Steve Running

Recent decline in the global land evapotranspiration trend due to limited moisture supply

More than half of the solar energy absorbed by land surfaces is currently used to evaporate water. Climate change is expected to intensify the hydrological cycle and to alter evapotranspiration, with implications for ecosystem services and feedback to regional and global climate. Evapotranspiration changes may already be under way, but direct observational constraints are lacking at the global scale. Until such evidence is available, changes in the water cycle on land—a key diagnostic criterion of the effects of climate change and variability—remain uncertain. Here we provide a data-driven estimate of global land evapotranspiration from 1982 to 2008, compiled using a global monitoring network, meteorological and remote-sensing observations, and a machine-learning algorithm. In addition, we have assessed evapotranspiration variations over the same time period using an ensemble of process-based land-surface models. Our results suggest that global annual evapotranspiration increased on average by 7.1 ± 1.0 millimetres per year per decade from 1982 to 1997. After that, coincident with the last major El Niño event in 1998, the global evapotranspiration increase seems to have ceased until 2008. This change was driven primarily by moisture limitation in the Southern Hemisphere, particularly Africa and Australia. In these regions, microwave satellite observations indicate that soil moisture decreased from 1998 to 2008. Hence, increasing soil-moisture limitations on evapotranspiration largely explain the recent decline of the global land-evapotranspiration trend. Whether the changing behaviour of evapotranspiration is representative of natural climate variability or reflects a more permanent reorganization of the land water cycle is a key question for earth system science.

Developing satellite-derived estimates of surface moisture status

Abstract Recent research has shown that the combination of spectral vegetation indices with thermal infrared observations may provide an effective method for parameterizing surface processes at large spatial scales. In this paper, we explore the remotely sensed surface temperature (Ts)/normalized difference vegetation index (NDVI) relationship regarding a) influence of biome type on the slope of Ts/NDVI, b) automating the definition of the relationship so that the surface moisture status can he compared with Ts/NDVI at continental scales. The analysis was carded out using 1) NOAA Advanced Very High Resolution Radiometer (AVHRR) data over a 300-km × 300-km area in western Montana under various land-use practices (grass, crops, and forests), 2) Earth Resources Observations Systems Data Center continental United States biweekly composite AVHRR data. A strong negative relationship was observed between NDVI and Ts over all biome types. The similarity of the Ts/NDVI relationships over different biomes indicated...

A Global System for Monitoring Ecosystem Service Change

Earths life-support systems are in flux, yet no centralized system to monitor and report these changes exists. Recognizing this, 77 nations agreed to establish the Group on Earth Observations (GEO). The GEO Biodiversity Observation Network (GEO BON) integrates existing data streams into one platform in order to provide a more complete picture of Earths biological and social systems. We present a conceptual framework envisioned by the GEO BON Ecosystem Services Working Group, designed to integrate national statistics, numerical models, remote sensing, and in situ measurements to regularly track changes in ecosystem services across the globe. This information will serve diverse applications, including stimulating new research and providing the basis for assessments. Although many ecosystem services are not currently measured, others are ripe for reporting. We propose a framework that will continue to grow and inspire more complete observation and assessments of our planets life-support systems.

Terrestrial Observation and Prediction System: integration of satellite and surface weather observations with ecosystem models

Satellite data are widely used in land surface models to compute carbon and water exchange processes. However, much of this work is retrospective in nature. To better represent current land surface conditions in weather/climate models or to provide timely information on ecosystem conditions for natural resource management, one must move from retrospective to real-time analysis. A number of advances allow us to develop a system that would allow such real-time assimilation. These include consistent and timely availability of land surface products from EOS/MODIS, and on-line availability of weather data from a number or surface weather stations. We have developed a data assimilation system, terrestrial observation and prediction system, that integrates satellite data, surface weather observations and weather/climate forecasts with a terrestrial ecosystem model. TOPS produces daily 1 km estimates of carbon and water fluxes using MODIS derived LAI, land cover and gridded meteorological data created using more than 2000 surface weather stations over the conterminous U.S. Daily outputs are expressed as anomalies from historical normals that were computed using 20 years (1982-2001) of satellite and surface weather data. TOPS is also capable of using short/mid-term weather/climate forecasts to produce forecasts of land surface conditions (snow pack, runoff, soil moisture and primary production) that are useful in resource management.

Ecohydrologic process modeling of mountain block groundwater recharge.

Regional mountain block recharge (MBR) is a key component of alluvial basin aquifer systems typical of the western United States. Yet neither water scientists nor resource managers have a commonly available and reasonably invoked quantitative method to constrain MBR rates. Recent advances in landscape-scale ecohydrologic process modeling offer the possibility that meteorological data and land surface physical and vegetative conditions can be used to generate estimates of MBR. A water balance was generated for a temperate 24,600-ha mountain watershed, elevation 1565 to 3207 m, using the ecosystem process model Biome-BGC (BioGeochemical Cycles) (Running and Hunt 1993). Input data included remotely sensed landscape information and climate data generated with the Mountain Climate Simulator (MT-CLIM) (Running et al. 1987). Estimated mean annual MBR flux into the crystalline bedrock terrain is 99,000 m(3) /d, or approximately 19% of annual precipitation for the 2003 water year. Controls on MBR predictions include evapotranspiration (radiation limited in wet years and moisture limited in dry years), soil properties, vegetative ecotones (significant at lower elevations), and snowmelt (dominant recharge process). The ecohydrologic model is also used to investigate how climatic and vegetative controls influence recharge dynamics within three elevation zones. The ecohydrologic model proves useful for investigating controls on recharge to mountain blocks as a function of climate and vegetation. Future efforts will need to investigate the uncertainty in the modeled water balance by incorporating an advanced understanding of mountain recharge processes, an ability to simulate those processes at varying scales, and independent approaches to calibrating MBR estimates.

Results from the carbon-land model intercomparison project (C-LAMP) and availability of the data on the earth system grid (ESG)

This paper describes the Carbon-Land Model Intercomparison Project (C-LAMP) being carried out through a collaboration between the Community Climate System Model (CCSM) Biogeochemistry Working Group, a DOE SciDAC-2 project, and the DOE Program for Climate Model Diagnosis and Intercomparison (PCMDI). The goal of the project is to intercompare terrestrial biogeochemistry models running within the CCSM framework to determine the best set of processes to include in future versions of CCSM. As a part of the project, observational datasets are being collected and used to score the scientific performance of these models following a well-defined set of metrics. In addition, metadata standards for terrestrial biosphere models are being developed to support archival and distribution of the C-LAMP model output via the Earth System Grid (ESG). Progress toward completion of this project and preliminary results from the first set of experiments are reported.

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 carbon budget and the interannual variability of regional carbon fluxes.

Seven ages of the PhD

Scientists share memories of doing doctorates in different decades, disciplines and locations, from the hunt for the structure of DNA to deciphering the human genome.

Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data-model comparison

Given the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data-model comparisons.

Effects of Climate and Lifeporm on Dry Matter Yield (E) from Simulations Using Biome-BGC

An ecosystem process simulation model, BIOME-BGC, is used in a sensitivity analysis to determine the factors that may cause the dry matter yield (epsilon) and annual net primary production to vary for different ecosystems. At continental scales, epsilon is strongly correlated with annual precipitation. At a single location, year-to-year variation in net primary production (NPP) and epsilon is correlated with either annual precipitation or minimum air temperatures. Simulations indicate that forests have lower epsilon than grasslands. The most sensitive parameter affecting forest epsilon is the total amount of living woody biomass, which affects NPP by increasing carbon loss by maintenance respiration. A global map of woody biomass should significantly improve estimates of global NPP using remote sensing.