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R. D. Koster, G. K. Walker, G. J. Collatz, and P. E. Thornton

Abstract

Long-term, global offline (land only) simulations with a dynamic vegetation phenology model are used to examine the control of hydroclimate over vegetation-related quantities. First, with a control simulation, the model is shown to capture successfully (though with some bias) key observed relationships between hydroclimate and the spatial and temporal variations of phenological expression. In subsequent simulations, the model shows that (i) the global spatial variation of seasonal phenological maxima is controlled mostly by hydroclimate, irrespective of distributions in vegetation type; (ii) the occurrence of high interannual moisture-related phenological variability in grassland areas is determined by hydroclimate rather than by the specific properties of grassland; and (iii) hydroclimatic means and variability have a corresponding impact on the spatial and temporal distributions of gross primary productivity (GPP).

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Sietse O. Los, G. James Collatz, Lahouari Bounoua, Piers J. Sellers, and Compton J. Tucker

Abstract

Anomalies in global vegetation greenness, SST, land surface air temperature, and precipitation exhibit linked, low-frequency interannual variations. These interannual variations were detected and analyzed for 1982–90 with a multivariate spectral method. The two most dominant signals for 1982–90 had periods of about 2.6 and 3.4 yr. Signals centered at 2.6 years per cycle corresponded to variations in the El Niño–Southern Oscillation index and explained about 28% of the variance in anomalies of SST, land surface air temperature, precipitation, and vegetation; these signals were most pronounced in 1) SST anomalies in the eastern equatorial Pacific Ocean, 2) land surface vegetation and precipitation anomalies in tropical and subtropical regions, and 3) land surface vegetation, precipitation, and temperature anomalies in North America. Signals at 3.4 years per cycle corresponded to variations in the North Atlantic oscillation index and explained 8.6% of the variance in the combined datasets; their occurrence was most pronounced in 1) Atlantic SST anomalies, 2) in land surface temperature and vegetation anomalies in Europe and eastern Asia, and 3) in precipitation and vegetation anomalies in sub-Saharan Africa, southern Africa, and eastern North America. Anomalies in vegetation were positively related to anomalies in precipitation throughout the Tropics and subtropics and in midlatitudes in the central parts of continents. Anomalies in vegetation and temperature were positively linked in coastal temperate climates such as in Europe and eastern Asia. These associations between temperature and vegetation may be explained by the sensitivity of the length of growing season to variations in temperature.

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L. Bounoua, G. J. Collatz, S. O. Los, P. J. Sellers, D. A. Dazlich, C. J. Tucker, and D. A. Randall

Abstract

The sensitivity of global and regional climate to changes in vegetation density is investigated using a coupled biosphere–atmosphere model. The magnitude of the vegetation changes and their spatial distribution are based on natural decadal variability of the normalized difference vegetation index (NDVI). Different scenarios using maximum and minimum vegetation cover were derived from satellite records spanning the period 1982–90.

Albedo decreased in the northern latitudes and increased in the Tropics with increased NDVI. The increase in vegetation density revealed that the vegetation’s physiological response was constrained by the limits of the available water resources. The difference between the maximum and minimum vegetation scenarios resulted in a 46% increase in absorbed visible solar radiation and a similar increase in gross photosynthetic CO2 uptake on a global annual basis. This increase caused the canopy transpiration and interception fluxes to increase and reduced those from the soil. The redistribution of the surface energy fluxes substantially reduced the Bowen ratio during the growing season, resulting in cooler and moister near-surface climate, except when soil moisture was limiting.

Important effects of increased vegetation on climate are

  • a cooling of about 1.8 K in the northern latitudes during the growing season and a slight warming during the winter, which is primarily due to the masking of high albedo of snow by a denser canopy; and

  • a year-round cooling of 0.8 K in the Tropics.

These results suggest that increases in vegetation density could partially compensate for parallel increases in greenhouse warming. Increasing vegetation density globally caused both evapotranspiration and precipitation to increase. Evapotranspiration, however, increased more than precipitation, resulting in a global soil-water deficit of about 15%. A spectral analysis on the simulated results showed that changes in the state of vegetation could affect the low-frequency modes of the precipitation distribution and might reduce its low-frequency variability in the Tropics while increasing it in northern latitudes.

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P. Guillevic, R. D. Koster, M. J. Suarez, L. Bounoua, G. J. Collatz, S. O. Los, and S. P. P. Mahanama

Abstract

The degree to which the interannual variability of vegetation phenology affects hydrological fluxes over land is investigated through a series of simulations with the Mosaic land surface model, run both offline and coupled to the NASA Seasonal-to-Interannual Prediction Project (NSIPP) atmospheric general circulation model (GCM). Over a 9-yr period, from 1982 to 1990, interannual variations of global biophysical land surface parameters (i.e., vegetation density and greenness fraction) are derived from Normalized Difference Vegetation Index (NDVI) data collected by the Advanced Very High Resolution Radiometers (AVHRRs). First the sensitivity of evapotranspiration to interannual variations in vegetation properties is evaluated through offline simulations that ignore feedbacks between the land surface and the atmospheric models, and interannual precipitation variations. Evapotranspiration is shown to be highly sensitive to variations in vegetation over wet continental surfaces that are not densely vegetated. The sensitivity is reduced by a saturation effect over dense vegetation covers and physiological control due to environmental stress over arid and semiarid regions.

Correlations between evapotranspiration and vegetation anomalies are reduced markedly in offline runs that impose interannual variations in both vegetation and precipitation. They are also strongly reduced in the coupled simulations. Although interannual variations in vegetation properties still influence transpiration and interception loss at the global scale in these runs, their impact on large-scale regional climate is much weaker, apparently because the impact is drowned out by atmospheric variability.

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P.J. Sellers, D.A. Randall, G.J. Collatz, J.A. Berry, C.B. Field, D.A. Dazlich, C. Zhang, G.D. Collelo, and L. Bounoua

Abstract

The formulation of a revised land surface parameterization for use within atmospheric general circulation models (GCMs) is presented. The model (SiB2) incorporates several significant improvements over the first version of the Simple Biosphere model (SiB) described in Sellers et al. The improvements can be summarized as follows:

(i) incorporation of a realistic canopy photosynthesis–conductance model to describe the simultaneous transfer of CO2 and water vapor into and out of the vegetation, respectively;

(ii) use of satellite data, as described in a companion paper, Part II, to describe the vegetation phonology;

(iii) modification of the hydrological submodel to give better descriptions of baseflows and a more reliable calculation of interlayer exchanges within the soil profile;

(iv) incorporation of a “patchy” snowmelt treatment, which prevents rapid thermal and surface reflectance transitions when the area-averaged snow cover is low and decreasing.

To accommodate the changes in (i) and (ii) above, the original two-layer vegetation canopy structure of SiB2 has been reduced to a single layer in SiB2. The use of satellite data in SiB2 and the performance of SiB2 when coupled to a GCM are described in the two companion papers, Part II and III.

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Piers J. Sellers, Compton J. Tucker, G. James Collatz, Sietse O. Los, Christopher O. Justice, Donald A. Dazlich, and David A. Randall

Abstract

The global parameter fields used in the revised Simple Biosphere Model (SiB2) of Sellers et al. are reviewed. The most important innovation over the earlier SiB1 parameter set of Dorman and Sellers is the use of satellite data to specify the time-varying phonological properties of FPAR, leaf area index. and canopy greenness fraction. This was done by processing a monthly 1° by 1° normalized difference vegetation index (NDVI) dataset obtained farm Advanced Very High Resolution Radiometer red and near-infrared data. Corrections were applied to the source NDVI dataset to account for (i) obvious anomalies in the data time series, (ii) the effect of variations in solar zenith angle, (iii) data dropouts in cold regions where a temperature threshold procedure designed to screen for clouds also eliminated cold land surface points, and (iv) persistent cloud cover in the Tropics. An outline of the procedures for calculating the land surface parameters from the corrected NDVI dataset is given, and a brief description is provided of source material, mainly derived from in situ observations, that was used in addition to the NDVI data. The datasets summarized in this paper should he superior to prescriptions currently used in most land surface parameterizations in that the spatial and temporal dynamics of key land surface parameters, in particular those related to vegetation, are obtained directly from a consistent set of global-scale observations instead of being inferred from a variety of survey-based land-cover classifications.

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L. Bounoua, G. J. Collatz, P. J. Sellers, D. A. Randall, D. A. Dazlich, S. O. Los, J. A. Berry, I. Fung, C. J. Tucker, C. B. Field, and T. G. Jensen

Abstract

The radiative and physiological effects of doubled atmospheric carbon dioxide (CO2) on climate are investigated using a coupled biosphere–atmosphere model. Five 30-yr climate simulations, designed to assess the radiative and physiological effects of doubled CO2, were compared to a 30-yr control run.

When the CO2 concentration was doubled for the vegetation physiological calculations only assuming no changes in vegetation biochemistry, the mean temperature increase over land was rather small (0.3 K) and was associated with a slight decrease in precipitation (−0.3%). In a second case, the vegetation was assumed to have adapted its biochemistry to a doubled CO2 (2 × CO2) atmosphere and this down regulation caused a 35% decrease in stomatal conductance and a 0.7-K increase in land surface temperature. The response of the terrestrial biosphere to radiative forcing alone—that is, a conventional greenhouse warming effect—revealed important interactions between the climate and the vegetation. Although the global mean photosynthesis exhibited no change, a slight stimulation was observed in the tropical regions, whereas in the northern latitudes photosynthesis and canopy conductance decreased as a result of high temperature stress during the growing season. This was associated with a temperature increase of more than 2 K greater in the northern latitudes than in the Tropics (4.0 K vs 1.7 K). These interactions also resulted in an asymmetry in the diurnal temperature cycle, especially in the Tropics where the nighttime temperature increase due to radiative forcing was about twice that of the daytime, an effect not discernible in the daily mean temperatures. The radiative forcing resulted in a mean temperature increase over land of 2.6 K and 7% increase in precipitation with the least effect in the Tropics. As the physiological effects were imposed along with the radiative effects, the overall temperature increase over land was 2.7 K but with a smaller difference (0.7 K) between the northern latitudes and the Tropics. The radiative forcing resulted in an increase in available energy at the earth’s surface and, in the absence of physiological effects, the evapotranspiration increased. However, changes in the physiological control of evapotranspiration due to increased CO2 largely compensated for the radiative effects and reduced the evapotranspiration approximately to its control value.

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P. J. Sellers, B. W. Meeson, J. Closs, J. Collatz, F. Corprew, D. Dazlich, F. G. Hall, Y. Kerr, R. Koster, S. Los, K. Mitchell, J. McManus, D. Myers, K.-J. Sun, and P. Try

A comprehensive series of global datasets for land-atmosphere models has been collected, formatted to a common grid, and released on a set of CD-ROMs. This paper describes the motivation for and the contents of the dataset.

In June of 1992, an interdisciplinary earth science workshop was convened in Columbia, Maryland, to assess progress in land-atmosphere research, specifically in the areas of models, satellite data algorithms, and field experiments. At the workshop, representatives of the land-atmosphere modeling community defined a need for global datasets to prescribe boundary conditions, initialize state variables, and provide near-surface meteorological and radiative forcings for their models. The International Satellite Land Surface Climatology Project (ISLSCP), a part of the Global Energy and Water Cycle Experiment, worked with the Distributed Active Archive Center of the National Aeronautics and Space Administration Goddard Space Flight Center to bring the required datasets together in a usable format. The data have since been released on a collection of CD-ROMs.

The datasets on the CD-ROMs are grouped under the following headings: vegetation; hydrology and soils; snow, ice, and oceans; radiation and clouds; and near-surface meteorology. All datasets cover the period 1987–88, and all but a few are spatially continuous over the earth's land surface. All have been mapped to a common 1° × 1° equal-angle grid. The temporal frequency for most of the datasets is monthly. A few of the near-surface meteorological parameters are available both as six-hourly values and as monthly means.

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D.A. Randall, D.A. Dazlich, C. Zhang, A.S. Denning, P.J. Sellers, C.J. Tucker, L. Bounoua, J.A. Berry, G.J. Collatz, C.B. Field, S.O. Los, C.O. Justice, and I. Fung

Abstract

SiB2, the second-generation land-surface parameterization developed by Sellers et al., has been incorporated into the Colorado State University general circulation model and tested in multidecade simulation. The control run uses a “bucket” hydrology but employs the same surface albedo and surface roughness distributions as the SiB2 run.

Results show that SiB2 leads to a general warming of the continents, as evidenced in the ground temperature, surface air temperature, and boundary-layer-mean potential temperature. The surface sensible heat flux increases and the latent heat flux decreases. This warming occurs virtually everywhere but is most spectacular over Siberia in winter.

Precipitation generally decreases over land but increases in the monsoon regions, especially the Amazon basin in January and equatorial Africa and Southeast Asia in July. Evaporation decreases considerably, especially in dry regions such as the Sahara. The excess of precipitation over evaporation increases in the monsoon regions.

The precipitable water (vertically integrated water vapor content) generally decreases over land but increases in the monsoon regions. The mixing ratio of the boundary-layer air decreases over newly all continental areas, however, including the monsoon regions. The average (composite) maximum boundary-layer depth over the diurnal cycle increases in the monsoon regions, as does the average PBL turbulence kinetic energy. The average boundary-layer wind speed also increases over most continental regions.

Groundwater content generally increases in rainy regions and decreases in dry regions, so that SiB2 has a tendency to increase its spatial variability. SiB2 leas to a general reduction of cloudiness over land. The net surface longwave cooling of the surface increases quite dramatically over land, in accordance with the increased surface temperatures and decreased cloudiness. The solar radiation absorbed at the ground also increases.

SiB2 has modest effects on the simulated general circulation of the atmosphere. Its most important impacts on the model are to improve the simulations of surface temperature and snow cover and to enable the simulation of the net rate of terrestrial carbon assimilation

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S. O. Los, N. H. Pollack, M. T. Parris, G. J. Collatz, C. J. Tucker, P. J. Sellers, C. M. Malmström, R. S. DeFries, L. Bounoua, and D. A. Dazlich

Abstract

Global, monthly, 1° by 1° biophysical land surface datasets for 1982–90 were derived from data collected by the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA-7, -9, and -11 satellites. The AVHRR data are adjusted for sensor degradation, volcanic aerosol effects, cloud contamination, short-term atmospheric effects (e.g., water vapor and aerosol effects ⩽2 months), solar zenith angle variations, and missing data. Interannual variation in the data is more realistic as a result. The following biophysical parameters are estimated: fraction of photosynthetically active radiation absorbed by vegetation, vegetation cover fraction, leaf area index, and fraction of green leaves. Biophysical retrieval algorithms are tested and updated with data from intensive remote sensing experiments. The multiyear vegetation datasets are consistent spatially and temporally and are useful for studying spatial, seasonal, and interannual variability in the biosphere related to the hydrological cycle, the energy balance, and biogeochemical cycles. The biophysical data are distributed via the Internet by the Goddard Distributed Active Archive Center as a precursor to the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II. Release of more extensive, higher-resolution datasets (0.25° by 0.25°) over longer time periods (1982–97/98) is planned for ISLSCP Initiative II.

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