Multi-scale Atmospheric CO2 Variabilities over Southern Africa

2020 ◽  
Author(s):  
Boipelo B Thande ◽  
Gizaw Mengistu Tsidu ◽  
Anteneh Getachew Mengistu
Keyword(s):  
Southern Africa ◽  
Anthropogenic Activities ◽  
Statistical Technique ◽  
Ensemble Empirical Mode Decomposition ◽  
Reanalysis Data ◽  
In Situ Data ◽  
Mode Decomposition ◽  
Multi Temporal ◽  
Year 2000

<p>Carbon sinks play an important role in absorbing almost half of the CO<sub>2</sub> emissions emanating from anthropogenic activities. However, regional contributions of atmospheric CO<sub>2</sub> are not well known in Southern Africa. This is partly attributed to a shortage of in-situ data, data gaps, and limitation in the theory in modeling atmospheric CO<sub>2</sub> dynamics. The shortage of in-situ observations and poor model skills have created a need for assimilation of observations into models to assess the variability of atmospheric levels in near real-time globally. <span>In this study, we investigated the variabilities of XCO</span><sub><span>2</span></sub><span> at multi-temporal scales based on reanalysis data from the carbon tracker (CT) assimilation model over Southern Africa from the year 2000 to 2016. The ensemble empirical mode decomposition (EEMD) statistical technique was used to decompose the CO</span><sub><span>2</span></sub><span> time series into signals with different periodicities.</span><span> The results demonstrate that the different component signals are driven by</span><span> atmospheric, surface and oceanic forcings (e.g., rainfall, temperature, soil moisture, and SST)</span><span>.</span></p>

scholarly journals Use of Global Reanalysis Data in the Study of the Aridity Index in the Magdalena-Cauca Macro-Basin, Colombia

10.29007/92l9 ◽  
2018 ◽  
Author(s):  
Carolina Vega-Viviescas ◽  
David A. Zamora ◽  
Erasmo A. Rodríguez
Keyword(s):  
Southern Oscillation ◽  
Pearson Correlation ◽  
Regional Scale ◽  
Correlation Coefficients ◽  
Aridity Index ◽  
Remote Sensing Data ◽  
Reanalysis Data ◽  
In Situ Data ◽  
Global Reanalysis

The Magdalena-Cauca macro-basin (MCMB) in Colombia, by its tropical location, annually experiences the effects of movement of the Intertropical Convergence Zone, and it is highly affected by interannual macro-climatic phenomena, such as El Niño– Southern Oscillation (ENSO). With the aim of increasing the use of global reanalysis and remote sensing data for supporting water management decisions at the watershed scale and within the framework of the eartH2Observe research project, the aridity index (AI) was calculated with three different data sources. Precipitation products and AI results were compared with their corresponding in-situ national official data. The comparison shows high correlations between the AI derived from observed data and AI obtained from the reanalysis, with Pearson correlation coefficients above 0.8 for two of the products investigated. This shows the importance of using global reanalysis data in water availability studies on a regional scale for the MCMB and the potential of this information in others macrobasins in Colombia including the Orinoquia and Amazon regions, where in-situ data is scarce.

scholarly journals An Evaluation of the Parallel Ensemble Empirical Mode Decomposition Method in Revealing the Role of Downscaling Processes Associated with African Easterly Waves in Tropical Cyclone Genesis

2016 ◽  
Vol 33 (8) ◽  
pp. 1611-1628 ◽  
Author(s):  
Yuling Wu ◽  
Bo-Wen Shen
Keyword(s):  
Tropical Cyclone ◽  
Empirical Mode Decomposition ◽  
Ensemble Empirical Mode Decomposition ◽  
Reanalysis Data ◽  
Tropical Cyclone Genesis ◽  
African Easterly Waves ◽  
Horizontal Shear ◽  
Easterly Waves ◽  
Mode Decomposition

AbstractIn this study the parallel ensemble empirical mode decomposition (PEEMD) is applied for an analysis of 10-yr (2004–13) ERA-Interim global reanalysis data in order to explore the role of downscaling processes associated with African easterly waves (AEWs) in tropical cyclone (TC) genesis. The focus of the study was aimed at understanding the downscaling process in multiscale flows during storm intensification. To represent the various length scales of atmospheric systems, intrinsic mode functions (IMFs) were extracted from the reanalysis data using the PEEMD. It was found that the nonoscillatory trend mode can be used to represent large-scale environmental flow and that the third oscillatory mode (IMF3) can be used to represent AEW/TC scale systems. The results 1) identified 42 developing cases from 272 AEWs, where 25 of them eventually developed into hurricanes; 2) indicated that the maximum for horizontal shear largely occurs over the ocean for the IMF3 and over land near the coast for the trend mode for developing cases, suggesting shear transfer between the trend mode and the IMF3; 3) displayed opposite wind shear tendencies for the trend mode and the IMF3 during storm intensification, signifying that the downscaling process was active in 13 hurricane cases along their tracks; and 4) showed that among the 42 developing cases, only 13 of the 25 hurricanes were found to have significant downscaling transfer features, so other processes such as upscaling processes may play an important role in the other developing cases, especially for the remaining 12 hurricane cases. In a future study, the authors intend to investigate the upscaling process between the convection scale and AEWs/TCs, which requires data at a finer grid resolution.

scholarly journals A method for monitoring hydrological conditions beneath herbaceous wetlands using multi-temporal ALOS PALSAR coherence data

2015 ◽  
Vol XL-7/W4 ◽  
pp. 221-226 ◽  
Author(s):  
M. Zhang ◽  
Z. Li ◽  
B. Tian ◽  
J. Zhou ◽  
J. Zeng
Keyword(s):  
Effective Area ◽  
Interferometric Synthetic Aperture Radar ◽  
Alos Palsar ◽  
Hydrological Conditions ◽  
In Situ Data ◽  
Key Indicator ◽  
Multi Temporal ◽  
First Time ◽  
Good Agreement

Reed marshes, the world’s most widespread type of wetland vegetation, are undergoing major changes as a result of climate changes and human activities. The presence or absence of water in reed marshes has a significant impact on the whole ecosystem and remains a key indicator to identify the effective area of a wetland and help estimate the degree of degeneration. Past studies have demonstrated the use of interferometric synthetic aperture radar (InSAR) to map water-level changes for flooded reeds. However, the identification of the different hydrological states of reed marshes is often poorly understood. The analysis given in this paper shows that L-band interferometric coherence is very sensitive to the water surface conditions beneath reed marshes and so can be used as classifier. A method based on a statistical analysis of the coherence distributions for wet and dry reeds using InSAR pairs was, therefore, investigated in this study. The experimental results were validated by in-situ data and showed very good agreement. This is the first time that information about the water cover under herbaceous wetlands has been derived using interferometric coherence values. This method can also effectively and easily be applied to monitor the hydrological conditions beneath other herbaceous wetlands.

Present-Day Atmospheric Simulations Using GISS ModelE: Comparison to In Situ, Satellite, and Reanalysis Data

2006 ◽  
Vol 19 (2) ◽  
pp. 153-192 ◽  
Author(s):  
Gavin A. Schmidt ◽  
Reto Ruedy ◽  
James E. Hansen ◽  
Igor Aleinov ◽  
Nadine Bell ◽  
...  
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Reanalysis Data ◽  
Full Description ◽  
Marine Stratocumulus ◽  
Sea Level Pressure ◽  
In Situ Data ◽  
Basic Physics ◽  
Goddard Institute

Abstract A full description of the ModelE version of the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) and results are presented for present-day climate simulations (ca. 1979). This version is a complete rewrite of previous models incorporating numerous improvements in basic physics, the stratospheric circulation, and forcing fields. Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced. The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere temperatures and winds, cloud heights, precipitation, and sea level pressure. Data–model comparisons continue, however, to highlight persistent problems in the marine stratocumulus regions.

scholarly journals Problems with the retrieval of glacier net surface balance from SAR imagery

2005 ◽  
Vol 42 ◽  
pp. 209-216 ◽  
Author(s):  
Ian A. Brown ◽  
Per Klingbjer ◽  
Andy Dean
Keyword(s):  
Mass Balance ◽  
Glacier Mass Balance ◽  
In Situ Data ◽  
Amplitude Data ◽  
Multi Temporal ◽  
Geophysical Processes ◽  
Sar Imagery ◽  
Arctic Glacier ◽  
Surface Balance

AbstractThere are relatively few comparisons between synthetic aperture radar (SAR) observations and glacier mass-balance measurements. More typically, SAR has been deployed to identify changes in the end-of-summer snowline and other facies boundaries. In this paper, we analyze the geophysical processes affecting SAR amplitude data over two Arctic glacier systems in northern Scandinavia to assess the potential of SAR observations for the retrieval of surface balance parameters. Using a backscatter model and in situ data, we identify the controls on SAR imagery in terms of mass-balance measurement and discuss the glaciological parameters which can reasonably be derived from multi-temporal SAR data. Our results show that amplitude SAR imagery, in the absence of in situ measurements, is not capable of providing meaningful mass-balance data. We show that backscatter from temperate glaciers is affected primarily by snow grain-size and density, and therefore processes such as firnification or depth-hoar formation can complicate the analysis of imagery. We conclude that SAR imagery over temperate glaciers can provide valuable proxy information but not direct mass-balance terms.

scholarly journals Multi-temporal runoff-sediment discharge relationships

2022 ◽  
Author(s):  
Honglin Xiao ◽  
Jinping Zhang ◽  
Hongyuan Fang
Keyword(s):  
Ensemble Empirical Mode Decomposition ◽  
Annual Runoff ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Sediment Discharge ◽  
Discharge Data ◽  
Temporal Correlations ◽  
Mode Decomposition ◽  
Multi Temporal ◽  
Runoff Sediment

To understand the runoff-sediment discharge relationship , this study examined the annual runoff and sediment discharge data obtained from the Tangnaihai hydrometric station. The data were decomposed into multiple time scales through Complete Ensemble Empirical Mode Decomposition with adaptive noise (CEEMDAN). Furthermore, double cumulative curves were plotted and the cointegration theory was employed to analyze the microscopic and macroscopic multi-temporal correlations between the runoff and the sediment discharge and their detailed evolution.

scholarly journals Comparing Multiple Precipitation Products against In-Situ Observations over Different Climate Regions of Pakistan

2019 ◽  
Vol 11 (6) ◽  
pp. 628 ◽  
Author(s):  
Waheed Ullah ◽  
Guojie Wang ◽  
Gohar Ali ◽  
Daniel Tawia Hagan ◽  
Asher Bhatti ◽  
...  
Keyword(s):  
Primary Source ◽  
Tropical Rainfall Measuring Mission ◽  
Reanalysis Data ◽  
Climate Data ◽  
Satellite Precipitation ◽  
In Situ Data ◽  
The North ◽  
Precipitation Seasonality ◽  
In Situ Observations

Various state-of-the-art gridded satellite precipitation products (GPPs) have been derived from remote sensing and reanalysis data and are widely used in hydrological studies. An assessment of these GPPs against in-situ observations is necessary to determine their respective strengths and uncertainties. GPPs developed from satellite observations as a primary source were compared to in-situ observations, namely the Climate Hazard group Infrared Precipitation with Stations (CHIRPS), Multi-Source Weighted-Ensemble Precipitation (MSWEP), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA). These products were compared to in-situ data from 51 stations, spanning 1998–2016, across Pakistan on daily, monthly, annual and interannual time scales. Spatiotemporal climatology was well captured by all products, with more precipitation in the north eastern parts during the monsoon months and vice-versa. Daily precipitation with amount larger than 10 mm showed significant (95%, Kolmogorov-Smirnov test) agreement with the in-situ data, especially TMPA, followed by CHIRPS and MSWEP. At monthly scales, there were significant correlations (R) between the GPPs and in-situ records, suggesting similar dynamics; however, statistical metrics suggested that the performance of these products varies from north towards south. Temporal agreement on an interannual scale was higher in the central and southern parts which followed precipitation seasonality. TMPA performed the best, followed in order by CHIRPS, MSWEP and PERSIANN-CDR.

ENSEMBLE EMPIRICAL MODE DECOMPOSITION WITH SUPERVISED CLUSTER ANALYSIS

2013 ◽  
Vol 05 (01) ◽  
pp. 1350005 ◽  
Author(s):  
CHIH-YU KUO ◽  
SHAO-KUAN WEI ◽  
PI-WEN TSAI
Keyword(s):  
Cluster Analysis ◽  
Empirical Mode Decomposition ◽  
Single Mode ◽  
Ensemble Empirical Mode Decomposition ◽  
Intrinsic Mode Functions ◽  
Wind Turbine Noise ◽  
Mode Decomposition ◽  
General Rules ◽  
Multi Mode

Ensemble empirical mode decomposition (EEMD) is a noise-assisted data analysis method which decomposes a signal into a collection of intrinsic mode functions (IMFs). There nevertheless appears a multi-mode problem where signals with a similar timescale are decomposed into different IMF components. A possible solution to this problem is to recombine the multi-mode IMF components into a proper single mode but as of yet, no general rules have been proposed in the literature. This paper presents the incorporation of a statistical cluster analysis to assist in the diagnosis of multi-mode IMFs and to recombine them based on the classified clusters. As a result, signals are reorganized into a condensed set of clustered intrinsic mode functions (CIMFs). The method is applied to two sets of artificially synthesized signals and two sets of practical signals: wind turbine noise and earthquake motion. These applications demonstrate that, with the additional cluster analysis, the multi-mode problem can be largely eliminated in a statistically reliable manner, and in situ applications can be improved.

scholarly journals Evaluation of reanalysis data in the study of meteorological and hydrological droughts in the Magdalena-Cauca river basin, Colombia

DYNA ◽  
2019 ◽  
Vol 86 (211) ◽  
pp. 268-277
Author(s):  
Carolina Vega Viviescas ◽  
Erasmo Alfredo Rodríguez Sandoval
Keyword(s):  
River Basin ◽  
Reanalysis Data ◽  
Natural Phenomenon ◽  
Sources Of Information ◽  
In Situ Data ◽  
Historical Series ◽  
Good Potential ◽  
Drought Indicators ◽  
Hydrological Droughts

Droughts are a natural phenomenon of water deficit and represent one of the most dangerous natural hazards to human activities; accordingly, its understanding and monitoring are vital. For doing this, long historical series of precipitation and evapotranspiration are considered; however, the sources of this observed information on land are usually limited spatially and temporally. Consequently, the use of complementary sources of information, such as reanalysis, is appropriate in areas with scarce information. Thus, we have evaluated the use of the reanalysis databases of the eartH2Observe project (WFDEI & MSWEP) in the Magdalena-Cauca river basin in Colombia, through the calculation of three drought indicators (SPI, SPEI & WCI). The indices calculated with the in-situ data identified ten drought events of great affectation in the basin. Applying statistical and a Bootstrap uncertainty analysis, we evaluate the performance of the reanalysis, finding that the use of the MSWEP precipitation product has a good potential for the analysis of droughts in Colombia

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