scholarly journals Atmospheric Teleconnection-Based Extreme Drought Prediction in the Core Drought Region in China

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 232 ◽  
Author(s):  
Qinggang Gao ◽  
Jong-Suk Kim ◽  
Jie Chen ◽  
Hua Chen ◽  
Joo-Heon Lee
Keyword(s):  
Large Scale ◽  
Principal Component ◽  
Predictive Performance ◽  
Kendall Test ◽  
Mitigation Measures ◽  
Coefficient Of Determination ◽  
Atmospheric Teleconnection ◽  
Teleconnection Patterns ◽  
Drought Prediction ◽  
Quartile Group

This paper aims to improve the predictability of extreme droughts in China by identifying their relationship with atmospheric teleconnection patterns (ATPs). Firstly, a core drought region (CDR) is defined based on historical drought analysis to investigate possible prediction methods. Through the investigation of the spatial-temporal characteristics of spring drought using a modified Mann–Kendall test, the CDR is found to be under a decadal drying trend. Using principal component analysis, four principal components (PCs), which explain 97% of the total variance, are chosen out of eight teleconnection indices. The tree-based model reveals that PC1 and PC2 can be divided into three groups, in which extreme spring drought (ESD) frequency differs significantly. The results of Poisson regression on ESD and PCs showed good predictive performance with R-squared value larger than 0.8. Furthermore, the results of applying the neural networks for PCs showed a significant improvement in the issue of under-estimation of the upper quartile group in ESD, with a high coefficient of determination of 0.91. This study identified PCs of large-scale ATPs that are candidate parameters for ESD prediction in the CDR. We expect that our findings can be helpful in undertaking mitigation measures for ESD in China.

Influence of Atmospheric Teleconnections on Interannual Variability of Boreal Fires

2020 ◽  
Author(s):  
Zhiyi Zhao ◽  
Zhongda Lin ◽  
Fang Li
Keyword(s):  
Interannual Variability ◽  
Large Scale ◽  
Driving Forces ◽  
Southern Oscillation ◽  
Burned Area ◽  
East Atlantic ◽  
Local Climate ◽  
Atmospheric Teleconnection ◽  
Teleconnection Patterns ◽  
Global Carbon

<p>Wildfires are common in boreal forests around the world and strongly affect regional ecosystem processes and global carbon cycle. Previous studies have suggested that local climate is a dominant driver of boreal fires. However, the impacts of large-scale atmospheric teleconnection patterns on boreal fires and related physical processes remain largely unclear. This study investigates the influence of nine leading atmospheric teleconnection modes and El Niño-Southern Oscillation (ENSO) on the interannual variability of simultaneous summer fires in the boreal regions based on 1997-2015 GFED4s burned area, NCEP/NCAR atmospheric reanalysis, and HadISST sea surface temperature. Results show that ENSO has only a weak effect on boreal fires, distinct from its robust influence on the tropical fires. Instead, the interannual variability of burned area in the boreal regions is significantly regulated by five teleconnection patterns. Specifically, East Pacific-North Pacific (EP/NP) and East Atlantic/West Russia (EA/WR) patterns affect the burned area in North America, North Atlantic Oscillation (NAO) and East Atlantic (EA) patterns for Asia, and the Pacific-North American (PNA) pattern for Europe. Related to the teleconnections, the larger burned area is attributable to warmer surface by an anomalous high-pressure above and drier surface due to less moisture transport from the neighboring oceans. The results improve our understanding of driving forces of interannual variability of boreal fires and then regional and global carbon budgets.</p>

Baroclinic and Barotropic Annular Variability in the Northern Hemisphere

2015 ◽  
Vol 72 (3) ◽  
pp. 1117-1136 ◽  
Author(s):  
David W. J. Thompson ◽  
Ying Li
Keyword(s):  
Time Series ◽  
Kinetic Energy ◽  
Northern Hemisphere ◽  
Large Scale ◽  
Spectral Power ◽  
Principal Component ◽  
Eddy Kinetic Energy ◽  
Annular Mode ◽  
Teleconnection Patterns ◽  
Mean Kinetic Energy

Abstract Large-scale variability in the Northern Hemisphere (NH) circulation can be viewed in the context of three primary types of structures: 1) teleconnection patterns, 2) a barotropic annular mode, and 3) a baroclinic annular mode. The barotropic annular mode corresponds to the northern annular mode (NAM) and has been examined extensively in previous research. Here the authors examine the spatial structure and time-dependent behavior of the NH baroclinic annular mode (NBAM). The NAM and NBAM have very different signatures in large-scale NH climate variability. The NAM emerges as the leading principal component (PC) time series of the zonal-mean kinetic energy. It dominates the variance in the wave fluxes of momentum, projects weakly onto the eddy kinetic energy and wave fluxes of heat, and can be modeled as Gaussian red noise with a time scale of ~10 days. In contrast, the NBAM emerges as the leading PC time series of the eddy kinetic energy. It is most clearly identified when the planetary-scale waves are filtered from the data, dominates the variance in the synoptic-scale eddy kinetic energy and wave fluxes of heat, and has a relatively weak signature in the zonal-mean kinetic energy and the wave fluxes of momentum. The NBAM is marked by weak but significant enhanced spectral power on time scales of ~20–25 days. The NBAM is remarkably similar to its Southern Hemisphere counterpart despite the pronounced interhemispheric differences in orography and land–sea contrasts.

scholarly journals Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

2017 ◽  
Author(s):  
Eric Mortensen ◽  
Shu Wu ◽  
Michael Notaro ◽  
Steven Vavrus ◽  
Rob Montgomery ◽  
...  
Keyword(s):  
El Niño ◽  
Large Scale ◽  
El Nino ◽  
Southern Oscillation ◽  
Local Level ◽  
Principal Component ◽  
Spatiotemporal Variability ◽  
Climate Indices ◽  
Southern Peru ◽  
Drought Prediction

Abstract. Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semi-arid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal drought. Droughts here are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region’s hydrologic cycle. An extensive season-ahead drought prediction model is developed to help bolster existing capacity of stakeholders to plan for and mitigate the deleterious impacts of this hydrologic extreme. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to eleven potential predictors to produce an ensemble forecast of January-March precipitation. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. Extending the lead time and spatially disaggregating precipitation predictions to the local level may further assist regional stakeholders and policymakers preparing for drought.

scholarly journals A conceptual prediction model of seasonal drought processes using atmospheric and oceanic Standardized Anomalies: application in four recent severe drought events in China

2017 ◽  
Author(s):  
Zhenchen Liu ◽  
Guihua Lu ◽  
Hai He ◽  
Zhiyong Wu ◽  
Jian He
Keyword(s):  
Prediction Model ◽  
Water Resource Management ◽  
Large Scale ◽  
Mitigation Measures ◽  
Drought Severity ◽  
Severe Drought ◽  
Climate Forecast ◽  
Simple Method ◽  
Seasonal Drought ◽  
Drought Prediction

Abstract. Reliable drought prediction is fundamental for end water managers to develop and implement drought mitigation measures. Considering the idea that drought development is closely related to the spatial-temporal evolution of large-scale circulation patterns, we develop a conceptual prediction model of seasonal drought processes based on atmospheric/oceanic Standardized Anomalies (SA). Empirical Orthogonal Function (EOF) analysis was firstly applied to drought-related SA of 200 hPa/500 hPa geo-potential height (HGT) and sea surface temperature (SST), respectively. Subsequently, SA-based predictors were built based on the spatial configuration of the first EOF modes. This drought prediction model is essentially the synchronous statistical relationship between 90-day-accumulated atmospheric/oceanic SA-based predictors and 3-month SPI (SPI3), calibrated by the simple method of stepwise regression. It is forced by seasonal climate forecast models like the NCEP Climate Forecast System Version 2 (CFSv2). It can make seamless drought prediction for operational use after being calibrated year-by-year. Model application during four recent severe drought events in China indicates its good performance at predicting seasonal drought development, despite its weakness in predicting drought severity. Therefore, it can provide some valuable information and is a worthy reference for seasonal water resource management.

scholarly journals Remote Sensing of Local Warming Trend in Alberta, Canada during 2001–2020, and Its Relationship with Large-Scale Atmospheric Circulations

2021 ◽  
Vol 13 (17) ◽  
pp. 3441
Author(s):  
Quazi K. Hassan ◽  
Ifeanyi R. Ejiagha ◽  
M. Razu Ahmed ◽  
Anil Gupta ◽  
Elena Rangelova ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Correlation Analysis ◽  
Large Scale ◽  
Kendall Test ◽  
Warming Trend ◽  
Small Magnitude ◽  
Teleconnection Patterns ◽  
Local Warming ◽  
Slope Estimator ◽  
Time Series Images

Here, the objective was to study the local warming trend and its driving factors in the natural subregions of Alberta using a remote-sensing approach. We applied the Mann–Kendall test and Sen’s slope estimator on the day and nighttime MODIS LST time-series images to map and quantify the extent and magnitude of monthly and annual warming trends in the 21 natural subregions of Alberta. We also performed a correlation analysis of LST anomalies (both day and nighttime) of the subregions with the anomalies of the teleconnection patterns, i.e., Pacific North American (PNA), Pacific decadal oscillation (PDO), Arctic oscillation (AO), and sea surface temperature (SST, Niño 3.4 region) indices, to identify the relationship. May was the month that showed the most significant warming trends for both day and night during 2001–2020 in most of the subregions in the Rocky Mountains and Boreal Forest. Subregions of Grassland and Parkland in southern and southeastern parts of Alberta showed trends of cooling during daytime in July and August and a small magnitude of warming in June and August at night. We also found a significant cooling trend in November for both day and night. We identified from the correlation analysis that the PNA pattern had the most influence in the subregions during February to April and October to December for 2001–2020; however, none of the atmospheric oscillations showed any significant relationship with the significant warming/cooling months.

scholarly journals Content-Based Estimation of Brain MRI Tilt in Three Orthogonal Directions

2021 ◽  
Author(s):  
Pooja Prabhu ◽  
A. K. Karunakar ◽  
Sanjib Sinha ◽  
N. Mariyappa ◽  
G. K. Bhargava ◽  
...  
Keyword(s):  
Large Scale ◽  
Brain Mri ◽  
Similarity Measures ◽  
Principal Component ◽  
Brain Anatomy ◽  
Morphological Operations ◽  
Mr Images ◽  
Tilt Correction ◽  
Brain Mr Images ◽  
The Brain

AbstractIn a general scenario, the brain images acquired from magnetic resonance imaging (MRI) may experience tilt, distorting brain MR images. The tilt experienced by the brain MR images may result in misalignment during image registration for medical applications. Manually correcting (or estimating) the tilt on a large scale is time-consuming, expensive, and needs brain anatomy expertise. Thus, there is a need for an automatic way of performing tilt correction in three orthogonal directions (X, Y, Z). The proposed work aims to correct the tilt automatically by measuring the pitch angle, yaw angle, and roll angle in X-axis, Z-axis, and Y-axis, respectively. For correction of the tilt around the Z-axis (pointing to the superior direction), image processing techniques, principal component analysis, and similarity measures are used. Also, for correction of the tilt around the X-axis (pointing to the right direction), morphological operations, and tilt correction around the Y-axis (pointing to the anterior direction), orthogonal regression is used. The proposed approach was applied to adjust the tilt observed in the T1- and T2-weighted MR images. The simulation study with the proposed algorithm yielded an error of 0.40 ± 0.09°, and it outperformed the other existing studies. The tilt angle (in degrees) obtained is ranged from 6.2 ± 3.94, 2.35 ± 2.61, and 5 ± 4.36 in X-, Z-, and Y-directions, respectively, by using the proposed algorithm. The proposed work corrects the tilt more accurately and robustly when compared with existing studies.

scholarly journals Principal component analysis tomography in near-infrared integral field spectroscopy of young stellar objects – I. Revisiting the high-mass protostar W33A

2021 ◽  
Vol 503 (1) ◽  
pp. 270-291
Author(s):  
F Navarete ◽  
A Damineli ◽  
J E Steiner ◽  
R D Blum
Keyword(s):  
Large Scale ◽  
Near Infrared ◽  
Rotation Axis ◽  
Principal Component ◽  
Young Stellar Objects ◽  
High Mass ◽  
Continuum Emission ◽  
Rotating Disc ◽  
Stellar Objects ◽  
K Band

ABSTRACT W33A is a well-known example of a high-mass young stellar object showing evidence of a circumstellar disc. We revisited the K-band NIFS/Gemini North observations of the W33A protostar using principal components analysis tomography and additional post-processing routines. Our results indicate the presence of a compact rotating disc based on the kinematics of the CO absorption features. The position–velocity diagram shows that the disc exhibits a rotation curve with velocities that rapidly decrease for radii larger than 0.1 arcsec (∼250 au) from the central source, suggesting a structure about four times more compact than previously reported. We derived a dynamical mass of 10.0$^{+4.1}_{-2.2}$ $\rm {M}_\odot$ for the ‘disc + protostar’ system, about ∼33 per cent smaller than previously reported, but still compatible with high-mass protostar status. A relatively compact H2 wind was identified at the base of the large-scale outflow of W33A, with a mean visual extinction of ∼63 mag. By taking advantage of supplementary near-infrared maps, we identified at least two other point-like objects driving extended structures in the vicinity of W33A, suggesting that multiple active protostars are located within the cloud. The closest object (Source B) was also identified in the NIFS field of view as a faint point-like object at a projected distance of ∼7000 au from W33A, powering extended K-band continuum emission detected in the same field. Another source (Source C) is driving a bipolar $\rm {H}_2$ jet aligned perpendicular to the rotation axis of W33A.

scholarly journals Identification of Efficient Sampling Techniques for Probabilistic Voltage Stability Analysis of Renewable-Rich Power Systems

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2328
Author(s):  
Mohammed Alzubaidi ◽  
Kazi N. Hasan ◽  
Lasantha Meegahapola ◽  
Mir Toufikur Rahman
Keyword(s):  
Monte Carlo ◽  
Stability Analysis ◽  
Power Systems ◽  
Large Scale ◽  
Voltage Stability ◽  
Sampling Technique ◽  
Coefficient Of Determination ◽  
Sampling Techniques ◽  
Quasi Monte Carlo ◽  
Efficient Sampling

This paper presents a comparative analysis of six sampling techniques to identify an efficient and accurate sampling technique to be applied to probabilistic voltage stability assessment in large-scale power systems. In this study, six different sampling techniques are investigated and compared to each other in terms of their accuracy and efficiency, including Monte Carlo (MC), three versions of Quasi-Monte Carlo (QMC), i.e., Sobol, Halton, and Latin Hypercube, Markov Chain MC (MCMC), and importance sampling (IS) technique, to evaluate their suitability for application with probabilistic voltage stability analysis in large-scale uncertain power systems. The coefficient of determination (R2) and root mean square error (RMSE) are calculated to measure the accuracy and the efficiency of the sampling techniques compared to each other. All the six sampling techniques provide more than 99% accuracy by producing a large number of wind speed random samples (8760 samples). In terms of efficiency, on the other hand, the three versions of QMC are the most efficient sampling techniques, providing more than 96% accuracy with only a small number of generated samples (150 samples) compared to other techniques.

scholarly journals Farmers’ Perceptions of Commercial Insect-Based Feed for Sustainable Livestock Production in Kenya

2021 ◽  
Vol 13 (10) ◽  
pp. 5359
Author(s):  
Afrika Onguko Okello ◽  
Jonathan Makau Nzuma ◽  
David Jakinda Otieno ◽  
Michael Kidoido ◽  
Chrysantus Mbi Tanga
Keyword(s):  
Food Systems ◽  
Large Scale ◽  
Principal Component ◽  
Farm Income ◽  
Purchase Decisions ◽  
Wealth Status ◽  
Feed Formulation ◽  
Alternative Protein ◽  
Livestock Products ◽  
The Impact

The utilization of insect-based feeds (IBF) as an alternative protein source is increasingly gaining momentum worldwide owing to recent concerns over the impact of food systems on the environment. However, its large-scale adoption will depend on farmers’ acceptance of its key qualities. This study evaluates farmer’s perceptions of commercial IBF products and assesses the factors that would influence its adoption. It employs principal component analysis (PCA) to develop perception indices that are subsequently used in multiple regression analysis of survey data collected from a sample of 310 farmers. Over 90% of the farmers were ready and willing to use IBF. The PCA identified feed performance, social acceptability of the use of insects in feed formulation, feed versatility and marketability of livestock products reared on IBF as the key attributes that would inform farmers’ purchase decisions. Awareness of IBF attributes, group membership, off-farm income, wealth status and education significantly influenced farmers’ perceptions of IBF. Interventions such as experimental demonstrations that increase farmers’ technical knowledge on the productivity of livestock fed on IBF are crucial to reducing farmers’ uncertainties towards acceptability of IBF. Public partnerships with resource-endowed farmers and farmer groups are recommended to improve knowledge sharing on IBF.

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