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>

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.

scholarly journals An algorithm to detect non-background signals in greenhouse gas time series from European tall tower and mountain stations

2021 ◽  
Vol 14 (9) ◽  
pp. 6119-6135
Author(s):  
Alex Resovsky ◽  
Michel Ramonet ◽  
Leonard Rivier ◽  
Jerome Tarniewicz ◽  
Philippe Ciais ◽  
...  
Keyword(s):  
Time Series ◽  
Atmospheric Transport ◽  
Anomalous Behavior ◽  
Synoptic Scale ◽  
Short Term ◽  
Noise Component ◽  
Statistical Framework ◽  
Polynomial Fit ◽  
Daily Data ◽  
Tall Tower

Abstract. We present a statistical framework to identify regional signals in station-based CO2 time series with minimal local influence. A curve-fitting function is first applied to the detrended time series to derive a harmonic describing the annual CO2 cycle. We then combine a polynomial fit to the data with a short-term residual filter to estimate the smoothed cycle and define a seasonally adjusted noise component, equal to 2 standard deviations of the smoothed cycle about the annual cycle. Spikes in the smoothed daily data which surpass this ±2σ threshold are classified as anomalies. Examining patterns of anomalous behavior across multiple sites allows us to quantify the impacts of synoptic-scale atmospheric transport events and better understand the regional carbon cycling implications of extreme seasonal occurrences such as droughts.

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.

Cloud Properties over the North Slope of Alaska: Identifying the Prevailing Meteorological Regimes

2012 ◽  
Vol 25 (23) ◽  
pp. 8238-8258 ◽  
Author(s):  
Johannes Mülmenstädt ◽  
Dan Lubin ◽  
Lynn M. Russell ◽  
Andrew M. Vogelmann
Keyword(s):  
Time Series ◽  
Climate Model ◽  
North Slope ◽  
Test Cases ◽  
Synoptic Scale ◽  
Long Time Series ◽  
The North ◽  
Cloud Properties ◽  
North Slope Of Alaska ◽  
Long Time

Abstract Long time series of Arctic atmospheric measurements are assembled into meteorological categories that can serve as test cases for climate model evaluation. The meteorological categories are established by applying an objective k-means clustering algorithm to 11 years of standard surface-meteorological observations collected from 1 January 2000 to 31 December 2010 at the North Slope of Alaska (NSA) site of the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM). Four meteorological categories emerge. These meteorological categories constitute the first classification by meteorological regime of a long time series of Arctic meteorological conditions. The synoptic-scale patterns associated with each category, which include well-known synoptic features such as the Aleutian low and Beaufort Sea high, are used to explain the conditions at the NSA site. Cloud properties, which are not used as inputs to the k-means clustering, are found to differ significantly between the regimes and are also well explained by the synoptic-scale influences in each regime. Since the data available at the ARM NSA site include a wealth of cloud observations, this classification is well suited for model–observation comparison studies. Each category comprises an ensemble of test cases covering a representative range in variables describing atmospheric structure, moisture content, and cloud properties. This classification is offered as a complement to standard case-study evaluation of climate model parameterizations, in which models are compared against limited realizations of the Earth–atmosphere system (e.g., from detailed aircraft measurements).

scholarly journals Atmospheric 14C Variability Recorded in Tree Rings from Peninsular India: Implications for Fossil Fuel CO2 Emission and Atmospheric Transport

Radiocarbon ◽  
2008 ◽  
Vol 50 (3) ◽  
pp. 321-330 ◽  
Author(s):  
Supriyo Chakraborty ◽  
Koushik Dutta ◽  
Amalava Bhattacharyya ◽  
Mohit Nigam ◽  
Edward A G Schuur ◽  
...  
Keyword(s):  
Time Series ◽  
Fossil Fuel ◽  
Atmospheric Transport ◽  
Central India ◽  
Tectona Grandis ◽  
Peninsular India ◽  
Local Emission ◽  
Teak Tree ◽  
C Value ◽  
Peak Value

Radiocarbon analysis in annual rings of a teak tree (Tectona grandis) is reported in comparison with previously published results. Samples (disks) were collected from Hoshangabad (22°30′N, 78°E), Madhya Pradesh, in central India. The previously published sample was collected from Thane (19°12′N, 73°E), Maharashtra, near the west coast of India (Chakraborty et al. 1994). Two short Δ14C time series were reconstructed with these tree samples to capture the bomb peak of atmospheric 14C and the spatial variability in this record. These time series represent the periods 1954–1977 and 1959–1980 for Hoshangabad and Thane, respectively. The 14C peaks in these places appear around 1964–1965. The Hoshangabad tree records a peak Δ14C value of 708 ± 8%, which conforms to the peak value of Northern Hemisphere Zone 3 as described in Hua and Barbetti (2004). But the peak Δ14C at Thane is somewhat less (630 ± 8%) probably due to the dilution by fossil fuel CO2 free of 14C emanating from the neighboring industrial areas. This depletion of peak values has been used to estimate the local emission of fossil fuel CO2, which is approximately 2.3% of the background atmospheric CO2 concentration.

Preliminary results of the first assessment of 20 years of dust activity in the Patagonia desert (South America) with aerosol products from the MODIS sensors

2021 ◽  
Author(s):  
Santiago Gassó ◽  
Pawan Gupta ◽  
Paul Ginoux ◽  
Robert Levy
Keyword(s):  
Time Series ◽  
South America ◽  
Volcanic Eruptions ◽  
Transport Processes ◽  
Dust Storms ◽  
Biological Processes ◽  
Aerosol Transport ◽  
Deep Blue ◽  
Fire Activity ◽  
Analysis Of Time Series

<p>Aerosol transport processes in the Southern Hemisphere (SH) have been the center of renewed attention in the last two decades because of a number of major geophysical events such as volcanic eruptions (Chile and Argentina), biomass burning (Australia and Chile) and dust storms (Australia and Argentina).<br><br>While volcanic and fire activity in the SH have been the focus of several studies, there is a dearth of satellite assessments of dust activity. The lack of such analysis impairs the understanding of biological processes in the Southern Ocean and of the provenance of dust found in snow at the surface of East Antarctica.<br><br>This presentation will show an analysis of time series of Aerosol Optical Depths over the Patagonia desert in South America. Data from two aerosol algorithms (Dark Target and Deep Blue) will be jointly analyzed to establish a timeline of dust activity in the region. Also, dust proxies from both algorithms will be compared with ground-based observations of visibility at different airports in the area. Once an understanding of frequency and time evolution of the dust activity is achieved, first estimations of ocean-going dust fluxes will be derived.</p>

Combining Sentinel-1 and ALOS-2 observations for soil moisture retrieval

2021 ◽  
Author(s):  
Anna Balenzano ◽  
Giuseppe Satalino ◽  
Francesco Lovergine ◽  
Davide Palmisano ◽  
Francesco Mattia ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Temporal Resolution ◽  
Surface Soil ◽  
Earth Science ◽  
Observation System ◽  
Final Report ◽  
Surface Soil Moisture ◽  
Error Characterization ◽  
L Band

<p>One of the limitations of presently available Synthetic Aperture Radar (SAR) surface soil moisture (SSM) products is their moderated temporal resolution (e.g., 3-4 days) that is non optimal for several applications, as most user requirements point to a temporal resolution of 1-2 days or less. A possible path to tackle this issue is to coordinate multi-mission SAR acquisitions with a view to the future Copernicus Sentinel-1 (C&D and Next Generation) and L-band Radar Observation System for Europe (ROSE-L).</p><p>In this respect, the recent agreement between the Japanese (JAXA) and European (ESA) Space Agencies on the use of SAR Satellites in Earth Science and Applications provides a framework to develop and validate multi-frequency and multi-platform SAR SSM products. In 2019 and 2020, to support insights on the interoperability between C- and L-band SAR observations for SSM retrieval, Sentinel-1 and ALOS-2 systematic acquisitions over the TERENO (Terrestrial Environmental Observatories) Selhausen (Germany) and Apulian Tavoliere (Italy) cal/val sites were gathered. Both sites are well documented and equipped with hydrologic networks.</p><p>The objective of this study is to investigate the integration of multi-frequency SAR measurements for a consistent and harmonized SSM retrieval throughout the error characterization of a combined C- and L-band SSM product. To this scope, time series of Sentinel-1 IW and ALOS-2 FBD data acquired over the two sites will be analysed. The short time change detection (STCD) algorithm, developed, implemented and recently assessed on Sentinel-1 data [e.g., Balenzano et al., 2020; Mattia et al., 2020], will be tailored to the ALOS-2 data. Then, the time series of SAR SSM maps from each SAR system will be derived separately and aggregated in an interleaved SSM product. Furthermore, it will be compared against in situ SSM data systematically acquired by the ground stations deployed at both sites. The study will assess the interleaved SSM product and evaluate the homogeneous quality of C- and L-band SAR SSM maps.</p><p> </p><p> </p><p>References</p><p>Balenzano. A., et al., “Sentinel-1 soil moisture at 1km resolution: a validation study”, submitted to Remote Sensing of Environment (2020).</p><p>Mattia, F., A. Balenzano, G. Satalino, F. Lovergine, A. Loew, et al., “ESA SEOM Land project on Exploitation of Sentinel-1 for Surface Soil Moisture Retrieval at High Resolution,” final report, contract number 4000118762/16/I-NB, 2020.</p>

scholarly journals A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 2: Optimization scheme and identical twin experiment of atmospheric CO<sub>2</sub> inversion

2017 ◽  
Vol 10 (6) ◽  
pp. 2201-2219 ◽  
Author(s):  
Yosuke Niwa ◽  
Yosuke Fujii ◽  
Yousuke Sawa ◽  
Yosuke Iida ◽  
Akihiko Ito ◽  
...  
Keyword(s):  
Transport Model ◽  
Surface Fluxes ◽  
Identical Twin ◽  
Inversion Problem ◽  
Model Errors ◽  
Optimization Scheme ◽  
Error Covariance ◽  
Optimal Setting ◽  
Source Sink ◽  
Quasi Newton

Abstract. A four-dimensional variational method (4D-Var) is a popular technique for source/sink inversions of atmospheric constituents, but it is not without problems. Using an icosahedral grid transport model and the 4D-Var method, a new atmospheric greenhouse gas (GHG) inversion system has been developed. The system combines offline forward and adjoint models with a quasi-Newton optimization scheme. The new approach is then used to conduct identical twin experiments to investigate optimal system settings for an atmospheric CO2 inversion problem, and to demonstrate the validity of the new inversion system. In this paper, the inversion problem is simplified by assuming the prior flux errors to be reasonably well known and by designing the prior error correlations with a simple function as a first step. It is found that a system of forward and adjoint models with smaller model errors but with nonlinearity has comparable optimization performance to that of another system that conserves linearity with an exact adjoint relationship. Furthermore, the effectiveness of the prior error correlations is demonstrated, as the global error is reduced by about 15 % by adding prior error correlations that are simply designed when 65 weekly flask sampling observations at ground-based stations are used. With the optimal setting, the new inversion system successfully reproduces the spatiotemporal variations of the surface fluxes, from regional (such as biomass burning) to global scales. The optimization algorithm introduced in the new system does not require decomposition of a matrix that establishes the correlation among the prior flux errors. This enables us to design the prior error covariance matrix more freely.

scholarly journals Stochastic modeling of transient surface scalar and momentum fluxes in turbulent boundary layers

2021 ◽  
Author(s):  
Marten Klein ◽  
David O. Lignell ◽  
Heiko Schmidt
Keyword(s):  
Boundary Layers ◽  
Control Parameter ◽  
Layer Structure ◽  
Numerical Models ◽  
Turbulent Boundary Layers ◽  
Transport Processes ◽  
Surface Fluxes ◽  
One Dimensional ◽  
Weather And Climate ◽  
Normal Transport

&lt;p&gt;Turbulence is ubiquitous in atmospheric boundary layers and manifests itself by transient transport processes on a range of scales. This range easily reaches down to less than a meter, which is smaller than the typical height of the first grid cell layer adjacent to the surface in numerical models for weather and climate prediction. In these models, the bulk-surface coupling plays an important role for the evolution of the atmosphere but it is not feasible to fully resolve it in applications. Hence, the overall quality of numerical weather and climate predictions crucially depends on the modeling of subfilter-scale transport processes near the surface. A standing challenge in this regard is the robust but efficient representation of transient and non-Fickian transport such as counter-gradient fluxes that arise from stratification and rotation effects.&lt;/p&gt;&lt;p&gt;We address the issues mentioned above by utilizing a stochastic one-dimensional turbulence (ODT) model. For turbulent boundary layers, ODT aims to resolve the wall-normal transport processes on all relevant scales but only along a single one-dimensional domain (column) that is aligned with the vertical. Molecular diffusion and unbalanced Coriolis forces are directly resolved, whereas effects of turbulent advection and stratification are modeled by stochastically sampled sequence of mapping (eddy) events. Each of these events instantaneously modifies the flow profiles by a permutation of fluid parcels across a selected size interval. The model is of lower order but obeys fundamental conservation principles and Richardson's 1/4 law by construction.&lt;/p&gt;&lt;p&gt;In this study, ODT is applied as stand-alone tool in order to investigate nondimensional control parameter dependencies of the scalar and momentum transport in turbulent channel, neutral, and stably-stratified Ekman flows up to (friction) Reynolds number &lt;em&gt;Re&lt;/em&gt; = &lt;em&gt;O&lt;/em&gt;(10&lt;sup&gt;4&lt;/sup&gt;). We demonstrate that ODT is able to capture the state-space statistics of transient surface fluxes as well as the boundary-layer structure and nondimensional control parameter dependencies of low-order flow statistics.&lt;br&gt;Very good to reasonable agreement with available reference data is obtained for various observables using fixed model set-ups. We conclude that ODT is an economical turbulence model that is able to not only capture but also predict the wall-normal transport and surface fluxes in multiphysics turbulent boundary layers.&lt;/p&gt;

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