Edward J. Hyer

Global Monitoring and Forecasting of Biomass-Burning Smoke: Description of and Lessons From the Fire Locating and Modeling of Burning Emissions (FLAMBE) Program

Recently, global biomass-burning research has grown from what was primarily a climate field to include a vibrant air quality observation and forecasting community. While new fire monitoring systems are based on fundamental Earth Systems Science (ESS) research, adaptation to the forecasting problem requires special procedures and simplifications. In a reciprocal manner, results from the air quality research community have contributed scientifically to basic ESS. To help exploit research and data products in climate, ESS, meteorology and air quality biomass burning communities, the joint Navy, NASA, NOAA, and University Fire Locating and Modeling of Burning Emissions (FLAMBE) program was formed in 1999. Based upon the operational NOAA/NESDIS Wild-Fire Automated Biomass Burning Algorithm (WF_ABBA) and the near real time University of Maryland/NASA MODIS fire products coupled to the operational Navy Aerosol Analysis and Prediction System (NAAPS) transport model, FLAMBE is a combined ESS and operational system to study the nature of smoke particle emissions and transport at the synoptic to continental scales. In this paper, we give an overview of the FLAMBE system and present fundamental metrics on emission and transport patterns of smoke. We also provide examples on regional smoke transport mechanisms and demonstrate that MODIS optical depth data assimilation provides significant variance reduction against observations. Using FLAMBE as a context, throughout the paper we discuss observability issues surrounding the biomass burning system and the subsequent propagation of error. Current indications are that regional particle emissions estimates still have integer factors of uncertainty.

Model comparisons for estimating carbon emissions from North American wildland fire

Research activities focused on estimating the direct emissions of carbon from wildland fires across North America are reviewed as part of the North American Carbon Program disturbance synthesis. A comparison of methods to estimate the loss of carbon from the terrestrial biosphere to the atmosphere from wildland fires is presented. Published studies on emissions from recent and historic time periods and five specific cases are summarized, and new emissions estimates are made using contemporary methods for a set of specific fire events. Results from as many as six terrestrial models are compared. We find that methods generally produce similar results within each case, but estimates vary based on site location, vegetation (fuel) type, and fire weather. Area normalized emissions range from 0.23 kg C m−2 for shrubland sites in southern California/NW Mexico to as high as 6.0 kg C m−2 in northern conifer forests. Total emissions range from 0.23 to 1.6 Tg C for a set of 2003 fires in chaparral-dominated landscapes of California to 3.9 to 6.2 Tg C in the dense conifer forests of western Oregon. While the results from models do not always agree, variations can be attributed to differences in model assumptions and methods, including the treatment of canopy consumption and methods to account for changes in fuel moisture, one of the main drivers of variability in fire emissions. From our review and synthesis, we identify key uncertainties and areas of improvement for understanding the magnitude and spatial-temporal patterns of pyrogenic carbon emissions across North America.

Impacts of enhanced biomass burning in the boreal forests in 1998 on tropospheric chemistry and the sensitivity of model results to the injection height of emissions

derived inventories for the fire emissions that differ by a factor of two. We find that it is essential to use both surface and column observations of CO to constrain the magnitude of the fire emissions and their injection altitude. Our results show that the larger of the two inventories appears more reliable and that about half of the emissions were injected above the boundary layer. The boreal fire emissions cause a much larger enhancement in ozone when about half the emissions are released above the boundary layer than when they are releasedexclusivelyintheboundarylayer,asaconsequenceoftheroleofPANasasourceof NOx as air descends in regions far from the fires. Citation: Leung, F.-Y. T., J. A. Logan, R. Park, E. Hyer, E. Kasischke, D. Streets, and L. Yurganov (2007), Impacts of enhanced biomass burning in the boreal forests in 1998 on tropospheric chemistry and the sensitivity of model results to the injection height of emissions, J. Geophys. Res., 112, D10313, doi:10.1029/2006JD008132.

The 2013 Rim Fire: Implications for Predicting Extreme Fire Spread, Pyroconvection, and Smoke Emissions

AbstractThe 2013 Rim Fire, which burned over 104,000 ha, was one of the most severe fire events in California’s history, in terms of its rapid growth, intensity, overall size, and persistent smoke plume. At least two large pyrocumulonimbus (pyroCb) events were observed, allowing smoke particles to extend through the upper troposphere over a large portion of the Pacific Northwest. However, the most extreme fire spread was observed on days without pyroCb activity or significant regional convection. A diverse archive of ground, airborne, and satellite data collected during the Rim Fire provides a unique opportunity to examine the conditions required for both extreme spread events and pyroCb development. Results highlight the importance of upper-level and nocturnal meteorology, as well as the limitations of traditional fire weather indices. The Rim Fire dataset also allows for a detailed examination of conflicting hypotheses surrounding the primary source of moisture during pyroCb development. All pyroCbs wer...

Revealing important nocturnal and day-to-day variations in fire smoke emissions through a multiplatform inversion

We couple airborne, ground-based, and satellite observations; conduct regional simulations; and develop and apply an inversion technique to constrain hourly smoke emissions from the Rim Fire, the third largest observed in California, USA. Emissions constrained with multiplatform data show notable nocturnal enhancements (sometimes over a factor of 20), correlate better with daily burned area data, and are a factor of 2–4 higher than a priori estimates, highlighting the need for improved characterization of diurnal profiles and day-to-day variability when modeling extreme fires. Constraining only with satellite data results in smaller enhancements mainly due to missing retrievals near the emissions source, suggesting that top-down emission estimates for these events could be underestimated and a multiplatform approach is required to resolve them. Predictions driven by emissions constrained with multiplatform data present significant variations in downwind air quality and in aerosol feedback on meteorology, emphasizing the need for improved emissions estimates during exceptional events.

Sensitivity of Mesoscale Modeling of Smoke Direct Radiative Effect to the Emission Inventory: a Case Study in Northern Sub-Saharan African Region

An ensemble approach is used to examine the sensitivity of smoke loading and smoke direct radiative effect in the atmosphere to uncertainties in smoke emission estimates. Seven different fire emission inventories are applied independently to WRF-Chem model (v3.5) with the same model configuration (excluding dust and other emission sources) over the northern sub-Saharan African (NSSA) biomass-burning region. Results for November and February 2010 are analyzed, respectively representing the start and end of the biomass burning season in the study region. For February 2010, estimates of total smoke emission vary by a factor of 12, but only differences by factors of 7 or less are found in the simulated regional (15°W–42°E, 13°S–17°N) and monthly averages of column PM2.5 loading, surface PM2.5 concentration, aerosol optical depth (AOD), smoke radiative forcing at the top-of-atmosphere and at the surface, and air temperature at 2 m and at 700 hPa. The smaller differences in these simulated variables may reflect the atmospheric diffusion and deposition effects to dampen the large difference in smoke emissions that are highly concentrated in areas much smaller than the regional domain of the study. Indeed, at the local scale, large differences (up to a factor of 33) persist in simulated smoke-related variables and radiative effects including semi-direct effect. Similar results are also found for November 2010, despite differences in meteorology and fire activity. Hence, biomass burning emission uncertainties have a large influence on the reliability of model simulations of atmospheric aerosol loading, transport, and radiative impacts, and this influence is largest at local and hourly-to-daily scales. Accurate quantification of smoke effects on regional climate and air quality requires further reduction of emission uncertainties, particularly for regions of high fire concentrations such as NSSA.

Evaluating the impact of multisensor data assimilation on a global aerosol particle transport model

By evaluating quality-assured Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target (DT), MODIS Deep Blue (DB), Multiangle Imaging Spectroradiometer (MISR), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol products assimilated into the U. S. Navy Aerosol Analysis and Prediction System (NAAPS), the impact of single-sensor and multisensor data assimilation on aerosol optical depth (AOD) analysis and forecast skill is characterized using ground-based Level 2 Aerosol Robotic Network (AERONET) data sets during the 2007 boreal summer (June–August 2007). The single-sensor assimilation experiment suggests that all products tested can improve NAAPS performance on a regional or a global scale. The multisensor assimilation experiment suggests that model improvement is greatest with the combined use of Terra and Aqua MODIS DT products, largely due to data density. Incremental improvements are identified, as a function of data density, over regions such as the Saharan desert when adding MISR and MODIS DB products. The inclusion of CALIOP data is mass-neutral by definition and has an insignificant impact on the NAAPS 00 h analysis. CALIOP assimilation does improve the 48 h forecast from NAAPS due to more accurate 00 h vertical distribution and hence forecasted advection. Root-mean-square errors exceeding 0.1 are found over East Asia and North Africa for both the NAAPS analysis and satellite AOD data, indicating that satellite aerosol products in these two regions need improvement. Similarly, low correlation is found between NAAPS and AERONET over Australia, even with the use of all available satellite aerosol products, suggesting that more detailed examination of some critical regions is necessary.

CALIOP Aerosol Subset Processing for Global Aerosol Transport Model Data Assimilation

A system for processing Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite-based 0.532 and 1.064 elastic and polarization lidar datasets for global aerosol transport model assimilation is described. A method for constructing one-degree along-track and cloud-free signal composite averages, consistent with Navy Aerosol Analysis and Prediction System (NAAPS) model gridding, using CALIOP Level 1B attenuated backscatter and Level 2 cloud boundary-height products is outlined. Optimal vertical resolutions and relative signal uncertainties for the composite signal averages are described for both day and nighttime measurement scenarios. Depolarization profiles are described for the 0.532 channel as well as attenuated color ratio profiles using 0.532 and 1.064 attenuated backscatter measurements. Constrained by NAAPS model aerosol optical depths, processed attenuated backscatter profiles are inverted to solve for extinction and backscatter coefficients, their ratio, and extinction coefficient profiles which serve as the basis for data assimilation.

Quantifying the potential for high‐altitude smoke injection in the North American boreal forest using the standard MODIS fire products and subpixel‐based methods

All chemical transport models require an estimation of the vertical distribution of smoke particles near the source. This study quantitatively examines the strengths and weaknesses of several fire products for characterizing plume buoyancy and injection heights in the North American boreal forest during 2004–2005. Observations from the Multiangle Imaging Spectroradiometer show that 21% of smoke plumes are injected more than 500 m above the boundary layer (BL500) and 8% exceed 2.5 km above ground level. Corresponding observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) show that probability of injection above the BL500 exceeds 60% for pixel-based fire radiative power (FRPp) values above ~2500 MW. Increasing values of subpixel-retrieved fire area and temperature also correspond to higher injections but only after removing fire pixels with a weak 11 µm fire signal and clustering. The probability of injection above the BL500 reaches 50% when the subpixel radiant flux (FRPf flux) exceeds 20 kW/m2, highlighting its potential for estimating plume buoyancy. However, these data have limitations similar to FRPp, where the highest probability of injection corresponds to a small percentage of the data set (5–18%), and many high-altitude injections occur with lower values. Examinations of individual smoke plumes highlight the importance of combining pixel-level and subpixel outputs and show that plume injection is also sensitive to the fire pixel spatial distribution and meteorology. Therefore, an optimal method for predicting high-altitude injections will require some combination of injection climatology, FRPp, FRPf flux, and meteorology, but each variables importance will depend on fire event characteristics.

Detection of vegetation fires and burnt areas by remote sensing in insular Southeast Asian conditions: current status of knowledge and future challenges

The humid tropical insular Southeast Asian region is one of the most biologically diverse areas in the world. It contains around 70 Gt of carbon stored in peat deposits susceptible to burning when drained and it has significantly higher population density than any other humid tropical region. This region experiences yearly fire activity of anthropogenic origin with widely varying extent and severity. At the same time, there are several geographic, climatic, and social aspects that complicate fire monitoring in the region. In this review article, we analyse the current knowledge and limitations of active fire detection and burnt area mapping in insular Southeast Asia, highlighting the special characteristics of the region that affect all types of remote-sensing-based regional-level fire monitoring. We conclude that the monitoring methods currently employed have serious limitations that directly affect the reliability of results for fire and burnt area monitoring in this region. With the materials and methods presently available, the regional and global effects of fire activity taking place in insular Southeast Asia are in danger of being underestimated. New approaches utilizing higher spatial and temporal resolution remote-sensing data are needed for more detailed quantification of fire activity and subsequently improved estimation of the effects of fires in this region.