scholarly journals Satellite-Observed Variations and Trends in Carbon Monoxide over Asia and Their Sensitivities to Biomass Burning

2020 ◽  
Vol 12 (5) ◽  
pp. 830 ◽  
Author(s):  
Xun Zhang ◽  
Jane Liu ◽  
Han Han ◽  
Yongguang Zhang ◽  
Zhe Jiang ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Biomass Burning ◽  
Interannual Variation ◽  
Correlation Coefficients ◽  
Temporal Variations ◽  
South Siberia ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Annual Means ◽  
Total Column

As the carbon monoxide (CO) total column over Asia is among the highest in the world, it is important to characterize its variations in space and time. Using Measurements of Pollution in the Troposphere (MOPITT) and Atmospheric InfraRed Sounder (AIRS) satellite data, the variations and trends in CO total column over Asia and its seven subregions during 2003–2017 are investigated in this study. The CO total column in Asia is higher in spring and winter than in summer and autumn. The seasonal maximum and minimum are in spring and summer respectively in the regional mean over Asia, varying between land and oceans, as well as among the subregions. The CO total column in Asia shows strong interannual variation, with a regional mean coefficient of variation of 5.8% in MOPITT data. From 2003 to 2017, the annual mean of CO total column over Asia decreased significantly at a rate of (0.58 ± 0.15)% per year (or −(0.11 ± 0.03) × 1017 molecules cm−2 per year) in MOPITT data, resulting from significant CO decreases in winter, summer, and spring. In most of the subregions, significant decreasing trends in CO total column are also observed, more obviously over areas with high CO total column, including eastern regions of China and the Sichuan Basin. The regional decreasing trends in these areas are over 1% per year. Over the entire Asia, and in fire-prone subregions including South Siberia, Indo-China Peninsula, and Indonesia, we found significant correlations between the MOPITT CO total column and the fire counts from the Moderate Resolution Imaging Spectroradiometer (MODIS). The variations in MODIS fire counts may explain 58%, 60%, 36%, and 71% of the interannual variation in CO total column in Asia and these three subregions, respectively. Over different land cover types, the variations in biomass burning may explain 62%, 52%, and 31% of the interannual variation in CO total column, respectively, over the forest, grassland, and shrubland in Asia. Extremes in CO total column in Asia can be largely explained by the extreme fire events, such as the fires over Siberia in 2003 and 2012 and over Indonesia in 2006 and 2015. The significant decreasing trends in MODIS fire counts inside and outside Asia suggest that global biomass burning may be a driver for the decreasing trend in CO total column in Asia, especially in spring. In general, the variations and trends in CO total column over Asia detected by AIRS are similar to but smaller than those by MOPITT. The two datasets show similar spatial and temporal variations in CO total column over Asia, with correlation coefficients of 0.86–0.98 in the annual means. This study shows that the interannual variation in atmospheric CO in Asia is sensitive to biomass burning, while the decreasing trend in atmospheric CO over Asia coincides with the decreasing trend in MODIS fire counts from 2003 to 2017.

scholarly journals Tropospheric carbon monoxide variability from AIRS and IASI under clear and cloudy conditions

2013 ◽  
Vol 13 (6) ◽  
pp. 16337-16366 ◽  
Author(s):  
J. Warner ◽  
F. Carminati ◽  
Z. Wei ◽  
W. Lahoz ◽  
J.-L. Attié
Keyword(s):  
Carbon Monoxide ◽  
Emission Inventory ◽  
Correlation Coefficients ◽  
Retrieval Algorithm ◽  
Atmospheric Infrared Sounder ◽  
Fire Emissions ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Mask

Abstract. We study the Carbon Monoxide (CO) variability in the last decade measured by NASA's Atmospheric InfraRed Sounder (AIRS) on the Earth Observing Systems (EOS)/Aqua satellite and Europe's Infrared Atmospheric Sounder Interferometer (IASI) on MetOp platform. The focus of this study is to analyze CO variability and short-term trends separately for background CO and new emissions based on a new statistical approach. The AIRS Level 2 (L2) retrieval algorithm, as well as the IASI products from NOAA, utilizes cloud clearing to treat cloud contaminations in the signals; and this increases the data coverage significantly to a yield of more than 50% of the total measurements (Susskind et al., 2003). We first study if the cloud clearing affects CO retrievals and the subsequent trend studies by using the collocated Moderate Resolution Imaging Spectroradiometer (MODIS) (Ackerman et al., 1998) cloud mask to identify AIRS clear sky scenes. We then separate AIRS CO data into clear and cloud-cleared scenes and into background and new emissions, respectively. Furthermore, we carry out a similar study for the IASI CO and discuss the consistency with AIRS. We validate the CO variability of the emissions developed from AIRS against other emission inventory databases (i.e., Global Fire Emissions Database – GFED3 and the MACC/CityZEN UE – MACCity) and calculate that the correlation coefficients between the AIRS CO emissions and the emission inventory databases are 0.726 for the Northern Hemisphere (NH) and 0.915 for the Southern Hemisphere (SH).

scholarly journals Quantitative assessment of AOD from 17 CMIP5 models based on satellite-derived AOD over India

2016 ◽  
Vol 34 (8) ◽  
pp. 657-671 ◽  
Author(s):  
Amit Misra ◽  
Vijay P. Kanawade ◽  
Sachchida Nand Tripathi
Keyword(s):  
Interannual Variation ◽  
Correlation Coefficients ◽  
Quantitative Information ◽  
Cmip5 Models ◽  
Modis Aod ◽  
Longitudinal Variations ◽  
Different Seasons ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Aerosol optical depth (AOD) values from 17 CMIP5 models are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) derived AODs over India. The objective is to identify the cases of successful AOD simulation by CMIP5 models, considering satellite-derived AOD as a benchmark. Six years of AOD data (2000–2005) from MISR and MODIS are processed to create quality-assured gridded AOD maps over India, which are compared with corresponding maps of 17 CMIP5 models at the same grid resolution. Intercomparison of model and satellite data shows that model-AOD is better correlated with MISR-derived AOD than MODIS. The correlation between model-AOD and MISR-AOD is used to segregate the models into three categories identifying their performance in simulating the AOD over India. Maps of correlation between model-AOD and MISR-/MODIS-AOD are generated to provide quantitative information about the intercomparison. The two sets of data are examined for different seasons and years to examine the seasonal and interannual variation in the correlation coefficients. Latitudinal and longitudinal variations in AOD as simulated by models are also examined and compared with corresponding variations observed by satellites.

Assessment of Arctic Cloud Cover Anomalies in Atmospheric Reanalysis Products Using Satellite Data

2016 ◽  
Vol 29 (17) ◽  
pp. 6065-6083 ◽  
Author(s):  
Yinghui Liu ◽  
Jeffrey R. Key
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Global Climate ◽  
Correlation Coefficients ◽  
Cloud Amount ◽  
Satellite Observation ◽  
Skill Score ◽  
Global Climate Models ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Cloud cover is one of the largest uncertainties in model predictions of the future Arctic climate. Previous studies have shown that cloud amounts in global climate models and atmospheric reanalyses vary widely and may have large biases. However, many climate studies are based on anomalies rather than absolute values, for which biases are less important. This study examines the performance of five atmospheric reanalysis products—ERA-Interim, MERRA, MERRA-2, NCEP R1, and NCEP R2—in depicting monthly mean Arctic cloud amount anomalies against Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations from 2000 to 2014 and against Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) observations from 2006 to 2014. All five reanalysis products exhibit biases in the mean cloud amount, especially in winter. The Gerrity skill score (GSS) and correlation analysis are used to quantify their performance in terms of interannual variations. Results show that ERA-Interim, MERRA, MERRA-2, and NCEP R2 perform similarly, with annual mean GSSs of 0.36/0.22, 0.31/0.24, 0.32/0.23, and 0.32/0.23 and annual mean correlation coefficients of 0.50/0.51, 0.43/0.54, 0.44/0.53, and 0.50/0.52 against MODIS/CALIPSO, indicating that the reanalysis datasets do exhibit some capability for depicting the monthly mean cloud amount anomalies. There are no significant differences in the overall performance of reanalysis products. They all perform best in July, August, and September and worst in November, December, and January. All reanalysis datasets have better performance over land than over ocean. This study identifies the magnitudes of errors in Arctic mean cloud amounts and anomalies and provides a useful tool for evaluating future improvements in the cloud schemes of reanalysis products.

scholarly journals Evaluation of MODIS Water Vapour Products over ALGERIA using Radiosonde Data

2021 ◽  
Vol 44 ◽  
Author(s):  
Houaria Namaoui ◽  
Salem Kahlouche ◽  
Ahmed Hafidh Belbachir
Keyword(s):  
Water Vapour ◽  
Satellite Data ◽  
Correlation Coefficients ◽  
Precipitable Water ◽  
Radiosonde Data ◽  
Precipitable Water Vapour ◽  
Total Precipitable Water ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Remote sensing of atmospheric water vapour using GNSS and Satellite data has become an efficient tool in meteorology and climate research. Many satellite data have been increasingly used to measure the content of water vapour in the atmosphere and to characterize its temporal and spatial variations. In this paper, we have used observations from radiosonde data collected from three stations (Algiers, Bechar and Tamanrasset) in Algeria from January to December 2012 to evaluate Moderate Resolution Imaging Spectroradiometer (MODIS) total precipitable water vapour (PWV) products. Results show strong agreement between the total precipitable water contents estimated based on radiosondes observations and the ones measured by the sensor MODIS with the correlation coefficients in the range 0.69 to 0.95 and a mean bias, which does not exceed 1.5.  

scholarly journals Determination of enhancement ratios of HCOOH relative to CO in biomass burning plumes by the Infrared Atmospheric Sounding Interferometer (IASI)

2017 ◽  
Vol 17 (18) ◽  
pp. 11089-11105 ◽  
Author(s):  
Matthieu Pommier ◽  
Cathy Clerbaux ◽  
Pierre-Francois Coheur
Keyword(s):  
Southeast Asia ◽  
Biomass Burning ◽  
Surface Wind ◽  
Geographic Location ◽  
Surface Wind Speed ◽  
Weather Forecasts ◽  
Atmospheric Sounding ◽  
Agricultural Burning ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Formic acid (HCOOH) concentrations are often underestimated by models, and its chemistry is highly uncertain. HCOOH is, however, among the most abundant atmospheric volatile organic compounds, and it is potentially responsible for rain acidity in remote areas. HCOOH data from the Infrared Atmospheric Sounding Interferometer (IASI) are analyzed from 2008 to 2014 to estimate enhancement ratios from biomass burning emissions over seven regions. Fire-affected HCOOH and CO total columns are defined by combining total columns from IASI, geographic location of the fires from Moderate Resolution Imaging Spectroradiometer (MODIS), and the surface wind speed field from the European Centre for Medium-Range Weather Forecasts (ECMWF). Robust correlations are found between these fire-affected HCOOH and CO total columns over the selected biomass burning regions, allowing the calculation of enhancement ratios equal to 7.30  ×  10−3 ± 0.08  ×  10−3 mol mol−1 over Amazonia (AMA), 11.10  ×  10−3 ± 1.37  ×  10−3 mol mol−1 over Australia (AUS), 6.80  ×  10−3 ± 0.44  ×  10−3 mol mol−1 over India (IND), 5.80  ×  10−3 ± 0.15  ×  10−3 mol mol−1 over Southeast Asia (SEA), 4.00  ×  10−3 ± 0.19  ×  10−3 mol mol−1 over northern Africa (NAF), 5.00  ×  10−3 ± 0.13  ×  10−3 mol mol−1 over southern Africa (SAF), and 4.40  ×  10−3 ± 0.09  ×  10−3 mol mol−1 over Siberia (SIB), in a fair agreement with previous studies. In comparison with referenced emission ratios, it is also shown that the selected agricultural burning plumes captured by IASI over India and Southeast Asia correspond to recent plumes where the chemistry or the sink does not occur. An additional classification of the enhancement ratios by type of fuel burned is also provided, showing a diverse origin of the plumes sampled by IASI, especially over Amazonia and Siberia. The variability in the enhancement ratios by biome over the different regions show that the levels of HCOOH and CO do not only depend on the fuel types.

scholarly journals Observations of Supermicron-Sized Aerosols Originating from Biomass Burning in South Central Africa

2021 ◽  
Author(s):  
Rose Marie Miller ◽  
Greg M. McFarquhar ◽  
Robert M. Rauber ◽  
Joseph R. O'Brien ◽  
Siddhant Gupta ◽  
...  
Keyword(s):  
Black Carbon ◽  
Biomass Burning ◽  
Single Particle ◽  
Central Africa ◽  
Submicron Particles ◽  
Back Trajectories ◽  
Active Fire ◽  
South Central ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. During the three years of the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign, the NASA Orion P-3 was equipped with a 2D-Stereo (2D-S) probe that imaged particles with maximum dimension (D) ranging from 10 < D < 1280 µm. The 2D-S recorded supermicron-sized aerosol particles (SAPs) outside of clouds within biomass burning plumes during flights over the Southeast Atlantic off Africa’s coast. Numerous SAPs with 10 < D < 1520 µm were observed in 2017 and 2018 at altitudes between 1230 m and 3500 m, 1000 km from the coastline mostly between 7–11° S. No SAPs were observed in 2016 as flights were conducted further south and further from the coastline. Number concentrations of black carbon (rBC) measured by a single particle soot photometer ranged from 200 to 1200 cm−3 when SAPs were observed. Transmission electron microscopy images of submicron particulates, collected on Holey carbon grid filters, revealed particles with potassium salts, black carbon and organics while energy-dispersive X-ray spectroscopy spectra detected potassium, a tracer for biomass burning, indicating that the submicron particles originated from biomass burning in addition to black carbon. NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) three-day back trajectories show a source in northern Angola for times when large SAPs were observed. Fire Information for Resource Management System Moderate Resolution Imaging Spectroradiometer (MODIS) 6 active fire maps showed extensive biomass burning at these locations. Given the back trajectories, the high number concentrations of rBC, and the presence of elemental tracers indicative of biomass burning, it is hypothesized that the SAPs imaged by the 2D-S are examples of unburned plant material previously seen in biomass burning smoke close to the source.

scholarly journals Global Distribution of Column Satellite Aerosol Optical Depth to Surface PM2.5 Relationships

2020 ◽  
Vol 12 (12) ◽  
pp. 1985 ◽  
Author(s):  
Sundar Christopher ◽  
Pawan Gupta
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Large Population ◽  
Correlation Coefficients ◽  
Large Spread ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Using a combined Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) mid-visible aerosol optical depth (AOD) product at 0.1 × 0.1-degree spatial resolution and collocated surface PM2.5 (particulate matter with aerodynamic diameter smaller than 2.5 μm) monitors, we provide a global five-year (2015–2019) assessment of the spatial and seasonal AOD–PM2.5 relationships of slope, intercepts, and correlation coefficients. Only data from ground monitors accessible through an open air-quality portal that are available to the worldwide community for air quality research and decision making are used in this study. These statistics that are reported 1 × 1-degree resolution are important since satellite AOD is often used in conjunction with spatially limited surface PM2.5 monitors to estimate global distributions of surface particulate matter concentrations. Results indicate that more than 3000 ground monitors are now available for PM2.5 studies. While there is a large spread in correlation coefficients between AOD and PM2.5, globally, averaged over all seasons, the correlation coefficient is 0.55 with a unit AOD producing 54 μgm−3 of PM2.5 (Slope) with an intercept of 8 μgm−3. While the number of surface PM2.5 measurements has increased by a factor of 10 over the last decade, a concerted effort is still needed to continue to increase these monitors in areas that have no surface monitors, especially in large population centers that will further leverage the strengths of satellite data.

scholarly journals A new transport mechanism of biomass burning from Indochina as identified by modeling studies

2009 ◽  
Vol 9 (20) ◽  
pp. 7901-7911 ◽  
Author(s):  
C.-Y. Lin ◽  
H.-m. Hsu ◽  
Y. H. Lee ◽  
C. H. Kuo ◽  
Y.-F. Sheng ◽  
...  
Keyword(s):  
East Asia ◽  
Biomass Burning ◽  
Transport Mechanism ◽  
Dominant Role ◽  
Indochina Peninsula ◽  
Active Fire ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Simulation Results ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Biomass burning in the Indochina Peninsula (Indochina) is one of the important ozone sources in the low troposphere over East Asia in springtime. Moderate Resolution Imaging Spectroradiometer (MODIS) data show that 20 000 or more active fire detections occurred annually in spring only from 2000 to 2007. In our tracer modeling study, we identify a new mechanism transporting the tracer over Indochina that is significantly different from the vertical transport mechanism over the equatorial areas such as Indonesia and Malaysia. Simulation results demonstrate that the leeside troughs over Indochina play a dominant role in the uplift of the tracer below 3 km, and that the strong westerlies prevailing above 3 km transport the tracer. These fundamental mechanisms have a major impact on the air quality downwind from Indochina over East Asia. The climatological importance of such a leeside trough is also discussed.

New simple approach to understand the spatial and vertical distribution of biomass burning CO emission based on the MOPITT vertical measurements

2020 ◽  
Author(s):  
Chuyong Lin ◽  
Jason Cohen
Keyword(s):  
South America ◽  
Biomass Burning ◽  
Large Scale ◽  
Central Africa ◽  
Western Africa ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Significant Spread ◽  
Spatial And Vertical Distribution

&lt;p&gt;A simple variance-maximization approach, based on 19 years of weekly Moderate Resolution Imaging spectroradiometer (MOPITT) CO vertical measurements, was employed to quantify the spatial distribution of the global seasonal biomass burning region. Results demonstrate there are a few large-scale and typical biomass burning regions responsible for most of the biomass burning emissions throughout the world, with the largest of these such regions located in Amazonian South America, Western Africa, Indonesia, and Northern Southeast Asia (Eastern India, Northern Myanmar, Laos, Vietnam and Eastern Bangladesh), which are highly associated with the results of Global Fire Emission Database(GFED). The CO is primarily lofted to and spreads downwind at 800mb or 700mb with three exceptions: The Maritime Continent and South America where there is significant spread at 300mb consistent with known deep- and pyro-convection; and Southern Africa where there is significant spread at 600mb. The total mass of CO lofted into the free troposphere ranges from 46% over Central Africa to 92% over Australia.&lt;/p&gt;

scholarly journals A climate-scale satellite record for carbon monoxide: the MOPITT Version 7 product

2017 ◽  
Vol 10 (7) ◽  
pp. 2533-2555 ◽  
Author(s):  
Merritt N. Deeter ◽  
David P. Edwards ◽  
Gene L. Francis ◽  
John C. Gille ◽  
Sara Martínez-Alonso ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Near Infrared ◽  
Retrieval Algorithm ◽  
Bias Drift ◽  
New Strategy ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Atmospheric Carbon Monoxide ◽  
Climate Scale ◽  
Cloud Mask

Abstract. The MOPITT (Measurements of Pollution in the Troposphere) satellite instrument has been making observations of atmospheric carbon monoxide since 2000. Recent enhancements to the MOPITT retrieval algorithm have resulted in the release of the version 7 (V7) product. Improvements include (1) representation of growing atmospheric concentrations of N2O, (2) use of meteorological fields from the MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications) reanalysis for the entire MOPITT mission (instead of MERRA), (3) use of the MODIS (Moderate-Resolution Imaging Spectroradiometer) Collection 6 cloud mask product (instead of Collection 5), (4) a new strategy for radiance-bias correction and (5) an improved method for calibrating MOPITT's near-infrared (NIR) radiances. Statistical comparisons of V7 validation results with corresponding V6 results are presented, using aircraft in situ measurements as the reference. Clear improvements are demonstrated for V7 products with respect to overall retrieval biases, bias variability and bias drift uncertainty.

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