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Seasonal and Interannual Assessment of Cloud Cover and Atmospheric Constituents Across the Amazon (2000 - 2015): Insights for Remote Sensing and Climate Analysis

The quantitative assessment of cloud cover and atmospheric constituents improves our ability to exploit the climate feedback into the Amazon basin. In the 21st century, three droughts have already occurred in the Amazonia (e.g. 2005, 2010, 2015), inducing regional changes in the seasonal patterns of atmospheric constituents. In addition to climate, the atmospheric dynamic and attenuation properties are long-term challenges for satellite-based remote sensing of this ecosystem: high cloudiness, abundant water vapor content and biomass burning season. Therefore, while climatology analysis supports the understanding of atmospheric variability and trends, it also offers valuable insights for remote sensing applications. In this study, we evaluate the seasonal and interannual variability of cloud cover and atmospheric constituents (aerosol loading, water vapor and ozone content) over the Amazon basin, with focus on both climate analysis and remote sensing implications. We take the advantage of new atmosphere daily products at 1 km resolution derived from Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data. An intercomparison of Aerosol Robotic Network (AERONET) and MAIAC aerosol optical depth (AOD) and columnar water vapor (CWV) showed quantitative information with a correlation coefficient higher than 0.81. Our results show distinct regional patterns of cloud cover across the Amazon basin: northwestern region presets a persistent cloud cover (> 80%) throughout the year, while low cloud cover (0-20%) occurs in the southern Amazon during the dry season. The cloud-free period in the southern Amazon is followed by an increase in the atmospheric burden due to fire emissions. Our results reveal that AOD records are changing in terms of area and intensity. During the 2005 and 2010 droughts, the positive AOD anomalies (δ > 0.1) occurred over 39.03% (240.3 million ha) and 27.14% (165.99 million ha) of total basin in the SON season, respectively. In contrast, the recent 2015 drought occurred towards the end of year (October through December) and these anomalies were observed over 23.72% (145 million ha) affecting areas in the central and eastern Amazon unlike previous droughts. The water vapor presents high concentration values (4.0-5.0 g/sq.cm) in the wet season (DJF), while we observed a strong spatial gradient from northwestern to southeastern of the basin during the dry season. In addition, we also found a positive trend of water vapor content ( ∼0.3 g/sq.cm) between 2000 and 2015. The total ozone typically varies between 220 and 270 DU, and it has a seasonal change of ∼25-35 DU from wet season to dry season caused by large emissions of ozone precursors and long-range transport. Finally, while this study contributes to climatological analysis of atmospheric constituents, the remote sensing users can also understand the regional constraints caused by atmospheric attenuation, such as high aerosol loading and cloud obstacles for surface observations.

ozone↗

Analysis of CO Transport from Australia Fires and Its Impact to Ozone, Water Vapor and Clouds Using CrIS Single-Field-of-View Sounder Products and Other Remote Sensing and MERRA-2 Reanalysis Data

Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles, and the long-range transport of the smoke plumes poses great impact to climate change, such as altering the Antarctic ozone (O3) hole. Spaceborne observations from satellites have been proven successful in monitoring CO from wildfires in the past decade and can be used to examine the associated CO transport. The primary remote sensing data used in this study is the Single Field of View (SFOV) Sounder Atmospheric Product (SiFSAP) derived from the Cross-track Infrared Sounder (CrIS) on SNPP, a new product that will be generated at NASA and released to the public in a few months. SiFSAP has a high spatial resolution of ~14 km and includes atmospheric profiles of temperature, water vapor, CO, O3, as well as cloud products, and as the SiFSAP algorithm performs both day- and night-time retrievals, it provides an additional observation for night-time in comparison to the day-time-only solar polar satellite instruments such as MOPPIT, OMPS, and TROPOMI. Most recent significant improvements in the quality of this product plus its good spatial resolution (better than most global weather and climate models) enable us to conduct process-oriented analysis of CO transport, and the variation of water vapor, O3 and clouds (optical depth, effective radius and cloud height) within and around the fire plumes. The wind fields from MERRA-2 reanalysis will be used to help characterize the transport. Other remote sensing data, such as CO from AIRS, MOPPIT and TROPOMI, O3 from OMPS and TROPOMI, as well as the UV aerosol index from OMI and OMPS, will be used and compared with SiFSAP sounder products. Cross-validation of CO and O3 from these different sensors with the corresponding MERRA-2 products will also be carried out. Along the plume transport path, some enhancement of O3 and correlation between fire aerosol, cloud optical depth and water vapor have been found but need further investigation. Using the transport of fire plumes over the Southern Pacific Ocean as a unique testbed, this study will demonstrate the trace species monitoring capability of current satellite observations, in particular, for CO and O3, and hopefully, it will provide some insight on the impacts on fire emissions on air quality and climate.

Xiaozhen (Shawn) Xiong↗

Land Cover Change Analysis and Spatial Variations in Southeast Asian Nations: Insights on Spatial Scale Dynamics

Land cover type is a fundamental aspect of studies using remote sensing for environmental analysis such as monitoring deforestation, quantifying wildland fire emissions, and more. There are many land cover products available for varying time periods and spatial resolutions, each with different land cover class definitions and number of land cover classes. These differences yield inherent variation in land cover estimates. In this study, we explore the spatial and areal variation between two major datasets for their commonly available time of 2018 to 2022 (MODIS 500m Land Cover and Esri Sentinel-2 10m land cover) in the continental Southeast Asia countries of Cambodia, Laos, Myanmar, Thailand, and Vietnam. To enable comparison, we resampled the datasets and reclassified the land cover classes to a common scheme. Major disagreement was detected between Esri and MODIS, especially for the wetlands/flooded vegetation class in which only 3.6% of pixels were in agreement. In addition to quantifying variation between the datasets, we quantify land cover change at the decadal scale of 2001, 2011, and 2021 for each country and identified province-level hotspots of land cover change. Cambodia experienced the highest rate of land cover change with 67.8% of total land area changed, followed by Vietnam (58.6%), Laos (50.2%), Myanmar (46.9%), and Thailand (46.3%). The highest rate of land cover change was detected in Odtar Mean Chey, Cambodia, which had large swaths of forest area cleared for agricultural production, river damming, and more. Ultimately, many areas in the region experienced forest clearing for crop production (i.e. rice) which appeared to be classified as wetland in the MODIS product, and crop in the Esri product. Myanmar was the only country which did not experience net decline in forest area over the 2001 to 2021 time period.

Land Cover Change↗

Gaseous emissions from Canadian boreal forest fires

CO2-normalized emission ratios for carbon monoxide (CO), hydrogen (H2), methane (CH4), total nonmethane hydrocarbons (TNMHC), and nitrous oxide (N2O) were determined from smoke samples collected during low-altitude helicopter flights over two prescribed fires in northern Ontario, Canada. The emission ratios determined from these prescribed boreal forest fires are compared to emission ratios determined over two graminoid (grass) wetlands fires in central Florida and are found to be substantially higher (elevated levels of reduced gas production relative to CO2) during all stages of combustion. These results argue strongly for the need to characterize biomass burning emissions from the major global vegetation/ecosystems in order to couple combustion emissions to their vegetation/ecosystem type.

Cofer, Wesley R., III↗

Integrated Active Fire Retrievals and Biomass Burning Emissions Using Complementary Near-Coincident Ground, Airborne and Spaceborne Sensor Data

Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed near coincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge between ground and spaceborne data sets providing high quality reference information to support satellite fire retrieval error analyses and fire emissions estimates. We found excellent agreement between peak fire radiant heat flux data (less than 1% error) derived from near-coincident ground radiometers and AMS. Both MODIS and GOES imager active fire products were negatively influenced by the presence of thick smoke, which was misclassified as cloud by their algorithms, leading to the omission of fire pixels beneath the smoke, and resulting in the underestimation of their retrieved fire radiative power (FRP) values for the burn plot, compared to the reference airborne data. Agreement between airborne and spaceborne FRP data improved significantly after correction for omission errors and atmospheric attenuation, resulting in as low as 5 difference between AquaMODIS and AMS. Use of in situ fuel and fire energy estimates in combination with a collection of AMS, MODIS, and GOES FRP retrievals provided a fuel consumption factor of 0.261 kg per MJ, total energy release of 14.5 x 10(exp 6) MJ, and total fuel consumption of 3.8 x 10(exp 6) kg. Fire emissions were calculated using two separate techniques, resulting in as low as 15 difference for various species

airborne scanner↗

Measurement of Fire Radiative Energy from Space and Implications for Fire-Disaster Monitoring and Smoke Emissions Modeling

Measurement of fire radiative energy (FRE) release rate or power (FRP) from satellite provides a vital mechanism for distinguishing different strengths of fires. Analysis of 1-km resolution fire data, acquired globally by the MODerate-resolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites from 2000 to 2006, showed instantaneous FRP values ranging between 0.02 MW and 1866 MW, to which simple thresholds can be applied to categorize fires by strength, in a similar fashion as the strengths of earthquakes and hurricanes. Analysis of regional mean FRP per unit area of land (FRP flux) shows that at peak fire season in certain regions, fires can be responsible for up to 0.2 W/m2 at peak time of day. When considered as the active fire contribution to the direct surface radiative forcing (RF) in the different fire regions, this order of magnitude of FRF fluxes is non negligible. It has been determined experimentally that the amount of FRE released by a fire over the course of its duration is directly proportional to the amount of biomass consumed by it. Furthermore, at the satellite observation scale, the rate of release of FRE (i.e. FRP) is proportional to the rate of biomass consumption, and that of emission of smoke particulates and eventually also other smoke constituents. Therefore, current research efforts are geared toward deriving simple parameterizations that will facilitate direct input of FRP measurements in models, not only to improve the accuracy of burned-biomass and smoke emissions estimations, but also to reduce the hitherto practiced heavy reliance on multiple indirect parameters with indeterminate uncertainties.

Ichoku, Charles↗

Forest Understory Fire in the Brazilian Amazon in ENSO and Non-ENSO Years: Area Burned and Committed Carbon Emissions

"Understory fires" that burn the floor of standing forests are one of the most important types of forest impoverishment in the Amazon, especially during the severe droughts of El Nino Southern Oscillation (ENSO) episodes. However, we are aware of no estimates of the areal extent of these fires for the Brazilian Amazon and, hence, of their contribution to Amazon carbon fluxes to the atmosphere. We calculated the area of forest understory fires for the Brazilian Amazon region during an El Nino (1998) and a non El Nino (1995) year based on forest fire scars mapped with satellite images for three locations in eastern and southern Amazon, where deforestation is concentrated. The three study sites represented a gradient of both forest types and dry season severity. The burning scar maps were used to determine how the percentage of forest that burned varied with distance from agricultural clearings. These spatial functions were then applied to similar forest/climate combinations outside of the study sites to derive an initial estimate for the Brazilian Amazon. Ninety-one percent of the forest area that burned in the study sites was within the first kilometer of a clearing for the non ENSO year and within the first four kilometers for the ENSO year. The area of forest burned by understory forest fire during the severe drought (ENSO) year (3.9 millions of hectares) was 13 times greater than the area burned during the average rainfall year (0.2 million hectares), and twice the area of annual deforestation rate. Dense forest was, proportionally, the forest area most affected by understory fires during the El Nino year, while understory fires were concentrated in transitional forests during the year of average rainfall. Our estimate of aboveground tree biomass killed by fire ranged from 0.06 Pg to 0.38 Pg during the ENSO and from 0,004 Pg to 0,024 Pg during the non ENSO.

Alencar, A.↗

The effects of fire on biogenic emissions of methane and nitric oxide from wetlands

Enhanced emissions of methane (CH4) and nitric oxide (NO) were measured following three controlled burns in a Florida wetlands in 1987 and 1988. Wetlands are the major global source of methane resulting from metabolic activity of methanogenic bacteria. Methanogens require carbon dioxide, acetate, or formate for their growth and the metabolic production of methane. All three water-soluble compounds are produced in large concentrations during biomass burning. Postfire methane emissions exceeded 0.15 g CH 4/sq m per day. Preburn and postburn measurements of soil nutrients indicate significant postburn increases in soil ammonium, from 8.35 to 13.49 parts per million (ppm) in the upper 5 cm of the Juncus marsh and from 8.83 to 23.75 ppm in the upper 5 cm of the Spartina marsh. Soil nitrate concentrations were found to decrease in both marshes after the fire. These measurements indicate that the combustion products of biomass burning exert an important 'fertilizing' effect on the biosphere and on the biogenic production of environmentally significant atmospheric gases.

Levine, Joel S.↗

The Darkening of the Greenland Ice Sheet: Trends, Drivers and Projections (1981-2100)

The surface energy balance and meltwater production of the Greenland ice sheet (GrIS) are modulated by snow and ice albedo through the amount of absorbed solar radiation. Here we show, using space-borne multispectral data collected during the 3 decades from 1981 to 2012, that summertime surface albedo over the GrIS decreased at a statistically significant (99 %) rate of 0.02 decade(sup -1) between 1996 and 2012. Over the same period, albedo modelled by the Modele Atmospherique Regionale (MAR) also shows a decrease, though at a lower rate (approximately -0.01 decade(sup -1)) than that obtained from space-borne data. We suggest that the discrepancy between modelled and measured albedo trends can be explained by the absence in the model of processes associated with the presence of light-absorbing impurities. The negative trend in observed albedo is confined to the regions of the GrIS that undergo melting in summer, with the dry snow zone showing no trend. The period 1981-1996 also showed no statistically significant trend over the whole GrIS. Analysis of MAR outputs indicates that the observed albedo decrease is attributable to the combined effects of increased near-surface air temperatures, which enhanced melt and promoted growth in snow grain size and the expansion of bare ice areas, and to trends in light-absorbing impurities (LAI) on the snow and ice surfaces. Neither aerosol models nor in situ and remote sensing observations indicate increasing trends in LAI in the atmosphere over Greenland. Similarly, an analysis of the number of fires and BC emissions from fires points to the absence of trends for such quantities. This suggests that the apparent increase of LAI in snow and ice might be related to the exposure of a "dark band" of dirty ice and to increased consolidation of LAI at the surface with melt, not to increased aerosol deposition. Albedo projections through to the end of the century under different warming scenarios consistently point to continued darkening, with albedo anomalies averaged over the whole ice sheet lower by 0.08 in 2100 than in 2000, driven solely by a warming climate. Future darkening is likely underestimated because of known underestimates in modelled melting (as seen in hindcasts) and because the model albedo scheme does not currently include the effects of LAI, which have a positive feedback on albedo decline through increased melting, grain growth, and darkening.

surface energy↗

Trace gas emissions from a mid-latitude prescribed chaparral fire

Smoke-plume gas samples were collected at altitudes from 35-670 m above the ground over the San Dimas Experimental Forest during a 400-acre prescribed chaparral fire. Mean emission ratios relative to CO2 for CO, H2, CH4, and total nonmethane hydrocarbons were lower than previous values obtained for large biomass-burning field experiments. Comparison of samples from vigorously flaming and mixed stages of combustion revealed little differences in CO2 normalized emission ratios for these gases (except for N2O).

Cofer, Wesley R., III↗

Emissions Relationships in Western Forest Fire Plumes: I. Reducing the Effect of Mixing Errors on Emission Factors

Studies of emission factors from biomass burning using aircraft data complement the results of lab studies and extend them to conditions of immense hot conflagrations. We illustrate and discuss emission relationships for 422 individual samples from many forest-fire plumes in the Western US. The samples are from two NASA investigations: ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) and SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys). This work provides sample-by-sample enhancement ratios (EnRs) for 23 gases and particulate properties. Many EnRs provide candidates for emission ratios (ERs, corresponding to the EnR at the source) when the origin and degree of transformation is understood and appropriate. From these, emission factors (EFs) can be estimated when the fuel dry mass consumed is known or can be estimated using the carbon mass budget approach. This analysis requires understanding the interplay of mixing of the plume with surrounding air. Some initial examples emphasize that measured C(tot) = CO2 + CO in a fire plume does not necessarily describe the emissions of the total carbon liberated in the flames, C(burn). Rather, it represents C(tot) = C(burn) + C(bkgd), which includes possibly varying background concentrations for entrained air. Consequently, we present a simple theoretical description for plume entrainment for multiple tracers from flame to hundreds of kilometers downwind and illustrate some intrinsic linear behaviors. The analysis suggests a Mixed Effects Regression Emission Technique (MERET), which can eliminate occasional strong biases associated with the commonly used normalized excess mixing ratio (NEMR) method. MERET splits C(tot) to reveal C(burn) by exploiting the fact that C(burn) and all tracers respond linearly to dilution, while each tracer has consistent EnR behavior (slope of tracer concentration with respect to C(burn)). The two effects are separable. Two or three or preferably more emission indicators are required as a minimum; here we used ten. Limited variations in the EnRs for each tracer can be incorporated and the variations and co-variations analyzed. The percentage CO yield (or the modified combustion efficiency) plays some role. Other co-relationships involving nitrogen and organic classes are more prominent; these have strong relationships to the C(burn) to O3 emission relationship. In summary, MERET allows fine spatial resolution (EnRs for individual observations) and comparison of similar plumes distant in time and space. Alkene ratios provide us with an approximate photochemical timescale. This allows discrimination and definition, by fire situation, of ERs, allowing us to estimate emission factors.

Chatfield, Robert B.↗

The Impacts of Recent Drought on Fire, Forest Loss, and Regional Smoke Emissions in Lowland Bolivia

In the southern Amazon relationships have been established among drought, human activities that cause forest loss, fire, and smoke emissions. We explore the impacts of recent drought on fire, forest loss, and atmospheric visibility in lowland Bolivia. To assess human influence on fire, we consider climate, fire, and vegetation dynamics in an area largely excluded from human activities since 1979, Noel Kempff Mercado National Park (NK) in northeastern Bolivia. We use data from five sources: the Moderate Resolution Imaging Spectroradiometer Collection 6 active fire product (2001-2015) (MODIS C6), Global Fire Weather Database (GFWED) data (1982-2015), MODIS land cover data (2001-2010), MODIS forest loss data (2000-2012), and the regional extinction coefficient for the southwestern Amazon (i.e., B(sub ext)), which is derived from horizontal visibility data from surface stations at the World Meteorological Organization (WMO) level (1973-2015). The B(sub ext) is affected by smoke and acts as a proxy for visibility and regional fire emissions. In lowland Bolivia from 2001 to 2015, interannual Drought Code (DC) variability was linked to fire activity, while from 1982 to 2015, interannual DC variability was linked to B(sub ext). From 2001 to 2015, the B(sub ext) and MODIS C6 active fire data for lowland Bolivia captured fire seasonality, and covaried between low- and high-fire years. Consistent with previous studies, our results suggest B(sub ext)t can be used as a longer-term proxy of regional fire emissions in southwestern Amazonia. Overall, our study found drought conditions were the dominant control on interannual fire variability in lowland Bolivia, and fires within NK were limited to the Cerrado and seasonally inundated wetland biomes. Our results suggest lowland Bolivian tropical forests were susceptible to human activities that may have amplified fire during drought. Human activities and drought need to be considered in future projections of southern Amazonian fire, in regard to carbon emissions and global climate.

Forest Loss↗

Emission Factors for Crop Residue and Prescribed Fires in the Eastern US during FIREX-AQ

Agricultural and prescribed burning activities emit large amounts of trace gases and aerosols on regional to global scales. We present a compilation of emission factors (EFs) and emission ratios (ERs) from the eastern portion of the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign in 2019 in the United States, which sampled burning of crop residues and other prescribed fire fuels. FIREX-AQ provided comprehensive chemical characterization of 53 crop residue and 22 prescribed fires. Crop residues burned at different modified combustion efficiencies (MCE), with corn residue burning at higher MCE than other fuel types. Prescribed fires burned at lower MCE (<0.90) which is typical, while grasslands burned at lower MCE (0.90) than normally observed due to moist, green, growing season fuels. Most non-methane volatile organic compounds (NMVOCs) were significantly anticorrelated with MCE except for ethanol and NMVOCs that were measured with less certainty. We identified 23 species where crop residue fires differed by more than 50% from prescribed fires at the same MCE. Crop residue EFs were greater for species related to agricultural chemical use and fuel composition as well as oxygenated NMVOCs possibly due to the presence of metals such as potassium. Prescribed EFs were greater for monoterpenes (5×). FIREX-AQ crop residue average EFs generally agreed with the previous agricultural fire study in the US but had large disagreements with global compilations. FIREX-AQ observations show the importance of regionally-specific and fuel-specific EFs as first steps to reduce uncertainty in modeling the air quality impacts of fire emissions.

air quality↗

2020 Wildfire Plumes Observed by Satellite and Ground Sensors in the San Francesco Bay Area

The main purpose of this research is to study the spreading of the 2020 wildfire plumes in the San Francisco Bay Area. Last year’s fire plumes have caused severe impact on regional air quality and public health over large part of the west coast. We studied fire plumes with two datasets: aerosol optical depth (AOD) retrieved from MODIS sensor onboard two NASA satellites (Terra and Aqua), and surface PM2.5 measurements from US EPA. Satellite can monitor fire plumes from a top-down view, including active fire location, emission amount, spreading of the fire plume in both horizontal and vertical directions. EPA records air quality using the ground network of in-situ sensors. In general the two points of view are consistent with each other. But in the peak of the 2020 fire season, we found an episode where the AOD and PM2.5 are out-of-phase for two days. We explored the possible mechanism for this shift with available meteorological measurements, including both ground measurements and sounding data. By tracking the evolution of the sounding data, we concluded a heated near surface inversion layer might shield the region from aloft fire plumes for two days before they touch down and severely downgraded the air quality over the whole Bay area.

Hazem Mahmoud↗

2020 Wildfire Plumes Observed by Satellite and Ground Sensors at San Francisco Bay

The main purpose of this research is to study the spreading of the 2020 wildfire plumes in the San Francisco Bay Area. Last year’s fire plumes have caused severe impact on regional air quality and public health over large part of the west coast. We studied fire plumes with two datasets: aerosol optical depth (AOD) retrieved from MODIS sensor onboard two NASA satellites (Terra and Aqua), and surface PM2.5 measurements from US Environmental Protection Agency (EPA). Satellite can monitor fire plumes from a top-down view, including active fire location, emission amount, spreading of the fire plume in both horizontal and vertical directions. EPA records air quality using the ground network of in-situ sensors. In general, the two points of view are consistent with each other. But in the peak of the 2020 fire season, we found an episode where the AOD and PM2.5 are out-of-phase for two days, in addition data from NASA satellite AERONET was use to corroborate AOD information for the episode, yielding similar results. Thereafter, we explored the possible mechanism for this shift with available meteorological measurements, including both ground measurements and sounding data. By tracking the evolution of the sounding data, we concluded a heated near surface inversion layer might shield the region from aloft fire plumes for two days before they touch down and severely downgraded the air quality over the whole Bay area.

Hazem Mahmoud↗

Fan Beam Emission Tomography for Laminar Fires

Obtaining information on the instantaneous structure of turbulent and transient flames is important in a wide variety of applications such as fire safety, pollution reduction, flame spread studies, and model validation. Durao et al. has reviewed the different methods of obtaining structure information in reacting flows. These include Tunable Laser Absorption Spectroscopy, Fourier Transform Infrared Spectroscopy, and Emission Spectroscopy to mention a few. Most flames emit significant radiation signatures that are used in various applications such as fire detection, light-off detection, flame diagnostics, etc. Radiation signatures can be utilized to maximum advantage for determining structural information in turbulent flows. Emission spectroscopy is most advantageous in the infrared regions of the spectra, principally because these emission lines arise from transitions in the fundamental bands of stable species such as CO2 and H2O. Based on the above, the objective of this work was to develop a fan beam emission tomography system to obtain the local scalar properties such as temperature and mole fractions of major gas species from path integrated multi-wavelength infrared radiation measurements.

Sivathanu, Yudaya↗