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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

A GEO Hyperspectral Mission For Continental-Scale Carbon Cycle Observations

For both terrestrial and ocean carbon cycle science objectives, a hyperspectral geostationary sensor should enable the development of new remote sensing measurements for important but as yet unobservable variables, and with the overall goal of linking both terrestrial and ocean carbon cycle processes to climate variability. For terrestrial research, accurate estimates of carbon, water and energy (CWE) exchange between the terrestrial biosphere and atmosphere are needed to identify the geographical locations of carbon sources/sinks and to improve regional climate models and global climate change assessments. It is an enormous challenge to estimate CWE exchange from the infrequent temporal coverage provided by most polar-orbiting satellites, and without benefit of spectral indices that capture vegetation responses to stress conditions that down-regulate photosynthesis. Physiological status can be better assessed with spectral indices based on continuous, narrow (5 nm) bands, as can seasonal and annual terrestrial productivity. For coastal and ocean constituents, narrow-band observations in the ultraviolet and visible are essential to investigate the variability, dynamics and biogeochemical cycles of the world s coastal and open ocean regions, which will in turn help in measuring ocean productivity and predicting the variability of Ocean carbon uptake and its role in climate change scenarios. The GSFC Carbon Team has been pursuing a geostationary hyperspectral instrument, which would revolutionize our knowledge of biological processes on land, in the ocean, and along the coast by providing multiple, diurnal coverage. Preliminary studies in Goddard's Instrument Synthesis and Analysis Laboratory (ISAL) indicate that we can meet many of our science requirements: full spectral coverage (360-1000 nm); narrow bandwidths (5-10 nm); adequate ground resolution (100-200 m); and continental-scale coverage 4-6 times per day; all the while achieving a signal to noise ratio of between 500 and 1000 to 1. However, an innovative and bold focal plane design and a large mirror (1.8 meter diameter) would be required. The development of our science requirements and the results of the initial design study will be presented as well as our most recent technological developments.

Gervin, Janette C.↗
NASA NTRS1998

Assimilation of Goes-Derived Skin Temperature Tendencies into Mesoscale Models to Improve Forecasts of near Surface Air Temperature and Mixing Ratio

A technique has been developed for assimilating GOES-FR skin temperature tendencies into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature chance closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. An advantage of this technique for short-range forecasts (0-48 h) is that it does not require a complex land-surface formulation within the atmospheric model. As a result, the need to specify poorly known soil and vegetative characteristics is eliminated. The GOES assimilation technique has been incorporated into the PSU/NCAR MM5. Results will be presented to demonstrate the ability of the assimilation scheme to improve short- term (0-48h) simulations of near-surface air temperature and mixing ratio during the warm season for several selected cases which exhibit a variety of atmospheric and land-surface conditions. In addition, validation of terms in the simulated surface energy budget will be presented using in situ data collected at the Southern Great Plains (SGP) Cloud And Radiation Testbed (CART) site as part of the Atmospheric Radiation Measurements Program (ARM).

Lapenta, William M.↗
NASA NTRS2023

Maldives Climate II: Evaluating the Potential Impacts of Sea Level Rise on Human Development and Coastal Infrastructure

The Republic of the Maldives is a low-lying island nation in the Indian Ocean which has experienced rapid urbanization, landcover changes, and sea level rise over recent years. The growth of tourism, coastal erosion, and urbanization have all driven land reclamation efforts across many islands. As in-situ landcover change monitoring has proven difficult across the vast archipelago, the NASA DEVELOP team collaborated with the Maldives Ministry of Environment, Climate Change, and Technology; USAID; and the U.S. Department of State, to utilize Earth observations to predict sea level rise impacts on coastal infrastructure. The team used a supervised classification algorithm within Google Earth Engine to create land use maps and time series analyses of nine islands and atolls using imagery from Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, Sentinel-2 Multispectral Instrument, and PlanetScope, covering a combined period of 2000 through 2023. Additionally, the team projected coastal inundation with a modified deterministic Bathtub model utilizing elevation data from CoastalDEM and 2050-2100 Shared Socioeconomic Pathway scenarios identified in the NASA Sea Level Rise Projection Tool. The team found that islands undergoing urban growth experienced a 23% decrease in vegetation between 2014 and 2022. Furthermore, the model predicted that 51–57% of the study area’s-built environment has a chance of inundation by 2100 under the low and high sea level scenarios. These analyses demonstrate how remote sensing can be used to both track land use changes over time and project how coastlines will be affected by sea level rise.

remote sensing↗
NASA NTRS1983

Seasonal soybean crop reflectance

Data are presented from field measurements of 1980 including 5 acquisitions of handheld radiometer reflectance measurements, 7 complete sets of parameters for implementing the Suits mode, and other biophysical parameters to characterize the soybean canopy. LANDSAT calculations on the simulated Brazilian soybean reflectance are included along with data collected during the summer and fall on 1981 on soybean single leaf optical parameters for three irrigation treatments. Tests of the Suits vegetative canopy reflectance model for the full hemisphere of observer directions as well as the nadir direction show moderate agreement for the visible channels of the MSS and poor agreement in the near infrared channel. Temporal changes in the spectral characteristics of the single leaves were seen to occur as a function of maturity which demonstrates that the absorptance of a soybean single leaf is more a function of thetransmittancee characteristics than the seasonally consistent single leaf reflectance.

Lemaster, E. W.↗
NASA NTRS2011

Subsurface Emission Effects in AMSR-E Measurements: Implications for Land Surface Microwave Emissivity Retrieval

An analysis of land surface microwave emission time series shows that the characteristic diurnal signature associated with subsurface emission in sandy deserts carry over to arid and semi-arid region worldwide. Prior work found that diurnal variation of Special Sensor Microwave/Imager (SSM/I) brightness temperatures in deserts was small relative to International Satellite Cloud Climatology Project land surface temperature (LST) variation and that the difference varied with surface type and was largest in sand sea regions. Here we find more widespread subsurface emission effects in Advanced Microwave Scanning Radiometer-EOS (AMSR-E) measurements. The AMSR-E orbit has equator crossing times near 01:30 and 13 :30 local time, resulting in sampling when near-surface temperature gradients are likely to be large and amplifying the influence of emission depth on effective emitting temperature relative to other factors. AMSR-E measurements are also temporally coincident with Moderate Resolution Imaging Spectroradiometer (MODIS) LST measurements, eliminating time lag as a source of LST uncertainty and reducing LST errors due to undetected clouds. This paper presents monthly global emissivity and emission depth index retrievals for 2003 at 11, 19, 37, and 89 GHz from AMSR-E, MODIS, and SSM/I time series data. Retrieval model fit error, stability, self-consistency, and land surface modeling results provide evidence for the validity of the subsurface emission hypothesis and the retrieval approach. An analysis of emission depth index, emissivity, precipitation, and vegetation index seasonal trends in northern and southern Africa suggests that changes in the emission depth index may be tied to changes in land surface moisture and vegetation conditions

Galantowicz, John F.↗
NASA NTRS2012

Investigating the Potential Range Expansion of the Vector Mosquito Aedes Aegypti in Mexico with NASA Earth Science Remote Sensing Results

In tropical and sub ]tropical regions, the mosquito Aedes aegypti is the major vector for the virus causing dengue, a serious public health issue in these areas. Through ongoing NSF- and NASA-funded studies, field surveys of Aedes aegypti and an integrated modeling approach are being used to improve our understanding of the potential range of the mosquito to expand toward heavily populated high elevation areas such as Mexico City under various climate change and socio ]economic scenarios. This work serves three primary objectives: (1) Employ NASA remotely-sensed data to supplement the environmental monitoring and modeling component of the project. These data-- for example, surface temperature, precipitation, vegetation indices, soil moisture and elevation-- are critical for understanding the habitat necessary for mosquito survival and abundance; (2) Implement training sessions to instruct scientists and students from Mexico and the U.S. on how to use remote sensing and implement the NASA SERVIR Regional Visualization and Monitoring System; (3) Employ the SERVIR framework to optimize the dissemination of key project results in order to increase their societal relevance and benefits in developing climate adaptation strategies. Field surveys of larval, pupal and adult Aedes aegypti, as well as detailed physical and social household characteristics, were conducted in the summers of 2011and 2012 at geographic scales from the household to the community along a transect from sea level to 2400 m ASL. These data are being used in models to estimate Aedes aegypti habitat suitability. In 2011, Aedes aegypti were identified at an elevation of over 2150 m in Puebla, the highest elevation at which this species has been observed.

Crosson, W. L.↗
NASA NTRS1995

AVIRIS spectral trajectories for forested areas of the Gifford Pinchot National Forest

A simple mixing model employing reference endmembers (green vegetation, non-photosynthetic vegetation, soil and shade), and using 180 AVIRIS bands, was used to establish an interpretive framework for a forested area in the Pacific Northwest. A regrowth trend, based on changes in the endmember proportions, was defined for conifers that extends from clearcuts to mature forest, and by implication to old growth. Deciduous species within replanted forest plots caused the fractions to be displaced from the main coniferous regrowth trend and to move toward the green vegetation fraction. The results indicate that the spectral information in AVIRIS can be inverted to estimate approximate stand age and relative proportion of deciduous species in the context of the area studied. Using AVIRIS we measured a 3 to 5 percent increase in woody material in old-growth forest, as distinct from other mature forest. This result is consistent with a predicted increase in NPV in old-growth forest, based on field observations. Previous application of the mixing analysis to a TM image of the same area separated old growth based solely on the shade fraction; however the approach required successful removal of shade introduced by topography. Our new results suggest that with the high spectral resolution and high signal-to-noise of AVIRIS images it may be possible to characterize and map old-growth forests in the Northwest using both the NPV fraction and shade.

Sabol, Donald E., Jr.↗
NASA NTRS2019

20,000 Years of Societal Vulnerability and Adaptation to Climate Change in Southwest Asia

The Fertile Crescent, its hilly flanks and surrounding drylands has been a critical region for studying how climate has influenced societal change, and this review focuses on the region over the last 20,000 years. The complex social, economic, and environmental landscapes in the region today are not new phenomena and understanding their interactions requires a nuanced, multidisciplinary understanding of the past. This review builds on a history of collaboration between the social and natural palaeoscience disciplines. We provide a multidisciplinary, multiscalar perspective on the relevance of past climate, environmental, and archaeological research in assessing present day vulnerabilities and risks for the populations of southwest Asia. We discuss the complexity of palaeoclimatic data interpretation, particularly in relation to hydrology, and provide an overview of key time periods of palaeoclimatic interest. We discuss the critical role that vegetation plays in the human–climate–environment nexus and discuss the implications of the available palaeoclimate and archaeological data, and their interpretation, for palaeonarratives of the region, both climatically and socially. We also provide an overview of how modelling can improve our understanding of past climate impacts and associated change in risk to societies. We conclude by looking to future work, and identify themes of “scale” and “seasonality” as still requiring further focus. We suggest that by appreciating a given locale's place in the regional hydroscape, be it an archaeological site or palaeoenvironmental archive, more robust links to climate can be made where appropriate and interpretations drawn will demand the resolution of factors acting across multiple scales.

Levant↗
NASA NTRS2013

Daily MODIS 500 m Reflectance Anisotropy Direct Broadcast (DB) Products for Monitoring Vegetation Phenology Dynamics

Land surface vegetation phenology is an efficient bio-indicator for monitoring ecosystem variation in response to changes in climatic factors. The primary objective of the current article is to examine the utility of the daily MODIS 500 m reflectance anisotropy direct broadcast (DB) product for monitoring the evolution of vegetation phenological trends over selected crop, orchard, and forest regions. Although numerous model-fitted satellite data have been widely used to assess the spatio-temporal distribution of land surface phenological patterns to understand phenological process and phenomena, current efforts to investigate the details of phenological trends, especially for natural phenological variations that occur on short time scales, are less well served by remote sensing challenges and lack of anisotropy correction in satellite data sources. The daily MODIS 500 m reflectance anisotropy product is employed to retrieve daily vegetation indices (VI) of a 1 year period for an almond orchard in California and for a winter wheat field in northeast China, as well as a 2 year period for a deciduous forest region in New Hampshire, USA. Compared with the ground records from these regions, the VI trajectories derived from the cloud-free and atmospherically corrected MODIS Nadir BRDF (bidirectional reflectance distribution function) adjusted reflectance (NBAR) capture not only the detailed footprint and principal attributes of the phenological events (such as flowering and blooming) but also the substantial inter-annual variability. This study demonstrates the utility of the daily 500 m MODIS reflectance anisotropy DB product to provide daily VI for monitoring and detecting changes of the natural vegetation phenology as exemplified by study regions comprising winter wheat, almond trees, and deciduous forest.

Vegetation↗
NASA NTRS2020

Global Carbon Cycle and Climate Feedbacks in the NASA GISS ModelE2.1

We present results from the NASA GISS ModelE2.1‐G‐CC Earth System Model with coupled climate‐carbon cycle simulations that were submitted to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) Coupled Climate‐Carbon Cycle MIP (C4MIP). Atmospheric CO2 concentration and carbon budgets for the land and ocean in the historical simulations were generally consistent with observations. Low simulated atmospheric CO2 concentrations during 1850‐1950 were due to excess uptake from prescribed land cover change, which erroneously replaced arid shrublands with higher biomass crops, and assumed high 2004 LAI values in vegetated lands throughout the historical simulation. At the end of the historical period, slightly higher simulated CO2 than observed resulted from the land being an insufficient net carbon sink, despite the net effect of CO2 fertilization and warming‐induced increases to leaf photosynthetic capacity. The global ocean carbon uptake agreed well with the observations with the largest discrepancies in the low latitudes. Future climate projection at 2091‐2100 agreed with CMIP5 models in the northward shift, of temperate deciduous forest climate and expansion across Eurasia along 60 °N latitude, and dramatic regional biome shifts from drying and warming in continental Europe. Carbon feedback parameters were largely similar to the CMIP5 model ensemble. For our model, the variation of land feedback parameters within the uncertainty arises from the fertilization feedback being less sensitive due to lack of increased vegetation growth, and the comparably more negative ocean carbon‐climate feedback is due to the large slowdown of the Atlantic overturning circulation.

Carbon cycle↗
NASA NTRS1993

Mapping and monitoring changes in vegetation communities of Jasper Ridge, CA, using spectral fractions derived from AVIRIS images

An important application of remote sensing is to map and monitor changes over large areas of the land surface. This is particularly significant with the current interest in monitoring vegetation communities. Most of traditional methods for mapping different types of plant communities are based upon statistical classification techniques (i.e., parallel piped, nearest-neighbor, etc.) applied to uncalibrated multispectral data. Classes from these techniques are typically difficult to interpret (particularly to a field ecologist/botanist). Also, classes derived for one image can be very different from those derived from another image of the same area, making interpretation of observed temporal changes nearly impossible. More recently, neural networks have been applied to classification. Neural network classification, based upon spectral matching, is weak in dealing with spectral mixtures (a condition prevalent in images of natural surfaces). Another approach to mapping vegetation communities is based on spectral mixture analysis, which can provide a consistent framework for image interpretation. Roberts et al. (1990) mapped vegetation using the band residuals from a simple mixing model (the same spectral endmembers applied to all image pixels). Sabol et al. (1992b) and Roberts et al. (1992) used different methods to apply the most appropriate spectral endmembers to each image pixel, thereby allowing mapping of vegetation based upon the the different endmember spectra. In this paper, we describe a new approach to classification of vegetation communities based upon the spectra fractions derived from spectral mixture analysis. This approach was applied to three 1992 AVIRIS images of Jasper Ridge, California to observe seasonal changes in surface composition.

Sabol, Donald E., Jr.↗
NASA NTRS1990

Potential evapotranspiration and the likelihood of future drought

The possibility that the greenhouse warming predicted by the GISS general-circulation model and other GCMs could lead to severe droughts is investigated by means of numerical simulations, with a focus on the role of potential evapotranspiration E(P). The relationships between precipitation (P), E(P), soil moisture, and vegetation changes in GCMs are discussed; the empirically derived Palmer drought-intensity index and a new supply-demand index (SDDI) based on changes in P - E(P) are described; and simulation results for the period 1960-2060 are presented in extensive tables, graphs, and computer-generated color maps. Simulations with both drought indices predict increasing drought frequency for the U.S., with effects already apparent in the 1990s and a 50-percent frequency of severe droughts by the 2050s. Analyses of arid periods during the Mesozoic and Cenozoic are shown to support the use of the SDDI in GCM drought prediction.

Rind, D.↗
NASA NTRS2002

Land and Land-use Change in the Climate Sensitive High Plains: An Automated Approach with Landsat

The High Plains is an economically important and climatologically sensitive region of the United States and Canada. The High Plains contain 100,000 sq km of Holocene sand dunes and sand sheets that are currently stabilized by natural vegetation. Droughts and the larger threat of global warming are climate phenomena that could cause depletion of natural vegetation and make this region susceptible to sand dune reactivation. The original proposal was directed toward the use of Landsat TM data to establish the state and ongoing changes of the surface in the 1.2 million sq. km, semi-arid High Plains region of the central US, A key objective was to develop a model to predict the reactivation of the 100,000 sq. km of Holocene dunes found on the High Plains during an extended drought. At least one Landsat 5 image per year for 1985, 1988 and 1996 was obtained for 32 scenes on the High Plains to coincide with wet and dry years. Additional Landsat 7 data were acquired for 1999 and 2000 primarily for Colorado and Nebraska. As luck would have it, there was no severe drought during the study period 1985-2000. Attention was focused on developing methods for mapping dry vs. green vegetation on sparsely vegetated rangelands in sandy soils, since these were the areas most susceptible to surface reactivation during a drought.

Goetz, Alexander F.↗
NASA NTRS1993

Simulated retrieval of land surface parameters using multichannel satellite microwave radiometry

The current global change research emphasis on understanding water and energy fluxes at the land-atmosphere interface provided renewed interest in using passive microwave satellite data for land studies. Radiative transfer models of microwave emission and scattering in the soil-vegetation-atmosphere column, though still in the process of development, can be used to estimate the accuracies with which land surface parameters can be derived from satellite data. These parameters include surface soil moisture, surface temperature, vegetation water content, and atmospheric water content. A microwave radiative transfer model is used to develop linear and nonlinear versions of a multichannel retrieval algorithm to simulate retrievals of the surface and atmospheric parameters. These simulations include the effect of additive noise, and examine the effects of nonlinearities in the radiative transfer models. However, effects of spatial heterogeneity are not considered. Satellite data to which the retrieval algorithms may be applied include the SSMR and SSM/I, and in future will include the Multifrequency Imaging Microwave Radiometer (MIMR) to be launched as part of the Earth Observing System (EOS). The Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7 satellite provided data from 1978 to 1987 at five microwave frequencies between 6.6 and 37 GHz. The series of Special Sensor Microwave/Imager (SSM/I) instruments launched on the DMSP satellites provide data from 1987 to the present at four frequencies between 19.35 and 8.5 GHz. Spatial resolutions of the data range from approximately 12 to 120 km depending on the frequency. Examples using data from these sensors are shown to indicate the results of applying retrieval algorithms based on model simulations to real data.

Njoku, Eni G.↗
NASA NTRS1999

Quantifying BRDF Effects in Comparing Landsat-7 and AVIRIS Near-Simultaneous Acquisitions for Studies of High Plains Vegetation Cover

Approximately 100,000 sq. km of the High Plains of the central United States are covered by sand dunes and sand sheets deposited during the Holocene. Soil-dating evidence shows that there were at least four periods of dune reactivation during major droughts in the last 10,000 years. The dunes in this region are anchored by vegetation. We have undertaken a study of land-use change in the High Plains from 1985 to the present using Landsat 5 TM and Landsat 7 ETM+ images to map variation in vegetation cover during wet and dry years. Mapping vegetation cover of less than 20% is important in modeling potential surface reactivation since at this level the vegetation no longer sufficiently shields sandy surfaces from movement by wind. Landsat TM data have both the spatial resolution and temporal coverage to facilitate vegetation cover analysis for model development and verification. However, there is still the question of how accurate TM data are for the measurement of both growing and senescent vegetation in and and semi-arid regions. AVIRIS provides both high spectral resolution as well as high signal-to-noise ratio and can be used to test the accuracy of Landsat TM and ETM+ data. We have analyzed data from AVIRIS flown nearly concurrently with a Landsat 7 overpass. The comparison between an AVIRIS image swath of 11 km width subtending a 30 deg. angle and the same area covered by a 0.8 deg. angle from Landsat required accounting for the BRDF. A normalization technique using the ratio of the reflectances from registered AVIRIS and Landsat data proved superior to the techniques of column averaging on AVIRIS data alone published previously by Kennedy et al. This technique can be applied to aircraft data covering a wider swath angle than AVIRIS to develop BRDF responses for a wide variety of surfaces more efficiently than from ground measurements.

Goetz, A. F. H.↗
NASA NTRS2012

Recent Upgrades to NASA SPoRT Initialization Datasets for the Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its National Weather Service (NWS) partners that can initialize specific fields for local model runs within the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS). In last year's NWA abstract on this topic, the suite of SPoRT products supported in the STRC EMS was presented, which includes a Sea Surface Temperature (SST) composite, a Great Lakes sea-ice extent, a Green Vegetation Fraction (GVF) composite, and NASA Land Information System (LIS) gridded output. This abstract and companion presentation describes recent upgrades made to the SST and GVF composites, as well as the real-time LIS runs. The Great Lakes sea-ice product is unchanged from 2011. The SPoRT SST composite product has been expanded geographically and as a result, the resolution has been coarsened from 1 km to 2 km to accommodate the larger domain. The expanded domain covers much of the northern hemisphere from eastern Asia to western Europe (0 N to 80 N latitude and 150 E to 10 E longitude). In addition, the NESDIS POES-GOES product was added to fill in gaps caused by the Moderate Resolution Imaging Spectroradiometer (MODIS) being unable to sense in cloudy regions, replacing the recently-lost Advanced Microwave Scanning Radiometer for EOS with negligible change to product fidelity. The SST product now runs twice per day for Terra and Aqua combined data collections from 0000 to 1200 UTC and from 1200 to 0000 UTC, with valid analysis times at 0600 and 1800 UTC. The twice-daily compositing technique reduces the overall latency of the previous version while still representing the diurnal cycle characteristics. The SST composites are available at approximately four hours after the end of each collection period (i.e. 1600 UTC for the nighttime analysis and 0400 UTC for the daytime analysis). The real-time MODIS GVF composite has only received minor updates in the past year. The domain was expanded slightly to extend further west, north, and east to improve coverage over parts of southern Canada. Minor adjustments were also made to the manner in which GVF is calculated from the distribution of maximum Normalized Difference Vegetation Index from MODIS. The presentation will highlight some examples of the substantial inter-annual change in GVF that occurred from 2010 to 2011 in the U.S. Southern Plains as a result of the summer 2011 drought, and the early vegetation green up across the eastern U.S. due to the very warm conditions in March 2012. Finally, the SPoRT LIS runs the operational Noah land surface model (LSM) in real time over much of the eastern half of the CONUS. The Noah LSM is continually cycled in real time, uncoupled to any model, and driven by operational atmospheric analyses over a long-term, multi-year integration. The LIS-Noah provides the STRC EMS with high-resolution (3 km) LSM initialization data that are in equilibrium with the operational analysis forcing. The Noah LSM within the SPoRT LIS has been upgraded from version 2.7.1 to version 3.2, which has improved look-up table attributes for several land surface quantities. The surface albedo field is now being adjusted based on the input real-time MODIS GVF, thereby improving the net radiation. Also, the LIS-Noah now uses the newer MODIS-based land use classification scheme (i.e. the International Biosphere-Geosphere Programme [IGBP]) that has a better depiction of urban corridors in areas where urban sprawl has occurred. STRC EMS users interested in initializing their LSM fields with high-resolution SPoRT LIS data should set up their model domain with the MODIS-IGBP 20-class land use database and select Noah as the LSM.

Case, Jonathan L.↗
NASA NTRS1985

The role of isoprene oxidation in the tropospheric ozone budget in the tropics

A comprehensive chemical mechanism for the oxidation of isoprene (a hydrocarbon, C5H8 emitted primarily by vegetation) by OH and O3 in the troposphere was developed and incorporated into a one-dimensional steady-state photochemical model of the troposphere. Flux boundary conditions for NOx (NO + NO2), HNO3, O3, and CO were used to investigate the changes produced in the tropospheric concentrations and integrated column of ozone from including isoprene chemistry in the model. Two calculations were performed at 15 deg N latitude for annual conditions using identical flux boundary conditions for NOx, HNO3, O3, and CO; in one calculation, the chemistry describing isoprene oxidation was included while in the other it was not. Both sets of calculations included reactions describing the chemistry of anthropogenic nonmethane hydrocarbons. The calculations showed decreases in concentrations of ozone throughout the troposphere when isoprene chemistry was included. Concentrations of NOx and HNO3 increased in the lower troposphere and decreased in the upper troposphere while concentrations of CO and PAN increased throughout the troposphere when isoprene chemistry was included. Implications of this study to the budgets of these species in the tropics is discussed.

Brewer, D. A.↗
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↗