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NASA NTRS2017

The SMAP Level-4 ECO Project: Linking the Terrestrial Water and Carbon Cycles

The SMAP (Soil Moisture Active Passive) Level-4 projects aims to develop a fully coupled hydrology-vegetation data assimilation algorithm to generate improved estimates of modeled hydrological fields and carbon fluxes. This includes using the new NASA Catchment-CN (Catchment-Carbon-Nitrogen) model, which combines the Catchment land surface hydrology model with dynamic vegetation components from the Community Land Model version 4 (CLM4). As such, Catchment-CN allows a more realistic, fully coupled feedback between the land hydrology and the biosphere. The L4 ECO project further aims to inform the model through the assimilation of Soil Moisture Active Passive (SMAP) brightness temperature observations as well as observations of Moderate Resolution Imaging Spectroradiometer (MODIS) fraction of absorbed photosynthetically active radiation (FPAR). Preliminary results show that the assimilation of SMAP observations leads to consistent improvements in the model soil moisture skill. An evaluation of the Catchment-CN modeled vegetation characteristics showed that a calibration of the model's vegetation parameters is required before an assimilation of MODIS FPAR observations is feasible.

MODIS↗

NASA NTRS2018

The SMAP Level-4 ECO Project: Improving Terrestrial Flux Estimates Through Coupled Hydrology-Vegetation Data Assimilation

Simulations of hydrologic and vegetation states as well as water, energy and carbon fluxes from the land surface to the atmosphere are crucial for a wide range of applications, including agricultural advisories, forecasts of (short-term) atmospheric behavior and seasonal weather predictions including forecasts of extreme events, such as heatwaves or droughts. The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Eco-Hydrology (L4-ECO) project aims to improve modeled estimates of the terrestrial water, energy and carbon fluxes and states by developing a fully-coupled hydrology-vegetation data assimilation system. This system is developed around the NASA Goddard Earth Observing System (GEOS) Catchment-CN land surface model, which combines land hydrology and energy balance components of the GEOS Catchment model with dynamic vegetation components of the Community Land Model version 4. Catchment-CN fully couples the terrestrial water, energy and carbon cycles, allowing feedbacks from the land hydrology to the biosphere and vice versa.Here, we implement a calibration of the Catchment-CN vegetation parameterization against observations of the fraction of absorbed photosynthetically active radiation (FPAR) from the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve the model's standalone skill. Later, the DA algorithm used to produce the SMAP L4 soil moisture product will be adapted to Catchment-CN to assimilate SMAP brightness temperatures and inform the model's land hydrology component. Finally, the DA system will be further extended to assimilate MODIS FPAR observations in order to constrain the model's dynamic vegetation component.In this presentation, we demonstrate that the Catchment-CN parameter calibration leads to more realistic vegetation simulations and reduces the root mean squared error between modeled and observed vegetation states across the model's various plant functional types. We also show that the assimilation of SMAP observations is able to improve the average correlation, bias and unbiased RMSE between the modeled surface and root zone soil moisture estimates, and ground observations from the SMAP core validation sites.

Kolassa, Jana↗

NASA NTRS2011

Utilization of ancillary data sets for SMAP algorithm development and product generation

Once launched in late 2014/early 2015, the Soil Moisture Active Passive (SMAP) mission will provide high resolution global mapping of soil moisture and its freeze/thaw state every 2-3 days. These measurements are valuable to improved understanding of the Earth’s water, energy, and carbon cycles, and to applications of societal benefit. In order for soil moisture and freeze/thaw to be retrieved accurately from SMAP microwave data, a variety of global static and dynamic ancillary data are required. The choice of which ancillary datasets to use for SMAP products will be based on a number of factors including availability and ease of use, their inherent error and resulting impact on SMAP retrieval accuracies, and compatibility with similar choices made by ESA’s SMOS mission.

O’Neill, Peggy E.↗

NASA NTRS2012

Incorporating Plant Phenology Dynamics in a Biophysical Canopy Model

The Multi-Layer Canopy Model (MLCan) is a vegetation model created to capture plant responses to environmental change. Themodel vertically resolves carbon uptake, water vapor and energy exchange at each canopy level by coupling photosynthesis, stomatal conductance and leaf energy balance. The model is forced by incoming shortwave and longwave radiation, as well as near-surface meteorological conditions. The original formulation of MLCan utilized canopy structural traits derived from observations. This project aims to incorporate a plant phenology scheme within MLCan allowing these structural traits to vary dynamically. In the plant phenology scheme implemented here, plant growth is dependent on environmental conditions such as air temperature and soil moisture. The scheme includes functionality that models plant germination, growth, and senescence. These growth stages dictate the variation in six different vegetative carbon pools: storage, leaves, stem, coarse roots, fine roots, and reproductive. The magnitudes of these carbon pools determine land surface parameters such as leaf area index, canopy height, rooting depth and root water uptake capacity. Coupling this phenology scheme with MLCan allows for a more flexible representation of the structure and function of vegetation as it responds to changing environmental conditions.

environmental changes↗

NASA NTRS2018

The SMAP Level-4 ECO Product - Phase 1: Improving Vegetation Simulations Through Observation-Driven Parameter Estimation

Simulations of hydrological fields as well as water, energy and carbon fluxes from the land surface to the atmosphere are crucial for a wide range of applications, including agricultural advisories, forecasts of (short-term) atmospheric behavior and seasonal weather predictions including forecasts of extreme events, such as heatwaves or droughts. The NASA Soil Moisture Active Passive (SMAP) mission Level-4 (L4) Eco-Hydrology (ECO) project aims to improve modeled estimates of the terrestrial water, energy and carbon fluxes and states by developing a fully-coupled hydrology-vegetation data assimilation (DA) algorithm. The DA system is developed for the NASA Goddard Earth Observing System version 5 (GEOS-5) Catchment-CN land surface model, which combines land hydrology components of the GEOS-5 Catchment model with dynamic vegetation components of the Community Land Model version 4. Catchment-CN fully couples the terrestrial water, energy and carbon cycles, allowing feedbacks from the land hydrology to the biosphere and vice versa. For SMAP L4 ECO a calibration of the Catchment-CN vegetation parameterization against observations of the fraction of absorbed photosynthetically active radiation (FPAR) from the Moderate Resolution Imaging Spectroradiometer (MODIS) is implemented to improve the model's standalone skill. Next, the DA algorithm used to produce the SMAP L4 soil moisture product is adapted to Catchment-CN to assimilate SMAP brightness temperatures and inform the model's land hydrology component. The DA system is further extended to assimilate MODIS FPAR observations in order to constrain the model's dynamic vegetation component. In this presentation, we demonstrate that the Catchment-CN parameter calibration leads to more realistic vegetation simulations and reduces the root mean squared error between modeled and observed vegetation states across the model's various plant functional types. We also show that the assimilation of SMAP observations is able to improve the average correlation, bias and unbiased RMSE between the modeled surface and root zone soil moisture estimates, and ground observations from the SMAP core validation sites.

Kolassa, J.↗

NASA NTRS2015

Spin-Up and Tuning of the Global Carbon Cycle Model Inside the GISS ModelE2 GCM

Planetary carbon cycle involves multiple phenomena, acting at variety of temporal and spacial scales. The typical times range from minutes for leaf stomata physiology to centuries for passive soil carbon pools and deep ocean layers. So, finding a satisfactory equilibrium state becomes a challenging and computationally expensive task. Here we present the spin-up processes for different configurations of the GISS Carbon Cycle model from the model forced with MODIS observed Leaf Area Index (LAI) and prescribed ocean to the prognostic LAI and to the model fully coupled to the dynamic ocean and ocean biology. We investigate the time it takes the model to reach the equilibrium and discuss the ways to speed up this process. NASA Goddard Institute for Space Studies General Circulation Model (GISS ModelE2) is currently equipped with all major algorithms necessary for the simulation of the Global Carbon Cycle. The terrestrial part is presented by Ent Terrestrial Biosphere Model (Ent TBM), which includes leaf biophysics, prognostic phenology and soil biogeochemistry module (based on Carnegie-Ames-Stanford model). The ocean part is based on the NASA Ocean Biogeochemistry Model (NOBM). The transport of atmospheric CO2 is performed by the atmospheric part of ModelE2, which employs quadratic upstream algorithm for this purpose.

Climate model↗

NASA NTRS2006

A Unique Perspective from Space on our Planet: Science, Technologies and Applications

The study of Planet earth is a very complex problem. It has many non-linear and chaotic systems operating in parallel and have interdependencies. In reality, these systems/phenomena s are not well understood or mathematically modeled because of our lack of knowledge of such intricate processes. However, in order to further the subject of Earth as an integrated system, space provides excellent vantage points to look at these processes in multidimensional framework. For example, we can make strives to understand the global water cycle, carbon cycle, atmospheric chemistry, biomass changes, oceans and solid Earth variations by making multitude of global measurements such as soil moisture, precipitation, tropospheric and stratospheric gases, aerosols, tropospheric winds, ocean salinity, ocean color, vegetation cover, crustal dynamics and many more. Such suites of measurements derive the coupled models so we may predict the changes due to natural and anthropogenic forcing. NASA along with other international space agencies have made tremendous investments in recent years in developing and flying remote sensing space borne sensors to enable these measurements. These science measurements and products are further used to address pressing issues such as coastal zone erosion, air quality, severe weather, water availability and quality, public health, fires, earthquakes, land slides and others for societal benefits. This presentation provides a comprehensive overview of NASA s science investigations, related technologies and satellites/sensors and applications.

Habib, Shaid↗

NASA NTRS2004

Discrimination And Biophysical Characterization Of Brazilian Cerrado Physiognomies With Eo-1 Hyperspectral Hyperion

The savanna, typically found in the sub-tropics and seasonal tropics, are the dominant vegetation biome type in the southern hemisphere, covering approximately 45% of the South America. In Brazil, the savanna, locally known as "cerrado," is the most intensely stressed biome with both natural environmental pressures (e.g., the strong seasonality in weather, extreme soil nutrient impoverishment, and widespread fire occurrences) and rapid/aggressive land conversions (Skole et al., 1994; Ratter et al., 1997). Better characterization and discrimination of cerrado physiognomies are needed in order to improve understanding of cerrado dynamics and its impact on carbon storage, nutrient dynamics, and the prospect for sustainable land use in the Brazilian cerrado biome. Satellite remote sensing have been known to be a useful tool for land cover and land use mapping (Rougharden et al., 1991; Hansen et al., 2000). However, attempts to discriminate and classify Brazilian cerrado using multi-spectral sensors (e.g., Landsat TM) and/or moderate resolution sensors (e.g., NOAA AVHRR NDVI) have often resulted in a limited success due partly to small contrasts depicted in their multiband, spectral reflectance or vegetation index values among cerrado classes (Seyler et al., 2002; Fran a and Setzer, 1998). In this study, we aimed to improve discrimination as well as biophysical characterization of the Brazilian cerrado physiognomies with hyperspectral remote sensing. We used Hyperion, the first satellite-based hyperspectral imager, onboard the Earth Observing-1 (EO-1) platform.

Miura, Tomoaki↗

NASA NTRS2018

Modeling the Distribution and Type of High-Latitude Natural Wetlands for Methane Studies

High latitude (>50N) natural wetlands emit a substantial amount of methane to the atmosphere, and are located in a region of amplified warming. Northern hemisphere high latitudes are characterized by cold climates, extensive permafrost, poor drainage, short growing seasons, and slow decay rates. Under these conditions, organic carbon accumulates in the soil, sequestering CO2 from the atmosphere. Methanogens produce methane from this carbon reservoir, converting stored carbon into a powerful greenhouse gas. Methane emission from wetland ecosystems depends on vegetation type, climate characteristics (e.g, precipitation amount and seasonality, temperature, snow cover, etc.), and geophysical variables (e.g., permafrost, soil type, and landscape slope). To understand how wetland methane dynamics in this critical region will respond to climate change, we have to first understand how wetlands themselves will change and therefore, what the primary controllers of wetland distribution and type are. Understanding these relationships permits data-anchored, physically-based modeling of wetland distribution and type in other climate scenarios, such as paleoclimates or future climates, a necessary first step toward modeling wetland methane emissions in these scenarios. We investigate techniques and datasets for predicting the distribution and type of high latitude (>50N) natural wetlands from a suite of geophysical and climate predictors. Hierarchical clustering is used to derive an empirical methane-centric wetland model. The model is applied in a multistep process first to predict the distribution of wetlands from relevant geophysical parameters, and then, given the predicted wetland distribution, to classify the wetlands into methane-relevant types using an expanded suite of climate and biogeophysical variables. As the optimum set of predictor variables is not known a priori, the model is applied iteratively, and each simulation is evaluated with respect to observed high-latitude wetlands.

Romanski, Joy↗

NASA NTRS2011

Determining the Local Abundance of Martian Methane and its 13-C/l2-C and D/H Isotopic Ratios for Comparison with Related Gas and Soil Analysis on the 2011 Mars Science Laboratory (MSL) Mission

Understanding the origin of Martian methane will require numerous complementary measurements from both in situ and remote sensing investigations and laboratory work to correlate planetary surface geophysics with atmospheric dynamics and chemistry. Three instruments (Quadrupole Mass Spectrometer (QMS), Gas Chromatograph (GC) and Tunable Laser Spectrometer (TLS)) with sophisticated sample handling and processing capability make up the Sample Analysis at Mars (SAM) analytical chemistry suite on NASA s 2011 Mars Science Laboratory (MSL) Mission. Leveraging off the SAM sample and gas processing capability that includes methane enrichment, TLS has unprecedented sensitivity for measuring absolute methane (parts-per-trillion), water, and carbon dioxide abundances in both the Martian atmosphere and evolved from heated soil samples. In concert with a wide variety of associated trace gases (e.g. SO2, H2S, NH3, higher hydrocarbons, organics, etc.) and other isotope ratios measured by SAM, TLS will focus on determining the absolute abundances of methane, water and carbon dioxide, and their isotope ratios: 13C/12C and D/H in methane; 13C/12C and 18O/17O/16O in carbon dioxide; and 18O/17O/16O and D/H in water. Measurements near the MSL landing site will be correlated with satellite (Mars Express, Mars 2016) and ground-based observations.

Webster, Christopher R.↗

NASA NTRS2005

Effects of Aerosol on Atmospheric Dynamics and Hydrologic Processes during Boreal Spring and Summer

Global and regional climate impacts of present-day aerosol loading during boreal spring are investigated using the NASA finite volume General Circulation Model (fvGCM). Three-dimensional distributions of loadings of five species of tropospheric aerosols, i.e., sulfate, black carbon, organic carbon, soil dust, and sea salt are prescribed from outputs of the Goddard Ozone Chemistry Aerosol Radiation and Transport model (GOCART). The aerosol loadings are used to calculate the extinction coefficient, single scattering albedo, and asymmetric factor at eleven spectral wavelengths in the radiative transfer code. We find that aerosol-radiative forcing during boreal spring excites a wavetrain-like pattern in tropospheric temperature and geopotential height that emanates from Northern Africa, through Eurasia, to northeastern Pacific. Associated with the teleconnection is strong surface cooling over regions with large aerosol loading, i.e., China, India, and Africa. Low-to-mid tropospheric heating due to shortwave absorption is found in regions with large loading of dust (Northern Africa, and central East Asia), and black carbon (South and East Asia). In addition pronounced surface cooling is found over the Caspian Sea and warming over Eurasian and northeastern Asia, where aerosol loadings are relatively low. These warming and cooling are components of teleconnection pattern produced primarily by atmospheric heating from absorbing aerosols, i.e., dust from North Africa and.black carbon from South and East Asia. Effects of aerosols on atmospheric hydrologic cycle in the Asian monsoon region are also investigated. Results show that absorbing aerosols, i.e., black carbon and dust, induce large-scale upper-level heating anomaly over the Tibetan Plateau in April and May, ushering in an early onset of the Indian summer monsoon. Absorbing aerosols also enhance lower-level heating and anomalous ascent over northern India, intensifying the Indian monsoon. Overall, the aerosol-induced large-scale surface temperature cooling leads to a reduction of monsoon rainfall over the East Asia continent, and adjacent oceanic regions.

Lau, William K. M.↗

NASA NTRS2005

Effects of Aerosol on Atmospheric Dynamics and Hydrologic Processes During Boreal Spring and Summer

Global and regional climate impacts of present-day aerosol loading during boreal spring are investigated using the NASA finite volume General Circulation Model (fvGCM). Three-dimensional distributions of loadings of five species of tropospheric aerosols, i.e., sulfate, black carbon, organic carbon, soil dust, and sea salt are prescribed from outputs of the Goddard Ozone Chemistry Aerosol Radiation and Transport model (GOCART). The aerosol loadings are used to calculate the extinction coefficient, single scattering albedo, and asymmetric factor at eleven spectral wavelengths in the radiative transfer code. We find that aerosol-radiative forcing during boreal spring excites a wavetrain-like pattern in tropospheric temperature and geopotential height that emanates from Northern Africa, through Eurasia, to northeastern Pacific. Associated with the teleconnection is strong surface cooling over regions with large aerosol loading, i.e., China, India, and Africa. Low-to-mid tropospheric heating due to shortwave absorption is found in regions with large loading of dust (Northern Africa, and central East Asia), and black carbon (South and East Asia). In addition pronounced surface cooling is found over the Caspian Sea and warming over Eurasian and northeastern Asia, where aerosol loadings are relatively low. These warming and cooling are components of teleconnection pattern produced primarily by atmospheric heating from absorbing aerosols, i.e., dust from North Africa and black carbon from South and East Asia. Effects of aerosols on atmospheric hydrologic cycle in the Asian monsoon region are also investigated. Results show that absorbing aerosols, i.e., black carbon and dust, induce large-scale upper-level heating anomaly over the Tibetan Plateau in April and May, ushering in an early onset of the Indian summer monsoon. Absorbing aerosols also enhance lower-level heating and anomalous ascent over northern India, intensifying the Indian monsoon. Overall, the aerosol-induced large-scale surface tempera- cooling leads to a reduction of monsoon rainfall over the East Asia continent, and adjacent oceanic regions.

Lau, William K. M.↗

NASA NTRS2015

Evaluation of Spaceborne L-band Radiometer Measurements for Terrestrial Freeze/Thaw Retrievals in Canada

The landscape freeze/thaw (FT) state has an important impact on the surface energy balance, carbon fluxes, and hydrologic processes; the timing of spring melt is linked to active layer dynamics in permafrost areas. L-band (1.4 GHz) microwave emission could allow the monitoring of surface state dynamics due to its sensitivity to the pronounced permittivity difference between frozen and thawed soil. The aim of this paper is to evaluate the performance of both Aquarius and Soil Moisture and Ocean Salinity (SMOS) L-band passive microwave measurements using a polarization ratio-based algorithm for landscape FT monitoring. Weekly L-band satellite observations are compared with a large set of reference data at 48 sites across Canada spanning three environments: tundra, boreal forest, and prairies. The reference data include in situ measurements of soil temperature (Tsoil) and air temperature (Tair), and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and snow cover area (SCA) products. Results show generally good agreement between Lband FT detection and the surface state estimated from four reference datasets. The best apparent accuracies for all seasons are obtained using Tair as the reference. Aquarius radiometer 2 (incidence angle of 39.6) data gives the best accuracies (90.8), while for SMOS the best results (87.8 of accuracy) are obtained at higher incidence angles (55- 60). The FT algorithm identifies both freeze onset and end with a delay of about one week in tundra and two weeks in forest and prairies, when compared to Tair. The analysis shows a stronger FT signal at tundra sites due to the typically clean transitions between consistently frozen and thawed conditions (and vice versa) and the absence of surface vegetation. Results in the prairies were poorer because of the influence of vegetation growth in summer (which decreases the polarization ratio) and the high frequency of ephemeral thaw events during winter. Freeze onset and end maps created from the same algorithm applied to SMOS and Aquarius measurements characterize similar FT patterns over Canada. This study shows the potential of using L-band spaceborne observations for FT monitoring, but underlines some limitations due to ice crusts in the snowpack, liquid water content in snow cover during the spring freeze to thaw transition, and vegetation growth.

soil freeze/thaw↗

NASA NTRS2004

Quantifying Grassland-to-Woodland Transitions and the Implications for Carbon and Nitrogen Dynamics in the Southwest United States

Replacement of grasslands and savannas by shrublands and woodlands has been widely reported in tropical, temperate and high-latitude rangelands worldwide (Archer 1994). These changes in vegetation structure may reflect historical shifts in climate and land use; and are likely to influence biodiversity, productivity, above- and below ground carbon and nitrogen sequestration and biophysical aspects of land surface-atmosphere interactions. The goal of our proposed research is to investigate how changes in the relative abundance of herbaceous and woody vegetation affect carbon and nitrogen dynamics across heterogeneous savannas and shrub/woodlands. By linking actual land-cover composition (derived through spectral mixture analysis of AVIRIS, TM, and AVHRR imagery) with a process-based ecosystem model, we will generate explicit predictions of the C and N storage in plants and soils resulting from changes in vegetation structure. Our specific objectives will be to (1) continue development and test applications of spectral mixture analysis across grassland-to-woodland transitions; (2) quantify temporal changes in plant and soil C and N storage and turnover for remote sensing and process model parameterization and verification; and (3) couple landscape fraction maps to an ecosystem simulation model to observe biogeochemical dynamics under changing landscape structure and climatological forcings.

Wessman, Carol A.↗

NASA NTRS1999

Application of Spaceborne Scatterometer for Mapping Freeze-Thaw State in Northern Landscapes as a Measure of Ecological and Hydrological Processes

Landscape freeze/thaw transitions coincide with marked shifts in albedo, surface energy and mass exchange, and associated snow dynamics. Monitoring landscape freeze/thaw dynamics would improve our ability to quantify the interannual variability of boreal hydrology and river runoff/flood dynamics. The annual duration of frost-free period also bounds the period of photosynthetic activity in boreal and arctic regions thus affecting the annual carbon budget and the interannual variability of regional carbon fluxes. In this study, we use the NASA scatterometer (NSCAT) to monitor the temporal change in the radar backscatter signature across selected ecoregions of the boreal zone. We have measured vegetation tissue temperatures, soil temperature profiles, and micrometeorological parameters in situ at selected sites along a north-south transect extending across Alaska from Prudhoe Bay to the Kenai Peninsula and in Siberia near the Yenisey River. Data from these stations have been used to quantify the scatterometer's sensitivity to freeze/thaw state under a variety of terrain and landcover conditions. Analysis of the NSCAT temporal response over the 1997 spring thaw cycle shows a 3 to 5 dB change in measured backscatter that is well correlated with the landscape springtime thaw process. Having verified the instrument's capability to monitor freeze/thaw transitions, regional scale mosaicked data are applied to derive temporal series of freeze/thaw transition maps for selected circumpolar high latitude regions. These maps are applied to derive areal extent of frozen and thawed landscape and demonstrate the utility of spaceborne radar for operational monitoring of seasonal freeze-thaw dynamics and associated biophysical processes for the circumpolar high latitudes.

McDonald, Kyle↗

NASA NTRS1994

Episodic nitrous oxide soil emissions in Brazilian savanna (cerrado) fire-scars

The seasonally burned cerrados of Brazil are the largest savanna-type ecosystem of South America and their contribution to the global atmospheric nitrous oxide (N20) budget is unknown. Four types of fire-scarred cerrado along a vegetation gradient from grassland to forest were investigated during the wet season of 1992/93. The effect of fire and subsequent water additions on epiodic emissions of N2O and the associated profile dynamic of soil/gas phase N2O concentrations were studied for several months. Additionally, the effect on episodic emissions of N2O of nitrate and glucose additions to a cerrado soil after fire and the associated profile dynamic of soil/gas phase N2O mixing ratios were determined. Finally, N2O episodic emissions in cerrado converted to corn, soybean, and pasture fields were investigated during one growing/wet season. Results showed N2O consumption/emission for the four fire-scared savanna ecosystems, for nitrogen and carbon fertilization, and for agriculture/pasture ranging from -0.3 to +0.7, 1.8 to 9.1, and 0.5 to 3.7 g N2O-N ha(exp -1) d(exp -1), respectively. During the wet season the cerrado biome does not appear to be a major source of N2O to the troposphere, even following fire events. However, the results of this study suggest that conversion of the cerrado to high input agriculture, with liming and fertilization, can increase N2O emissions more than ten fold.

Nobre, A. D.↗

NASA NTRS2001

An Integrated Use of Experimental, Modeling and Remote Sensing Techniques to Investigate Carbon and Phosphorus Dynamics in the Humid Tropics

Moist tropical forests comprise one of the world's largest and most diverse biomes, and exchange more carbon, water, and energy with the atmosphere than any other ecosystem. In recent decades, tropical forests have also become one of the globe's most threatened biomes, subjected to exceptionally high rates of deforestation and land degradation. Thus, the importance of and threats to tropical forests are undeniable, yet our understanding of basic ecosystem processes in both intact and disturbed portions of the moist tropics remains poorer than for almost any other major biome. Our approach in this project was to take a multi-scale, multi-tool approach to address two different problems. First, we wanted to test if land-use driven changes in the cycles of probable limiting nutrients in forest systems were a key driver in the frequently observed pattern of declining pasture productivity and carbon stocks. Given the enormous complexity of land use change in the tropics, in which one finds a myriad of different land use types and intensities overlain on varying climates and soil types, we also wanted to see if new remote sensing techniques would allow some novel links between parameters which could be sensed remotely, and key biogeochemical variables which cannot. Second, we addressed to general questions about the role of tropical forests in the global carbon cycle. First, we used a new approach for quantifying and minimizing non-biological artifacts in the NOAA/NASA AVHRR Pathfinder time series of surface reflectance data so that we could address potential links between Amazonian forest dynamics and ENSO cycles. Second, we showed that the disequilibrium in C-13 exchanged between land and atmosphere following tropical deforestation probably has a significant impact on the use of 13-CO2 data to predict regional fluxes in the global carbon cycle.

Townsend, Alan R.↗

NASA NTRS2021

Disentangling the Regional Climate Impacts of Competing Vegetation Responses to Elevated Atmospheric CO2

Biophysical vegetation responses to elevated atmospheric carbon dioxide (CO2) affect regional hydroclimate through two competing mechanisms. Higher CO2 increases leaf area (LAI), thereby increasing transpiration and water losses. Simultaneously, elevated CO2 reduces stomatal conductance and transpiration, thereby increasing rootzone soil moisture. Which mechanism dominates in the future is highly uncertain, partly because these two processes are difficult to explicitly separate within dynamic vegetation models. We address this challenge by using the GISS ModelE global climate model to conduct a novel set of idealized 2×CO2 sensitivity experiments to: evaluate the total vegetation biophysical contribution to regional climate change under high CO2; and quantify the separate contributions of enhanced LAI and reduced stomatal conductance to regional hydroclimate responses. We find that increased LAI exacerbates soil moisture deficits across the sub‐tropics and more water‐limited regions, but also attenuates warming by ∼0.5–1°C in the US Southwest, Central Asia, Southeast Asia, and northern South America. Reduced stomatal conductance effects contribute ∼1°C of summertime warming. For some regions, enhanced LAI and reduced stomatal conductance produce nonlinear and either competing or mutually amplifying hydroclimate responses. In northeastern Australia, these effects combine to exacerbate radiation‐forced warming and contribute to year‐round water limitation. Conversely, at higher latitudes these combined effects result in less warming than would otherwise be predicted due to nonlinear responses. These results highlight substantial regional variation in CO2‐driven vegetation responses and the importance of improving model representations of these processes to better quantify regional hydroclimate impacts.

Regional climate impacts↗