

scholarly journals Atmospheric dynamics of extreme discharge events from 1979 to 2016 in the southern Central Andes

2020 ◽  
Vol 55 (11-12) ◽  
pp. 3485-3505
Author(s):  
F. Castino ◽  
B. Bookhagen ◽  
A. de la Torre
Keyword(s):  
Return Period ◽  
Heavy Rainfall ◽  
Monsoon Season ◽  
Central Andes ◽  
Atmospheric Dynamics ◽  
Convective Systems ◽  
The North ◽  
Southern Central ◽  
Cold Surges ◽  
Semi Arid

Abstract During the South-American Monsoon season, deep convective systems occur at the eastern flank of the Central Andes leading to heavy rainfall and flooding. We investigate the large- and meso-scale atmospheric dynamics associated with extreme discharge events (> 99.9th percentile) observed in two major river catchments meridionally stretching from humid to semi-arid conditions in the southern Central Andes. Based on daily gauge time series and ERA-Interim reanalysis, we made the following three key observations: (1) for the period 1940–2016 daily discharge exhibits more pronounced variability in the southern, semi-arid than in the northern, humid catchments. This is due to a smaller ratio of discharge magnitudes between intermediate (0.2 year return period) and rare events (20 year return period) in the semi-arid compared to the humid areas; (2) The climatological composites of the 40 largest discharge events showed characteristic atmospheric features of cold surges based on 5-day time-lagged sequences of geopotential height at different levels in the troposphere; (3) A subjective classification revealed that 80% of the 40 largest discharge events are mainly associated with the north-northeastward migration of frontal systems and 2/3 of these are cold fronts, i.e. cold surges. This work highlights the importance of cold surges and their related atmospheric processes for the generation of heavy rainfall events and floods in the southern Central Andes.

Characteristics of Precipitating Convective Systems in the Premonsoon Season of South Asia

2011 ◽  
Vol 12 (2) ◽  
pp. 157-180 ◽  
Author(s):  
Ulrike Romatschke ◽  
Robert A. Houze
Keyword(s):  
South Asia ◽  
Tropical Rainfall Measuring Mission ◽  
Maximum Size ◽  
Early Morning ◽  
Mountain Ranges ◽  
Convective Systems ◽  
Diurnal Cycles ◽  
Synoptic Forcing ◽  
Trmm Precipitation ◽  
Downslope Flow

Abstract Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data obtained over South Asia during eight premonsoon seasons (March–May) show that the precipitation is more convective in nature and more sensitive to synoptic forcing than during the monsoon. Over land areas, most rain falls from medium-sized systems (8500–35 000 km2 in horizontal area). In continental regions near the Himalayas, these medium-sized systems are favored by 500-mb trough conditions and are of two main types: 1) systems triggered by daytime heating over high terrain and growing to reach maximum size a few hours later and 2) systems triggered at night, as moist upstream flow is lifted over cold downslope flow from the mountains, and reaching maximum development upstream of the central and eastern Himalayas in the early morning hours. Systems triggered by similar mechanisms also account for the precipitation maxima in mountainous coastal regions, where the diurnal cycles are dominated by systems triggered in daytime over the higher coastal terrain. Medium-sized nocturnal systems are also found upstream of coastal mountain ranges. West-coastal precipitation systems over India and Myanmar are favored when low pressure systems occur over the upstream oceans, whereas Indian east-coastal systems occur when high pressure dominates over Bangladesh. Over the Bay of Bengal, the dominant systems are larger (>35 000 km2), and have large stratiform components. They occur in connection with depressions over the Bay and exhibit a weaker diurnal cycle.

scholarly journals Intra-seasonal variation of surface air temperature in Nepal Himalayas

MAUSAM ◽  
2022 ◽  
Vol 53 (3) ◽  
pp. 281-288
Author(s):  
KENICHI UENO ◽  
ADARSHA P. POKHREL
Keyword(s):  
Seasonal Variation ◽  
Air Temperature ◽  
Monsoon Season ◽  
Surface Air Temperature ◽  
Circulation Pattern ◽  
Synoptic Scale ◽  
Local Circulation ◽  
Pressure System ◽  
Surface Temperature Variation ◽  
Unique Surface

Intra-seasonal variation of surface air temperature observed by the automatic weather station at Syangpoche in Khumbu region, Nepal Himalayas, is analyzed.  In the monsoon season, temperature was nearly constant with large decrease in insolation due to monsoon clouds.  On the other hand, large intra-seasonal variation existed in the winter with increase in temperature associated with passing synoptic scale high-pressure system which disturb local circulation pattern as well as decrease in temperature due to the nighttime strong radiative cooling under the condition of snow covers.  Monsoon clouds and deep valley system caused unique surface temperature variation.

scholarly journals A Synoptic Scale Perspective on Greenland Ice Core δ18O Variability and Related Teleconnection Patterns

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 294
Author(s):  
Norel Rimbu ◽  
Monica Ionita ◽  
Gerrit Lohmann
Keyword(s):  
Ice Core ◽  
Ice Cores ◽  
Synoptic Scale ◽  
Local Climate ◽  
Rossby Wave Breaking ◽  
Weather Patterns ◽  
Teleconnection Patterns ◽  
Climate Anomalies ◽  
The North ◽  
Oxygen Isotope Ratios

The variability of stable oxygen isotope ratios (δ18O) from Greenland ice cores is commonly linked to changes in local climate and associated teleconnection patterns. In this respect, in this study we investigate ice core δ18O variability from a synoptic scale perspective to assess the potential of such records as proxies for extreme climate variability and associated weather patterns. We show that positive (negative) δ18O anomalies in three southern and central Greenland ice cores are associated with relatively high (low) Rossby Wave Breaking (RWB) activity in the North Atlantic region. Both cyclonic and anticyclonic RWB patterns associated with high δ18O show filaments of strong moisture transport from the Atlantic Ocean towards Greenland. During such events, warm and wet conditions are recorded over southern, western and central part of Greenland. In the same time the cyclonic and anticyclonic RWB patterns show enhanced southward advection of cold polar air masses on their eastern side, leading to extreme cold conditions over Europe. The association between high δ18O winters in Greenland ice cores and extremely cold winters over Europe is partly explained by the modulation of the RWB frequency by the tropical Atlantic sea surface temperature forcing, as shown in recent modeling studies. We argue that δ18O from Greenland ice cores can be used as a proxy for RWB activity in the Atlantic European region and associated extreme weather and climate anomalies.

scholarly journals The Combined Effects of SST and the North Atlantic Subtropical High-Pressure System on the Atlantic Basin Tropical Cyclone Interannual Variability

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 329
Author(s):  
Albenis Pérez-Alarcón ◽  
José C. Fernández-Alvarez ◽  
Rogert Sorí ◽  
Raquel Nieto ◽  
Luis Gimeno
Keyword(s):  
High Pressure ◽  
Interannual Variability ◽  
Central America ◽  
North Atlantic ◽  
The West ◽  
The Bahamas ◽  
Pressure System ◽  
North Atlantic Subtropical High ◽  
The North ◽  
The North Atlantic

The combined effect of the sea surface temperature (SST) and the North Atlantic subtropical high-pressure system (NASH) in the interannual variability of the genesis of tropical cyclones (TCs) and landfalling in the period 1980–2019 is explored in this study. The SST was extracted from the Centennial Time Scale dataset from the National Oceanic and Atmospheric Administration (NOAA), and TC records were obtained from the Atlantic Hurricane Database of the NOAA/National Hurricane Center. The genesis and landfalling regions were objectively clustered for this analysis. Seven regions of TC genesis and five for landfalling were identified. Intercluster differences were observed in the monthly frequency distribution and annual variability, both for genesis and landfalling. From the generalized least square multiple regression model, SST and NASH (intensity and position) covariates can explain 22.7% of the variance of the frequency of TC genesis, but it is only statistically significant (p < 0.1) for the NASH center latitude. The SST mostly modulates the frequency of TCs formed near the West African coast, and the NASH latitudinal variation affects those originated in the Lesser Antilles arc. For landfalling, both covariates explain 38.7% of the variance; however, significant differences are observed in the comparison between each region. With a statistical significance higher than 90%, SST and NASH explain 33.4% of the landfalling variability in the archipelago of the Bahamas and central–eastern region of Cuba. Besides, landfalls in the Gulf of Mexico and Central America seem to be modulated by SST. It was also found there was no statistically significant relationship between the frequency of genesis and landfalling with the NASH intensity. However, the NASH structure modulates the probability density of the TCs trajectory that make landfall once or several times in their lifetime. Thus, the NASH variability throughout a hurricane season affects the TCs trajectory in the North Atlantic basin. Moreover, we found that the landfalling frequency of TCs formed near the West Africa coast and the central North Atlantic is relatively low. Furthermore, the SST and NASH longitude center explains 31.6% (p < 0.05) of the variance of the landfalling intensity in the archipelago of the Bahamas, while the SST explains 26.4% (p < 0.05) in Central America. Furthermore, the 5-year moving average filter revealed decadal and multidecadal variability in both genesis and landfalling by region. Our findings confirm the complexity of the atmospheric processes involved in the TC genesis and landfalling.

scholarly journals Time-Delay Identification Using Multiscale Ordinal Quantifiers

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 969
Author(s):  
Miguel C. Soriano ◽  
Luciano Zunino
Keyword(s):  
Time Series ◽  
Time Delay ◽  
Real World ◽  
Propagation Speed ◽  
Real World Data ◽  
External Observer ◽  
The North ◽  
Weather Phenomenon ◽  
The North Atlantic Oscillation ◽  
Finite Propagation Speed

Time-delayed interactions naturally appear in a multitude of real-world systems due to the finite propagation speed of physical quantities. Often, the time scales of the interactions are unknown to an external observer and need to be inferred from time series of observed data. We explore, in this work, the properties of several ordinal-based quantifiers for the identification of time-delays from time series. To that end, we generate artificial time series of stochastic and deterministic time-delay models. We find that the presence of a nonlinearity in the generating model has consequences for the distribution of ordinal patterns and, consequently, on the delay-identification qualities of the quantifiers. Here, we put forward a novel ordinal-based quantifier that is particularly sensitive to nonlinearities in the generating model and compare it with previously-defined quantifiers. We conclude from our analysis on artificially generated data that the proper identification of the presence of a time-delay and its precise value from time series benefits from the complementary use of ordinal-based quantifiers and the standard autocorrelation function. We further validate these tools with a practical example on real-world data originating from the North Atlantic Oscillation weather phenomenon.

scholarly journals Climatology and Meteorological Evolution of Major Wildfire Events over the Northeast United States

2013 ◽  
Vol 28 (1) ◽  
pp. 175-193 ◽  
Author(s):  
Joseph B. Pollina ◽  
Brian A. Colle ◽  
Joseph J. Charney
Keyword(s):  
United States ◽  
Coastal Plain ◽  
Large Scale ◽  
Trajectory Analysis ◽  
Synoptic Pattern ◽  
Pressure System ◽  
Northeast United States ◽  
The North ◽  
North American Regional Reanalysis ◽  
Regional Reanalysis

Abstract This study presents a spatial and temporal climatology of major wildfire events, defined as &gt;100 acres burned (&gt;40.47 ha, where 1 ha = 2.47 acre), in the northeast United States from 1999 to 2009 and the meteorological conditions associated with these events. The northeast United States is divided into two regions: region 1 is centered over the higher terrain of the northeast United States and region 2 is primarily over the coastal plain. About 59% of all wildfire events in these two regions occur in April and May, with ~76% in region 1 and ~53% in region 2. There is large interannual variability in wildfire frequency, with some years having 4–5 times more fire events than other years. The synoptic flow patterns associated with northeast United States wildfires are classified using the North American Regional Reanalysis. The most common synoptic pattern for region 1 is a surface high pressure system centered over the northern Appalachians, which occurred in approximately 46% of all events. For region 2, the prehigh anticyclone type extending from southeast Canada and the Great Lakes to the northeast United States is the most common pattern, occurring in about 46% of all events. A trajectory analysis highlights the influence of large-scale subsidence and decreasing relative humidity during the events, with the prehigh pattern showing the strongest subsidence and downslope drying in the lee of the Appalachians.

Cloud Properties over the North Slope of Alaska: Identifying the Prevailing Meteorological Regimes

2012 ◽  
Vol 25 (23) ◽  
pp. 8238-8258 ◽  
Author(s):  
Johannes Mülmenstädt ◽  
Dan Lubin ◽  
Lynn M. Russell ◽  
Andrew M. Vogelmann
Keyword(s):  
Time Series ◽  
Climate Model ◽  
North Slope ◽  
Test Cases ◽  
Synoptic Scale ◽  
Long Time Series ◽  
The North ◽  
Cloud Properties ◽  
North Slope Of Alaska ◽  
Long Time

Abstract Long time series of Arctic atmospheric measurements are assembled into meteorological categories that can serve as test cases for climate model evaluation. The meteorological categories are established by applying an objective k-means clustering algorithm to 11 years of standard surface-meteorological observations collected from 1 January 2000 to 31 December 2010 at the North Slope of Alaska (NSA) site of the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM). Four meteorological categories emerge. These meteorological categories constitute the first classification by meteorological regime of a long time series of Arctic meteorological conditions. The synoptic-scale patterns associated with each category, which include well-known synoptic features such as the Aleutian low and Beaufort Sea high, are used to explain the conditions at the NSA site. Cloud properties, which are not used as inputs to the k-means clustering, are found to differ significantly between the regimes and are also well explained by the synoptic-scale influences in each regime. Since the data available at the ARM NSA site include a wealth of cloud observations, this classification is well suited for model–observation comparison studies. Each category comprises an ensemble of test cases covering a representative range in variables describing atmospheric structure, moisture content, and cloud properties. This classification is offered as a complement to standard case-study evaluation of climate model parameterizations, in which models are compared against limited realizations of the Earth–atmosphere system (e.g., from detailed aircraft measurements).

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