scholarly journals Modes of vertical thermodynamic and wind variability over the Maritime Continent

2017 ◽  
Vol 17 (7) ◽  
pp. 4611-4626 ◽  
Author(s):  
Jennie Bukowski ◽  
Derek J. Posselt ◽  
Jeffrey S. Reid ◽  
Samuel A. Atwood
Keyword(s):  
Temporal Variability ◽  
Large Scale ◽  
Cloud Model ◽  
Principal Component ◽  
Structure Functions ◽  
Radiosonde Data ◽  
Spatial And Temporal Variability ◽  
Maritime Continent ◽  
Convective Systems ◽  
Wind Variability

Abstract. The Maritime Continent (MC) is an exceedingly complex region from the perspective of both its meteorology and its aerosol characteristics. Convection in the MC is ubiquitous and assumes a wide variety of forms under the influence of an evolving large-scale dynamic and thermodynamic context. Understanding the interaction between convective systems and their environment, both individually and in the aggregate, requires knowledge of the dominant patterns of spatial and temporal variability. Ongoing cloud model ensemble studies require realistic perturbations to the atmospheric thermodynamic state to devise system sensitivities. Apart from modeling studies, evanescent signals in the tropical system are obscured by the underlying broad-scale meteorological variability, which if constrained could illuminate fine-scale physical processes. To this end, radiosonde observations from 2008 to 2016 are examined from three upper-air sounding sites within the MC for the purpose of exploring the dominant vertical temperature, humidity, and wind structures in the region. Principal component analysis is applied to the vertical atmospheric column to transform patterns present in radiosonde data into canonical thermodynamic and wind profiles for the MC. Both rotated and non-rotated principal components are considered, and the emerging structure functions reflect the fundamental vertical modes of short-term tropical variability. The results indicate that while there is tremendous spatial and temporal variability across the MC, the primary modes of vertical thermodynamic and wind variability in the region can be represented in a lower-dimensional subspace. In addition, the vertical structures are very similar among different sites around the region, though different structures may manifest more strongly at one location than another. The results indicate that, while different meteorology may be found in various parts of the MC at any given time, the processes themselves are remarkably consistent. The ability to represent this variability using a limited number of structure functions facilitates analysis of covariability between atmospheric structure and convective systems and also enables future systematic model-based ensemble analysis of cloud development, convection, and precipitation over the MC.

scholarly journals Modes of Vertical Thermodynamic and Wind Variability over the Maritime Continent

2016 ◽  
Author(s):  
Jennie Bukowski ◽  
Derek J. Posselt ◽  
Jeffrey S. Reid ◽  
Samuel A. Atwood
Keyword(s):  
Temporal Variability ◽  
Large Scale ◽  
Principal Component ◽  
Structure Functions ◽  
Dimensional Subspace ◽  
Radiosonde Data ◽  
Spatial And Temporal Variability ◽  
Convective Systems ◽  
Wind Variability ◽  
Wind Profiles

Abstract. The Maritime Content (MC) is an exceedingly complex region, both from the perspective of its meteorology and its aerosol characteristics. Convection in the MC is ubiquitous, and assumes a wide variety of forms under the influence of an evolving large scale dynamic and thermodynamic context. Understanding the interaction between convective systems and their environment, both individually and in the aggregate, requires knowledge of the dominant patterns of spatial and temporal variability. To this end, radiosonde observations from 2008–2016 are examined from three sounding release sites within the MC for the purpose of exploring the dominant vertical temperature, humidity, and wind structures in the region. Principal Component Analysis is applied to the vertical atmospheric column to transform patterns present in radiosonde data into canonical thermodynamic and wind profiles for the MC. Both rotated and non-rotated principal components are considered, and the emerging structure functions reflect the fundamental vertical modes of short-term tropical variability. The results indicate that while there is tremendous spatial and temporal variability across the MC, the primary modes of vertical thermodynamic and wind variability in the region can be represented in a lower-dimensional subspace. In addition, the vertical structures are very similar among different sites around the region, though different structures may manifest more strongly at one location than another. The results indicate that, while very different meteorology may be found in various parts of the MC at any given time, the processes themselves are remarkably consistent. The ability to represent this variability using a limited number of structure functions facilitates analysis of co-variability between atmospheric structure and convective systems, and also enables future systematic model-based ensemble analysis of cloud development, convection, and precipitation over the MC.

scholarly journals On the origin of variable structures in the winds of hot luminous stars

2013 ◽  
Vol 440 (1) ◽  
pp. 2-9 ◽  
Author(s):  
Yannick J. L. Michaux ◽  
Anthony F. J. Moffat ◽  
André-Nicolas Chené ◽  
Nicole St-Louis
Keyword(s):  
Magnetic Field ◽  
Empirical Evidence ◽  
Temporal Variability ◽  
Large Scale ◽  
Small Scale ◽  
Ionization Zone ◽  
Corotating Interaction Regions ◽  
Wind Variability ◽  
Global Magnetic Field ◽  
Interaction Regions

Abstract Examination of the temporal variability properties of several strong optical recombination lines in a large sample of Galactic Wolf–Rayet (WR) stars reveals possible trends, especially in the more homogeneous WC than the diverse WN subtypes, of increasing wind variability with cooler subtypes. This could imply that a serious contender for the driver of the variations is stochastic, magnetic subsurface convection associated with the 170 kK partial-ionization zone of iron, which should occupy a deeper and larger zone of greater mass in cooler WR subtypes. This empirical evidence suggests that the heretofore proposed ubiquitous driver of wind variability, radiative instabilities, may not be the only mechanism playing a role in the stochastic multiple small-scaled structures seen in the winds of hot luminous stars. In addition to small-scale stochastic behaviour, subsurface convection guided by a global magnetic field with localized emerging loops may also be at the origin of the large-scale corotating interaction regions as seen frequently in O stars and occasionally in the winds of their descendant WR stars.

Spatial and temporal variability of East African Kiremt season precipitation and large‐scale teleconnections

2019 ◽  
Vol 40 (2) ◽  
pp. 1241-1254 ◽  
Author(s):  
Daniel Broman ◽  
Balaji Rajagopalan ◽  
Thomas Hopson ◽  
Mekonnen Gebremichael
Keyword(s):  
Temporal Variability ◽  
Large Scale ◽  
Spatial And Temporal Variability ◽  
East African

Large-Scale Atmospheric Drivers of Snowfall on Thwaites Glacier

2020 ◽  
Author(s):  
Michelle Maclennan ◽  
Jan Lenaerts
Keyword(s):  
Temporal Variability ◽  
Large Scale ◽  
Climate Model ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Southern Annular Mode ◽  
Spatial And Temporal Variability ◽  
Atmospheric Conditions ◽  
Amundsen Sea ◽  
Weather Patterns

<p>High snowfall events on Thwaites Glacier are a key influencer of its ice mass change. In this study, we diagnose the mechanisms for orographic precipitation on Thwaites Glacier by analyzing the atmospheric conditions that lead to high snowfall events. A high-resolution regional climate model, RACMO2, is used in conjunction with MERRA-2 and ERA5 reanalysis to map snowfall and associated atmospheric conditions over the Amundsen Sea Embayment. We examine these conditions during high snowfall events over Thwaites Glacier to characterize the drivers of the precipitation and their spatial and temporal variability. Then we examine the seasonal differences in the associated weather patterns and their correlations with El Nino Southern Oscillation and the Southern Annular Mode. Understanding the large-scale atmospheric drivers of snowfall events allows us to recognize how these atmospheric drivers and consequent snowfall climatology will change in the future, which will ultimately improve predictions of accumulation on Thwaites Glacier.</p>

scholarly journals Downscaling of GCM-Simulated Precipitation Using Model Output Statistics

2014 ◽  
Vol 27 (1) ◽  
pp. 312-324 ◽  
Author(s):  
Jonathan M. Eden ◽  
Martin Widmann
Keyword(s):  
Statistical Downscaling ◽  
Temporal Variability ◽  
General Circulation ◽  
Large Scale ◽  
Principal Component ◽  
General Circulation Models ◽  
Model Output ◽  
Local Scaling ◽  
Simulated Precipitation ◽  
Model Output Statistics

Abstract Producing reliable estimates of changes in precipitation at local and regional scales remains an important challenge in climate science. Statistical downscaling methods are often utilized to bridge the gap between the coarse resolution of general circulation models (GCMs) and the higher resolutions at which information is required by end users. As the skill of GCM precipitation, particularly in simulating temporal variability, is not fully understood, statistical downscaling typically adopts a perfect prognosis (PP) approach in which high-resolution precipitation projections are based on real-world statistical relationships between large-scale atmospheric predictors and local-scale precipitation. Using a nudged simulation of the ECHAM5 GCM, in which the large-scale weather states are forced toward observations of large-scale circulation and temperature for the period 1958–2001, previous work has shown ECHAM5 skill in simulating temporal variability of precipitation to be high in many parts of the world. Here, the same nudged simulation is used in an alternative downscaling approach, based on model output statistics (MOS), in which statistical corrections are derived for simulated precipitation. Cross-validated MOS corrections based on maximum covariance analysis (MCA) and principal component regression (PCR), in addition to a simple local scaling, are shown to perform strongly throughout much of the extratropics. Correlation between downscaled and observed monthly-mean precipitation is as high as 0.8–0.9 in many parts of Europe, North America, and Australia. For these regions, MOS clearly outperforms PP methods that use temperature and circulation as predictors. The strong performance of MOS makes such an approach to downscaling attractive and potentially applicable to climate change simulations.

scholarly journals Atmospheric stratification over Namibia and the southeast Atlantic Ocean

2021 ◽  
Author(s):  
Danitza Klopper ◽  
Stuart J. Piketh ◽  
Roelof Burger ◽  
Simon Dirkse ◽  
Paola Formenti
Keyword(s):  
Temporal Variability ◽  
Region Of Interest ◽  
Temperature Inversion ◽  
Radiosonde Data ◽  
Spatial And Temporal Variability ◽  
Atmospheric Moisture ◽  
Boundary Layer Height ◽  
Atmospheric Stratification ◽  
Temperature Inversions ◽  
Good Agreement

Abstract. We currently have a limited understanding of the spatial and temporal variability in vertically stratified atmospheric layers over Namibia and the southeast Atlantic (SEA) Ocean. Stratified layers are relevant to the transport and dilution of local and long-range transported atmospheric constituents. This study used eleven years of global positioning system radio occultation (GPS-RO) signal refractivity data (2007–2017) over Namibia and the adjacent ocean surfaces, and three years of radiosonde data from Walvis Bay, Namibia, to study the character and variability in stratified layers. From the GPS-RO data and up to a height of 10 km, we studied the spatial and temporal variability in the point of minimum gradient in refractivity, and the temperature inversion height, depth and strength. We also present the temporal variability of temperature inversions and the boundary layer height (BLH) from radiosondes. The BLH was estimated by the parcel method, the top of a surface-based inversion, the top of a stable layer identified by the bulk Richardson number (RN), and the point of minimum gradient in the refractivity (for comparison with GPS-RO data). A comparison between co-located GPS-RO to radiosonde temperature profiles found good agreement between the two, and an average underestimation of GPS-RO to radiosonde temperatures of −0.45 ± 1.25 °C, with smaller differences further from the surface and with decreasing atmospheric moisture content. The minimum gradient (MG) of refractivity, calculated from these two datasets were generally in good agreement (230 ± 180 m), with an exeption of a few cases when differences exceeded 1000 m. The surface of MG across the region of interest was largely affected by macroscale circulation and changes in atmospheric moisture and cloud, and was not consistent with BLH(RN). We found correlations in the character of low-level inversions with macroscale circulation, radiation interactions with the surface, cloud cover over the ocean and the seasonal maximum in biomass burning over southern Africa. Radiative cooling on diurnal scales also affected elevated inversions between 2.5 and 10 km, with more co-occurring inversions observed at night and in the morning. Elevated inversions formed most frequently over the subcontinent and under subsidence by high-pressure systems in the colder months. Despite this macroscale influence peaking in the winter, the springtime inversions, like those at low levels, were strongest.

scholarly journals Southwest monsoon rainfall in Assam: An application of principal component analysis for understanding of variability

MAUSAM ◽  
2021 ◽  
Vol 68 (2) ◽  
pp. 357-366
Author(s):  
PIJUSH BASAK
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Temporal Variability ◽  
Monsoon Rainfall ◽  
Principal Component ◽  
Component Analysis ◽  
Southwest Monsoon ◽  
The State ◽  
Spatial And Temporal Variability ◽  
Southwest Monsoon Rainfall

The principal component analysis (PCA) is applied to understand the spatial and temporal variability of monsoonal rainfall in the state Assam in India. The Southwest Monsoon (SWM) rainfall data over 12 widely spread stations located over the state has been analyzed for a period of 60 years for understanding variability. A statistically significant trend and a above/below transition signal has been observed for a few stations and the corresponding principal components (PCs). Coherent regions of Northern and Southern Assam have been identified through PCA to bring out the possible significant signals. It is observed that some of PCs for state-wise and coherent regions have positive or negative trend and significant above/below transition.    

scholarly journals Spatial and Temporal Variability in Rainfall Erosivity Under Alpine Climate: A Slovenian Case Study Using Optical Disdrometer Data

2021 ◽  
Vol 9 ◽  
Author(s):  
Nejc Bezak ◽  
Sašo Petan ◽  
Matjaž Mikoš
Keyword(s):  
Temporal Variability ◽  
Large Scale ◽  
Annual Rainfall ◽  
Mean Annual Precipitation ◽  
Rainfall Erosivity ◽  
Spatial And Temporal Variability ◽  
Strongly Correlated ◽  
Erosion Rates ◽  
Precipitation Events

Rainfall erosivity is one of the most important parameters that influence soil erosion rates. It is characterized by a large spatial and temporal variability. For example, in Slovenia, which covers around 20,000 km2, the annual rainfall erosivity ranges from less than 1,000 MJ mm ha−1 h−1 to more than 10,000 MJ mm ha−1 h−1. Drop size distribution (DSD) data are needed to investigate rainfall erosivity characteristics. More than 2 years of DSD measurements using optical disdrometers located at six stations in Slovenia were used to investigate the spatial and temporal variability in rainfall erosivity in Slovenia. Experimental results have indicated that elevation is a poor predictor of rainfall erosivity and that erosivity is more strongly correlated to the mean annual precipitation. Approximately 90% of the total kinetic energy (KE) was accounted for in about 35% of 1 min disdrometer data. The highest 1 min intensities (I) and consequently also KE values were measured in summer followed by autumn and spring. The local KE-I equation yielded an acceptable fit to the measured data in case of all six stations. The relatively large percentage of 1 min rainfall intensities above 5 mm/h can at least partially explain some very high annual rainfall erosivity values (i.e., near or above 10,000 MJ mm ha−1 h−1). Convective and large-scale precipitation events also result in various rainfall erosivity characteristics. The station microlocation and wind impacts in case of some stations yielded relatively large differences between the data measured using the optical disdrometer and the pluviograph. Preliminary conclusions have been gathered, but further measurements are needed to get even better insight into spatial and temporal variability in rainfall erosivity under Alpine climate in Slovenia.

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