Abstract Forest disturbances are major sources of carbon dioxide to the atmosphere, and therefore impact global climate. Biogeophysical attributes, such as surface albedo (reflectivity), further control the climate‐regulating properties of forests. Using both tower‐based and remotely sensed data sets, we show that natural disturbances from wildfire, beetle outbreaks, and hurricane wind throw can significantly alter surface albedo, and the associated radiative forcing either offsets or enhances the CO 2 forcing caused by reducing ecosystem carbon sequestration over multiple years. In the examined cases, the radiative forcing from albedo change is on the same order of magnitude as the CO 2 forcing. The net radiative forcing resulting from these two factors leads to a local heating effect in a hurricane‐damaged mangrove forest in the subtropics, and a cooling effect following wildfire and mountain pine beetle attack in boreal forests with winter snow. Although natural forest disturbances currently represent less than half of gross forest cover loss, that area will probably increase in the future under climate change, making it imperative to represent these processes accurately in global climate models.
Multi-angle surface reflectance data from the NASA Jet Propulsion Laboratory Multi-angle Imaging Spectro-Radiometer (MISR) were used to map aboveground biomass density (AGB, Mg ha−1) in the forests of the southwestern United States inter-annually from 2000 to 2015. The approach uses a multi-angle index that has a loge relationship with AGB estimates in the National Biomass and Carbon Dataset 2000 (NBCD 2000). MISR Level 1B2 Terrain radiance data from May 15–June 15 of each year were converted to mapped surface bidirectional reflectance factors (BRFs) and leveraged to adjust the kernel weights of the RossThin-LiSparse-Reciprocal Bidirectional Reflectance Distribution Function (BRDF) model. The kernel weights with the lowest model-fitting RMSE were selected as the least likely to be cloud-contaminated and were used to generate synthetic MISR datasets. An optimal index calculated using BRFs modeled in the solar principal plane was found with respect to NBCD 2000 estimates for 19 sites near Mt. Lindsey, Colorado. These relationships were found in areas with AGB ranging from 20 to 190 Mg ha−1, with the model yielding R2 = 0.91 (RMSE: 15.4 Mg ha−1). With spectral-nadir metrics, the R2 values obtained were 0.07, 0.32, and 0.37 for NIR band BRFs, NDVI, and red band BRFs, respectively. For regional application, a simplified single coefficient model was fitted to the NBCD 2000 data, to account for variations in forest type, soils, and topography. The resulting AGB maps were consistent with estimates from up-scaled 2005 ICESat GLAS data and 2013 NASA Carbon Monitoring System airborne lidar-derived estimates for the Rim Fire area in California; and with the 2005 GLAS-based map across the southwestern United States. Trajectories were stable through time and losses from fire and beetle disturbance matched historical data in published sources. MISR estimates were found to reliably capture ABG compared to radar- and lidar-derived estimates across the southwestern United States (N = 11,019,944), with an RMSE of 37.0 Mg ha−1 and R2 = 0.9 vs GLAS estimates.
The Arctic climate is modulated, in part, by the presence of aerosols that affect the horizontal and vertical distribution of radiant energy passing through the atmosphere. Aerosols affect the surface‐atmosphere radiation balance directly through interactions with solar and terrestrial radiation and indirectly through interactions with cloud particles. During summer 2004 forest fires destroyed vast areas of boreal forest in Alaska and western Canada, releasing smoke into the atmosphere. Smoke aerosol passing over instrumented field sites near Barrow, Alaska, was monitored to determine its physical and optical properties and its impact on the surface radiation budget. Empirical determinations of the direct aerosol radiative forcing (DARF) by the smoke were used to corroborate simulations made using the Moderate Resolution Transmittance radiative transfer model, MODTRAN™5. DARF is defined as the change in net shortwave irradiance per unit of aerosol optical depth (AOD). DARF, varying with solar angle and surface type, was evaluated at the surface, at the top of the atmosphere (TOA), and within the intervening layers of the atmosphere. The TOA results are compared with fluxes derived from coincident satellite retrievals made using the Clouds and the Earth's Radiant Energy System (CERES) radiance data. Smoke tends to reduce the net shortwave irradiance at the surface while increasing it within layers in which it resides. Over the Arctic tundra during summer, a layer of smoke having AOD = 0.5 at 500 nm produces a diurnally averaged DARF of about −40 W m −2 at the surface and −20 W m −2 at TOA, while the layer itself tends to warm at a rate of ≈1 K d −1 . The tendency of smoke to cool the surface while heating the layer above may lead to increased atmospheric stability and suppress cloud formation. Radiative forcing at the top of the atmosphere is especially sensitive to small changes in surface albedo, evidenced in both the model results and satellite retrievals. TOA net shortwave flux decreases when smoke is present over dark surfaces and tends to increase if the underlying surface is bright. For example, at solar noon during midsummer at Barrow, a layer of smoke having AOD(500) = 0.5 will reduce the net shortwave flux at TOA by ≈30 W m −2 over the ocean while at the same time increasing it by 20 W m −2 over an adjacent area of melting sea ice. For smoke aerosol, the sensitivity of DARF to changing surface albedo (assuming a solar zenith angle of 50°) is about +15 W m −2 AOD −1 for every increase in surface albedo of 0.10. Throughout the Arctic summer, surface and TOA cooling and a tendency toward warming in the intervening atmospheric layers are the dominant radiative impacts of boreal smoke over the ocean and tundra areas, but the radiative forcing at TOA is positive over regions covered by ice or snow. Enhanced differential cooling/heating of ocean, ice, and snow due to the presence of smoke in the atmosphere may affect regional circulation patterns by perturbing diabatic processes. Should the frequency and intensity of boreal fires increase in the future because of global warming, the more persistent presence of smoke in the atmosphere may be manifest as a negative feedback at the surface. In addition, there will likely be indirect radiative impacts of the smoke as it influences cloudiness, which in turn further modulates the Arctic radiation budget.
Net ecosystem exchange (NEE) measurements using the eddy covariance technique have been widely used for calibration and evaluation of carbon flux estimates from terrestrial ecosystem models as well as for remote sensing-based estimates across various spatial and temporal scales. Therefore, it is vital to fully understand the land surface characteristics within the area contributing to these flux measurements (i.e. source area) when upscaling plot-scale tower measurements to regional-scale ecosystem estimates, especially in heterogeneous landscapes, such as mixed forests. We estimated the source area of a flux tower at a mixed forest (Harvard Forest in US) using a footprint model, and analyzed the spatial representativeness of the source area for the vegetation characteristics (density variation and magnitude) within the surrounding 1- and 1.5-km grid cells during two decades (1993–2011). Semi-variogram and window size analyses using 19 years of Landsat-retrieved enhanced vegetation index (EVI) confirmed that spatial heterogeneity within the 1-km grid cell has been gradually increasing for leaf-on periods. The overall prevailing source areas lay toward the southwest, yet there were considerable variations in the extents and the directions of the source areas. The source areas generally cover a large enough area to adequately represent the vegetation density magnitude and variation during both daytime and nighttime. We show that the variation in the daytime NEE during peak growing season should be more attributed to variations in the deciduous forest contribution within the source areas rather than the vegetation density. This study highlights the importance of taking account of the land cover variation within the source areas into gap-filling and upscaling procedures.
Abstract Satellite‐derived vegetation greenness and seasonal dynamics in the Amazon have generated considerable academic debate over the past two decades. Despite this, the phenological timing of Amazon forests and, in particular their responses to dry periods, remain poorly understood. Here we explicitly identify the diverse timing of vegetation canopy greenup onsets from 10‐min geostationary satellite observations, and compute the timing of both the start and end of dry periods from daily precipitation data. We, for the first time, reveal that the Amazon vegetation canopy regularly experiences two cycles of greenup onsets during a year. The occurrence of greenup onset varies diversely from the start to end of the dry periods, but demonstrates regular shifts in local areas, although irregular shifts across the region. The multiple greenup onsets show complex spatial shifts, which closely follow the spatial movement of dry periods. The results provide a new insight into our understanding of the complexity of Amazonian vegetation canopy dynamics during dry periods, which could significantly improve the simulation of carbon and water cycles.
Vicarious calibration is the determination of an on-orbit sensor’s radiometric response using measurements over test sites such as Railroad Valley (RRV), Nevada. It has the highest accuracy when a remote sensor’s view angle is aligned with that of the surface measurements, namely at a nadir view. For view angles greater than 10°, the dominant error is the uncertainty in the off-nadir correction factor. The factor is largest in the back-scatter principal plane and can reach 20%. The Orbiting-Carbon Observatory has access to a number of datasets to determine this deviation. These include measurements from field instruments such as the Portable Apparatus for Rapid Acquisition of Bidirectional Observation of the Land and Atmosphere (PARABOLA), as well as satellite measurements from Multi-angle Imaging SpectroRadiometer (MISR) and MODerate resolution Imaging Spectroradiometer (MODIS). The correction factor derived from PARABOLA is consistent in time and space to within 2% for view angles as large as 30°. Field spectrometer data show that the correction term is spectrally invariant. For this reason, a time-invariant model of RRV surface reflectance, along with empirically derived coefficients, is sufficient to use in the calibration of off-nadir sensors, provided there has been no recent rainfall. With this off-nadir correction, calibrations can be expected to have uncertainties within 5%.
Above ground biomass (AGB) is a parameter commonly used for assessment of grassland systems. Destructive AGB measurements, although accurate, are time consuming and are not easily undertaken on a repeat basis or over large areas. Structure-from-Motion (SfM) photogrammetry and Terrestrial Laser Scanning (TLS) are two technologies that have the potential to yield precise 3D structural measurements of vegetation quite rapidly. Recent advances have led to the successful application of TLS and SfM in woody biomass estimation, but application in natural grassland systems remains largely untested. The potential of these techniques for AGB estimation is examined considering 11 grass plots with a range of biomass in South Dakota, USA. Volume metrics extracted from the TLS and SfM 3D point clouds, and also conventional disc pasture meter settling heights, were compared to destructively harvested AGB total (grass and litter) and AGB grass plot measurements. Although the disc pasture meter was the most rapid method, it was less effective in AGB estimation (AGBgrass r2 = 0.42, AGBtotal r2 = 0.32) than the TLS (AGBgrass r2 = 0.46, AGBtotal r2 = 0.57) or SfM (AGBgrass r2 = 0.54, AGBtotal r2 = 0.72) which both demonstrated their utility for rapid AGB estimation of grass systems.
Mountain thunderstorms often originate in preferred regions of the topography, as shown qualitatively by pilot reports and more quantitatively by meteorological radar, satellite, and lightning detector studies. To further investigate the phenomenon of mountain thunderstorm initiation, we used time sequences of GOES imagery to locate storms and to trace them back to their points of origin. Using three summers of data from days which started out clear, we backtracked over 600 storms in the mountains of Colorado and northern New Mexico. We plotted the origin points on a terrain map and drew contours of initiation frequency to identify regions with a high likelihood of producing thunderstorms. We found that initiation sites tended to cluster into identifiable geographical locations or "genesis zones", consistent with findings based on the other data sources. When cloud propagation effects were taken into account, the locations of these genesis zones were also consistent with the locations of clustering regions found in the other studies. In addition to regions where thunderstorm initiations tended to cluster, there were regions that they tended to avoid, including such broad mountain basins as South Park and the San Luis Valley, and such wide river valleys as the Gunnison and Colorado. Besides finding preferred locations for storm initiation, we were also able to stratify the data by ridgetop wind direction. Many of the genesis zones were active only under certain wind regimes. For example, in the southern Sangre de Cristo Mountains, storm initiations tended to occur to the lee of the range under southwesterly, northwesterly, and southeasterly flow at ridgetops. Knowledge of the prevailing flow directions under which genesis zones were active allowed us to determine mechanisms which contributed to storm initiation.
The academician Xiaowen Li devoted much of his life to pursuing fundamental research in remote sensing. A pioneer in the geometric-optical modeling of vegetation canopies, his work is held in high regard by the international remote sensing community. He codeveloped the Li–Strahler geometric-optic model, and this paper was selected by a member of the International Society for Optical Engineering (SPIE) milestone series. As a chief scientist, Xiaowen Li led a scientific team that made outstanding advances in bidirectional reflectance distribution modeling, directional thermal emission modeling, comprehensive experiments, and the understanding of spatial and temporal scale effects in remote sensing information, and of quantitative inversions utilizing remote sensing data. In addition to his broad research activities, he was noted for his humility and his dedication in making science more accessible for the general public. Here, the life and academic contributions of Xiaowen Li to the field of quantitative remote sensing science are briefly reviewed.
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