Publications

Observing the carbon-climate system

Increases in atmospheric CO2 and CH4 result from a combination of forcing from anthropogenic emissions and Earth System feedbacks that reduce or amplify the effects of those emissions on atmospheric concentrations. Despite decades of research carbon-climate feedbacks remain poorly quantified. The impact of these uncertainties on future climate are of increasing concern, especially in the wake of recent climate negotiations. Emissions, long concentrated in the developed world, are now shifting to developing countries, where the emissions inventories have larger uncertainties. The fraction of anthropogenic CO2 remaining in the atmosphere has remained remarkably constant over the last 50 years. Will this change in the future as the climate evolves? Concentrations of CH4, the 2nd most important greenhouse gas, which had apparently stabilized, have recently resumed their increase, but the exact cause for this is unknown. While greenhouse gases affect the global atmosphere, their sources and sinks are remarkably heterogeneous in time and space, and traditional in situ observing systems do not provide the coverage and resolution to attribute the changes to these greenhouse gases to specific sources or sinks. In the past few years, space-based technologies have shown promise for monitoring carbon stocks and fluxes. Advanced versions of these capabilities could transform our understanding and provide the data needed to quantify carbon-climate feedbacks. A new observing system that allows resolving global high resolution fluxes will capture variations on time and space scales that allow the attribution of these fluxes to underlying mechanisms.

Remote sensing of tropical ecosystems: Atmospheric correction and cloud masking matter

Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazônia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 — Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90% and 99%, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased aerosol levels was observed during the dry season, with an inverse dependence of NDVI on aerosol optical thickness (AOT). NDVI observations processed with MAIAC showed highly reproducible and stable inter-annual patterns with little or no dependence on cloud cover, and no significant dependence on AOT (p <0.05). In addition to a better detection of cloudy pixels, MAIAC obtained about 20–80% more cloud free pixels, depending on season, a considerable amount for land analysis given the very high cloud cover (75–99%) observed at any given time in the area. We conclude that a new generation of atmospheric correction algorithms, such as MAIAC, can help to dramatically improve vegetation estimates over tropical rain forest, ultimately leading to reduced uncertainties in satellite-derived vegetation products globally.

Identifying the Dimensions of Degraded Impact Structures Using Digital Elevation Models: A Proof of Concept for Silicate Planets

Determining the physical dimensions of hypervelocity impact structures is challenging due to erosion of their primary relief features on Earth. Critical measurements, such as outer rim diameter, are important for estimating the kinetic energy released and subsequent environmental effects. We developed a Radial Profile Analysis System algorithm, which uses a digital elevation model (DEM) to identify topographic rings surrounding a complex impact structure through an iterative process that assigns the most consistently identified positive relief ring as the apparent outer rim. We investigated five terrestrial impact structures across a range of apparent diameters whose physical dimensions are well established from geological or geophysical studies. Multiple DEM data sets from 2 to 30 m horizontal resolution were evaluated to determine the role of spatial resolution in estimating apparent outer rim diameters. The most reliable predictions were achieved using the 12 m TanDEM-X data set with an estimated error ≤16%. We then achieved an estimated error ≤8% when applying the algorithm to three Martian peak ring impact structures (Kepler, Lowell, and Lyot) using 200 m resolution DEMs, and 1%–13% when applied to a 600 m resolution DEM of the Mead multi-ringed impact structure on Venus. Our results indicated that apparent outer rim diameters of complex impact structures can be estimated using these methods with reasonable reliability, but prediction efficacy decreased with decreasing DEM vertical fidelity. Application of these methods to additional impact structures is required to quantify prediction uncertainty before applying this methodology to more recent impact structures with questionable diameters.

Application of AVHRR vegetation index to study atmosphere-biosphere exchange of CO2

The Advanced Very High Resolution Radiometer (AVHRR) satellite-borne sensor is presently used, together with field data, to determine the geographic distributions of the seasonal exchange of CO2 between the earth's atmosphere and the terrestrial biota. The exchange functions thus obtained are validated in virtue of the ability to reproduce the observed annual cycle of atmospheric CO2 in a three-dimensional tracer transport model. The AVHRR is carried by the TIROS-N series of polar-orbiting satellites.

Remote Sensing of Biomass Burning in the Tropics

Variability of terrestrial CO2 fluxes after volcanic eruptions

No abstract is provided for this article.

Monitoring forest degradation from charcoal production with historical Landsat imagery. A case study in southern Mozambique

We used historical Landsat imagery to monitor forest degradation from charcoal production in the main supplying region of the Mozambican capital, Maputo, during a ten-year period (2008–2018). We applied a change detection method that exploits temporal NDVI dynamics associated with charcoal production. This forest degradation temporal sequence exposes the magnitude and the spatial and temporal dynamics of charcoal production, which is the main forest degradation driver in sub-Saharan Africa. The annual area under charcoal production has been steadily increasing since 2008 and reached 11 673 ha in 2018. The total forest degraded extent in the study area during the 10-year study period covered 79 630 ha, which represents 68% of the available mopane woodlands in 2008. Only 5% of the available mopane woodlands area remain undisturbed in the study area. Total gross carbon emissions associated charcoal production during this 10-year period were estimated in 1.13 Mt. These results mark forest degradation from charcoal production as the main driver of forest cover change in southern Mozambique. They also denote that, while charcoal production may be relatively localized in space, its implications for forest cover change and carbon emissions in a sub-Saharan African context are relevant at larger geographical scales. This study represents a proof of concept of the feasibility of medium resolution Earth observation data to monitor forest degradation from charcoal production in the context of the growing urban energy demand. It also highlights the potential opportunities to improve REDD+ monitoring, reporting and verification efforts in sub-Saharan Africa as a first step toward designing effective management and policy interventions.

The potential of satellite remote sensing of ecological conditions for survey and forecasting desert-locust activity

Agricultural crops and rangeland resources over above 30 million km2 in some 55 Third World countries arc subject to ravages by the desert locust. Successful breeding, triggered by suitable ecological conditions when widespread rainfall results in development of vegetation in the desert-locust recession area, can produce rapid increases in desert-locust populations, resulting, if uncontrolled, in large numbers of highly mobile and devastating swarms containing billions of locusts. Satellite remote sensing offers the only possibility of monitoring the 16 million km2 desert-locust recession area situated largely in remote and inaccessible deserts of northern and eastern Africa, the Near East, and south-west Asia. Use of LANDSAT and National Oceanic and Atmospheric Administration (NOAA) satellite imagery for analyses of green vegetation blooms in desert-locust breeding areas suggests an operational programme based upon the NOAA Advanced Very-High-Resolution Radiometer sensor

The Zhamanshin Impact Event: Potential Implications for Environmental Responses and Biological Linkages on Earth and Beyond

At least one large-body (diameter > 1.1 km) hypervelocity cratering event occurred during ~ 0.8-0.90 Ma (Zhamanshin, Kazakhstan) in the Middle Pleistocene Transition period. Analysis designed to reduce uncertainty in the dimensions of the Zhamanshin structure employing high resolution topography demonstrated that it likely generated a ~ 26.5 km diameter multi-ring crater. This is at least two times larger than the current best estimates. Using a range of accepted impactor sizes, velocities, compositions, and angles of impact, such impacts typically yield kinetic energies of impact over 240,000 Megatons (TNT). Explosive energetic events of this magnitude (e.g., Yellowstone Caldera) at other times (K-Pg) have created global environmental effects. The factor of two discrepancy in the dimensions of Zhamanshin increases the kinetic energy yield by factors of 7-10, with significantly larger environmental consequences. This justifies examination of rapid climate transitions linked to biological consequences, including those related to environmental perturbations, at ~0.9 Ma.

I. Vegetation [in “State of the Climate in 2009”]

Interannual Covariability in Northern Hemisphere Air Temperatures and Greenness associated with ENSO and the AO

An evaluation of the first four LANDSAT-D thematic mapper reflective sensors for monitoring vegetation: A comparison with other satellite sensor systems

The first four LANDSAT-D thematic mapper sensors were evaluated and compared to: the return beam vidicon (RBV) and multispectral scanners (MSS) sensors from LANDSATS 1, 2, and 3; Colvocoresses' proposed 'operational LANDSAT' three band system; and the French SPOT three band system using simulation/intergration techniques and in situ collected spectral reflectance data. Sensors were evaluated by their ability to discriminate vegetation biomass, chlorophyll concentration, and leaf water content. The thematic mapper and SPOT bands were found to be superior in a spectral resolution context to the other three sensor systems for vegetational applications. Significant improvements are expected for most vegetational analyses from LANDSAT-D thematic mapper and SPOT imagery over MSS and RBV imagery.

Recovery of Above Ground Biomass and Foliar Nitrogen in Yellowstone National Park after the 1988 Fire

Assessing soybean leaf area and leaf biomass by spectral measurements

Red and photographic infrared spectral radiances were correlated with soybean total leaf area index, green leaf area index, chlorotic leaf area index, green leaf biomass, chlorotic leaf biomass, and total biomass. The most significant correlations were found to exist between the IR/red radiance ratio data and green leaf area index and/or green leaf biomass (r squared equals 0.85 and 0.86, respectively). These findings demonstrate that remote sensing data can supply information basic to soybean canopy growth, development, and status by nondestructive determination of the green leaf area or green leaf biomass.

A 1981-2012 Non-stationary AVHRR NDVI Global 8-km Data Set (Invited)

No abstract is provided for this article.

Satellite observed seasonal and inter-annual variation of vegetation over the Kalahari, The Great Victoria Desert, and The Great Sandy Desert: 1979–1984

We present time-series observations by two spaceborne sensors over three desert regions, the Kalahari (in southern Africa), and the Great Victoria Desert and the Great Sandy Desert (in western Australia). The observations are by the Advanced Very High Resolution Radiometer on board the NOAA-7 satellite from April 1982 to December 1984, and by the Scanning Multichannel Microwave Radiometer on board the Nimbus-7 satellite from January 1979 to February 1985. The objective was to compare and contrast seasonal and interannual variation of vegetation over these three deserts using the normalized difference vegetation index and the 37 GHz brightness temperature. The seasonal variation from both sensors was found to be most pronounced over the Kalahari, followed by the Great Sandy Desert and the Great Victoria Desert. The normalized difference vegetation index was roughly identical over the two Australian deserts and was significantly higher for the Kalahari. Additionally, there was no consistent change from both sensors over the two Australian deserts, but a consistent decrease from 1979 to 1984 over the Kalahari was found in the 37 GHz microwave data.

Global Disease Outbreaks Associated with the 2015–2016 El Niño Event

Interannual climate variability patterns associated with the El Niño-Southern Oscillation phenomenon result in climate and environmental anomaly conditions in specific regions worldwide that directly favor outbreaks and/or amplification of variety of diseases of public health concern including chikungunya, hantavirus, Rift Valley fever, cholera, plague, and Zika. We analyzed patterns of some disease outbreaks during the strong 2015–2016 El Niño event in relation to climate anomalies derived from satellite measurements. Disease outbreaks in multiple El Niño-connected regions worldwide (including Southeast Asia, Tanzania, western US, and Brazil) followed shifts in rainfall, temperature, and vegetation in which both drought and flooding occurred in excess (14–81% precipitation departures from normal). These shifts favored ecological conditions appropriate for pathogens and their vectors to emerge and propagate clusters of diseases activity in these regions. Our analysis indicates that intensity of disease activity in some ENSO-teleconnected regions were approximately 2.5–28% higher during years with El Niño events than those without. Plague in Colorado and New Mexico as well as cholera in Tanzania were significantly associated with above normal rainfall (p &lt; 0.05); while dengue in Brazil and southeast Asia were significantly associated with above normal land surface temperature (p &lt; 0.05). Routine and ongoing global satellite monitoring of key climate variable anomalies calibrated to specific regions could identify regions at risk for emergence and propagation of disease vectors. Such information can provide sufficient lead-time for outbreak prevention and potentially reduce the burden and spread of ecologically coupled diseases.

Assessment of ecological conditions associated with the 1980/81 desert locust plague upsurge in West Africa using environmental satellite data

National Oceanic and Atmospheric Administration (NOAA) satellite data from the Advanced Very High Resolution Radiometer (AVHRR) sensor were analysed to document the vegetation biomass dynamics associated with the regional desert-locust upsurge in West Africa during 1980/81, which affected an area of some 600 000 km2 in Mali, Niger and Algeria. Comparisons were made among locust population survey reports, rainfall records from eighteen stations in the same area, and the satellite data in vegetation index format. The satellite-recorded temporal and spatial distributions of desert vegetation biomass were closely correlated with both the locust population surveys and the available rainfall data. An attempt was made to develop a quantitative relationship between a satellite-derived potential breeding activity factor (PBAF) and the observed desert locust populations. Analysis of the multitemporal satellite data set indicates that, had the NOAA/AVHRR vegetation index data been operationally available in June 1980, effective preventive control measures would have only been necessary for an area of 600 km2.