scholarly journals Model simulations of atmospheric methane (1997–2016) and their evaluation using NOAA and AGAGE surface and IAGOS-CARIBIC aircraft observations

2020 ◽  
Vol 20 (9) ◽  
pp. 5787-5809
Author(s):  
Peter H. Zimmermann ◽  
Carl A. M. Brenninkmeijer ◽  
Andrea Pozzer ◽  
Patrick Jöckel ◽  
Franziska Winterstein ◽  
...  
Keyword(s):  
Shale Gas ◽  
General Circulation ◽  
Fossil Fuel ◽  
A Priori ◽  
Circulation Model ◽  
Optimization Procedure ◽  
Rice Cultivation ◽  
Coefficient Of Determination ◽  
Atmospheric Methane ◽  
Tropical Wetlands

Abstract. Methane (CH4) is an important greenhouse gas, and its atmospheric budget is determined by interacting sources and sinks in a dynamic global environment. Methane observations indicate that after almost a decade of stagnation, from 2006, a sudden and continuing global mixing ratio increase took place. We applied a general circulation model to simulate the global atmospheric budget, variability, and trends of methane for the period 1997–2016. Using interannually constant CH4 a priori emissions from 11 biogenic and fossil source categories, the model results are compared with observations from 17 Advanced Global Atmospheric Gases Experiment (AGAGE) and National Oceanic and Atmospheric Administration (NOAA) surface stations and intercontinental Civil Aircraft for the Regular observation of the atmosphere Based on an Instrumented Container (CARIBIC) flights, with > 4800 CH4 samples, gathered on > 320 flights in the upper troposphere and lowermost stratosphere. Based on a simple optimization procedure, methane emission categories have been scaled to reduce discrepancies with the observational data for the period 1997–2006. With this approach, the all-station mean dry air mole fraction of 1780 nmol mol−1 could be improved from an a priori root mean square deviation (RMSD) of 1.31 % to just 0.61 %, associated with a coefficient of determination (R2) of 0.79. The simulated a priori interhemispheric difference of 143.12 nmol mol−1 was improved to 131.28 nmol mol−1, which matched the observations quite well (130.82 nmol mol−1). Analogously, aircraft measurements were reproduced well, with a global RMSD of 1.1 % for the measurements before 2007, with even better results on a regional level (e.g., over India, with an RMSD of 0.98 % and R2=0.65). With regard to emission optimization, this implied a 30.2 Tg CH4 yr−1 reduction in predominantly fossil-fuel-related emissions and a 28.7 Tg CH4 yr−1 increase of biogenic sources. With the same methodology, the CH4 growth that started in 2007 and continued almost linearly through 2013 was investigated, exploring the contributions by four potential causes, namely biogenic emissions from tropical wetlands, from agriculture including ruminant animals, and from rice cultivation, and anthropogenic emissions (fossil fuel sources, e.g., shale gas fracking) in North America. The optimization procedure adopted in this work showed that an increase in emissions from shale gas (7.67 Tg yr−1), rice cultivation (7.15 Tg yr−1), and tropical wetlands (0.58 Tg yr−1) for the period 2006–2013 leads to an optimal agreement (i.e., lowest RMSD) between model results and observations.

scholarly journals Model simulations of atmospheric methane and their evaluation using AGAGE/NOAA surface- and IAGOS-CARIBIC aircraft observations, 1997–2014

2018 ◽  
Author(s):  
Peter H. Zimmermann ◽  
Carl A. M. Brenninkmeijer ◽  
Andrea Pozzer ◽  
Patrick Jöckel ◽  
Andreas Zahn ◽  
...  
Keyword(s):  
Shale Gas ◽  
Atmospheric Chemistry ◽  
General Circulation ◽  
A Priori ◽  
Circulation Model ◽  
Gas Production ◽  
Coefficient Of Determination ◽  
Atmospheric Methane ◽  
Synoptic Variability ◽  
Methane Distribution

Abstract. The global budget and trends of atmospheric methane (CH4) have been simulated with the EMAC atmospheric chemistry – general circulation model for the period 1997 through 2014. Observations from AGAGE and NOAA surface stations and intercontinental CARIBIC flights indicate a transient period of declining methane increase during 1997 through 1999, followed by seven years of stagnation and a sudden resumed increase after 2006. Starting the simulation with a global methane distribution, scaled to match the station measurements in January 1997 and using inter-annually constant CH4 sources from eleven categories together with photochemical and soil sinks, the model reproduces the observations during the transient and constant period from 1997 through 2006 in magnitude as well as seasonal and synoptic variability. The atmospheric CH4 calculations in our model setup are linearly dependent on the source strengths, allowing source segregated simulation of eleven biogenic and fossil emission categories (tagging), with the aim to analyze global observations and derive the source specific CH4 steady state lifetimes. Moreover, tagging enables a-posteriori rescaling of individual emissions with proportional effects on the corresponding inventories and offers a method to approximate the station measurements in terms of lowest RMS. Enhancing the a priori biogenic tropical wetland emissions by ~ 29 Tg/y, compensated by a reduction of anthropogenic fossil CH4 emissions, the all-station mean dry air mole fraction of 1792 nmol/mol could be simulated within a RMS of 0.37 %. The coefficient of determination R2 = 0.87 indicates good agreement with observed variability and the calculated 2000–2005 average interhemispheric methane difference between selected NH and SH stations of 119 nmol/mol matches the observations. The CH4 samples from 95 intercontinental CARIBIC flights for the period 1997–2006 are also accurately simulated by the model, with a 2000–2006 average CH4 mixing ratio of 1786 nmol/mol, and 65 % of the measured variability being captured. This includes tropospheric and stratospheric data. To explain the growth of CH4 from 2007 through 2013 in term of sources, an emission increase of 28.3 Tg/y CH4 is needed. We explore the contributions of two potential causes, one representing natural emissions from wetlands in the tropics and the other anthropogenic shale gas production emissions in North America. A 62.6 % tropical wetland contribution and of 37.4 % by shale gas emissions optimally fit the trend, and simulates CH4 from 2007–2013 with an RMS of 7.1 nmol/mol (0.39 %). The coefficient of determination of R2 = 0.91 indicates even higher significance than before 2006. The 4287 samples collected during 232 CARIBIC flights after 2007 are simulated with an RMS of 1.3 % and R2 = 0.8, indicating that the model reproduces the seasonal and synoptic variability of CH4 in the upper troposphere and lower stratosphere.

Towards AOD1B RL07

2020 ◽  
Author(s):  
Linus Shihora ◽  
Henryk Dobslaw
Keyword(s):  
General Circulation ◽  
A Priori ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Temporal Variations ◽  
Ocean Dynamics ◽  
Global Ocean ◽  
Ocean Bottom ◽  
Data Set ◽  
Priori Information

<p>The Atmosphere and Ocean De-Aliasing Level-1B (AOD1B) product provides a priori information about temporal variations in the Earth's gravity field caused by global mass variability in the atmosphere and ocean and is routinely used as background model in satellite gravimetry. The current version 06 provides Stokes coefficients expanded up to d/o 180 every 3 hours. It is based on ERA-Interim and the ECMWF operational model for the atmosphere, and simulations with the global ocean general circulation model MPIOM consistently forced with the fields from the same atmospheric data-set.</p> <p>We here present preliminary numerical experiments in the development towards a new release 07 of AOD1B. The experiments are performed with the TP10 configuration of MPIOM and include (I) new hourly atmospheric forcing based on the new ERA-5 reanalysis from ECMWF; (II) an improved bathymetry around Antarctica including cavities under the ice shelves; and (III) an explicit implementation of the feedback effects of self-attraction and loading to ocean dynamics. The simulated ocean bottom pressure variability is discussed with respect to AOD1B version 6 as well as in situ ocean observations. A preliminary timeseries of hourly AOD1B-like coefficients for the year 2019 that incorporate the above mentioned improvements will be made available for testing purposes.</p>

scholarly journals Towards constraints on fossil fuel emissions from total column carbon dioxide

2013 ◽  
Vol 13 (8) ◽  
pp. 4349-4357 ◽  
Author(s):  
G. Keppel-Aleks ◽  
P. O. Wennberg ◽  
C. W. O'Dell ◽  
D. Wunch
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Fossil Fuel ◽  
Atmospheric General Circulation Model ◽  
Source Region ◽  
Circulation Model ◽  
Policy Tool ◽  
Total Column ◽  
Gosat Satellite ◽  
Fossil Fuel Emissions

Abstract. We assess the large-scale, top-down constraints on regional fossil fuel emissions provided by observations of atmospheric total column CO2, XCO2. Using an atmospheric general circulation model (GCM) with underlying fossil emissions, we determine the influence of regional fossil fuel emissions on global XCO2 fields. We quantify the regional contrasts between source and upwind regions and probe the sensitivity of atmospheric XCO2 to changes in fossil fuel emissions. Regional fossil fuel XCO2 contrasts can exceed 0.7 ppm based on 2007 emission estimates, but have large seasonal variations due to biospheric fluxes. Contamination by clouds reduces the discernible fossil signatures. Nevertheless, our simulations show that atmospheric fossil XCO2 can be tied to its source region and that changes in the regional XCO2 contrasts scale linearly with emissions. We test the GCM results against XCO2 data from the GOSAT satellite. Regional XCO2 contrasts in GOSAT data generally scale with the predictions from the GCM, but the comparison is limited by the moderate precision of and relatively few observations from the satellite. We discuss how this approach may be useful as a policy tool to verify national fossil emissions, as it provides an independent, observational constraint.

scholarly journals Retrieval of δ<sup>18</sup>O and δD in atmospheric water vapour from ground-based FTIR

2014 ◽  
Vol 7 (1) ◽  
pp. 195-231 ◽  
Author(s):  
N. V. Rokotyan ◽  
V. I. Zakharov ◽  
K. G. Gribanov ◽  
F.-M. Bréon ◽  
J. Jouzel ◽  
...  
Keyword(s):  
Water Vapour ◽  
General Circulation ◽  
Near Infrared ◽  
A Priori ◽  
Circulation Model ◽  
Infrared Region ◽  
Atmospheric Water ◽  
Atmospheric Water Vapour ◽  
Δ18o And Δd ◽  
Atmospheric Transmittance

Abstract. This paper investigates the possibility of retrieving isotopic composition of atmospheric water vapour from high-resolution ground based measurements of atmospheric transmittance spectra in the near-infrared region (4000–11 000 cm−1). Simulated measurements of atmospheric transmittance were analyzed in order to find clear spectral signatures of H218O, HDO and H216O. Appropriate signals of the species of interest were found and also identified in measured spectra recorded by ground-based Fourier transform infrared spectrometer (FTIR) at the Institute of Environmental Physics of Bremen University. A set of H218O, HDO and H216O spectroscopic windows is presented. Theoretical estimations of the retrieval precision indicate that spectra recorded by ground-based FTIR spectrometers can be used to measure the seasonal cycle of δ18O and δD in the atmosphere. Studying the influence of the a priori on retrieval results shows low sensitivity to a priori assumptions. Impact of the uncertainties in spectroscopic line parameters of water isotopologues on precision of the retrieval of δ18O and δD is investigated. Time series of δ18O retrieved from ground-based FTIR spectra are represented for the first time. Comparison with the results of ECHAM5-wiso isotopic general circulation model simulations demonstrates a good agreement for "summer" measurements. Conversely, the comparison of "winter" measurements and modeling result show a discrepancy that demonstrate worse agreement that may be connected with incorrect temperature dependence of spectroscopic parameters.

scholarly journals Technical Note: Latitude-time variations of atmospheric column-average dry air mole fractions of CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O

2012 ◽  
Vol 12 (16) ◽  
pp. 7767-7777 ◽  
Author(s):  
R. Saito ◽  
P. K. Patra ◽  
N. Deutscher ◽  
D. Wunch ◽  
K. Ishijima ◽  
...  
Keyword(s):  
General Circulation ◽  
Fossil Fuel ◽  
Transport Model ◽  
Circulation Model ◽  
Technical Note ◽  
Transport Processes ◽  
Total Carbon ◽  
Poor Correlation ◽  
Model Estimate ◽  
Total Column

Abstract. We present a comparison of an atmospheric general circulation model (AGCM)-based chemistry-transport model (ACTM) simulation with total column measurements of CO2, CH4 and N2O from the Total Carbon Column Observing Network (TCCON). The model is able to capture observed trends, seasonal cycles and inter hemispheric gradients at most sampled locations for all three species. The model-observation agreements are best for CO2, because the simulation uses fossil fuel inventories and an inverse model estimate of non-fossil fuel fluxes. The ACTM captures much of the observed seasonal variability in CO2 and N2O total columns (~81 % variance, R>0.9 between ACTM and TCCON for 19 out of 22 cases). These results suggest that the transport processes in troposphere and stratosphere are well represented in ACTM. Thus the poor correlation between simulated and observed CH4 total columns, particularly at tropical and extra-tropical sites, have been attributed to the uncertainties in surface emissions and loss by hydroxyl radicals. While the upward-looking total column measurements of CO2 contains surface flux signals at various spatial and temporal scales, the N2O measurements are strongly affected by the concentration variations in the upper troposphere and stratosphere.

scholarly journals Climate Variability and Corn Yields in Semiarid Ceará, Brazil

2007 ◽  
Vol 46 (2) ◽  
pp. 226-240 ◽  
Author(s):  
Liqiang Sun ◽  
Huilan Li ◽  
M. Neil Ward ◽  
David F. Moncunill
Keyword(s):  
General Circulation ◽  
Goodness Of Fit ◽  
Crop Yields ◽  
Circulation Model ◽  
Coefficient Of Determination ◽  
Climate Index ◽  
Corn Yield ◽  
Climate Variables ◽  
Potential Predictability ◽  
Weather Index

Abstract Understanding of climate influence on crop yields can help in the design of policies to reduce climate-related vulnerability in many parts of the world, including the target of this case study—the state of Ceará, Brazil. The study has examined the relationships between climate variations and corn yields and, in addition, has estimated the potential predictability of corn yields in Ceará drawing on the now well-established seasonal predictability of the region’s climate based on prevailing patterns of sea surface temperature (SST), especially in the tropical Atlantic and tropical Pacific Oceans. The relationships between corn yields and climate variables have been explored using observed data for the period of 1952–2001. A linear regression–based corn-yield model was evaluated by comparing the model-simulated yields with the observations using three goodness-of-fit measures: the coefficient of determination, the index of agreement, and the mean absolute error. A comparative performance analysis was carried out on several climate variables to determine the most appropriate climate index for simulating corn yields in Ceará. A weather index was defined to measure the severity of drought and flooding conditions in the growing season for corn. The analysis indicated that the weather index is the best climate parameter for simulating corn yields in Ceará. The observed weather index can explain 56.8% of the variance of the observed corn yields. High potential predictability of the weather index was revealed by the evaluation of an ensemble of 10 runs with the NCEP Regional Spectral Model nested into the ECHAM4.5 atmospheric general circulation model, driven with observed SSTs in each season for the period of 1971–2000. Whereas these runs are based on the actual observed SST pattern in each season, other studies have shown that persistence of SST over several months is sufficient for a true predictive capability. The aim here was to show that the SST-forced component of climate variation does translate into the weather features that are important for crop yields. Indeed, the results demonstrate the striking extent to which the year-to-year changes in SST force local climate characteristics that can specify the year-to-year variations in corn yields. The variance of corn yield explained by the SST-driven model was 49.5%.

scholarly journals YAC 1.2.0: An extendable coupling software for Earth system modelling

2016 ◽  
Author(s):  
M. Hanke ◽  
R. Redler ◽  
T. Holfeld ◽  
M. Yastremsky
Keyword(s):  
General Circulation ◽  
A Priori ◽  
Circulation Model ◽  
System Model ◽  
System Modelling ◽  
Earth System ◽  
Parallel Performance ◽  
Neighbourhood Search ◽  
Physical Fields ◽  
Model Components

Abstract. A light-weight software framework has been developed as a library to realise the coupling of Earth system model components. The software provides a parallelised 2-dimensional neighbourhood search, interpolation, and communication for the coupling between any two model components. The software offers flexible coupling of physical fields defined on regular and irregular grids on the sphere without a priori assumptions about the particular grid structure or grid element types. All supported grids can be combined with any of the supported interpolations. We describe our approach and provide an overview about some of the algorithms we are using and the implemented functionality. The parallel performance is examined with a set of realistic use cases. The coupling software is now used for the coupling of the model components in the Icosahedral nonhydrostatic (ICON) general circulation model.

A Predictability Measure Applied to Seasonal Predictions of the Arctic Oscillation

2007 ◽  
Vol 20 (18) ◽  
pp. 4733-4750 ◽  
Author(s):  
Youmin Tang ◽  
Hai Lin ◽  
Jacques Derome ◽  
Michael K. Tippett
Keyword(s):  
Confidence Level ◽  
General Circulation ◽  
Arctic Oscillation ◽  
A Priori ◽  
Circulation Model ◽  
The Arctic ◽  
Ensemble Prediction ◽  
Central Pacific ◽  
The Arctic Oscillation ◽  
Sst Anomalies

Abstract In this study, ensemble seasonal predictions of the Arctic Oscillation (AO) were conducted for 51 winters (1948–98) using a simple global atmospheric general circulation model. A means of estimating a priori the predictive skill of the AO ensemble predictions was developed based on the relative entropy (R) of information theory, which is a measure of the difference between the forecast and climatology probability density functions (PDFs). Several important issues related to the AO predictability, such as the dominant precursors of forecast skill and the degree of confidence that can be placed in an individual forecast, were addressed. It was found that R is a useful measure of the confidence that can be placed on dynamical predictions of the AO. When R is large, the prediction is likely to have a high confidence level whereas when R is small, the prediction skill is more variable. A small R is often accompanied by a relatively weak AO index. The value of R is dominated by the predicted ensemble mean. The relationship identified here, between model skills and the R of an ensemble prediction, offers a practical means of estimating the confidence level of a seasonal forecast of the AO using the dynamical model. Through an analysis of the global sea surface temperature (SST) forcing, it was found that the winter AO-related R is correlated significantly with the amplitude of the SST anomalies over the tropical central Pacific and the North Pacific during the previous October. A large value of R is usually associated with strong SST anomalies in the two regions, whereas a poor prediction with a small R indicates that SST anomalies are likely weak in these two regions and the observed AO anomaly in the specific winter is likely caused by atmospheric internal dynamics.

scholarly journals YAC 1.2.0: new aspects for coupling software in Earth system modelling

2016 ◽  
Vol 9 (8) ◽  
pp. 2755-2769 ◽  
Author(s):  
Moritz Hanke ◽  
René Redler ◽  
Teresa Holfeld ◽  
Maxim Yastremsky
Keyword(s):  
General Circulation ◽  
A Priori ◽  
Circulation Model ◽  
System Model ◽  
System Modelling ◽  
Earth System ◽  
Performance Measurements ◽  
Neighbourhood Search ◽  
Physical Fields ◽  
Model Components

Abstract. A lightweight software library has been developed to realise the coupling of Earth system model components. The software provides parallelised two-dimensional neighbourhood search, interpolation, and communication for the coupling between any two model components. The software offers flexible coupling of physical fields defined on regular and irregular grids on the sphere without a priori assumptions about grid structure or grid element types. All supported grids can be combined with any of the supported interpolations. We describe the new aspects of our approach and provide an overview of the implemented functionality and of some algorithms we use. Preliminary performance measurements for a set of realistic use cases are presented to demonstrate the potential performance and scalability of our approach. YAC 1.2.0 is now used for the coupling of the model components in the Icosahedral Nonhydrostatic (ICON) general circulation model.

Sign in / Sign up

Export Citation Format

Share Document