Elaine Matthews

Three-Dimensional Model Synthesis of the Global Methane Cycle

The geographic and seasonal emission distributions of the major sources and sinks of atmospheric methane were compiled using methane flux measurements and energy and agricultural statistics in conjunction with global digital data bases of land surface characteristics and anthropogenic activities. Chemical destruction of methane in the atmosphere was calculated using three-dimensional OH fields every 5 days taken from Spivakovsky et al. (1990a, b). The signatures of each of the sources and sinks in the atmosphere were simulated using a global three-dimensional tracer transport model. Candidate methane budget scenarios were constructed according to mass balance of methane and its carbon isotopes. The verisimilitude of the scenarios was tested by their ability to reproduce the meridional gradient and seasonal variations of methane observed in the atmosphere. Constraints imposed by all the atmospheric observations are satisfied simultaneously by several budget scenarios. A preferred budget comprises annual destruction rates of 450 Tg by OH oxidation and 10 Tg by soil absorption and annual emissions of 80 Tg from fossil sources, 80 Tg from domestic animals, and 35 Tg from wetlands and tundra poleward of 50°N. Emissions from landfills, tropical swamps, rice fields, biomass burning, and termites total 295 Tg; however, the individual contributions of these terms cannot be determined uniquely because of the lack of measurements of direct fluxes and of atmospheric methane variations in regions where these sources are concentrated.

Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive

We present a description of the ModelE2 version of the Goddard Institute for Space Studies (GISS) General Circulation Model (GCM) and the configurations used in the simulations performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). We use six variations related to the treatment of the atmospheric composition, the calculation of aerosol indirect effects, and ocean model component. Specifically, we test the difference between atmospheric models that have noninteractive composition, where radiatively important aerosols and ozone are prescribed from precomputed decadal averages, and interactive versions where atmospheric chemistry and aerosols are calculated given decadally varying emissions. The impact of the first aerosol indirect effect on clouds is either specified using a simple tuning, or parameterized using a cloud microphysics scheme. We also use two dynamic ocean components: the Russell and HYbrid Coordinate Ocean Model (HYCOM) which differ significantly in their basic formulations and grid. Results are presented for the climatological means over the satellite era (1980–2004) taken from transient simulations starting from the preindustrial (1850) driven by estimates of appropriate forcings over the 20th Century. Differences in base climate and variability related to the choice of ocean model are large, indicating an important structural uncertainty. The impact of interactive atmospheric composition on the climatology is relatively small except in regions such as the lower stratosphere, where ozone plays an important role, and the tropics, where aerosol changes affect the hydrological cycle and cloud cover. While key improvements over previous versions of the model are evident, these are not uniform across all metrics.

Global inundation dynamics inferred from multiple satellite observations, 1993–2000

Wetlands and surface waters are recognized to play important roles in climate, hydrologic and biogeochemical cycles, and availability of water resources. Until now, quantitative, global time series of spatial and temporal dynamics of inundation have been unavailable. This study presents the first global estimate of monthly inundated areas for 1993-2000. The data set is derived from a multisatellite method employing passive microwave land surface emissivities calculated from SSM/I and ISCCP observations, ERS scatterometer responses, and AVHRR visible and near-infrared reflectances. The satellite data are used to calculate inundated fractions of equal area grid cells (0.25° x 0.25° at the equator), taking into account the contribution of vegetation to the passive microwave signal. Global inundated area varies from a maximum of 5.86 x 10 6 km 2 (average for 1993-2000) to a mean minimum of 2.12 x 10 6 km 2 . These values are considered consistent with existing independent, static inventories. The new multisatellite estimates also show good agreement with regional high-resolution SAR observations over the Amazon basin. The seasonal and interannual variations in inundation have been evaluated against rain rate estimates from the Global Precipitation Climatology Project (GPCP) and water levels in wetlands, lakes, and rivers measured with satellite altimeters. The inundation data base is now being used for hydrology modeling and methane studies in GCMs.

Microwave land surface emissivities estimated from SSM/I observations

Microwave emissivities of land surfaces are estimated from special sensor microwave/imager (SSM/I) observations by removing the contributions from the atmosphere, clouds, and rain using ancillary satellite data (International Satellite Cloud Climatology Project (ISCCP) and TIROS Operational Vertical Sounder (TOVS) products). In the first step, cloud-free SSM/I observations are isolated with the help of collocated visible/infrared satellite observations (ISCCP data). The cloud-free atmospheric contribution is then calculated, from an estimate of the local atmospheric temperature-humidity profile (TOVS retrieval). Finally, with the surface skin temperature derived from IR observations (ISCCP estimate), the surface emissivity is calculated for all the SSM/I channels. As an exploration the method is applied to the SSM/I data for four months in 1991 within the Meteosat observation area. The magnitude and fluctuations of the atmospheric contributions are estimated along with the effect of surface temperature variations. Correspondences between geographical and seasonal patterns of the emissivities and topography, vegetation, flooding, and snow cover are analyzed. The potential for using microwave emissivities to monitor vegetation phenology and surface properties at regional and continental scale is investigated, and the possibility of retrieving atmospheric parameters (water vapor content, cloud liquid water path, and precipitation) over land is discussed.

Remote sensing of global wetland dynamics with multiple satellite data sets

Thiss tudy isthe firs t global effort to quantify seasonality and extent of inundation with a suite of satellite observations, including passive and active microwave along with visible and infrared measurements. A clustering tech- nique which merges the satellite observations is used to de- tect inundation. Monthly flooded areasare then calculated by estimating pixel fractional coverage of flooding using the passive microwave signal and a linear mixture model with end-memberscalibrated with radar obs ervationsto account for vegetation cover. The global results, comprising natural wetlands, irrigated rice, and lakes/rivers, indicate a min- imum inundated area for the July 1992-June 1993 period of 2.16x10 6 km 2 , about 38% of the maximum 5.75x10 6 km 2 , to be compared to maximum areasof 5.83x10 6 km 2 and 5.70x10 6 km 2 from independent data sets. Comprehensive evaluation requires substantial additions to the sparse ob- servational record now available.

Mapping the land surface for global atmosphere-biosphere models: Toward continuous distributions of vegetation's functional properties

Global land surface characteristics are important boundary conditions for global models that describe exchanges of water, energy, and carbon dioxide between the atmosphere and biosphere. Existing data sets of global land cover are based on classification schemes that characterize each grid cell as a discrete vegetation type. Consequently, parameter fields derived from these data sets are dependent on the particular scheme and the number of vegetation types it includes. The functional controls on exchanges of water, energy, and carbon dioxide between the atmosphere and biosphere are now well enough understood that it is increasingly feasible to model these exchanges using a small number of vegetation characteristics that either are related to or closely related to the functional controls. Ideally, these characteristics would be mapped as continuous distributions to capture mixtures and gradients in vegetation within the cell size of the model. While such an approach makes it more difficult to build models from detailed observations at a small number of sites, it increases the potential for capturing functionally important variation within, as well as between, vegetation types. Globally, the vegetation characteristics that appear to be most important in controlling fluxes of water, energy, and carbon dioxide include (1) growth form (tree, shrub, herb), (2) seasonality of woody vegetation (deciduous, evergreen), (3) leaf type (broadleaf, coniferous), (4) photosynthetic pathway of nonwoody vegetation (C3, C4), (5) longevity (annual, perennial), and (6) type and intensity of disturbance (e.g., cultivation, fire history). Many of these characteristics can be obtained through remote sensing, though some require ground-based information. The minimum number and the identity of the required land surface characteristics almost certainly vary with the intended objective, but the philosophy of driving models with continuous distributions of a small number of land surface characteristics is likely to be applicable to a broad range of problems.

Changes in land surface water dynamics since the 1990s and relation to population pressure

[1] We developed a remote sensing approach based on multi-satellite observations, which provides an unprecedented estimate of monthly distribution and area of land-surface open water over the whole globe. Results for 1993 to 2007 exhibit a large seasonal and inter-annual variability of the inundation extent with an overall decline in global average maximum inundated area of 6% during the fifteen-year period, primarily in tropical and subtropical South America and South Asia. The largest declines of open water are found where large increases in population have occurred over the last two decades, suggesting a global scale effect of human activities on continental surface freshwater: denser population can impact local hydrology by reducing freshwater extent, by draining marshes and wetlands, and by increasing water withdrawals. Citation: Prigent, C., F. Papa, F. Aires, C. Jimenez, W. B. Rossow, and E. Matthews (2012), Changes in land surface water dynamics since the 1990s and relation to population pressure, Geophys. Res. Lett., 39, L08403, doi:10.1029/2012GL051276.

Global litter production, pools, and turnover times: Estimates from measurement data and regression models

Systematic and compatible databases to quantify composition, distribution, and turnover times of carbon in global litter were developed and evaluated. The study employs an integrated approach, estimating related litter pools and fluxes using a variety of data-based and model-based techniques. The analysis includes direct estimates and indirect, or proxy, estimates of litter production and pools; steady-state turnover times are estimated from the two. Proxies for litter production include net primary productivity and root respiration-soil respiration relationships. In addition to implementing a suite of regression models, >1100 published measurements of litter components, along with site characteristics, were integrated into a baseline data set and used to estimate litter production and pools. Historically, global estimates of litter production have ranged from 75 to 135 Pg dm/yr; several estimates from this study suggest values in the middle of this range, from 90 to 100 Pg dm/yr. The estimate of aboveground litter production from the compiled measurements, 39 Pg dm/yr, includes mainly forest, woodland, and wooded grassland; other grassland, shrubland, and xeromorphic communities that occupy ∼25% of the ice-free land surface are unrepresented in the present compilation. Aboveground litter production may be 5–10 Pg dm/yr higher with the inclusion of these ecosystems, and the total, including belowground production, may approach 90–110 Pg dm/year. Two novel production estimates derived from soil- and root-respiration relationships are 93 Pg and 100 Pg dm/yr. These estimates have the major advantage of accounting for both aboveground and belowground litter; the latter is rarely included and can account for a substantial fraction of total production. Production of coarse woody detritus may add ∼12 Pg dm/yr to the fine litter total. The global litter pool has previously been estimated at ∼100 to 400 Pg dm. The fine litter pool estimated here from the measurement compilation is 136 Pg dm. Although this partial estimate includes ecosystems covering just under half the ice-free land surface, it encompasses forests and woodlands which have the largest pools. Inclusion of the remaining ecosystems may add ∼25 Pg, raising the total to ∼160 Pg dm. An additional ∼150 Pg dm is estimated for the coarse woody detrital pool. Global mean steady state turnover times of litter estimated from the pool and production data range from 1.4 to 3.4 years; mean turnover time from the partial forest/woodland measurement compilation is ∼5 years, and turnover time for coarse woody detritus is ∼13 years. By encompassing spatial distribution, composition, and magnitude, along with numerous field measurements, this integrated approach has begun to yield compositional and ecosystem constraints on modeled global and regional litter fields and NPP allocation schemes in ecosystem models.

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. Passive and active microwave observations are sensitive to overall vegetation structure: they respond to absorption, emission, and scattering by vegetation elements, including woody parts. Backscattering coefficients from ERS-1 are not sensitive to atmospheric variations and exhibit good potential for vegetation discrimination with ∼10 dB dynamic range between rain forest to arid grassland. Passive microwave measurements also show some ability to characterize vegetation but are less sensitive than active measurements. However, passive observations show sensitivity to the underlying surface wetness that enables detection of wetlands even in densely vegetated areas. Merging the data sets using clustering techniques capitalizes on the complementary strengths of the instruments for vegetation discrimination and shows promising potential for land cover characterization on a global basis.

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 one-dimensional, 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 8-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. Two soil classification data sets show good correspondence of sand dunes and the microwave signature of significant penetration. This suggests that this analysis of microwave observations, along with other remote sensing technics, can be used to map the sand dunes in large, poorly surveyed deserts; a map of the sand dune fields in the Sahara and Saudi Arabia is derived from SSM/I observations.