Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses
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Xue‐Yan Zhang↗
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Biogeochemical Effects of Rising Atmospheric CO2 on Terrestrial and Ocean Systems
Rising carbon dioxide (CO2) has decreased seawater pH at long-term observing stations around the world, including in the open ocean north of Oahu, Hawaii, near Alaska's Aleutian Islands, the Gulf of Maine shore, and on Gray's Reef in the southeastern United States. This ocean acidification process has already affected some marine species and altered fundamental ecosystem processes, and further effects are likely. While atmospheric CO rises at approximately the same rate all over the globe, its non-climate effects on land vary depending on climate and dominant species. In terrestrial ecosystems, rising atmospheric CO concentrations are expected to increase plant photosynthesis, growth, and water-use efficiency, though these effects are reduced when nutrients, drought or other factors limit plant growth. Rising CO would likely change carbon storage and influence terrestrial hydrology and biogeochemical cycling, but concomitant effects on vegetation composition and nutrient feedbacks are challenging to predict, making decadal forecasts uncertain. Consequences of rising atmospheric CO are expected to include difficult-to-predict changes in the ecosystem services that terrestrial and ocean systems provide to humans. For instance, ocean acidification resulting from rising CO has decreased the supply of larvae that sustains commercial shellfish production in the northwestern United States. In addition, CO fertilization (increases) plus warming (decreases) are changing terrestrial crop yields. Continued persistence of uptake of carbon by the land and ocean is uncertain. Climate and environmental change create complex feedbacks to the carbon cycle and it is not clear how feedbacks modulate future effects of rising CO on carbon sinks. These are several mechanisms that could reduce future sink capacity.
Biogeochemical↗
Dust Emissions, Transport, and Deposition Simulated with the NASA Finite-Volume General Circulation Model
Mineral dust aerosols have radiative impacts on Earth's atmosphere, have been implicated in local and regional air quality issues, and have been identified as vectors for transporting disease pathogens and bringing mineral nutrients to terrestrial and oceanic ecosystems. We present for the first time dust simulations using online transport and meteorological analysis in the NASA Finite-Volume General Circulation Model (FVGCM). Our dust formulation follows the formulation in the offline Georgia Institute of Technology-Goddard Global Ozone Chemistry Aerosol Radiation and Transport Model (GOCART) using a topographical source for dust emissions. We compare results of the FVGCM simulations with GOCART, as well as with in situ and remotely sensed observations. Additionally, we estimate budgets of dust emission and transport into various regions.
Colarco, Peter↗
MODIS Aerosol Observations used to Constrain Dust Distributions and Lifecycle in the NASA GEOS-5 Model
Approximately 240 Tg of mineral dust aerosol are transported annually from Saharan Africa to the Atlantic Ocean. Dust affects the Earth radiation budget, and plays direct (through scattering and absorption of radiation) and indirect (through modification of cloud properties and environment) roles in climate. Deposition of dust to the surface provides an important nutrient source to terrestrial and oceanic ecosystems. Dust is additionally a contributor to adverse air quality. Among the tools toward understanding the lifecycle and impacts of mineral dust aerosols are numerical models. Important constraints on these models come from quantitative satellite observations, like those from the space-based Moderate Resolution Imaging Spectroradiometer (MODIS). In particular, Kauhan et al. [2005] used MODIS aerosol observations to infer transport and deposition fluxes of Saharan dust over the Atlantic, Caribbean, and Amazonian basins. Those observations are used here to constrain the transport of dust and its interannual variability simulated in the NASA GEOS-5 general circulation model and data assimilation system. Significant uncertainty exists in the MODIS-derived fluxes, however, due to uncertainty in the wind fields provided by meteorological analyses in this region. That same uncertainty in the wind fields is manifest in our GEOS-5 simulations of dust distributions. Here we use MODIS observations to investigate the seasonality and location of the Saharan dust plume and explore through sensitivity analysis of our model the meteorological controls on the dust distribution, including dust direct radiative effects and sub-gridscale source and sink processes.
Colarco, P.↗
Numerical Prediction of Dust
Covers the whole breadth of mineral dust research, from a scientific perspective Presents interdisciplinary work including results from field campaigns, satellite observations, laboratory studies, computer modelling and theoretical studies Explores the role of dust as a player and recorder of environmental change This volume presents state-of-the-art research about mineral dust, including results from field campaigns, satellite observations, laboratory studies, computer modelling and theoretical studies. Dust research is a new, dynamic and fast-growing area of science and due to its multiple roles in the Earth system, dust has become a fascinating topic for many scientific disciplines. Aspects of dust research covered in this book reach from timescales of minutes (as with dust devils, cloud processes, and radiation) to millennia (as with loess formation and oceanic sediments), making dust both a player and recorder of environmental change. The book is structured in four main parts that explore characteristics of dust, the global dust cycle, impacts of dust on the Earth system, and dust as a climate indicator. The chapters in these parts provide a comprehensive, detailed overview of this highly interdisciplinary subject. The contributions presented here cover dust from source to sink and describe all the processes dust particles undergo while travelling through the atmosphere. Chapters explore how dust is lifted and transported, how it affects radiation, clouds, regional circulations, precipitation and chemical processes in the atmosphere, and how it deteriorates air quality. The book explores how dust is removed from the atmosphere by gravitational settling, turbulence or precipitation, how iron contained in dust fertilizes terrestrial and marine ecosystems, and about the role that dust plays in human health. We learn how dust is observed, simulated using computer models and forecast. The book also details the role of dust deposits for climate reconstructions. Scientific observations and results are presented, along with numerous illustrations. This work has an interdisciplinary appeal and will engage scholars in geology, geography, chemistry, meteorology and physics, amongst others with an interest in the Earth system and environmental change.
dust↗
Quantification of Trans-Atlantic Dust Transport from Seven-year (2007-2013) Record of CALIPSO Lidar Measurements
The trans-Atlantic dust transport has important implications for human and ecosystem health, the terrestrial and oceanic biogeochemical cycle,weather systems, and climate. This study provides an observation-based multiyear estimate of trans-Atlantic dust transport using a 7-year (2007-2013) record of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements of the three dimensional distribution of aerosol backscatter, extinction and depolarization ratio in both cloud-free and above-cloud conditions. We estimate that on a basis of the 7-year average and integration over 10 deg S-30 deg N, 182 Tg a(exp -1) dust leaves the coast of North Africa at 15 deg W, of which 132 Tg a(exp -1) and 43 Tg a(exp -1) reaches 35 deg W and 75 deg W, respectively. These flux estimates have an overall known uncertainty of +/-(45-70)%. Because of lack of reliable observations, uncertainties associated with the diurnal variation of dust and the missing below-cloud dust cannot be quantified. Significant seasonal variations are observed in both the magnitude of total dust mass flux and its meridional and vertical distributions. The interannual variability of annual dust mass flux is highly anti-correlated with the prior-year Sahel Precipitation Index. Using only cloud-free aerosol observations to calculate dust mass flux could introduce a high bias when compared with all-sky conditions that include both cloud-free and above-cloud aerosol observations. The bias is about 20% at 35 deg W and 75 deg W in boreal winter and spring based on the 7-year average, as long as dust within and below low-level clouds is negligible.
trans-Atlantic dust transport↗
Characterization of the Temporal-Spatial Variability of Trans-Atlantic Dust Transport Based on CALIPSO Lidar Measurements
The trans-Atlantic dust transport has important implications for human and ecosystem health, the terrestrial and oceanic biogeochemical cycle, weather systems, and climate. A reliable assessment of these influences requires the characterization of dust distributions in three dimensions and over long time periods. We provide an observation-based multiyear estimate of trans-Atlantic dust transport by using a 7-year (2007 - 2013) lidar record from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) in both cloud-free and above-cloud conditions. We estimate that on a basis of the 7-year average and integration over 10S - 30N, 182 Tg a-1 dust leaves the coast of North Africa at 15W, of which 132 Tg a-1 and 43 Tg a-1 reaches 35W and 75W, respectively. These flux estimates have an overall known uncertainty of (45 - 70). The 7-year average of dust deposition into the Amazon Basin is estimated to be 28 (8 - 48) Tg a-1 or 29 (8 - 50) kg ha-1 a-1. This imported dust could provide about 0.022 (0.006 - 0.037) Tg P of phosphorus per year, equivalent to 23 (7 - 39) g P ha-1 a-1 to fertilize the Amazon rainforest, which is comparable to the loss of phosphorus to rainfall. Significant seasonal variations are observed in both the magnitude of total dust transport and its meridional and vertical distributions. The observed large interannual variability of annual dust transport is highly anti-correlated with the prior-year Sahel Precipitation Index. Comparisons of CALIPSO measurements with surface-based observations and model simulations will also be discussed.
Transport↗
Regional Rates of Young US Forest Growth Estimated From Annual Landsat Disturbance History and IKONOS Stereo Imagery
Forests of the Contiguous United States (CONUS) have been found to be a large contributor to the global atmospheric carbon sink. The magnitude and nature of this sink is still uncertain and recent studies have sought to define the dynamics that control its strength and longevity. The Landsat series of satellites has been a vital resource to understand the long-term changes in land cover that can impact ecosystem function and terrestrial carbonstock. We combine annual Landsat forest disturbance history from 1985 to 2011 with single date IKONOS stereoimagery to estimate the change in young forest canopy height and above ground live dry biomass accumulation for selected sites in the CONUS. Our approach follows an approximately linear growth rate following clearing over short intervals and does not estimate the distinct non-linear growth rate over longer intervals.We produced canopy height models by differencing digital surface models estimated from IKONOS stereo pairs with national elevation data (NED). Correlations between height and biomass were established independently using airborne LiDAR, and then applied to the IKONOS-estimated canopy height models. Graphing current biomass against time since disturbance provided biomass accumulation rates. For 20 study sites distributed across five regions of the CONUS, 19 showed statistically significant recovery trends (p is less than 0.001) with canopy growth from 0.26 m yr-1to 0.73 m yr-1. Above ground live dry biomass (AGB) density accumulation ranged from 1.31 t/ha yr-1 to 12.47 t/ha yr-1. Mean forest AGB accumulationwas 6.31 t/ha yr-1 among all sites with significant growth trends. We evaluated the accuracy of our estimates by comparing to field estimated site index curves of growth, airborne LiDAR data, and independent model predictions of C accumulation. Growth estimates found with this approach are consistent with site index curves and total biomass estimates fall within the range of field estimates. This is aviable approach to estimate forest biomass accumulation in regions with clear-cut harvest disturbances.
Neigh, Christopher S. R.↗
Satellite and airborne remote sensing of gross primary productivity in boreal Alaskan lakes
In terrestrial and marine ecosystems, remote sensing has been used to estimate gross primary productivity (GPP) for decades, but few applications exist for shallow freshwater ecosystems.Here we show field-based GPP correlates with satellite and airborne lake color across a range of optically and limnologically diverse lakes in interior Alaska. A strong relationship between in situ GPP derived from stable oxygen isotopes (δ18O) and space-based lake color from satellites (e.g. Landsat-8, Sentinel-2 and CubeSats) and airborne imagery (AVIRIS-NG) demonstrates the potential power of this technique for improving spatial and temporal monitoring of lake GPP when coupled with additional field validation measurements across different systems. In shallow waters clear enough for sunlight to reach lake bottoms, both submerged vegetation (macrophytes and algae) and phytoplankton likely contribute to GPP. The stable isotopes and remotely sensed shallow lake color used here integrate both components. These results demonstrate the utility of lake color as a feasible means for mapping lake GPP from remote sensing. This novel methodology estimates GPP from remote sensing in shallow lakes by combining field measurements of oxygen isotopes with airborne, satellite and CubeSat imagery. This use of lake color for providing insight into ecological processes of shallow lakes is recommended, especially for remote arctic and boreal landscapes.
airborne remote sensing↗
The Ocean’s Breath: How Autonomous Robotic Vehicles at Sea and Super Computers are Helping us Understand the Carbon Cycle in the Ocean
Carbon dioxide due to human activities such as fossil fuel burning has well-known and concerning implications for global temperatures as well as terrestrial and marine ecosystems. Hence, an important objective of NASA Earth science is to observe and understand the variations in the global carbon cycle and the associated climate and ecosystem impacts in the context of past and projected anthropogenic emissions. In my presentation, I will tell the story of how some of my collaborators and I are using autonomous robotic vehicles and super computers to try to untangle the mysteries of the carbon cycle in the ocean, which depends in fascinating ways on atmospheric and ocean physics, marine ecosystem dynamics, as well as the chemistry of the seawater.
Ocean's breath↗
Intrinsic Dimensionality as a Metric for the Impact of Mission Design Parameters
High-resolution space-based spectral imaging of the Earth's surface delivers critical information for monitoring changes in the Earth system as well as resource management and utilization. Orbiting spectrometers are built according to multiple design parameters, including ground sampling distance (GSD), spectral resolution, temporal resolution, and signal-to-noise ratio. Different applications drive divergent instrument designs, so optimization for wide-reaching missions is complex. The Surface Biology and Geology component of NASA's Earth System Observatory addresses science questions and meets applications needs across diverse fields, including terrestrial and aquatic ecosystems, natural disasters, and the cryosphere. The algorithms required to generate the geophysical variables from the observed spectral imagery each have their own inherent dependencies and sensitivities, and weighting these objectively is challenging. Here, we introduce intrinsic dimensionality (ID), a measure of information content, as an applications-agnostic, data-driven metric to quantify performance sensitivity to various design parameters. ID is computed through the analysis of the eigenvalues of the image covariance matrix, and can be thought of as the number of significant principal components. This metric is extremely powerful for quantifying the information content in high-dimensional data, such as spectrally resolved radiances and their changes over space and time. We find that the ID decreases for coarser GSD, decreased spectral resolution and range, less frequent acquisitions, and lower signal-to-noise levels. This decrease in information content has implications for all derived products. ID is simple to compute, providing a single quantitative standard to evaluate combinations of design parameters, irrespective of higher-level algorithms, products, applications, or disciplines.
Intrinsic dimensionality↗
Ocean Carbon and Biogeochemistry Scoping Workshop on Terrestrial and Coastal Carbon Fluxes in the Gulf of Mexico, St. Petersburg, FL
Despite their relatively small surface area, ocean margins may have a significant impact on global biogeochemical cycles and, potentially, the global air-sea fluxes of carbon dioxide. Margins are characterized by intense geochemical and biological processing of carbon and other elements and exchange large amounts of matter and energy with the open ocean. The area-specific rates of productivity, biogeochemical cycling, and organic/inorganic matter sequestration are high in coastal margins, with as much as half of the global integrated new production occurring over the continental shelves and slopes (Walsh, 1991; Doney and Hood, 2002; Jahnke, in press). However, the current lack of knowledge and understanding of biogeochemical processes occurring at the ocean margins has left them largely ignored in most of the previous global assessments of the oceanic carbon cycle (Doney and Hood, 2002). A major source of North American and global uncertainty is the Gulf of Mexico, a large semi-enclosed subtropical basin bordered by the United States, Mexico, and Cuba. Like many of the marginal oceans worldwide, the Gulf of Mexico remains largely unsampled and poorly characterized in terms of its air-sea exchange of carbon dioxide and other carbon fluxes. The goal of the workshop was to bring together researchers from multiple disciplines studying terrestrial, aquatic, and marine ecosystems to discuss the state of knowledge in carbon fluxes in the Gulf of Mexico, data gaps, and overarching questions in the Gulf of Mexico system. The discussions at the workshop were intended to stimulate integrated studies of marine and terrestrial biogeochemical cycles and associated ecosystems that will help to establish the role of the Gulf of Mexico in the carbon cycle and how it might evolve in the face of environmental change.
Air sea exchanges↗
Terrestrial nitrogen cycles: Some unanswered questions
Nitrogen is generally considered to be the element which most often limits the growth of plants in both natural and agricultural ecosystems. It regulates plant growth because photosynthetic rates are strongly dependent on the concentration of nitrogen in leaves, and because relatively large mounts of protein are required for cell division and growth. Yet nitrogen is abundant in the biosphere - the well-mixed pool in the atmosphere is considered inexhaustible compared to biotic demand, and the amount of already fixed organic nitrogen in soils far exceeds annual plant uptake in terrestrial ecosystems. In regions where natural vegetation is not nitrogen limited, continuous cultivation induces nitrogen deficiency. Nitrogen loss from cultivated lands is more rapid than that of other elements, and nitrogen fertilization is generally required to maintain crop yield under any continuous system. The pervasiveness of nitrogen deficiency in many natural and most managed sites is discussed.
Vitousek, P.↗
New Data-Driven Estimation of Terrestrial CO2 Fluxes in Asia Using a Standardized Database of Eddy Covariance Measurements, Remote Sensing Data, and Support Vector Regression
The lack of a standardized database of eddy covariance observations has been an obstacle for data-driven estimation of terrestrial carbon dioxide fluxes in Asia. In this study, we developed such a standardized database using 54 sites from various databases by applying consistent postprocessing for data-driven estimation of gross primary productivity (GPP) and net ecosystem carbon dioxide exchange (NEE). Data-driven estimation was conducted by using a machine learning algorithm: support vector regression (SVR), with remote sensing data for 2000 to 2015 period. Site-level evaluation of the estimated carbon dioxide fluxes shows that although performance varies in different vegetation and climate classifications, GPP and NEE at 8 days are reproduced (e.g., r (exp 2) =0.73 and 0.42 for 8 day GPP and NEE). Evaluation of spatially estimated GPP with Global Ozone Monitoring Experiment 2 sensor-based Sun-induced chlorophyll fluorescence shows that monthly GPP variations at subcontinental scale were reproduced by SVR (r (exp 2)=1.00, 0.94, 0.91, and 0.89 for Siberia, East Asia, South Asia, and Southeast Asia, respectively). Evaluation of spatially estimated NEE with net atmosphere-land carbon dioxide fluxes of Greenhouse Gases Observing Satellite (GOSAT) Level 4A product shows that monthly variations of these data were consistent in Siberia and East Asia; meanwhile, inconsistency was found in South Asia and Southeast Asia. Furthermore, differences in the land carbon dioxide fluxes from SVR-NEE and GOSAT Level 4A were partially explained by accounting for the differences in the definition of land carbon dioxide fluxes. These data-driven estimates can provide a new opportunity to assess carbon dioxide fluxes in Asia and evaluate and constrain terrestrial ecosystem models.
chlorophyll fluorescence↗
Building a Data Ecosystem: A New Data Stewardship Paradigm for the Multi-Mission Algorithm and Analysis Platform (MAAP)
New adaptive approaches to Earth observation data stewardship need to be adopted in order to allow for higher data volumes, heterogeneous data and constantly evolving technologies. The data ecosystem approach to stewardship offers a viable solution to this need by placing an emphasis on the relationships between data, technologies and people. In this paper, we present the Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform’s (MAAP) creation of a data ecosystem to support global aboveground terrestrial carbon dynamics research. We present the components needed to support the MAAP data ecosystem along with two data stewardship workflows used in the MAAP and the development of extended metadata for MAAP.
Bugbee, Kaylin↗
Earth observing satellite: Understanding the Earth as a system
There is now a plan for global studies which include two very large efforts. One is the International Geosphere/Biosphere Program (IGBP) sponsored by the International Council of Scientific Unions. The other initiative is Mission to Planet Earth, an unbrella program for doing three kinds of space missions. The major one is the Earth Observation Satellite (EOS). EOS is large polar orbiting satellites with heavy payloads. Two will be placed in orbit by NASA, one by the Japanese and one or two by ESA. The overall mission measurement objectives of EOS are summarized: (1) the global distribution of energy input to and energy output from the Earth; (2) the structure, state variables, composition, and dynamics of the atmosphere from the ground to the mesopause; (3) the physical and biological structure, state, composition, and dynamics of the land surface, including terrestrial and inland water ecosystems; (4) the rates, important sources and sinks, and key components and processes of the Earth's biogeochemical cycles; (5) the circulation, surface temperature, wind stress, sea state, and the biological activity of the oceans; (6) the extent, type, state, elevation, roughness, and dynamics of glaciers, ice sheets, snow and sea ice, and the liquid equivalent of snow in the global cryosphere; (7) the global rates, amounts, and distribution of precipitation; and (8) the dynamic motions of the Earth (geophysics) as a whole, including both rotational dynamics and the kinematic motions of the tectonic plates.
Soffen, Gerald↗
Impact of Footprint Diameter and Off-Nadir Pointing on the Precision of Canopy Height Estimates from Spaceborne Lidar
A spaceborne lidar mission could serve multiple scientific purposes including remote sensing of ecosystem structure, carbon storage, terrestrial topography and ice sheet monitoring. The measurement requirements of these different goals will require compromises in sensor design. Footprint diameters that would be larger than optimal for vegetation studies have been proposed. Some spaceborne lidar mission designs include the possibility that a lidar sensor would share a platform with another sensor, which might require off-nadir pointing at angles of up to 16 . To resolve multiple mission goals and sensor requirements, detailed knowledge of the sensitivity of sensor performance to these aspects of mission design is required. This research used a radiative transfer model to investigate the sensitivity of forest height estimates to footprint diameter, off-nadir pointing and their interaction over a range of forest canopy properties. An individual-based forest model was used to simulate stands of mixed conifer forest in the Tahoe National Forest (Northern California, USA) and stands of deciduous forests in the Bartlett Experimental Forest (New Hampshire, USA). Waveforms were simulated for stands generated by a forest succession model using footprint diameters of 20 m to 70 m. Off-nadir angles of 0 to 16 were considered for a 25 m diameter footprint diameter. Footprint diameters in the range of 25 m to 30 m were optimal for estimates of maximum forest height (R(sup 2) of 0.95 and RMSE of 3 m). As expected, the contribution of vegetation height to the vertical extent of the waveform decreased with larger footprints, while the contribution of terrain slope increased. Precision of estimates decreased with an increasing off-nadir pointing angle, but off-nadir pointing had less impact on height estimates in deciduous forests than in coniferous forests. When pointing off-nadir, the decrease in precision was dependent on local incidence angle (the angle between the off-nadir beam and a line normal to the terrain surface) which is dependent on the off-nadir pointing angle, terrain slope, and the difference between the laser pointing azimuth and terrain aspect; the effect was larger when the sensor was aligned with the terrain azimuth but when aspect and azimuth are opposed, there was virtually no effect on R2 or RMSE. A second effect of off-nadir pointing is that the laser beam will intersect individual crowns and the canopy as a whole from a different angle which had a distinct effect on the precision of lidar estimates of height, decreasing R2 and increasing RMSE, although the effect was most pronounced for coniferous crowns.
Pang, Yong↗
The Seasonal Cycle of Satellite Chlorophyll Fluorescence Observations and its Relationship to Vegetation Phenology and Ecosystem Atmosphere Carbon Exchange
Mapping of terrestrial chlorophyll uorescence from space has shown potentialfor providing global measurements related to gross primary productivity(GPP). In particular, space-based fluorescence may provide information onthe length of the carbon uptake period that can be of use for global carboncycle modeling. Here, we examine the seasonal cycle of photosynthesis asestimated from satellite fluorescence retrievals at wavelengths surroundingthe 740nm emission feature. These retrievals are from the Global OzoneMonitoring Experiment 2 (GOME-2) flying on the MetOp A satellite. Wecompare the fluorescence seasonal cycle with that of GPP as estimated froma diverse set of North American tower gas exchange measurements. Because the GOME-2 has a large ground footprint (40 x 80km2) as compared with that of the flux towers and requires averaging to reduce random errors, we additionally compare with seasonal cycles of upscaled GPP in the satellite averaging area surrounding the tower locations estimated from the Max Planck Institute for Biogeochemistry (MPI-BGC) machine learning algorithm. We also examine the seasonality of absorbed photosynthetically-active radiation(APAR) derived with reflectances from the MODerate-resolution Imaging Spectroradiometer (MODIS). Finally, we examine seasonal cycles of GPP as produced from an ensemble of vegetation models. Several of the data-driven models rely on satellite reflectance-based vegetation parameters to derive estimates of APAR that are used to compute GPP. For forested sites(particularly deciduous broadleaf and mixed forests), the GOME-2 fluorescence captures the spring onset and autumn shutoff of photosynthesis as delineated by the tower-based GPP estimates. In contrast, the reflectance-based indicators and many of the models tend to overestimate the length of the photosynthetically-active period for these and other biomes as has been noted previously in the literature. Satellite fluorescence measurements therefore show potential for improving model GPP estimates.
Joiner, J.↗