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In September and October 2015, widespread forest and peatland fires burned over large parts of maritime southeast Asia,most notably Indonesia,releasing large amounts of terrestrially-stored carbon into the atmosphere, primarily in the form of CO2, CO and CH4. With a mean emission rate of 11.3 Tg CO2 per day during Sept-Oct 2015, emissions from these fires exceeded the fossil fuel CO2 release rate of the European Union (EU28) (8.9 Tg CO2 per day) . Although seasonal fires are a frequent occurrence in the human modified landscapes found in Indonesia,the extent of the 2015 fires was greatly inflated by an extended drought period associated with a strong El Niño. We estimate carbon emissions from the 2015 fires to be the largest seen in maritime southeast Asia since those associated with the record breaking El Niño of 1997. Compared to that event, a much better constrained regional total carbon emission estimate can be made for the 2015 fires through the use of present-day satellite observations of the fire's radiative power output and atmospheric CO concentrations, processed using the modelling and assimilation framework of the Copernicus Atmosphere Monitoring Service (CAMS) and combined with unique in situ smoke measurements made on Kalimantan.

In September and October 2015 widespread forest and peatland fires burned over large parts of maritime southeast Asia, most notably Indonesia, releasing large amounts of terrestrially-stored carbon into the atmosphere, primarily in the form of CO2, CO and CH4. With a mean emission rate of 11.3 Tg CO2 per day during Sept-Oct 2015, emissions from these fires exceeded the fossil fuel CO2 release rate of the European Union (EU28) (8.9 Tg CO2 per day). Although seasonal fires are a frequent occurrence in the human modified landscapes found in Indonesia, the extent of the 2015 fires was greatly inflated by an extended drought period associated with a strong El Niño. We estimate carbon emissions from the 2015 fires to be the largest seen in maritime southeast Asia since those associated with the record breaking El Niño of 1997. Compared to that event, a much better constrained regional total carbon emission estimate can be made for the 2015 fires through the use of present-day satellite observations of the fire's radiative power output and atmospheric CO concentrations, processed using the modelling and assimilation framework of the Copernicus Atmosphere Monitoring Service (CAMS) and combined with unique in situ smoke measurements made on Kalimantan.

International audience ; Monitoring Atmospheric Composition and Climate (MACC/MACCII) currently represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu), which will become fully operational in the course of 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5 day forecasts of atmospheric composition fields. It is the only assimilation system world-wide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases (CO, O3, and NO2) covering the period between 2009 and 2012. A validation was performed based on CO and O3 surface observations from the Global Atmosphere Watch (GAW) network, O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and furthermore, NO2 tropospheric columns derived from the satellite sensors SCIAMACHY and GOME-2, and CO total columns derived from the satellite sensor MOPITT. The MACC system proved capable of reproducing reactive gas concentrations in consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations: for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the years, with monthly Modified Normalised Mean Biases (MNMBs) ranging between −30 and 30% at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterization. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at a highest, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range between −110 and 40% for ...

The Monitoring Atmospheric Composition and Climate (MACC) project represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu/), which became fully operational during 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5-day forecasts of atmospheric composition fields. It is the only assimilation system worldwide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases covering the period between 2009 and 2012. A validation was performed based on carbon monoxide (CO), nitrogen dioxide (NO2) and ozone (O3) surface observations from the Global Atmosphere Watch (GAW) network, the O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and, furthermore, NO2 tropospheric columns, as well as CO total columns, derived from satellite sensors. The MACC system proved capable of reproducing reactive gas concentrations with consistent quality; however, with a seasonally dependent bias compared to surface and satellite observations – for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the year, with monthly modified normalised mean biases (MNMBs) ranging between −30 and 30 % at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterisation. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at their highest level, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range from values between −110 and 40 % for NO2 and at most −20 % for CO, over the ...

Monitoring Atmospheric Composition and Climate (MACC/MACCII) currently represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu), which will become fully operational in the course of 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5 day forecasts of atmospheric composition fields. It is the only assimilation system world-wide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases (CO, O3, and NO2) covering the period between 2009 and 2012. A validation was performed based on CO and O3 surface observations from the Global Atmosphere Watch (GAW) network, O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and furthermore, NO2 tropospheric columns derived from the satellite sensors SCIAMACHY and GOME-2, and CO total columns derived from the satellite sensor MOPITT. The MACC system proved capable of reproducing reactive gas concentrations in consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations: for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the years, with monthly Modified Normalised Mean Biases (MNMBs) ranging between −30 and 30% at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterization. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at a highest, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range between −110 and 40% for NO2 and at most −20% for ...

International audience ; Monitoring Atmospheric Composition and Climate (MACC/MACCII) currently represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu), which will become fully operational in the course of 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5 day forecasts of atmospheric composition fields. It is the only assimilation system world-wide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases (CO, O3, and NO2) covering the period between 2009 and 2012. A validation was performed based on CO and O3 surface observations from the Global Atmosphere Watch (GAW) network, O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and furthermore, NO2 tropospheric columns derived from the satellite sensors SCIAMACHY and GOME-2, and CO total columns derived from the satellite sensor MOPITT. The MACC system proved capable of reproducing reactive gas concentrations in consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations: for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the years, with monthly Modified Normalised Mean Biases (MNMBs) ranging between −30 and 30% at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterization. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at a highest, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range between −110 and 40% for NO2 and at most −20% for CO, over the investigated regions. The underestimation is likely to result from a combination of errors concerning the dry deposition parameterization and certain limitations in the current emission inventories, together with an insufficiently established seasonality in the emissions.

International audience ; Monitoring Atmospheric Composition and Climate (MACC/MACCII) currently represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu), which will become fully operational in the course of 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5 day forecasts of atmospheric composition fields. It is the only assimilation system world-wide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases (CO, O3, and NO2) covering the period between 2009 and 2012. A validation was performed based on CO and O3 surface observations from the Global Atmosphere Watch (GAW) network, O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and furthermore, NO2 tropospheric columns derived from the satellite sensors SCIAMACHY and GOME-2, and CO total columns derived from the satellite sensor MOPITT. The MACC system proved capable of reproducing reactive gas concentrations in consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations: for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the years, with monthly Modified Normalised Mean Biases (MNMBs) ranging between −30 and 30% at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterization. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at a highest, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range between −110 and 40% for NO2 and at most −20% for CO, over the investigated regions. The underestimation is likely to result from a combination of errors concerning the dry deposition parameterization and certain limitations in the current emission inventories, together with an insufficiently established seasonality in the emissions.

International audience ; Monitoring Atmospheric Composition and Climate (MACC/MACCII) currently represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu), which will become fully operational in the course of 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5 day forecasts of atmospheric composition fields. It is the only assimilation system world-wide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases (CO, O3, and NO2) covering the period between 2009 and 2012. A validation was performed based on CO and O3 surface observations from the Global Atmosphere Watch (GAW) network, O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and furthermore, NO2 tropospheric columns derived from the satellite sensors SCIAMACHY and GOME-2, and CO total columns derived from the satellite sensor MOPITT. The MACC system proved capable of reproducing reactive gas concentrations in consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations: for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the years, with monthly Modified Normalised Mean Biases (MNMBs) ranging between −30 and 30% at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterization. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at a highest, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range between −110 and 40% for NO2 and at most −20% for CO, over the investigated regions. The underestimation is likely to result from a combination of errors concerning the dry deposition parameterization and certain limitations in the current emission inventories, together with an insufficiently established seasonality in the emissions.

Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, climate services providers, and health professionals. Owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions, the prediction of aerosol particle concentrations and properties in the numerical weather prediction (NWP) framework faces a number of challenges. The modeling of numerous aerosol-related parameters increases computational expense. Errors in aerosol prediction concern all processes involved in the aerosol life cycle including (a) errors on the source terms (for both anthropogenic and natural emissions), (b) errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), and (c) errors related to aerosol chemistry (e.g., nucleation, gas–aerosol partitioning, chemical transformation and growth, hygroscopicity). Finally, there are fundamental uncertainties and significant processing overhead in the diverse observations used for verification and assimilation within these systems. Indeed, a significant component of aerosol forecast development consists in streamlining aerosol-related observations and reducing the most important errors through model development and data assimilation. Aerosol particle observations from satellite- and ground-based platforms have been crucial to guide model development of the recent years and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near surface, and aircraft) and freely shared. This paper reviews current requirements for ...

Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centres due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, providers of climate services, and health professionals. The prediction of aerosol particle 5 properties in Numerical Weather prediction (NWP) models faces a number of challenges owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions. Errors in aerosol prediction concern all processes involved in the aerosol life cycle. These include errors on the source terms (for both anthropogenic and natural emissions), errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), as well 10 as errors related to aerosol chemistry (e.g., nucleation, gas-aerosol partitioning, chemical transformation and growth, hygroscopicity). The main goal of current research on aerosol forecast consists in prioritizing these errors and trying to reduce the most important ones through model development and data assimilation. Aerosol particle observations from satellite and ground-based platforms have been crucial to guide model development of the recent years, and have been made more readily 15 available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near-surface, and aircraft) and freely shared. This white paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centres. Some of the requirements are equally applicable to aerosol-climate research. However, the focus here is on the global operational prediction of aerosol properties such as mass concentrations ...