scholarly journals Hydrogen fluoride total and partial column time series above the Jungfraujoch from long-term FTIR measurements: Impact of the line-shape model, characterization of the error budget and seasonal cycle, and comparison with satellite and model data

2010 ◽  
Vol 115 (D22) ◽  
Author(s):  
P. Duchatelet ◽  
P. Demoulin ◽  
F. Hase ◽  
R. Ruhnke ◽  
W. Feng ◽  
...  
Keyword(s):  
Time Series ◽  
Hydrogen Fluoride ◽  
Line Shape ◽  
Seasonal Cycle ◽  
Model Data ◽  
Shape Model ◽  
Error Budget

scholarly journals Flexible approach for quantifying average long-term changes and seasonal cycles of tropospheric trace species

2019 ◽  
Author(s):  
David D. Parrish ◽  
Richard G. Derwent ◽  
Simon O'Doherty ◽  
Peter G. Simmonds
Keyword(s):  
Time Series ◽  
Seasonal Cycle ◽  
Linear Trend ◽  
Power Series Expansion ◽  
Mathematical Representation ◽  
Seasonal Cycles ◽  
Data Sets ◽  
Significant Information ◽  
Long Term Changes

Abstract. We present an approach to derive a systematic mathematical representation of the statistically significant features of the average long-term changes and seasonal cycle of concentrations of trace tropospheric species. The results for two illustrative data sets (time series of baseline concentrations of ozone and N2O at Mace Head, Ireland) indicate that a limited set of seven or eight parameter values provides this mathematical representation for both example species. This method utilizes a power series expansion to extract more information regarding the long-term changes than can be provided by oft-employed linear trend analyses. In contrast, the quantification of average seasonal cycles utilizes a Fourier series analysis that provides less detailed seasonal cycles than are sometimes represented as twelve monthly means; including that many parameters in the seasonal cycle representation is not usually statistically justified, and thereby adds unnecessary noise to the representation and prevents a clear analysis of the statistical uncertainty of the results. The approach presented here is intended to maximize the statistically significant information extracted from analyses of time series of concentrations of tropospheric species regarding their mean long-term changes and seasonal cycles, including non-linear aspects of the long-term trends. Additional implications, advantages and limitations of this approach are discussed.

scholarly journals Stellar activity analysis of Barnard’s Star: Very slow rotation and evidence for long-term activity cycle

2019 ◽  
Author(s):  
B Toledo-Padrón ◽  
J I González Hernández ◽  
C Rodríguez-López ◽  
A Suárez Mascareño ◽  
R Rebolo ◽  
...  
Keyword(s):  
Time Series ◽  
Spectroscopic Data ◽  
Rotation Period ◽  
Photometric Data ◽  
Activity Level ◽  
Slow Rotation ◽  
Activity Levels ◽  
Stellar Activity

Abstract The search for Earth-like planets around late-type stars using ultra-stable spectrographs requires a very precise characterization of the stellar activity and the magnetic cycle of the star, since these phenomena induce radial velocity (RV) signals that can be misinterpreted as planetary signals. Among the nearby stars, we have selected Barnard’s Star (Gl 699) to carry out a characterization of these phenomena using a set of spectroscopic data that covers about 14.5 years and comes from seven different spectrographs: HARPS, HARPS-N, CARMENES, HIRES, UVES, APF, and PFS; and a set of photometric data that covers about 15.1 years and comes from four different photometric sources: ASAS, FCAPT-RCT, AAVSO, and SNO. We have measured different chromospheric activity indicators (Hα, Ca II HK and Na I D), as well as the FWHM of the cross-correlation function computed for a sub-set of the spectroscopic data. The analysis of Generalized Lomb-Scargle periodograms of the time series of different activity indicators reveals that the rotation period of the star is 145 ± 15 days, consistent with the expected rotation period according to the low activity level of the star and previous claims. The upper limit of the predicted activity-induced RV signal corresponding to this rotation period is about 1 m/s. We also find evidence of a long-term cycle of 10 ± 2 years that is consistent with previous estimates of magnetic cycles from photometric time series in other M stars of similar activity levels. The available photometric data of the star also support the detection of both the long-term and the rotation signals.

A Method for Estimating the Evolution of Brewer-Dobson Circulation Upwelling

2020 ◽  
Author(s):  
Edward Charlesworth ◽  
Felix Ploeger ◽  
Mohamadu Diallo ◽  
Thomas Birner ◽  
Patrick Joeckel
Keyword(s):  
Balance Equation ◽  
Seasonal Cycle ◽  
Inverse Method ◽  
Lower Stratosphere ◽  
Climate Model ◽  
Vertical Mixing ◽  
Model Data ◽  
Absolute Value ◽  
Multiple Datasets

<p>Both theory and climate model results suggest that the Brewer-Dobson circulation should strengthen in the stratosphere with increasing greenhouse gas concentrations. Directly measuring the circulation strength is not possible, so verification of this sensitivity has been limited to indirect inferences from observed tracer fields of long-lived species. These methods, however, are complex and accumulation of the data required for them is difficult. When limiting discussion to the tropical lower stratosphere, ozone concentrations have shown to be consistent with an accelerating circulation. These measurements are particularly useful because of the long timeseries available from multiple datasets, but they have only been used for indirect investigations of the circulation strength, up until now.</p><p>In this work, we invert the ozone balance equation to solve for upwelling. By limiting the investigation to 70 hPa in the southern tropics and estimating upwelling anomalies from the long-term mean (and not the absolute value of upwelling) most chemical terms and both horizontal and vertical mixing can be neglected, and calculation of the remaining terms is straight-forward. To verify the validity of the method, a calculation of upwelling is performed using climate model data, from which a comparison of actual upwelling and upwelling from the inverse method can be made. The seasonal cycle of upwelling anomalies is compared to upwelling anomalies from reanalyses and model results, and trends and variability are discussed.</p>

Characterization of the Electron Density in Si+-Implanted InP by Means of Raman Scattering by Lo-Plasma Coupled Modes

1998 ◽  
Vol 540 ◽  
Author(s):  
J. Ibáñez ◽  
R. Cuscó ◽  
N. Blánco ◽  
G. González-Díaz ◽  
J. Jiménez ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Electron Density ◽  
Line Shape ◽  
Ion Beam ◽  
Coupled Modes ◽  
Shape Model ◽  
Sn Doping ◽  
Average Value ◽  
Ion Beam Implantation

AbstractWe have studied by means of Raman spectroscopy the electron density in two different n-type InP samples with similar doping densities, obtained, respectively, by ion-beam implantation of 150 keV Si+ and by uniform Sn doping during LEC growth. The Raman spectra recorded at 80 K display in both cases the L+ and L– phonon-plasmon coupled modes. For the homogeneously doped InP:Sn sample, a simultaneous fit to the L+ and L– peaks of a line shape model based on the Lindhard-Mermin dielectric function yields accurate values of the charge density. In the implanted sample, the nonuniformity of the charge distribution substantially broadens the L+ modes, but the line shape fit to the L– mode still yields an average value of the electron density in the region probed by the laser beam.

scholarly journals Validation of Precipitable Water Vapor within the NCEP/DOE Reanalysis Using Global GPS Observations from One Decade

2010 ◽  
Vol 23 (7) ◽  
pp. 1675-1695 ◽  
Author(s):  
Sibylle Vey ◽  
Reinhard Dietrich ◽  
Axel Rülke ◽  
Mathias Fritsche ◽  
Peter Steigenberger ◽  
...  
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Seasonal Cycle ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Atmospheric Temperature ◽  
Interannual Variations ◽  
Seasonal Signals ◽  
The Tropics

Abstract In contrast to previous studies validating numerical weather prediction (NWP) models using observations from the global positioning system (GPS), this paper focuses on the validation of seasonal and interannual variations in the water vapor. The main advantage of the performed validation is the independence of the GPS water vapor estimates compared to studies using water vapor datasets from radiosondes or satellite microwave radiometers that are already assimilated into the NWP models. Tropospheric parameters from a GPS reanalysis carried out in a common project of the Technical Universities in Munich and Dresden were converted into precipitable water (PW) using surface pressure observations from the WMO and mean atmospheric temperature data from ECMWF. PW time series were generated for 141 globally distributed GPS sites covering the time period from the beginning of 1994 to the end of 2004. The GPS-derived PW time series were carefully examined for their homogeneity. The validation of the NWP model from NCEP shows that the differences between the modeled and observed PW values are time dependent. In addition to establishing a long-term mean, this study also validates the seasonal cycle and interannual variations in the PW. Over Europe and large parts of North America the seasonal cycle and the interannual variations in the PW from GPS and NCEP agree very well. The results reveal a submillimeter accuracy of the GPS-derived PW anomalies. In the regions mentioned above, NCEP provides a highly accurate database for studies of long-term changes in the atmospheric water vapor. However, in the Southern Hemisphere large differences in the seasonal signals and in the PW anomalies were found between GPS and NCEP. The seasonal signal of the PW is underestimated by NCEP in the tropics and in Antarctica by up to 40% and 25%, respectively. Climate change studies based on water vapor data from NCEP should consider the large uncertainties in the analysis when interpreting these data, especially in the tropics.

scholarly journals Investigating the long-term evolution of subtropical ozone profiles applying ground-based FTIR spectrometry

2012 ◽  
Vol 5 (11) ◽  
pp. 2917-2931 ◽  
Author(s):  
O. E. García ◽  
M. Schneider ◽  
A. Redondas ◽  
Y. González ◽  
F. Hase ◽  
...  
Keyword(s):  
Time Series ◽  
Line Shape ◽  
Long Term Evolution ◽  
Term Evolution ◽  
Ozone Profile ◽  
Instrumental Line ◽  
Temperature Retrieval ◽  
Linear Trends ◽  
Better Than

Abstract. This study investigates the long-term evolution of subtropical ozone profile time series (1999–2010) obtained from ground-based FTIR (Fourier Transform InfraRed) spectrometry at the Izaña Observatory ozone super-site. Different ozone retrieval strategies are examined, analysing the influence of an additional temperature retrieval and different constraints. The theoretical assessment reveals that the FTIR system is able to resolve four independent ozone layers with a precision of better than 6% in the troposphere and of better than 3% in the lower, middle and upper stratosphere. This total error includes the smoothing error, which dominates the random error budget. Furthermore, we estimate that the measurement noise as well as uncertainties in the applied atmospheric temperature profiles and instrumental line shape are leading error sources. We show that a simultaneous temperature retrieval can significantly reduce the total random errors and that a regular determination of the instrumental line shape is important for producing a consistent long-term dataset. These theoretical precision estimates are empirically confirmed by daily intercomparisons with Electro Chemical Cell (ECC) sonde profiles. In order to empirically document the long-term stability of the FTIR ozone profile data we compare the linear trends and seasonal cycles as obtained from the FTIR and ECC time series. Concerning seasonality, in winter both techniques observe stratospheric ozone profiles that are typical middle latitude profiles (low tropopause, low ozone maximum concentrations) and in summer/autumn profiles that are typical tropical profiles (high tropopause, high maximum concentrations). The linear trends estimated from the FTIR and the ECC datasets agree within their error bars. For the FTIR time series, we observe a significant negative trend in the upper troposphere/lower stratosphere of about −0.2% yr−1 and a significant positive trend in the middle and upper stratosphere of about +0.3% yr−1 and +0.4% yr−1, respectively. Identifying such small trends is a difficult task for any measurement technique. In this context, super-sites applying different techniques are very important for the detection of reliable ozone trends.

RECURRENCE QUANTIFICATION ANALYSIS IN WATERSHED ECOSYSTEM RESEARCH

2011 ◽  
Vol 21 (04) ◽  
pp. 1113-1125 ◽  
Author(s):  
HOLGER LANGE
Keyword(s):  
Time Series ◽  
Recurrence Quantification Analysis ◽  
Data Driven ◽  
Model Data ◽  
Ecosystem Research ◽  
Data Comparison ◽  
Recurrence Quantification ◽  
Quantification Analysis ◽  
Term Monitoring

In ecosystem research, data-driven approaches to modeling are of major importance. Models are more often than not shaped by the spatiotemporal structure of the observations: an inverse modeling approach prevails. Here, I investigate the insights obtained from Recurrence Quantification Analysis of observed ecosystem time series. As a typical example of available long-term monitoring data, I choose time series from hydrology and hydrochemistry. Besides providing insights into the nonstationary and nonlinear dynamics of these variables, RQA also enables a detailed and temporally local model-data comparison.

scholarly journals Utilizing the Drake Passage Time-series to understand variability and change in subpolar Southern Ocean pCO<sub>2</sub>

2017 ◽  
Author(s):  
Amanda R. Fay ◽  
Nicole S. Lovenduski ◽  
Galen A. McKinley ◽  
David R. Munro ◽  
Colm Sweeney ◽  
...  
Keyword(s):  
Time Series ◽  
Southern Ocean ◽  
Seasonal Cycle ◽  
Drake Passage ◽  
Passage Time ◽  
Global Ocean ◽  
Carbon Uptake ◽  
Surface Ocean ◽  
Ocean Carbon

Abstract. The Southern Ocean is highly under-sampled for the purpose of assessing total carbon uptake and its variability. Since this region dominates the mean global ocean sink for anthropogenic carbon, understanding temporal change is critical. Underway measurements of pCO2 collected as part of the Drake Passage Time-series (DPT) program that began in 2002 inform our understanding of seasonally changing air-sea gradients in pCO2, and by inference the carbon flux in this region. Here, we utilize all available pCO2 observations collected in the subpolar Southern Ocean to evaluate how the seasonal cycle, interannual variability, and long-term trends in surface ocean pCO2 in the Drake Passage region compare to that of the broader subpolar Southern Ocean. Our results indicate that the Drake Passage is representative of the broader region in both seasonality and long term pCO2 trends shown through the agreement of timing and amplitude of seasonal cycles as well as trend magnitudes. The high temporal density of sampling by the DPT is critical to constraining estimates of the seasonal cycle of surface pCO2 in this region, as winter data remain sparse in areas outside of the Drake Passage. From 2002–2015, data show that carbon uptake has strengthened with surface ocean pCO2 trends less than the global atmospheric trend in the Drake Passage and the broader subpolar Southern Ocean. Analysis of spatial correlation shows Drake Passage pCO2 to be representative of pCO2 and its variability up to several hundred kilometers upstream of the region. We also compare DPT data from 2016 and early 2017 to contemporaneous pCO2 estimates from autonomous biogeochemical floats deployed as part of the Southern Ocean Carbon and Climate Observations and Modeling project (SOCCOM) so as to highlight the opportunity for evaluating data collected on autonomous observational platforms. Though SOCCOM floats sparsely sample the Drake Passage region for 2016–2017, their pCO2 estimates typically fall within the range of underway observations. Going forward, continuation of the Drake Passage Time-series will reduce uncertainties in Southern Ocean carbon uptake seasonality, variability, and trends, and provide an invaluable independent dataset for post-deployment quality control of sensors on autonomous floats. Together, these datasets will vastly increase our ability to monitor change in the ocean carbon sink.

scholarly journals Utilizing the Drake Passage Time-series to understand variability and change in subpolar Southern Ocean <i>p</i>CO<sub>2</sub>

2018 ◽  
Vol 15 (12) ◽  
pp. 3841-3855 ◽  
Author(s):  
Amanda R. Fay ◽  
Nicole S. Lovenduski ◽  
Galen A. McKinley ◽  
David R. Munro ◽  
Colm Sweeney ◽  
...  
Keyword(s):  
Time Series ◽  
Southern Ocean ◽  
Seasonal Cycle ◽  
Drake Passage ◽  
Passage Time ◽  
Global Ocean ◽  
Carbon Uptake ◽  
Surface Ocean ◽  
Ocean Carbon

Abstract. The Southern Ocean is highly under-sampled for the purpose of assessing total carbon uptake and its variability. Since this region dominates the mean global ocean sink for anthropogenic carbon, understanding temporal change is critical. Underway measurements of pCO2 collected as part of the Drake Passage Time-series (DPT) program that began in 2002 inform our understanding of seasonally changing air–sea gradients in pCO2, and by inference the carbon flux in this region. Here, we utilize available pCO2 observations to evaluate how the seasonal cycle, interannual variability, and long-term trends in surface ocean pCO2 in the Drake Passage region compare to that of the broader subpolar Southern Ocean. Our results indicate that the Drake Passage is representative of the broader region in both seasonality and long-term pCO2 trends, as evident through the agreement of timing and amplitude of seasonal cycles as well as trend magnitudes both seasonally and annually. The high temporal density of sampling by the DPT is critical to constraining estimates of the seasonal cycle of surface pCO2 in this region, as winter data remain sparse in areas outside of the Drake Passage. An increase in winter data would aid in reduction of uncertainty levels. On average over the period 2002–2016, data show that carbon uptake has strengthened with annual surface ocean pCO2 trends in the Drake Passage and the broader subpolar Southern Ocean less than the global atmospheric trend. Analysis of spatial correlation shows Drake Passage pCO2 to be representative of pCO2 and its variability up to several hundred kilometers away from the region. We also compare DPT data from 2016 and 2017 to contemporaneous pCO2 estimates from autonomous biogeochemical floats deployed as part of the Southern Ocean Carbon and Climate Observations and Modeling project (SOCCOM) so as to highlight the opportunity for evaluating data collected on autonomous observational platforms. Though SOCCOM floats sparsely sample the Drake Passage region for 2016–2017 compared to the Drake Passage Time-series, their pCO2 estimates fall within the range of underway observations given the uncertainty on the estimates. Going forward, continuation of the Drake Passage Time-series will reduce uncertainties in Southern Ocean carbon uptake seasonality, variability, and trends, and provide an invaluable independent dataset for post-deployment assessment of sensors on autonomous floats. Together, these datasets will vastly increase our ability to monitor change in the ocean carbon sink.

Non-parametric characterization of long-term rainfall time series

2018 ◽  
Vol 131 (3) ◽  
pp. 627-637 ◽  
Author(s):  
Harinarayan Tiwari ◽  
Brij Kishor Pandey
Keyword(s):  
Time Series ◽  
Rainfall Time Series ◽  
Non Parametric
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