Engineering topics

Matthews, Elaine

Publications and source records attributed to Matthews, Elaine.

14 records

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 NTRS2002

Climatic and Chemical Controls on Methane Emissions from Wetlands

Natural wetlands are the largest single source of methane to the atmosphere and the only one dominated by climate. Although interannual variations in methane emissions from short-term climate variations are becoming better understood, major uncertainties remain with respect to the sensitivity of wetlands and their CH4 emissions to climate variability, the sensitivity of suppression of wetland methane missions to changes in low-dose sulfate deposition, and the response of wetland dynamics to climate variations. We present results from modeling, field, and remote sensing research that integrate current understanding of the dynamics of wetlands and their methane emissions.

Matthews, Elaine↗

NASA NTRS2001

Modeling Modern Methane Emissions from Natural Wetlands: Model Description and Results - 1

Methane is an important greenhouse gas which contributes about 22 percent to the present greenhouse effect. Natural wetlands currently constitute the biggest methane source and were the major source in preindustrial times. Wetland emissions depend highly on the climate, i.e., on soil temperature and water table. To investigate the response of methane emissions from natural wetlands to climate variations, a process-based model that derives methane emissions from natural wetlands as a function of soil temperature, water table, and net primary productivity is used. For its application on the global scale, global data sets for all model parameters are generated. In addition, a simple hydrologic model is developed in order to simulate the position of the water table in wetlands. The hydrologic model is tested against data from different wetland sites, and the sensitivity of the hydrologic model to changes in precipitation is examined. The global methane hydrology model constitutes a tool to study temporal and spatial variations in methane emissions from natural wetlands. The model is applied using high-frequency atmospheric forcing fields from European Center for Medium-range Weather Forecasts (ECMWF) re-analyses of the period from 1982 to 1993. We calculate global annual methane emissions from wetlands to be 260 teragrams per year. Twenty-five percent of these methane emissions originate from wetlands north of 30 degrees North Latitude. Only 60 percent of the produced methane is emitted, while the rest is re-oxidized. A comparison of zonal integrals of simulated global wetland emissions and results obtained by an inverse modeling approach shows good agreement. In a test with data from two wetlands the seasonality of simulated and observed methane emissions agrees well.

Biogeochemical processes↗

NASA NTRS2001

Joint Characterization of Vegetation by Satellite Observations from Visible to Microwave Wavelengths - A Sensitivity Analysis

This study presents an evaluation and comparison of visible, near-infrared, passive, and active microwave observations for vegetation characterization on a global basis for a year, with spatial resolution compatible with climatological studies. Visible and near-infrared observations along with the Normalized Difference Vegetation Index come from the Advanced Very High Resolution Radiometer. An atlas of monthly mean microwave land surface emissivities from 19 to 85 GHz has been calculated from the Special Sensor Microwave/Imager for a year, suppressing the atmospheric problems encountered with the use of simple channel combinations. The active microwave measurements are provided by the ERS-1 scatterometer at 5.25 GHz. The capacity to discriminate between vegetation types and to detect the vegetation phenology is assessed in the context of a vegetation classification obtained from in situ observations. A clustering technique derived from the Kohonen topological maps is used to merge the three data sets and interpret their relative variations. NDVI varies with vegetation density but is not very sensitive in semiarid environments and in forested areas. Spurious seasonal cycles and large spatial variability in several areas suggest that atmospheric contamination and/or solar zenith angle drift still affect the NDVI.

NORMALIZED DIFFERENCE VEGETATIVE INDEX↗

NASA NTRS2001

Contribution of Changing Sources and Sinks to the Growth Rate of Atmospheric Methane Concentrations for the Last Two Decades

In situ measurements of atmospheric methane concentrations begun in the early 1980s show decadal trends, as well as large interannual variations, in growth rate. Recent research indicates that while wetlands can explain several of the large growth anomalies for individual years, the decadal trend may be the combined effect of increasing sinks, due to increases in tropospheric OH, and stabilizing sources. We discuss new 20-year histories of annual, global source strengths for all major methane sources, i.e., natural wetlands, rice cultivation, ruminant animals, landfills, fossil fuels, and biomass burning. We also present estimates of the temporal pattern of the sink required to reconcile these sources and atmospheric concentrations over this time period. Analysis of the individual emission sources, together with model-derived estimates of the OH sink strength, indicates that the growth rate of atmospheric methane observed over the last 20 years can only be explained by a combination of changes in source emissions and an increasing tropospheric sink. Direct validation of the global sources and the terrestrial sink is not straightforward, in part because some sources/sinks are relatively small and diffuse (e.g., landfills and soil consumption), as well as because the atmospheric record integrates multiple and substantial sources and tropospheric sinks in regions such as the tropics. We discuss ways to develop and test criteria for rejecting and/or accepting a suite of scenarios for the methane budget.

Matthews, Elaine↗

NASA NTRS2000

Remote Sensing of Global Wetland Dynamics

Although natural wetlands only cover about 4% of the earth's ice-free land surface, they are the world's largest methane (CH4) source and the only one dominated by climate. In addition, wetlands affect climate by modulating temperatures and heat fluxes, storing water, increasing evaporation, and altering the seasonality of runoff and river discharge to the oceans. Current CH4 emissions from wetlands are relatively well understood but the sensitivity of wetlands and their emissions to climate variations remains the largest uncertainty in the global CH4 cycle and could strongly influence predictions of future climate. Therefore, characterizing climate-sensitive processes prevailing in the world's wetlands is crucial to understanding and predicting physical and biogeochemical responses of wetlands to interannual and longer-term climate variations. Recent research has resulted in the first generation of models to predict methane emissions from wetlands but the models must still be applied to static data on wetland distributions. Moreover, no models currently exist to realistically predict the distribution and dynamics of wetlands themselves for the current, or any other, climate. The dominant obstacle to modeling wetland dynamics has been lack of remote sensing techniques and data useful for characterizing quantitatively the seasonal and interannual variations of wetlands. We report on initial remote sensing studies undertaken to validate a global hydrological model linking rivers, takes and wetlands. Using a combination of SSM/I microwave and TOPEX Poseidon altimetry data sets, we developed and applied techniques to quantify inundation extent and duration for several large wetlands in tropical Africa and South America. Our initial results indicate that seasonally-inundated wetlands can be well characterized over large spatial scales and at monthly time scales using these remote sensing data. The results also confirm that currently available remote sensing products can be applied to provide crucial data to the research community modeling global hydrological and biogeochemical cycles.

Matthews, Elaine↗

NASA NTRS2000

Contribution of Changing Sources and Sinks to the Growth Rate of Atmospheric Methane Concentrations for the Last Two Decades

Matthews, Elaine↗

NASA NTRS1999

Microwave Radiometric Signatures of Different Surface Types in Deserts

In arid environments, specific microwave signatures have been observed with the Special Sensor Microwave/Imager (SSM/I). For a given diurnal change in surface skin temperature, the corresponding change in the microwave brightness temperature is smaller than expected. With the help of a 1D, time-dependent heat conduction model, this behavior is explained by microwave radiation coming from different depths in the soil, depending on the soil type and on the microwave radiation frequency. Using the eight-times daily estimates of the surface skin temperature by the International Satellite Cloud Climatology Project (ISCCP) and a simple Fresnel model, collocated month-long time series of the SSM/I brightness temperatures and the surface skin temperatures give a consistent estimate of the effective microwave emissivity and penetration depth parameters. Results are presented and analyzed for the Sahara and the Arabian Peninsula, for July and November 1992. The case of the Australian desert is also briefly mentioned. Assuming a reasonable thermal diffusivity for the soil in desert areas, the microwave radiation is estimated to come from soil layers down to depths of at least five wavelengths in some locations. Regions where the microwave radiation comes from deeper soil layers also have large microwave emissivity polarization differences and large visible reflectances, suggesting that these areas correspond to sand dune fields.

Prigent, Catherine↗

NASA NTRS1998

Climate Forcings in the Industrial Era

The forcings that drive long-term climate change are not known with an accuracy sufficient to define future climate change. Anthropogenic greenhouse gases (GHGs), which are well measured, cause a strong positive (warming) forcing. But other, poorly measured, anthropogenic forcings, especially changes of atmospheric aerosols, clouds, and land-use patterns, cause a negative forcing that tends to offset greenhouse warming. One consequence of this partial balance is-that the natural forcing due to solar irradiance changes may play a larger role in long-term climate change than inferred from comparison with GHGs alone. Current trends in GHG climate forcings are smaller than in popular "business as usual" or 1% per year CO2 growth scenarios. The summary implication is a paradigm change for long-term climate projections: uncertainties in climate forcings have supplanted global climate sensitivity as the predominant issue.

Hansen, James E.↗

NASA NTRS1998

Perspective: Climate Forcings in the Industrial Era

The forcings that drive long-term climate change are not known with an accuracy sufficient to define future climate change. Anthropogenic greenhouse gases (GHGs), which are well measured, cause a strong positive (warming) forcing. But other, poorly measured, anthropogenic forcings, especially changes of atmospheric aerosols, clouds, and land-use patterns, cause a negative forcing that tends to offset greenhouse warming. One consequence of this partial balance is that the natural forcing due to solar irradiance changes may play a larger role in long-term climate change than inferred from comparison with GHGs alone. Current trends in GHG climate forcings are smaller than in popular "business as usual" or 1% per year CO growth scenarios. The summary implication is a paradigm change for long-term climate projections: uncertainties in climate forcings have supplanted global climate sensitivity as the predominant issue.

Hansen, James E.↗

NASA NTRS1994

Rice cultivation and methane emission: Documentation of distributed geographic data sets

High-resolution global data bases on the geographic and seasonal distribution of rice cultivation and associated methane emission, compiled by Matthews et al., were archived for public use. In addition to the primary data sets identifying location, seasonality, and methane emission from rice cultivation, a series of supporting data sets is included, allowing users not only to replicate the work of Matthews et al. but to investigate alternative cultivation and emission scenarios. The suite of databases provided, at 1 latitude by 1 longitude resolution for the globe, includes (1) locations of rice cultivation, (2) monthly arrays of actively growing rice areas, (3) countries and political subdivisions, and (4) monthly arrays of methane emission from rice cultivation. Ancillary data include (1) a listing, by country, of harvested rice areas and seasonal distribution of crop cycles and (2) country names and codes. Summary tables of zonal/monthly distributions of actively growing rice areas and of methane emissions are presented. Users should consult original publications for complete discussion of the data bases. This short paper is designed only to document formats of the distributed information and briefly describe the contents of the data sets and their initial application to evaluating the role of rice cultivation in the methane budget.

Matthews, Elaine↗

NASA NTRS1989

Global data bases on distribution, characteristics and methane emission of natural wetlands: Documentation of archived data tape

Global digital data bases on the distribution and environmental characteristics of natural wetlands, compiled by Matthews and Fung (1987), were archived for public use. These data bases were developed to evaluate the role of wetlands in the annual emission of methane from terrestrial sources. Five global 1 deg latitude by 1 deg longitude arrays are included on the archived tape. The arrays are: (1) wetland data source, (2) wetland type, (3) fractional inundation, (4) vegetation type, and (5) soil type. The first three data bases on wetland locations were published by Matthews and Fung (1987). The last two arrays contain ancillary information about these wetland locations: vegetation type is from the data of Matthews (1983) and soil type from the data of Zobler (1986). Users should consult original publications for complete discussion of the data bases. This short paper is designed only to document the tape, and briefly explain the data sets and their initial application to estimating the annual emission of methane from natural wetlands. Included is information about array characteristics such as dimensions, read formats, record lengths, blocksizes and value ranges, and descriptions and translation tables for the individual data bases.

Matthews, Elaine↗

NASA NTRS1987

Regional and seasonal variations of surface reflectance from satellite observations at 0.6 micron

A global series of seasonal visible surface reflectance maps derived from NOAA-5 Scanning Radiometer observations is presented. Methods for isolating clear-sky observations from satellite data are evaluated and the magnitude of atmospheric effects (Rayleigh scattering and ozone absorption) are presented. A preliminary analysis of digital vegetation and soils data bases, which were analyzed in conjunction with the satellite observations, is discussed. Regional and global reflectance homogeneity of land-cover types, and snow brightening for types, are presented. Results demonstrate that the statistical approach for isolating clear-sky radiances used in this study obtains accurate enough values for each location to allow meaningful measurements of seasonal, spatial and ecosystem variations in surface reflectance.

Matthews, Elaine↗

NASA NTRS1986

Data needs and data bases for climate studies

Two complementary global digital data bases of vegetation and land use, compiled at 1 deg resolution from published sources for use in climate studies, are discussed. The data bases were implemented, in several individually tailored formulations, in a series of climate related applications including: land-surface prescriptions in three-dimensional general circulation models, global biogeochemical cycles (CO2, methane), critical-area mapping for satellite monitoring of land-cover change, and large-scale remote sensing of surface reflectance. The climate applications are discussed with reference to data needs, and data availability from traditional and remote sensing sources.

Matthews, Elaine↗