Comparison of Regional Simulation of Biospheric CO2 Flux from the Updated Version of CarbonTracker Asia with FLUXCOM and Other Inversions over Asia

2020 ◽  
Author(s):  
Samuel Takele Kenea ◽  
Lev Labzovskii ◽  
Tae‐Young Goo ◽  
Shanlan Li ◽  
Young‐Suk Oh ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Transport Model ◽  
Southern Oscillation ◽  
Carbon Sink ◽  
Mixed Forest ◽  
Net Ecosystem Exchange ◽  
Co2 Flux ◽  
Atmospheric Composition ◽  
Carbon Uptake ◽  
The Impact

<p>There are still large uncertainties in the estimates of net ecosystem exchange of CO<sub>2</sub><br>(NEE) with atmosphere in Asia, particularly in the boreal and eastern part of temperate Asia. To<br>understand these uncertainties, we assessed the CarbonTracker Asia (CTA2017) estimates of the<br>spatial and temporal distributions of NEE through a comparison with FLUXCOM and the global<br>inversion models from the Copernicus Atmospheric Monitoring Service (CAMS), Monitoring<br>Atmospheric Composition and Climate (MACC), and Jena CarboScope in Asia, as well as<br>examining the impact of the nesting approach on the optimized NEE flux during the 2001–2013<br>period. The long‐term mean carbon uptake is reduced in Asia, which is −0.32 ± 0.22 PgC yr<sup>‐1</sup>,<br>whereas –0.58 ± 0.26 PgC yr<sup>‐1</sup> is shown from CT2017 (CarbonTracker global). The domain<br>aggregated mean carbon uptake from CTA2017 is found to be lower by 23.8%, 44.8%, and 60.5%<br>than CAMS, MACC, and Jena CarboScope, respectively. For example, both CTA2017 and CT2017<br>models captured the interannual variability (IAV) of the NEE flux with a different magnitude and<br>this leads to divergent annual aggregated results. Differences in the estimated interannual<br>variability of NEE in response to El Niño–Southern Oscillation (ENSO) may result from<br>differences in the transport model resolutions. These inverse models’ results have a substantial<br>difference compared to FLUXCOM, which was found to be –5.54 PgC yr<sup>‐1</sup>. On the one hand, we<br>showed that the large NEE discrepancies between both inversion models and FLUXCOM stem<br>mostly from the tropical forests. On the other hand, CTA2017 exhibits a slightly better correlation<br>with FLUXCOM over grass/shrub, fields/woods/savanna, and mixed forest than CT2017. The land<br>cover inconsistency between CTA2017 and FLUXCOM is therefore one driver of the discrepancy in<br>the NEE estimates. The diurnal averaged NEE flux between CTA2017 and FLUXCOM exhibits<br>better agreement during the carbon uptake period than the carbon release period. Both CTA2017<br>and CT2017 revealed that the overall spatial patterns of the carbon sink and source are similar, but<br>the magnitude varied with seasons and ecosystem types, which is mainly attributed to differences<br>in the transport model resolutions. Our findings indicate that substantial inconsistencies in the<br>inversions and FLUXCOM mainly emerge during the carbon uptake period and over tropical<br>forests. The main problems are underrepresentation of FLUXCOM NEE estimates by limited eddy<br>covariance flux measurements, the role of CO<sub>2</sub> emissions from land use change not accounted for<br>by FLUXCOM, sparseness of surface observations of CO<sub>2</sub> concentrations used by the assimilation<br>systems, and land cover inconsistency. This suggested that further scrutiny on the FLUXCOM and<br>inverse estimates is most likely required. Such efforts will reduce inconsistencies across various<br>NEE estimates over Asia, thus mitigating ecosystem‐driven errors that propagate the global<br>carbon budget. Moreover, this work also recommends further investigation on how the<br>changes/updates made in CarbonTracker affect the interannual variability of the aggregate and<br>spatial pattern of NEE flux in response to the ENSO effect over the region of interest.</p>

scholarly journals Comparison of Regional Simulation of Biospheric CO2 Flux from the Updated Version of CarbonTracker Asia with FLUXCOM and Other Inversions over Asia

2020 ◽  
Vol 12 (1) ◽  
pp. 145 ◽  
Author(s):  
Samuel Takele Kenea ◽  
Lev D. Labzovskii ◽  
Tae-Young Goo ◽  
Shanlan Li ◽  
Young-Suk Oh ◽  
...  
Keyword(s):  
Land Cover ◽  
Interannual Variability ◽  
Tropical Forests ◽  
Transport Model ◽  
Southern Oscillation ◽  
Carbon Sink ◽  
Mixed Forest ◽  
Atmospheric Composition ◽  
Carbon Uptake ◽  
The Impact

There are still large uncertainties in the estimates of net ecosystem exchange of CO2 (NEE) with atmosphere in Asia, particularly in the boreal and eastern part of temperate Asia. To understand these uncertainties, we assessed the CarbonTracker Asia (CTA2017) estimates of the spatial and temporal distributions of NEE through a comparison with FLUXCOM and the global inversion models from the Copernicus Atmospheric Monitoring Service (CAMS), Monitoring Atmospheric Composition and Climate (MACC), and Jena CarboScope in Asia, as well as examining the impact of the nesting approach on the optimized NEE flux during the 2001–2013 period. The long-term mean carbon uptake is reduced in Asia, which is −0.32 ± 0.22 PgC yr−1, whereas −0.58 ± 0.26 PgC yr−1 is shown from CT2017 (CarbonTracker global). The domain aggregated mean carbon uptake from CTA2017 is found to be lower by 23.8%, 44.8%, and 60.5% than CAMS, MACC, and Jena CarboScope, respectively. For example, both CTA2017 and CT2017 models captured the interannual variability (IAV) of the NEE flux with a different magnitude and this leads to divergent annual aggregated results. Differences in the estimated interannual variability of NEE in response to El Niño–Southern Oscillation (ENSO) may result from differences in the transport model resolutions. These inverse models’ results have a substantial difference compared to FLUXCOM, which was found to be −5.54 PgC yr−1. On the one hand, we showed that the large NEE discrepancies between both inversion models and FLUXCOM stem mostly from the tropical forests. On the other hand, CTA2017 exhibits a slightly better correlation with FLUXCOM over grass/shrub, fields/woods/savanna, and mixed forest than CT2017. The land cover inconsistency between CTA2017 and FLUXCOM is therefore one driver of the discrepancy in the NEE estimates. The diurnal averaged NEE flux between CTA2017 and FLUXCOM exhibits better agreement during the carbon uptake period than the carbon release period. Both CTA2017 and CT2017 revealed that the overall spatial patterns of the carbon sink and source are similar, but the magnitude varied with seasons and ecosystem types, which is mainly attributed to differences in the transport model resolutions. Our findings indicate that substantial inconsistencies in the inversions and FLUXCOM mainly emerge during the carbon uptake period and over tropical forests. The main problems are underrepresentation of FLUXCOM NEE estimates by limited eddy covariance flux measurements, the role of CO2 emissions from land use change not accounted for by FLUXCOM, sparseness of surface observations of CO2 concentrations used by the assimilation systems, and land cover inconsistency. This suggested that further scrutiny on the FLUXCOM and inverse estimates is most likely required. Such efforts will reduce inconsistencies across various NEE estimates over Asia, thus mitigating ecosystem-driven errors that propagate the global carbon budget. Moreover, this work also recommends further investigation on how the changes/updates made in CarbonTracker affect the interannual variability of the aggregate and spatial pattern of NEE flux in response to the ENSO effect over the region of interest.

scholarly journals On the ability of a global atmospheric inversion to constrain variations of CO<sub>2</sub> fluxes over Amazonia

2015 ◽  
Vol 15 (2) ◽  
pp. 1915-1952
Author(s):  
L. Molina ◽  
G. Broquet ◽  
P. Imbach ◽  
F. Chevallier ◽  
B. Poulter ◽  
...  
Keyword(s):  
South America ◽  
Amazon Basin ◽  
Transport Model ◽  
Net Ecosystem Exchange ◽  
Extreme Rainfall ◽  
Atmospheric Composition ◽  
Interannual Variations ◽  
The Impact ◽  
Seasonal And Interannual Variations ◽  
Atmospheric Inversion

Abstract. The exchanges of carbon, water, and energy between the atmosphere and the Amazon Basin have global implications for current and future climate. Here, the global atmospheric inversion system of the Monitoring of Atmospheric Composition and Climate service (MACC) was used to further study the seasonal and interannual variations of biogenic CO2 fluxes in Amazonia. The system assimilated surface measurements of atmospheric CO2 mole fractions made over more than 100 sites over the globe into an atmospheric transport model. This study added four surface stations located in tropical South America, a region poorly covered by CO2 observations. The estimates of net ecosystem exchange (NEE) optimized by the inversion were compared to independent estimates of NEE upscaled from eddy-covariance flux measurements in Amazonia, and against reports on the seasonal and interannual variations of the land sink in South America from the scientific literature. We focused on the impact of the interannual variation of the strong droughts in 2005 and 2010 (due to severe and longer-than-usual dry seasons), and of the extreme rainfall conditions registered in 2009. The spatial variations of the seasonal and interannual variability of optimized NEE were also investigated. While the inversion supported the assumption of strong spatial heterogeneity of these variations, the results revealed critical limitations that prevent global inversion frameworks from capturing the data-driven seasonal patterns of fluxes across Amazonia. In particular, it highlighted issues due to the configuration of the observation network in South America and the lack of continuity of the measurements. However, some robust patterns from the inversion seemed consistent with the abnormal moisture conditions in 2009.

scholarly journals Prior biosphere model impact on global terrestrial CO<sub>2</sub> fluxes estimated from OCO-2 retrievals

2019 ◽  
Vol 19 (20) ◽  
pp. 13267-13287 ◽  
Author(s):  
Sajeev Philip ◽  
Matthew S. Johnson ◽  
Christopher Potter ◽  
Vanessa Genovesse ◽  
David F. Baker ◽  
...  
Keyword(s):  
Transport Model ◽  
Net Ecosystem Exchange ◽  
Co2 Flux ◽  
Inverse Model ◽  
Chemical Transport Model ◽  
Error Statistics ◽  
Prior Model ◽  
The Tropics ◽  
Biosphere Model ◽  
The Impact

Abstract. This study assesses the impact of different state of the art global biospheric CO2 flux models, when applied as prior information, on inverse model “top-down” estimates of terrestrial CO2 fluxes obtained when assimilating Orbiting Carbon Observatory 2 (OCO-2) observations. This is done with a series of observing system simulation experiments (OSSEs) using synthetic CO2 column-average dry air mole fraction (XCO2) retrievals sampled at the OCO-2 satellite spatiotemporal frequency. The OSSEs utilized a 4-D variational (4D-Var) assimilation system with the GEOS-Chem global chemical transport model (CTM) to estimate CO2 net ecosystem exchange (NEE) fluxes using synthetic OCO-2 observations. The impact of biosphere models in inverse model estimates of NEE is quantified by conducting OSSEs using the NASA-CASA, CASA-GFED, SiB-4, and LPJ models as prior estimates and using NEE from the multi-model ensemble mean of the Multiscale Synthesis and Terrestrial Model Intercomparison Project as the “truth”. Results show that the assimilation of simulated XCO2 retrievals at OCO-2 observing modes over land results in posterior NEE estimates which generally reproduce “true” NEE globally and over terrestrial TransCom-3 regions that are well-sampled. However, we find larger spread among posterior NEE estimates, when using different prior NEE fluxes, in regions and seasons that have limited OCO-2 observational coverage and a large range in “bottom-up” NEE fluxes. Seasonally averaged posterior NEE estimates had standard deviations (SD) of ∼10 % to ∼50 % of the multi-model-mean NEE for different TransCom-3 land regions with significant NEE fluxes (regions/seasons with a NEE flux ≥0.5 PgC yr−1). On a global average, the seasonally averaged residual impact of the prior model NEE assumption on the posterior NEE spread is ∼10 %–20 % of the posterior NEE mean. Additional OCO-2 OSSE simulations demonstrate that posterior NEE estimates are also sensitive to the assumed prior NEE flux uncertainty statistics, with spread in posterior NEE estimates similar to those when using variable prior model NEE fluxes. In fact, the sensitivity of posterior NEE estimates to prior error statistics was larger than prior flux values in some regions/times in the tropics and Southern Hemisphere where sufficient OCO-2 data were available and large differences between the prior and truth were evident. Overall, even with the availability of spatiotemporally dense OCO-2 data, noticeable residual differences (up to ∼20 %–30 % globally and 50 % regionally) in posterior NEE flux estimates remain that were caused by the choice of prior model flux values and the specification of prior flux uncertainties.

scholarly journals On the ability of a global atmospheric inversion to constrain variations of CO<sub>2</sub> fluxes over Amazonia

2015 ◽  
Vol 15 (14) ◽  
pp. 8423-8438 ◽  
Author(s):  
L. Molina ◽  
G. Broquet ◽  
P. Imbach ◽  
F. Chevallier ◽  
B. Poulter ◽  
...  
Keyword(s):  
South America ◽  
Amazon Basin ◽  
Transport Model ◽  
Net Ecosystem Exchange ◽  
Extreme Rainfall ◽  
Atmospheric Composition ◽  
Interannual Variations ◽  
The Impact ◽  
Seasonal And Interannual Variations ◽  
Atmospheric Inversion

Abstract. The exchanges of carbon, water and energy between the atmosphere and the Amazon basin have global implications for the current and future climate. Here, the global atmospheric inversion system of the Monitoring of Atmospheric Composition and Climate (MACC) service is used to study the seasonal and interannual variations of biogenic CO2 fluxes in Amazonia during the period 2002–2010. The system assimilated surface measurements of atmospheric CO2 mole fractions made at more than 100 sites over the globe into an atmospheric transport model. The present study adds measurements from four surface stations located in tropical South America, a region poorly covered by CO2 observations. The estimates of net ecosystem exchange (NEE) optimized by the inversion are compared to an independent estimate of NEE upscaled from eddy-covariance flux measurements in Amazonia. They are also qualitatively evaluated against reports on the seasonal and interannual variations of the land sink in South America from the scientific literature. We attempt at assessing the impact on NEE of the strong droughts in 2005 and 2010 (due to severe and longer-than-usual dry seasons) and the extreme rainfall conditions registered in 2009. The spatial variations of the seasonal and interannual variability of optimized NEE are also investigated. While the inversion supports the assumption of strong spatial heterogeneity of these variations, the results reveal critical limitations of the coarse-resolution transport model, the surface observation network in South America during the recent years and the present knowledge of modelling uncertainties in South America that prevent our inversion from capturing the seasonal patterns of fluxes across Amazonia. However, some patterns from the inversion seem consistent with the anomaly of moisture conditions in 2009.

scholarly journals Prior biosphere model impact on global terrestrial CO<sub>2</sub> fluxes estimated from OCO-2 retrievals

2019 ◽  
Author(s):  
Sajeev Philip ◽  
Matthew S. Johnson ◽  
Christopher Potter ◽  
Vanessa Genovesse ◽  
David F. Baker ◽  
...  
Keyword(s):  
Transport Model ◽  
Temporal Frequency ◽  
Net Ecosystem Exchange ◽  
Co2 Flux ◽  
Chemical Transport Model ◽  
Error Statistics ◽  
Prior Model ◽  
Spatio Temporal ◽  
State Of The Science ◽  
The Impact

Abstract. This study assesses the impact of different state-of-the-science global biospheric CO2 flux models, when applied as prior information, on inverse modeling top-down estimates of terrestrial CO2 fluxes obtained when assimilating Orbiting Carbon Observatory 2 (OCO-2) observations. This is done with a series of Observing System Simulation Experiments (OSSEs) using synthetic CO2 column-average dry air mole fraction (XCO2) retrievals sampled at the OCO-2 satellite spatio-temporal frequency. The OSSEs used the four-dimensional variational (4D-Var) assimilation system with the GEOS-Chem global chemical transport model (CTM) to estimate CO2 net ecosystem exchange (NEE) fluxes using synthetic OCO-2 observations. The impact of biosphere models in inverse model estimates of NEE is quantified by conducting OSSEs using the NASA-CASA, CASA-GFED, SiB-4 and LPJ models as prior estimates and using NEE from the multi-model ensemble mean of the Multiscale Synthesis and Terrestrial Model Intercomparison Project as the truth. Results show that the assimilation of simulated XCO2 retrievals at OCO-2 observing modes over land results in posterior NEE estimates which generally reproduce true NEE globally and over terrestrial TransCom-3 regions that are well-sampled. However, we find larger spread among posterior NEE estimates, when using different prior NEE fluxes, in regions and seasons that have limited OCO-2 observational coverage and a large range in bottom-up NEE fluxes. Posterior NEE estimates had seasonally-averaged posterior NEE standard deviation (SD) of ~ 10 % to ~ 50 % of the multi-model-mean NEE for different TransCom-3 land regions with significant NEE fluxes (regions/seasons with a NEE flux ≥ 0.5 PgC yr−1). On a global average, the seasonally-averaged residual impact of the prior model NEE assumption on posterior NEE spread is ~ 10–20 % of the posterior NEE mean. Additional OCO-2 OSSE simulations demonstrate that posterior NEE estimates are also sensitive to the assumed prior NEE flux uncertainty statistics, with spread in posterior NEE estimates similar to those when using variable prior model NEE fluxes. In fact, the sensitivity of posterior NEE estimates to prior error statistics was larger compared to prior flux values in some regions/times of the Tropics and Southern Hemisphere where sufficient OCO-2 data was available and large differences between the prior and truth were evident. Overall, even with the availability of dense OCO-2 data, noticeable residual differences (up to ~ 20–30 % globally and 50 % regionally) in posterior NEE flux estimates remain that were caused by the choice of prior model flux values and the specification of prior flux uncertainties.

scholarly journals Extending methane profiles from aircraft into the stratosphere for satellite total column validation using the ECMWF C-IFS and TOMCAT/SLIMCAT 3-D model

2017 ◽  
Vol 17 (11) ◽  
pp. 6663-6678 ◽  
Author(s):  
Shreeya Verma ◽  
Julia Marshall ◽  
Mark Parrington ◽  
Anna Agustí-Panareda ◽  
Sebastien Massart ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Transport Model ◽  
A Priori ◽  
Atmospheric Composition ◽  
Random Errors ◽  
Chemical Transport Model ◽  
Spatial Coverage ◽  
Forecasting System ◽  
The Impact ◽  
Total Column

Abstract. Airborne observations of greenhouse gases are a very useful reference for validation of satellite-based column-averaged dry air mole fraction data. However, since the aircraft data are available only up to about 9–13 km altitude, these profiles do not fully represent the depth of the atmosphere observed by satellites and therefore need to be extended synthetically into the stratosphere. In the near future, observations of CO2 and CH4 made from passenger aircraft are expected to be available through the In-Service Aircraft for a Global Observing System (IAGOS) project. In this study, we analyse three different data sources that are available for the stratospheric extension of aircraft profiles by comparing the error introduced by each of them into the total column and provide recommendations regarding the best approach. First, we analyse CH4 fields from two different models of atmospheric composition – the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System for Composition (C-IFS) and the TOMCAT/SLIMCAT 3-D chemical transport model. Secondly, we consider scenarios that simulate the effect of using CH4 climatologies such as those based on balloons or satellite limb soundings. Thirdly, we assess the impact of using a priori profiles used in the satellite retrievals for the stratospheric part of the total column. We find that the models considered in this study have a better estimation of the stratospheric CH4 as compared to the climatology-based data and the satellite a priori profiles. Both the C-IFS and TOMCAT models have a bias of about −9 ppb at the locations where tropospheric vertical profiles will be measured by IAGOS. The C-IFS model, however, has a lower random error (6.5 ppb) than TOMCAT (12.8 ppb). These values are well within the minimum desired accuracy and precision of satellite total column XCH4 retrievals (10 and 34 ppb, respectively). In comparison, the a priori profile from the University of Leicester Greenhouse Gases Observing Satellite (GOSAT) Proxy XCH4 retrieval and climatology-based data introduce larger random errors in the total column, being limited in spatial coverage and temporal variability. Furthermore, we find that the bias in the models varies with latitude and season. Therefore, applying appropriate bias correction to the model fields before using them for profile extension is expected to further decrease the error contributed by the stratospheric part of the profile to the total column.

scholarly journals The impact of the 2015/2016 El Niño on global photosynthesis using satellite remote sensing

2018 ◽  
Vol 373 (1760) ◽  
pp. 20170409 ◽  
Author(s):  
Xiangzhong Luo ◽  
Trevor F. Keenan ◽  
Joshua B. Fisher ◽  
Juan-Carlos Jiménez-Muñoz ◽  
Jing M. Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Carbon Cycle ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Carbon Sink ◽  
Global Climate ◽  
Prognostic Models ◽  
Positive Anomaly ◽  
The Impact

The El Niño-Southern Oscillation exerts a large influence on global climate regimes and on the global carbon cycle. Although El Niño is known to be associated with a reduction of the global total land carbon sink, results based on prognostic models or measurements disagree over the relative contribution of photosynthesis to the reduced sink. Here, we provide an independent remote sensing-based analysis on the impact of the 2015–2016 El Niño on global photosynthesis using six global satellite-based photosynthesis products and a global solar-induced fluorescence (SIF) dataset. An ensemble of satellite-based photosynthesis products showed a negative anomaly of −0.7 ± 1.2 PgC in 2015, but a slight positive anomaly of 0.05 ± 0.89 PgC in 2016, which when combined with observations of the growth rate of atmospheric carbon dioxide concentrations suggests that the reduction of the land residual sink was likely dominated by photosynthesis in 2015 but by respiration in 2016. The six satellite-based products unanimously identified a major photosynthesis reduction of −1.1 ± 0.52 PgC from savannahs in 2015 and 2016, followed by a highly uncertain reduction of −0.22 ± 0.98 PgC from rainforests. Vegetation in the Northern Hemisphere enhanced photosynthesis before and after the peak El Niño, especially in grasslands (0.33 ± 0.13 PgC). The patterns of satellite-based photosynthesis ensemble mean were corroborated by SIF, except in rainforests and South America, where the anomalies of satellite-based photosynthesis products also diverged the most. We found the inter-model variation of photosynthesis estimates was strongly related to the discrepancy between moisture forcings for models. These results highlight the importance of considering multiple photosynthesis proxies when assessing responses to climatic anomalies. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

Climatological Biomass Burning CO – Where it comes from and where it goes.

2020 ◽  
Author(s):  
Nikos Daskalakis ◽  
Maria Kanakidou ◽  
Mihalis Vrekoussis ◽  
Laura Gallardo
Keyword(s):  
Biomass Burning ◽  
Transport Model ◽  
Source Region ◽  
Atmospheric Composition ◽  
Anthropogenic Sources ◽  
3 Dimensional ◽  
Source Regions ◽  
The World ◽  
Transport Patterns ◽  
The Impact

&lt;p&gt;Carbon Monoxide (CO) is an important atmospheric trace gas, and among the key O&lt;sub&gt;3&lt;/sub&gt; precursors in the troposphere, alongside NO&lt;sub&gt;x&lt;/sub&gt; and VOCs. It is among the most important sinks of OH radical in the atmosphere, which controls lifetime of CH&lt;sub&gt;4&lt;/sub&gt; &amp;#8212; a major greenhouse gas. Biomass burning sources contribute about 25% to the global emissions of CO, with the remaining CO being either emitted from anthropogenic sources, or being chemically formed in the atmosphere. Because of CO tropospheric lifetime is about two months; it can be transported in the atmosphere thus its sources have a hemispheric impact on atmospheric composition.&lt;/p&gt;&lt;p&gt;The extent of the impact of biomass burning to remote areas of the world through long range transport is here investigated using the global 3-dimensional chemistry transport model TM4-ECPL. For this, tagged biomass burning CO tracers from the 13 different HTAP (land) source regions are used in the model in order to evaluate the contribution of each source region to the CO concentrations in the 170 HTAP receptor regions that originate from biomass burning. The global simulations cover the period 1994&amp;#8212;2015 in order to derive climatological transport patterns for CO and assess the contribution of each of the source regions to each of the receptor regions in the global troposphere. The CO simulations are evaluated by comparison with satellite observations from MOPITT and ground based observations from WDCGG. We show the significant impact of biomass burning emissions to the most remote regions of the world.&lt;/p&gt;

scholarly journals Ammonia in the summertime Arctic marine boundary layer: sources, sinks, and implications

2016 ◽  
Vol 16 (4) ◽  
pp. 1937-1953 ◽  
Author(s):  
Gregory R. Wentworth ◽  
Jennifer G. Murphy ◽  
Betty Croft ◽  
Randall V. Martin ◽  
Jeffrey R. Pierce ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Transport Model ◽  
Canadian Arctic ◽  
Atmospheric Composition ◽  
Chemical Transport Model ◽  
Data Set ◽  
Baffin Bay ◽  
Melt Ponds ◽  
Ambient Nh3 ◽  
The Impact

Abstract. Continuous hourly measurements of gas-phase ammonia (NH3(g)) were taken from 13 July to 7 August 2014 on a research cruise throughout Baffin Bay and the eastern Canadian Arctic Archipelago. Concentrations ranged from 30 to 650 ng m−3 (40–870 pptv) with the highest values recorded in Lancaster Sound (74°13′ N, 84°00′ W). Simultaneous measurements of total ammonium ([NHx]), pH and temperature in the ocean and in melt ponds were used to compute the compensation point (χ), which is the ambient NH3(g) concentration at which surface–air fluxes change direction. Ambient NH3(g) was usually several orders of magnitude larger than both χocean and χMP (< 0.4–10 ng m3) indicating these surface pools are net sinks of NH3. Flux calculations estimate average net downward fluxes of 1.4 and 1.1 ng m−2 s−1 for the open ocean and melt ponds, respectively. Sufficient NH3(g) was present to neutralize non-sea-salt sulfate (nss-SO42−) in the boundary layer during most of the study. This finding was corroborated with a historical data set of PM2.5 composition from Alert, Nunavut (82°30′ N, 62°20′ W) wherein the median ratio of NH4+/nss-SO42− equivalents was greater than 0.75 in June, July and August. The GEOS-Chem chemical transport model was employed to examine the impact of NH3(g) emissions from seabird guano on boundary-layer composition and nss-SO42− neutralization. A GEOS-Chem simulation without seabird emissions underestimated boundary layer NH3(g) by several orders of magnitude and yielded highly acidic aerosol. A simulation that included seabird NH3 emissions was in better agreement with observations for both NH3(g) concentrations and nss-SO42− neutralization. This is strong evidence that seabird colonies are significant sources of NH3 in the summertime Arctic, and are ubiquitous enough to impact atmospheric composition across the entire Baffin Bay region. Large wildfires in the Northwest Territories were likely an important source of NH3, but their influence was probably limited to the Central Canadian Arctic. Implications of seabird-derived N-deposition to terrestrial and aquatic ecosystems are also discussed.

scholarly journals Does Global Warming Cause Intensified Interannual Hydroclimate Variability?

2012 ◽  
Vol 25 (9) ◽  
pp. 3355-3372 ◽  
Author(s):  
Richard Seager ◽  
Naomi Naik ◽  
Laura Vogel
Keyword(s):  
Global Warming ◽  
Interannual Variability ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Scientific Basis ◽  
Specific Humidity ◽  
Forced Circulation ◽  
Almost Everywhere ◽  
Circulation Anomalies ◽  
The Impact

The idea that global warming leads to more droughts and floods has become commonplace without clear indication of what is meant by this statement. Here, the authors examine one aspect of this problem and assess whether interannual variability of precipitation P minus evaporation E becomes stronger in the twenty-first century compared to the twentieth century, as deduced from an ensemble of models participating in Coupled Model Intercomparison Project 3. It is shown that indeed interannual variability of P − E does increase almost everywhere across the planet, with a few notable exceptions such as southwestern North America and some subtropical regions. The variability increases most at the equator and the high latitudes and least in the subtropics. Although most interannual P − E variability arises from internal atmosphere variability, the primary potentially predictable component is related to the El Niño–Southern Oscillation (ENSO). ENSO-driven interannual P − E variability clearly increases in amplitude in the tropical Pacific, but elsewhere the changes are more complex. This is not surprising in that ENSO-driven P − E anomalies are primarily caused by circulation anomalies combining with the climatological humidity field. As climate warms and the specific humidity increases, this term leads to an intensification of ENSO-driven P − E variability. However, ENSO-driven circulation anomalies also change, in some regions amplifying but in others opposing and even overwhelming the impact of rising specific humidity. Consequently, there is sound scientific basis for anticipating a general increase in interannual P − E variability, but the predictable component will depend in a more complex way on both thermodynamic responses to global warming and on how tropically forced circulation anomalies alter.

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