scholarly journals A Simple Procedure for Evaluating Global Cosmogenic 14C Production in the Atmosphere Using Neutron Monitor Data

Radiocarbon ◽  
2002 ◽  
Vol 44 (1) ◽  
pp. 149-157 ◽  
Author(s):  
D C Lowe ◽  
W Allan
Keyword(s):  
Time Series ◽  
Solar Cycle ◽  
Atomic Oxygen ◽  
Atmospheric Transport ◽  
Simple Procedure ◽  
Oxidation Mechanism ◽  
Temporal Distribution ◽  
Transport Processes ◽  
Solar Cycle 23 ◽  
Monitor Data

Radiocarbon (14C) produced by cosmogenic processes in the atmosphere reacts rapidly with atomic oxygen to form 14CO. The primary sink for this species is oxidation by the OH radical, the single most important oxidation mechanism for pollutants in the atmosphere. Hence, knowledge of the spatial and temporal distribution of 14CO allows important inferences to be made about atmospheric transport processes and the distribution of OH. Because the chemical lifetime of 14CO against OH attack is relatively short, 1–3 months, its distribution in the atmosphere should show modulations due to changes in 14C production caused by variations in the solar cycle. In this work we present a simple methodology to provide a time series of global 14C production to help interpret time series of atmospheric 14CO measurements covering the whole of solar cycle 23. We use data from neutron monitors, a readily available proxy for global 14C production, and show that an existing 6-year time series of 14CO data from Baring Head, New Zealand, tracks changes in global 14C production at the onset of solar cycle 23.

Using robust baseline extraction to examine synoptic-scale variability in European CO2

2020 ◽  
Author(s):  
Alex Resovsky ◽  
Michel Ramonet ◽  
Leonard Rivier ◽  
Sebastien Conil ◽  
Gerard Spain
Keyword(s):  
Time Series ◽  
Atmospheric Transport ◽  
Transport Processes ◽  
Surface Fluxes ◽  
Data Availability ◽  
Observation System ◽  
Back Trajectory ◽  
Synoptic Scale ◽  
Source Sink ◽  
Baseline Estimation

<p>Continuous measurements of long-lived greenhouse gases at ground-based monitoring stations are frequently influenced by regional surface fluxes and atmospheric transport processes, which induce variability at a range of timescales.  Dissecting this variability is critical to identifying long-term trends and understanding regional source-sink patterns, but it requires a robust characterization of the underlying signal comprising the background air composition at a given site.  Methods of background signal extraction that make use of chemical markers or meteorological filters yield reliable estimates, but often must be adapted for site-specific measurement conditions and data availability.  Statistical baseline extraction tools provide a more generally transferable alternative to such methods.  Here, we apply one such technique (REBS) to a continuous time series of atmospheric CO<sub>2</sub> readings at Mace Head, Ireland and compare the results to a modeled baseline signal obtained from local wind observations. We then assess REBS’ performance at two continental sites within the Integrated Carbon Observation System (ICOS) network at which baseline signals are derived using back-trajectory analyses.  Overall, we find that REBS effectively reduces the bias in wintertime baseline estimation relative to other statistical techniques, and thus represents a computationally inexpensive and transferable approach to baseline extraction in atmospheric time series. To investigate one potential application of such an approach, we examine wintertime synoptic-scale CO<sub>2</sub> excursions from the REBS baseline during the period 2015-2019.  Our goal is to identify relationships between the timing and strength of such events and to better understand sub-seasonal variability in CO<sub>2</sub> transport over Europe.</p>

Behavior of the atomic oxygen 557.7nm atmospheric emission in the solar cycle 23

2008 ◽  
Vol 41 (4) ◽  
pp. 655-659 ◽  
Author(s):  
A.V. Mikhalev ◽  
P. Stoeva ◽  
I.V. Medvedeva ◽  
B. Benev ◽  
A.V. Medvedev
Keyword(s):  
Solar Cycle ◽  
Atomic Oxygen ◽  
Atmospheric Emission ◽  
Solar Cycle 23

Mid-term Periodicities in Solar Radio Emission Corresponding to Sunspot Number During Solar Cycle 23

Solar Physics ◽  
2021 ◽  
Vol 296 (3) ◽  
Author(s):  
Mahender Aroori ◽  
Panditi Vemareddy ◽  
Partha Chowdhury ◽  
Ganji Yellaiah
Keyword(s):  
Solar Cycle ◽  
Radio Emission ◽  
Sunspot Number ◽  
Solar Radio ◽  
Solar Radio Emission ◽  
Solar Cycle 23

scholarly journals Evaluation of the atmospheric transport in a GCM using radon measurements: sensitivity to cumulus convection parameterization

2008 ◽  
Vol 8 (10) ◽  
pp. 2811-2832 ◽  
Author(s):  
K. Zhang ◽  
H. Wan ◽  
M. Zhang ◽  
B. Wang
Keyword(s):  
Vertical Distribution ◽  
Radon Concentration ◽  
Large Scale ◽  
Atmospheric Transport ◽  
Surface Concentration ◽  
Transport Processes ◽  
Cumulus Convection ◽  
Models Comparison ◽  
Convection Schemes ◽  
Convection Parameterization

Abstract. The radioactive species radon (222Rn) has long been used as a test tracer for the numerical simulation of large scale transport processes. In this study, radon transport experiments are carried out using an atmospheric GCM with a finite-difference dynamical core, the van Leer type FFSL advection algorithm, and two state-of-the-art cumulus convection parameterization schemes. Measurements of surface concentration and vertical distribution of radon collected from the literature are used as references in model evaluation. The simulated radon concentrations using both convection schemes turn out to be consistent with earlier studies with many other models. Comparison with measurements indicates that at the locations where significant seasonal variations are observed in reality, the model can reproduce both the monthly mean surface radon concentration and the annual cycle quite well. At those sites where the seasonal variation is not large, the model is able to give a correct magnitude of the annual mean. In East Asia, where radon simulations are rarely reported in the literature, detailed analysis shows that our results compare reasonably well with the observations. The most evident changes caused by the use of a different convection scheme are found in the vertical distribution of the tracer. The scheme associated with weaker upward transport gives higher radon concentration up to about 6 km above the surface, and lower values in higher altitudes. In the lower part of the atmosphere results from this scheme does not agree as well with the measurements as the other scheme. Differences from 6 km to the model top are even larger, although we are not yet able to tell which simulation is better due to the lack of observations at such high altitudes.

scholarly journals Trend Analysis of Annual and Seasonal River Runoff by Using Innovative Trend Analysis with Significant Test

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 95
Author(s):  
Yilinuer Alifujiang ◽  
Jilili Abuduwaili ◽  
Yongxiao Ge
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
River Runoff ◽  
Temporal Trends ◽  
Temporal Distribution ◽  
Trend Test ◽  
Data Series ◽  
Mk Test ◽  
Comparison Results ◽  
Innovative Trend Analysis

This study investigated the temporal patterns of annual and seasonal river runoff data at 13 hydrological stations in the Lake Issyk-Kul basin, Central Asia. The temporal trends were analyzed using the innovative trend analysis (ITA) method with significance testing. The ITA method results were compared with the Mann-Kendall (MK) trend test at a 95% confidence level. The comparison results revealed that the ITA method could effectively identify the trends detected by the MK trend test. Specifically, the MK test found that the time series percentage decreased from 46.15% in the north to 25.64% in the south, while the ITA method revealed a similar rate of decrease, from 39.2% to 29.4%. According to the temporal distribution of the MK test, significantly increasing (decreasing) trends were observed in 5 (0), 6 (2), 4 (3), 8 (0), and 8 (1) time series in annual, spring, summer, autumn, and winter river runoff data. At the same time, the ITA method detected significant trends in 7 (1), 9 (3), 6(3), 9 (3), and 8 (2) time series in the study area. As for the ITA method, the “peak” values of 24 time series (26.97%) exhibited increasing patterns, 25 time series (28.09%) displayed increasing patterns for “low” values, and 40 time series (44.94%) showed increasing patterns for “medium” values. According to the “low”, “medium”, and “peak” values, five time series (33.33%), seven time series (46.67%), and three time series (20%) manifested decreasing trends, respectively. These results detailed the patterns of annual and seasonal river runoff data series by evaluating “low”, “medium”, and “peak” values.

Sign in / Sign up

Export Citation Format

Share Document