National Oceanic And Atmospheric Administration/Earth System Research Laboratory Research Articles

Constraining the budget of atmospheric carbonyl sulfide using a 3-D chemical transport model

Abstract. Carbonyl sulfide (OCS) has emerged as a valuable proxy for photosynthetic uptake of carbon dioxide (CO2) and is known to be important in the formation of aerosols in the stratosphere. However, uncertainties in the global OCS budget remain large. This is mainly due to the following three flux terms: vegetation uptake, soil uptake and oceanic emissions. Bottom-up estimates do not yield a closed budget, which is thought to be due to tropical emissions of OCS that are not accounted for. Here we present a simulation of atmospheric OCS over the period 2004–2018 using the TOMCAT 3-D chemical transport model that is aimed at better constraining some terms in the OCS budget. Vegetative uptake of OCS is estimated by scaling gross primary productivity (GPP) output from the Joint UK Land Environment Simulator (JULES) using the leaf relative uptake (LRU) approach. The remaining surface budget terms are taken from available literature flux inventories and adequately scaled to bring the budget into balance. The model is compared with limb-sounding satellite observations made by the Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS) and surface flask measurements from 14 National Oceanic and Atmospheric Administration – Earth System Research Laboratory (NOAA-ESRL) sites worldwide. We find that calculating vegetative uptake using the LRU underestimates the surface seasonal cycle amplitude (SCA) in the Northern Hemisphere (NH) mid-latitudes and high latitudes by approximately 37 ppt (35 %). The inclusion of a large tropical source is able to balance the global budget, but further improvement to the SCA and phasing would likely require a flux inversion scheme. Compared to co-located ACE-FTS OCS profiles between 5 and 30 km, TOMCAT remains within 25 ppt (approximately 5 % of mean tropospheric concentration) of the measurements throughout the majority of this region and lies within the standard deviation of these measurements. This provides confidence in the representation of atmospheric loss and surface fluxes of OCS in the model. Atmospheric sinks account for 154 Gg S of the annual budget, which is 10 %–50 % larger than previous studies. Comparing the surface monthly anomalies from the NOAA-ESRL flask data to the model simulations shows a root-mean-square error range of 3.3–25.8 ppt. We estimate the total biosphere uptake to be 951 Gg S, which is in the range of recent inversion studies (893–1053 Gg S), but our terrestrial vegetation flux accounts for 629 Gg S of the annual budget, which is lower than other recent studies (657–756 Gg S). However, to close the budget, we compensate for this with a large annual oceanic emission term of 689 Gg S focused over the tropics, which is much larger than bottom-up estimates (285 Gg S). Hence, we agree with recent findings that missing OCS sources likely originate from the tropical region. This work shows that satellite OCS profiles offer a good constraint on atmospheric sinks of OCS through the troposphere and stratosphere and are therefore useful for helping to improve surface budget terms. This work also shows that the LRU approach is an adequate representation of the OCS vegetative uptake, but this method could be improved by various means, such as using a higher-resolution GPP product or plant-functional-type-dependent LRU. Future work will utilise TOMCAT in a formal inversion scheme to better quantify the OCS budget.

Measuring the impact of additional instrumentation on the skill of numerical weather prediction models at forecasting wind ramp events during the first Wind Forecast Improvement Project (WFIP)

AbstractThe first Wind Forecast Improvement Project (WFIP) was a DOE and NOAA‐funded 2‐year‐long observational, data assimilation, and modeling study with a 1‐year‐long field campaign aimed at demonstrating improvements in the accuracy of wind forecasts generated by the assimilation of additional observations for wind energy applications. In this paper, we present the results of applying a Ramp Tool and Metric (RT&M), developed during WFIP, to measure the skill of the 13‐km grid spacing National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL) Rapid Refresh (RAP) model at forecasting wind ramp events. To measure the impact on model skill generated by the additional observations, controlled data‐denial RAP simulations were run for six separate 7 to 12‐day periods (for a total of 55 days) over different seasons.The RT&M identifies ramp events in the time series of observed and forecast power, matches in time each forecast ramp event with the most appropriate observed ramp event, and computes the skill score of the forecast model penalizing both timing and amplitude errors. Because no unique definition of a ramp event exists (in terms of a single threshold of change in power over a single time duration), the RT&M computes integrated skill over a range of power change (Δp) and time period (Δt) values.A statistically significant improvement of the ramp event forecast skill is found through the assimilation of the special WFIP data in two different study areas, and variations in model skill between up‐ramp versus down‐ramp events are found.

Advances in representing interactive methane in ModelE2-YIBs (version 1.1)

Abstract. Methane (CH4) is both a greenhouse gas and a precursor of tropospheric ozone, making it an important focus of chemistry–climate interactions. Methane has both anthropogenic and natural emission sources, and reaction with the atmosphere's principal oxidizing agent, the hydroxyl radical (OH), is the dominant tropospheric loss process of methane. The tight coupling between methane and OH abundances drives indirect linkages between methane and other short-lived air pollutants and prompts the use of interactive methane chemistry in global chemistry–climate modeling. In this study, an updated contemporary inventory of natural methane emissions and the soil sink is developed using an optimization procedure that applies published emissions data to the NASA GISS ModelE2-Yale Interactive terrestrial Biosphere (ModelE2-YIBs) global chemistry–climate model. Methane observations from the global surface air-sampling network of the Earth System Research Laboratory (ESRL) of the US National Oceanic and Atmospheric Administration (NOAA) are used to guide refinement of the natural methane inventory. The wetland methane flux is calculated as a best fit; thus, the accuracy of this derived flux assumes accurate simulation of methane chemical loss in the atmosphere and accurate prescription of the other methane fluxes (anthropogenic and natural). The optimization process indicates global annual wetland methane emissions of 140 Tg CH4 yr−1. The updated inventory includes total global annual methane emissions from natural sources of 181 Tg CH4 yr−1 and a global annual methane soil sink of 60 Tg CH4 yr−1. An interactive methane simulation is run using ModelE2-YIBs, applying dynamic methane emissions and the updated natural methane emissions inventory that results from the optimization process. The simulated methane chemical lifetime of 10.4±0.1 years corresponds well to observed lifetimes. The simulated year 2005 global-mean surface methane concentration is 1.1 % higher than the observed value from the NOAA ESRL measurements. Comparison of the simulated atmospheric methane distribution with the NOAA ESRL surface observations at 50 measurement locations finds that the simulated annual methane mixing ratio is within 1 % (i.e., +1 % to −1 %) of the observed value at 76 % of locations. Considering the 50 stations, the mean relative difference between the simulated and observed annual methane mixing ratio is a model overestimate of only 0.5 %. Comparison of simulated annual column-averaged methane concentrations with SCIAMACHY satellite retrievals provides an independent post-optimization evaluation of modeled methane. The comparison finds a slight model underestimate in 95 % of grid cells, suggesting that the applied methane source in the model is slightly underestimated or the model's methane sink strength is slightly too strong outside of the surface layer. Overall, the strong agreement between simulated and observed methane lifetimes and concentrations indicates that the ModelE2-YIBs chemistry–climate model is able to capture the principal processes that control atmospheric methane.

Evaluating and Improving NWP Forecast Models for the Future: How the Needs of Offshore Wind Energy Can Point the Way

AbstractTo advance the understanding of meteorological processes in offshore coastal regions, the spatial variability of wind profiles must be characterized and uncertainties (errors) in NWP model wind forecasts quantified. These gaps are especially critical for the new offshore wind energy industry, where wind profile measurements in the marine atmospheric layer spanned by wind turbine rotor blades, generally 50–200 m above mean sea level (MSL), have been largely unavailable. Here, high-quality wind profile measurements were available every 15 min from the National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL)’s high-resolution Doppler lidar (HRDL) during a monthlong research cruise in the Gulf of Maine for the 2004 New England Air Quality Study. These measurements were compared with retrospective NWP model wind forecasts over the area using two NOAA forecast-modeling systems [North American Mesoscale Forecast System (NAM) and Rapid Refresh (RAP)]. HRDL profile measurements quantified model errors, including their dependence on height above sea level, diurnal cycle, and forecast lead time. Typical model wind speed errors were ∼2.5 m s−1, and vector-wind errors were ∼4 m s−1. Short-term forecast errors were larger near the surface—30% larger below 100 m than above and largest for several hours after local midnight (biased low). Longer-term, 12-h forecasts had the largest errors after local sunset (biased high). At more than 3-h lead times, predictions from finer-resolution models exhibited larger errors. Horizontal variability of winds, measured as the ship traversed the Gulf of Maine, was significant and raised questions about whether modeled fields, which appeared smooth in comparison, were capturing this variability. If not, horizontal arrays of high-quality, vertical-profiling devices will be required for wind energy resource assessment offshore. Such measurement arrays are also needed to improve NWP models.

CO2 annual and semiannual cycles from multiple satellite retrievals and models

AbstractSatellite CO2 retrievals from the Greenhouse gases Observing SATellite (GOSAT), Atmospheric Infrared Sounder (AIRS), and Tropospheric Emission Spectrometer (TES) and in situ measurements from the National Oceanic and Atmospheric Administration ‐ Earth System Research Laboratory (NOAA‐ESRL) Surface CO2 and Total Carbon Column Observing Network (TCCON) are utilized to explore the CO2 variability at different altitudes. A multiple regression method is used to calculate the CO2 annual cycle and semiannual cycle amplitudes from different data sets. The CO2 annual cycle and semiannual cycle amplitudes for GOSAT XCO2 and TCCON XCO2 are consistent but smaller than those seen in the NOAA‐ESRL surface data. The CO2 annual and semiannual cycles are smallest in the AIRS midtropospheric CO2 compared with other data sets in the Northern Hemisphere. The amplitudes for the CO2 annual cycle and semiannual cycle from GOSAT, TES, and AIRS CO2 are small and comparable to each other in the Southern Hemisphere. Similar regression analysis is applied to the Model for OZone And Related chemical Tracers‐2 and CarbonTracker model CO2. The convolved model CO2 annual cycle and semiannual cycle amplitudes are similar to those from the satellite CO2 retrievals, although the models tend to underestimate the CO2 seasonal cycle amplitudes in the Northern Hemisphere midlatitudes and underestimate the CO2 semiannual cycle amplitudes in the high latitudes. These results can be used to better understand the vertical structures for the CO2 annual cycle and semiannual cycle and help identify deficiencies in the models, which are very important for the carbon budget study.

High-precision surface-level CO2 and CH4 using off-axis integrated cavity output spectroscopy (OA-ICOS) over Shadnagar, India

An enhanced performance model of the greenhouse gas analyser (GGA) instrument from Los Gatos Research (LGR), which uses off-axis integrated cavity output spectroscopy (OA-ICOS) technology to obtain highly precise and accurate measurements, has been installed at the National Remote Sensing Center (NRSC), Shadnagar with the objective of generating a long-term record of measurements conforming to standards set by the World Meteorological Organisation (WMO). A calibration procedure to ensure the precision and accuracy of measurements was formulated using National Oceanic and Atmospheric Administration-Earth System Research Laboratory (NOAA-ESRL) calibration gases bearing WMO certification. The 10 s (1 σ) average precision of carbon dioxide (CO2) and (methane (CH4)) measurements by the GGA was 101 parts per billion volume (0.30 ppbv) and accuracy 78 ppbv (0.24 ppbv), respectively. The 5 s average of 1 Hz measurements was used to compute precision, which varied from 92.52 to 116.36 ppbv (1σ, 1 Hz = 0.66 parts per million volume (ppmv), WMO-2009)) for CO2 and CH4 0.45 ppbv to 0.55 ppbv (1 σ, 1 Hz = 2.48 ppbv, WMO-2009) respectively. Diurnal variation of greenhouse gas concentrations, temperature, and pressure, showed high fluctuations when cavity pressure and temperature varied from the standard values. The residuals of dry mixing ratios with respect to (w.r.t.) the NOAA span gases varied from +30 to −60 ppbv for CO2 and ±0.35 ppbv for CH4. A case study using the corrected observations over 1 year revealed the role of wind velocity and anthropogenic emissions, as well as the seasonal variations in the ambient concentrations of CO2 and CH4 gases near the surface.

Improvement of Statistical Postprocessing Using GEFS Reforecast Information

Abstract The National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL) generated a multidecadal (from 1985 to present) ensemble reforecast database for the 2012 version of the Global Ensemble Forecast System (GEFS). This dataset includes 11-member reforecasts initialized once per day at 0000 UTC. This GEFS version has a strong cold bias for winter and warm bias for summer in the Northern Hemisphere. Although the operational decaying average bias-correction approach performs well in winter and summer, it sometimes fails during the spring and fall transition seasons at long lead times (>~5 days). In this paper, 24- (1985–2008) and 25-yr (1985–2009) reforecast biases are used to calibrate 2-m temperature forecasts in 2009 and 2010, respectively. The reforecast-calibrated forecasts for both years are more accurate than those adjusted by the decaying average method during transition seasons. A long training period (>5 yr) is necessary to help avoid a large impact on bias correction from an extreme year case and keep a broader diversity of weather scenarios. The improvement from using the full 25-yr, 31-day window, weekly training dataset is almost equivalent to that from using daily training samples. This provides an option to reduce computational expenses while maintaining a desired accuracy. To provide the potential to improve forecast accuracy for transition seasons, reforecast information is added into the current operational bias-correction method. The relative contribution of the two methods is determined by the correlation between the ensemble mean and analysis. This method improves the forecast accuracy for most of the year with a maximum benefit during April–June.

An Observing System Simulation Experiment for the Unmanned Aircraft System Data Impact on Tropical Cyclone Track Forecasts

Abstract High-altitude, long-endurance unmanned aircraft systems (HALE UAS) are capable of extended flights for atmospheric sampling. A case study was conducted to evaluate the potential impact of dropwindsonde observations from HALE UAS on tropical cyclone track prediction; tropical cyclone intensity was not addressed. This study employs a global observing system simulation experiment (OSSE) developed at the National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL) that is based on the NOAA/National Centers for Environmental Prediction gridpoint statistical interpolation (GSI) data assimilation system and Global Forecast System (GFS) model. Different strategies for dropwindsonde deployment and UAS flight paths were compared. The introduction of UAS-deployed dropwindsondes was found to consistently improve the track forecast skill during the early forecast up to 96 h, with the caveat that the experiments omitted both vortex relocation and dropwindsondes from manned flights in the tropical cyclone region. The more effective UAS dropwindsonde deployment patterns sampled both the environment and the body of the tropical cyclone.

Sliding vane rotary compressor technology and energy saving

Energy saving, CO2 reduction, and energy generation from renewable sources represent the three cornerstones of the energetic and environmental commitments of all the countries in the world. These three elements may give a quantitative contribution to the sustainability in an industrial environment. Among them, the most important one, that represents a driver in many sectors, is the limitation of the CO2 concentration in the atmosphere: most recent data (2013) from National Oceanic and Atmospheric Administration – Earth System Research Laboratory (NOAA-ERSL) set at 395.55 parts per million (ppm) the CO2 in the atmosphere and the continuous increasing trend will quickly allow to reach the 450 ppm level which is considered as a safeguard limit to avoid irreversible environmental and socioeconomics problems. Looking at the energy consumption side, energy saving is a key factor. Compressed air production does not escape this requirement and, for the compressor manufacturing industry, this can represent an opportunity with great potential benefits. Compressed air is produced by electrical energy and the consumption accounts as much as 10% of industrial consumption of electricity. A lower estimate places at 6% this share but an additional 12% is estimated to be associated with the commercial and residential markets (portable tools, air pumps, pneumatic heating, ventilation, air conditioning, etc.). Hence, the overall compressor needs are estimated equal to 20% of the industrial electricity needs. Considering that industrial consumption of electricity represents a given share of the overall electrical energy consumption (it depends on the geographical context, social development, industrial level, etc.), with good approximation, compressed air can be associated to the overall electricity consumption and to primary energy consumption too. So, it can be compared with the other energy alternatives when the data are reliable and referred to real situations, actions to promote energy efficiency in compressed air systems can be identified with their real importance and compared with all the other measures. From many independent studies the most important energy saving measures are associated to the: (1) reduction of leakages on the distribution lines, (2) a more appropriate compressed air system design, (3) use of adjustable speed drives, (4) waste heat recovery. All these aspects, in a 10-year period of operation, weigh 70–75% of the overall compressed air costs. Therefore, the compressor technology is a key factor to reduce energy consumption including in it load control, variable speed operation, compressor sizing, etc. A great potential saving is associated to leaks, friction pipes, etc. but these actions are downstream of the compressed air production. After having discussed some issues concerning the future overall energy consumption and CO2 emissions, considering the development of the electricity market in the world in the near future, and overall energy characteristics of existing machines widely used in the compressed air market, the article goes deep inside a specific compressor technology which is represented by the sliding vanes rotary type. Principal processes inside these machines are discussed in the light of the recent scientific literature advancement of a theoretical and experimental nature. The general idea was that these machines are not so well known and their use is not so widespread: thanks to a deeper scientific interest over the past few years, these compressors had a notable performance improvement, thus a greater potential in industrial applications. Thanks to some intrinsic aspects, some energy issues are presented and related to specific processes inside the machine and compared with other compressors. The potential further improvements in terms of specific energy are discussed and addressed in main future research directions.

Global and regional emissions estimates for N<sub>2</sub>O

Abstract. We present a comprehensive estimate of nitrous oxide (N2O) emissions using observations and models from 1995 to 2008. High-frequency records of tropospheric N2O are available from measurements at Cape Grim, Tasmania; Cape Matatula, American Samoa; Ragged Point, Barbados; Mace Head, Ireland; and at Trinidad Head, California using the Advanced Global Atmospheric Gases Experiment (AGAGE) instrumentation and calibrations. The Global Monitoring Division of the National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL) has also collected discrete air samples in flasks and in situ measurements from remote sites across the globe and analyzed them for a suite of species including N2O. In addition to these major networks, we include in situ and aircraft measurements from the National Institute of Environmental Studies (NIES) and flask measurements from the Tohoku University and Commonwealth Scientific and Industrial Research Organization (CSIRO) networks. All measurements show increasing atmospheric mole fractions of N2O, with a varying growth rate of 0.1–0.7% per year, resulting in a 7.4% increase in the background atmospheric mole fraction between 1979 and 2011. Using existing emission inventories as well as bottom-up process modeling results, we first create globally gridded a priori N2O emissions over the 37 years since 1975. We then use the three-dimensional chemical transport model, Model for Ozone and Related Chemical Tracers version 4 (MOZART v4), and a Bayesian inverse method to estimate global as well as regional annual emissions for five source sectors from 13 regions in the world. This is the first time that all of these measurements from multiple networks have been combined to determine emissions. Our inversion indicates that global and regional N2O emissions have an increasing trend between 1995 and 2008. Despite large uncertainties, a significant increase is seen from the Asian agricultural sector in recent years, most likely due to an increase in the use of nitrogenous fertilizers, as has been suggested by previous studies.

Global and regional emission estimates for HCFC-22

Abstract. HCFC-22 (CHClF2, chlorodifluoromethane) is an ozone-depleting substance (ODS) as well as a significant greenhouse gas (GHG). HCFC-22 has been used widely as a refrigerant fluid in cooling and air-conditioning equipment since the 1960s, and it has also served as a traditional substitute for some chlorofluorocarbons (CFCs) controlled under the Montreal Protocol. A low frequency record on tropospheric HCFC-22 since the late 1970s is available from measurements of the Southern Hemisphere Cape Grim Air Archive (CGAA) and a few Northern Hemisphere air samples (mostly from Trinidad Head) using the Advanced Global Atmospheric Gases Experiment (AGAGE) instrumentation and calibrations. Since the 1990s high-frequency, high-precision, in situ HCFC-22 measurements have been collected at these AGAGE stations. Since 1992, the Global Monitoring Division of the National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL) has also collected flasks on a weekly basis from remote sites across the globe and analyzed them for a suite of halocarbons including HCFC-22. Additionally, since 2006 flasks have been collected approximately daily at a number of tower sites across the US and analyzed for halocarbons and other gases at NOAA. All results show an increase in the atmospheric mole fractions of HCFC-22, and recent data show a growth rate of approximately 4% per year, resulting in an increase in the background atmospheric mole fraction by a factor of 1.7 from 1995 to 2009. Using data on HCFC-22 consumption submitted to the United Nations Environment Programme (UNEP), as well as existing bottom-up emission estimates, we first create globally-gridded a priori HCFC-22 emissions over the 15 yr since 1995. We then use the three-dimensional chemical transport model, Model for Ozone and Related Chemical Tracers version 4 (MOZART v4), and a Bayesian inverse method to estimate global as well as regional annual emissions. Our inversion indicates that the global HCFC-22 emissions have an increasing trend between 1995 and 2009. We further find a surge in HCFC-22 emissions between 2005 and 2009 from developing countries in Asia – the largest emitting region including China and India. Globally, substantial emissions continue despite production and consumption being phased out in developed countries currently.

Interannual variability of carbon monoxide emission estimates over South America from 2006 to 2010

We present the first inverse modeling study to estimate CO emissions constrained by both surface and satellite observations. Our 4D‐Var system assimilates National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) surface and Measurements Of Pollution In The Troposphere (MOPITT) satellite observations jointly by fitting a bias correction scheme. This approach leads to the identification of a positive bias of maximum 5 ppb in MOPITT column‐averaged CO mixing ratios in the remote Southern Hemisphere (SH). The 4D‐Var system is used to estimate CO emissions over South America in the period 2006–2010 and to analyze the interannual variability (IAV) of these emissions. We infer robust, high spatial resolution CO emission estimates that show slightly smaller IAV due to fires compared to the Global Fire Emissions Database (GFED3) prior emissions. South American dry season (August and September) biomass burning emission estimates amount to 60, 92, 42, 16 and 93 Tg CO/yr for 2006 to 2010, respectively. Moreover, CO emissions probably associated with pre‐harvest burning of sugar cane plantations in São Paulo state are underestimated in current inventories by 50–100%. We conclude that climatic conditions (such as the widespread drought in 2010) seem the most likely cause for the IAV in biomass burning CO emissions. However, socio‐economic factors (such as the growing global demand for soy, beef and sugar cane ethanol) and associated deforestation fires, are also likely as drivers for the IAV of CO emissions, but are difficult to link directly to CO emissions.

In situ measurement of atmospheric carbon dioxide at Yanbian, China: Estimating its northeast Asian emission regions

High-precision (±0.1 ppm) and high-frequency (hourly averaged) in situ measurements of atmospheric carbon dioxide (CO2) were made for the first time from August 2005 to July 2007 at Yanbian, China using a non-dispersive Infrared (NDIR) analyzer with National Oceanic and Atmospheric Administration/Earth System Research Laboratory (NOAA/ESRL) standards. The results of these measurements are presented in this paper and are used to investigate the regional representativeness of regional background data at Yanbian and determine the CO2 emission source regions in Northeast Asia. The phase of the monthly variations at Yanbian reflects the special regional characteristics, which were overall in excellent agreement with other observatories in the middle-to-high latitudes in the Northern Hemisphere. Applying a hybrid receptor model to the regional emission source events in cold period (November–April), we estimated the distribution of the major CO2 emissions in the northeast Asia. The results indicated that the strongest potential emission areas contributing to Yanbian are the Beijing & Tianjin metropolitan areas, southwestern part of Shandong Province including Jinan, and Vladivostok. The results of this study reveal the usefulness of in situ CO2 measurements at Yanbian in establishing the scientific foundation for monitoring the large CO2 emission areas in northern China and Russia. Continued monitoring of CO2 at Yanbian within a regional network should provide significant contributions to both understanding the global/regional carbon cycle and constraining “top-down” emissions in Northeast Asia.

Comparing optimized CO emission estimates using MOPITT or NOAA surface network observations

This paper compares two global inversions to estimate carbon monoxide (CO) emissions for 2004. Either surface flask observations from the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) or CO total columns from the Measurement of Pollution in the Troposphere (MOPITT) instrument are assimilated in a 4D‐Var framework. Inferred emission estimates from the two inversions are consistent over the Northern Hemisphere (NH). For example, both inversions increase anthropogenic CO emissions over Europe (from 46 to 94 Tg CO/yr) and Asia (from 222 to 420 Tg CO/yr). In the Southern Hemisphere (SH), three important findings are reported. First, due to their different vertical sensitivity, the stations‐only inversion increases SH biomass burning emissions by 108 Tg CO/yr more than the MOPITT‐only inversion. Conversely, the MOPITT‐only inversion results in SH natural emissions (mainly CO from oxidation of NMVOCs) that are 185 Tg CO/yr higher compared to the stations‐only inversion. Second, MOPITT‐only derived biomass burning emissions are reduced with respect to the prior which is in contrast to previous (inverse) modeling studies. Finally, MOPITT derived total emissions are significantly higher for South America and Africa compared to the stations‐only inversion. This is likely due to a positive bias in the MOPITT V4 product. This bias is also apparent from validation with surface stations and ground‐truth FTIR columns. Our results show that a combined inversion is promising in the NH. However, implementation of a satellite bias correction scheme is essential to combine both observational data sets in the SH.

Optimizing global CO emission estimates using a four-dimensional variational data assimilation system and surface network observations

Abstract. We apply a four-dimensional variational (4D-VAR) data assimilation system to optimize carbon monoxide (CO) emissions for 2003 and 2004 and to reduce the uncertainty of emission estimates from individual sources using the chemistry transport model TM5. The system is designed to assimilate large (satellite) datasets, but in the current study only a limited amount of surface network observations from the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) is used to test the 4D-VAR system. By design, the system is capable to adjust the emissions in such a way that the posterior simulation reproduces background CO mixing ratios and large-scale pollution events at background stations. Uncertainty reduction up to 60 % in yearly emissions is observed over well-constrained regions and the inferred emissions compare well with recent studies for 2004. However, with the limited amount of data from the surface network, the system becomes data sparse resulting in a large solution space. Sensitivity studies have shown that model uncertainties (e.g., vertical distribution of biomass burning emissions and the OH field) and the prior inventories used, influence the inferred emission estimates. Also, since the observations only constrain total CO emissions, the 4D-VAR system has difficulties in separating anthropogenic and biogenic sources in particular. The inferred emissions are validated with NOAA aircraft data over North America and the agreement is significantly improved from the prior to posterior simulation. Validation with the Measurements Of Pollution In The Troposphere (MOPITT) instrument version 4 (V4) shows a slight improved agreement over the well-constrained Northern Hemisphere and in the tropics (except for the African continent). However, the model simulation with posterior emissions underestimates MOPITT CO total columns on the remote Southern Hemisphere (SH) by about 10 %. This is caused by a reduction in SH CO sources mainly due to surface stations on the high southern latitudes.

Assimilation of SCIAMACHY total column CO observations: Global and regional analysis of data impact

Carbon monoxide (CO) total column observations from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) on board Envisat‐1 are assimilated into the Global Modeling and Assimilation Office constituent assimilation system for the period 1 April to 20 December 2004. The impact of the assimilation on CO distribution is evaluated using independent surface flask observations from the National Oceanic and Atmospheric Administration (NOAA)/ESRL global cooperative air sampling network and Measurement of Ozone and Water Vapor by Airbus In‐Service Aircraft (MOZAIC) in situ CO profiles. Assimilation of SCIAMACHY data improves agreement of CO assimilation with both of these data sets on both global and regional scales compared to the free‐running model. Regional comparisons with MOZAIC profiles made in western Europe, the northeastern United States, and the Arabian Peninsula show improvements at all three locations in the free troposphere and into the boundary layer over Arabia and the northeastern United States. Comparisons with NOAA Earth System Research Laboratory data improve at about two thirds of the surface observation sites. The systematic model errors related to the uncertainty of CO surface sources and the chemistry of CO losses are investigated through experiments with increased surface CO emissions over the Arabian Peninsula and/or globally reduced hydroxyl radical (OH) concentrations. Both model changes decrease mean CO errors at all altitudes in comparison to MOZAIC data over Dubai and Abu Dhabi. In contrast, errors in the assimilated CO are reduced by the increased emissions for pressures ≥800 hPa and by the reduced OH for pressures ≤600 hPa. Our analysis suggests that CO emissions over Dubai in 2004 are more than double those in the 1998 emissions inventory.

Separating contributions from natural and anthropogenic sources in atmospheric methane from the Black Sea region, Romania

Abstract The Danube Delta-Black Sea region of Romania is an important wetland, and this preliminary study evaluates the significance of this region as a source of atmospheric CH 4 . Measurements of the mixing ratio and δ 13 C in CH 4 are reported from air and water samples collected at eight sites in the Danube Delta. High mixing ratios of CH 4 were found in air (2500–14,000 ppb) and dissolved in water samples (∼1–10 μmol L −1 ), demonstrating that the Danube Delta is an important natural source of CH 4 . The intercepts on Keeling plots of about −62‰ show that the main source of CH 4 in this region is microbial, probably resulting primarily from acetate fermentation. Atmospheric CH 4 and CO data from the NOAA/ESRL (National Oceanic and Atmospheric Administration/Earth System Research Laboratory) were used to make a preliminary estimate of biogenic CH 4 at the Black Sea sampling site at Constanta (BSC). These data were used to calculate ratios of CH 4 /CO in air samples, and using an assumed CH 4 /CO anthropogenic emissions ratio of 0.6, fossil fuel emissions at BSC were estimated. Biogenic CH 4 emissions were then estimated by a simple mass balance approach. Keeling plots of well-mixed air from the BSC site suggested a stronger wetland source in summer and a stronger fossil fuel source in winter.

NOMADS: A Climate and Weather Model Archive at the National Oceanic and Atmospheric Administration

An online archive of real-time and historical weather and climate model output and observational data is now available from the National Oceanic and Atmospheric Administration (NOAA). This archive, known as the NOAA National Operational Model Archive and Distribution System (NOMADS), was jointly initiated in 2001 by the National Climatic Data Center (NCDC), the National Centers for Environmental Prediction (NCEP), and the Geophysical Fluid Dynamics Laboratory (GFDL). At present, NOMADS provides access to real-time and historical 1) numerical weather prediction (NWP) model input and output, 2) GFDL's Coupled Global Climate Models (CGCM) output, 3) global and regional reanalysis from NCEP and the National Center for Atmospheric Research (NCAR), and 4) limited surface, upper-air, and satellite observational datasets from NCDC and NOAA's National Ocean Data Center (NODC) and Earth System Research Laboratory [formerly the Forecast System Laboratory (FSL)]. NOMADS is but one of many similar data services across the United States and abroad that are embracing and leveraging various pilot efforts toward distributed data access using agreed-to data transport and data format conventions. This allows for the interoperable access of various subsets of data across the Internet. These underlying community-driven agreements and the Open Source Project for a Network Data Access Protocol (OPeNDAP) data transport protocol form the core of NOMADS services as well as have the capability for “format neutral” access to data in many different formats and locations.