scholarly journals A Functional Response Metric for the Temperature Sensitivity of Tropical Ecosystems

2018 ◽  
Vol 22 (7) ◽  
pp. 1-20 ◽  
Author(s):  
Gretchen Keppel-Aleks ◽  
Samantha J. Basile ◽  
Forrest M. Hoffman
Keyword(s):  
Growth Rate ◽  
Time Scales ◽  
Northern Hemisphere ◽  
Temperature Sensitivity ◽  
Land Surface ◽  
Model Development ◽  
Terrestrial Ecosystems ◽  
Carbon Fluxes ◽  
Hemisphere Winter

Abstract Earth system models (ESMs) simulate a large spread in carbon cycle feedbacks to climate change, particularly in their prediction of cumulative changes in terrestrial carbon storage. Evaluating the performance of ESMs against observations and assessing the likelihood of long-term climate predictions are crucial for model development. Here, we assessed the use of atmospheric growth rate variations to evaluate the sensitivity of tropical ecosystem carbon fluxes to interannual temperature variations. We found that the temperature sensitivity of the observed growth rate depended on the time scales over which atmospheric observations were averaged. The temperature sensitivity of the growth rate during Northern Hemisphere winter is most directly related to the tropical carbon flux sensitivity since winter variations in Northern Hemisphere carbon fluxes are relatively small. This metric can be used to test the fidelity of interactions between the physical climate system and terrestrial ecosystems within ESMs, which is especially important since the short-term relationship between ecosystem fluxes and temperature stress may be related to the long-term feedbacks between ecosystems and climate. If the interannual temperature sensitivity is used to constrain long-term temperature responses, the inferred sensitivity may be biased by 20%, unless the seasonality of the relationship between the observed growth rate and tropical fluxes is taken into account. These results suggest that atmospheric data can be used directly to evaluate regional land fluxes from ESMs, but underscore that the interaction between the time scales for land surface processes and those for atmospheric processes must be considered.

scholarly journals Evaluating the potential of large-scale simulations to predict carbon fluxes of terrestrial ecosystems over a European Eddy Covariance network

2014 ◽  
Vol 11 (10) ◽  
pp. 2661-2678 ◽  
Author(s):  
M. Balzarolo ◽  
S. Boussetta ◽  
G. Balsamo ◽  
A. Beljaars ◽  
F. Maignan ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Land Surface ◽  
Large Scale ◽  
Meteorological Data ◽  
Model Development ◽  
Vapour Pressure Deficit ◽  
Terrestrial Ecosystems ◽  
Carbon Fluxes ◽  
Simulation Performance ◽  
Large Scale Simulations

Abstract. This paper reports a comparison between large-scale simulations of three different land surface models (LSMs), ORCHIDEE, ISBA-A-gs and CTESSEL, forced with the same meteorological data, and compared with the carbon fluxes measured at 32 eddy covariance (EC) flux tower sites in Europe. The results show that the three simulations have the best performance for forest sites and the poorest performance for cropland and grassland sites. In addition, the three simulations have difficulties capturing the seasonality of Mediterranean and sub-tropical biomes, characterized by dry summers. This reduced simulation performance is also reflected in deficiencies in diagnosed light-use efficiency (LUE) and vapour pressure deficit (VPD) dependencies compared to observations. Shortcomings in the forcing data may also play a role. These results indicate that more research is needed on the LUE and VPD functions for Mediterranean and sub-tropical biomes. Finally, this study highlights the importance of correctly representing phenology (i.e. leaf area evolution) and management (i.e. rotation–irrigation for cropland, and grazing–harvesting for grassland) to simulate the carbon dynamics of European ecosystems and the importance of ecosystem-level observations in model development and validation.

The use of multi-tracer flask-measurements to understand changes in the land-surface processes.

2021 ◽  
Author(s):  
Theertha Kariyathan ◽  
Wouter Peters ◽  
Julia Marshall ◽  
Ana Bastos ◽  
Markus Reichstein
Keyword(s):  
Northern Hemisphere ◽  
Land Surface ◽  
Seasonal Cycle ◽  
Growing Season ◽  
Plant Productivity ◽  
Surface Processes ◽  
Terrestrial Biosphere ◽  
Land Surface Processes ◽  
Species Analysis

<p>Carbon dioxide (CO<sub>2</sub>) is an important greenhouse gas, and it accounts for about 20% of the present-day anthropogenic greenhouse effect. Atmospheric CO<sub>2</sub> is cycled between the terrestrial biosphere and the atmosphere through various land-surface processes and thus links the atmosphere and terrestrial biosphere through positive and negative feedback. Since multiple trace gas elements are linked by common biogeochemical processes, multi-species analysis is useful for reinforcing our understanding and can help in partitioning CO<sub>2</sub> fluxes. For example, in the northern hemisphere, CO<sub>2</sub> has a distinct seasonal cycle mainly regulated by plant photosynthesis and respiration and it has a distinct negative correlation with the seasonal cycle of the δ<sup>13</sup>C isotope of CO<sub>2</sub>, due to a stronger isotopic fractionation associated with terrestrial photosynthesis. Therefore, multi-species flask-data measurements are useful for the long-term analysis of various green-house gases. Here we try to infer the complex interaction between the atmosphere and the terrestrial biosphere by multi-species analysis using atmospheric flask measurement data from different NOAA flask measurement sites across the northern hemisphere.</p><p>This study focuses on the long-term changes in the seasonal cycle of CO<sub>2</sub> over the northern hemisphere and tries to attribute the observed changes to driving land-surface processes through a combined analysis of the δ<sup>13</sup>C seasonal cycle. For this we generate metrics of different parameters of the CO<sub>2</sub> and δ<sup>13</sup>C seasonal cycle like the seasonal cycle amplitude given by the peak-to-peak difference of the cycle (indicative of the amount of CO<sub>2</sub> taken up by terrestrial uptake),  the intensity of plant productivity inferred from the slope of the seasonal cycle during the growing season , length of growing season and the start of the growing season. We analyze the inter-relation between these metrics and how they change across latitude and over time. We hypothesize that the CO<sub>2 </sub>seasonal cycle amplitude is controlled both by the intensity of plant productivity and period of the active growing season and that the timing of the growing season can affect the intensity of plant productivity. We then quantify these relationships, including their variation over time and latitudes and describe the effects of an earlier start of the growing season on the intensity of plant productivity and the CO<sub>2</sub> uptake by plants.</p>

scholarly journals Climate Data Records of Vegetation Variables from Geostationary SEVIRI/MSG Data: Products, Algorithms and Applications

2019 ◽  
Vol 11 (18) ◽  
pp. 2103 ◽  
Author(s):  
Francisco Javier García-Haro ◽  
Fernando Camacho ◽  
Beatriz Martínez ◽  
Manuel Campos-Taberner ◽  
Beatriz Fuster ◽  
...  
Keyword(s):  
Land Surface ◽  
Expert Knowledge ◽  
Terrestrial Ecosystems ◽  
Environmental Applications ◽  
Climate Data ◽  
Area Index ◽  
Infrared Imager ◽  
Statistical Relationships ◽  
Spectral Mixture

The scientific community requires long-term data records with well-characterized uncertainty and suitable for modeling terrestrial ecosystems and energy cycles at regional and global scales. This paper presents the methodology currently developed in EUMETSAT within its Satellite Application Facility for Land Surface Analysis (LSA SAF) to generate biophysical variables from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board MSG 1-4 (Meteosat 8-11) geostationary satellites. Using this methodology, the LSA SAF generates and disseminates at a time a suite of vegetation products, such as the leaf area index (LAI), the fraction of the photosynthetically active radiation absorbed by vegetation (FAPAR) and the fractional vegetation cover (FVC), for the whole Meteosat disk at two temporal frequencies, daily and 10-days. The FVC algorithm relies on a novel stochastic spectral mixture model which addresses the variability of soils and vegetation types using statistical distributions whereas the LAI and FAPAR algorithms use statistical relationships general enough for global applications. An overview of the LSA SAF SEVIRI/MSG vegetation products, including expert knowledge and quality assessment of its internal consistency is provided. The climate data record (CDR) is freely available in the LSA SAF, offering more than fifteen years (2004-present) of homogeneous time series required for climate and environmental applications. The high frequency and good temporal continuity of SEVIRI products addresses the needs of near-real-time users and are also suitable for long-term monitoring of land surface variables. The study also evaluates the potential of the SEVIRI/MSG vegetation products for environmental applications, spanning from accurate monitoring of vegetation cycles to resolving long-term changes of vegetation.

Phenology-induced energy and carbon fluxes in land surface models

2020 ◽  
Author(s):  
Jan De Pue ◽  
José Miguel Barrios ◽  
Fabienne Maignan ◽  
Liyang Liu ◽  
Philippe Ciais ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Terrestrial Ecosystems ◽  
Carbon Fluxes ◽  
Land Surface Models ◽  
Energy Fluxes ◽  
Wide Range ◽  
Surface Models ◽  
Modelling Strategies ◽  
Phenological Cycle

<p>The annual phenological cycle is of key importance for the carbon and energy fluxes in terrestrial ecosystems. Although the processes controlling budburst and leaf senescence are fairly well known, the connection between plant phenology and the carbon fluxes remains a challenging aspect in land surface modelling (LSM). In this study, the modelling strategies of three well stablished LSM are compared. The LSM considered in this study were: ORCHIDEE, ISBA-A-gs and the model driving the LSA-SAF evapotranspiration product (https://landsaf.ipma.pt). The latter model does not simulate the carbon fluxes but focuses on the computation of evapotranspiration and energy fluxes.<br>The phenological cycle is simulated explicitly in the ORCHIDEE model, using empirical relations based on temperature sum, water availability, and other variables. In the ISBA-A-gs model, phenology and LAI development is fully photosynthesis-driven. The phenology in the LSA-SAF model is driven by remote sensing forcing variables, such as LAI observations. Alternatively, the assimilation of remote sensing LAI products is a convenient method to improve the simulated phenological cycle in land surface models. A dedicated module for this operation is available in ISBA-A-gs.<br>Simulations were performed over a wide range of climatological conditions and plant functional types. The results were then validated with in-situ measurements conducted at Fluxnet stations. In addition to the comparison between measured and modelled carbon fluxes, the validation in this study included the intra-annual variation in the simulated phenological cycle.</p>

A LONG TERM FIELD EXPERIMENT FOR RADIATIVE TRANSFER MODEL DEVELOPMENT AND LAND SURFACE PROCESSES REMOTE SENSING

2008 ◽  
Vol 52 ◽  
pp. 13-18
Author(s):  
Hui LU ◽  
Toshio KOIKE ◽  
Hiroyuki TSUTSUI ◽  
David Ndegwa KURIA ◽  
Tobias GRAF ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Field Experiment ◽  
Land Surface ◽  
Model Development ◽  
Surface Processes ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Term Field

scholarly journals Analysis and Reduction of Systematic Errors through a Seamless Approach to Modeling Weather and Climate

2010 ◽  
Vol 23 (22) ◽  
pp. 5933-5957 ◽  
Author(s):  
G. M. Martin ◽  
S. F. Milton ◽  
C. A. Senior ◽  
M. E. Brooks ◽  
S. Ineson ◽  
...  
Keyword(s):  
Time Scales ◽  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
Spatial Scales ◽  
Full Range ◽  
Model Development ◽  
Model Performance ◽  
Systematic Errors ◽  
Wide Range

Abstract The reduction of systematic errors is a continuing challenge for model development. Feedbacks and compensating errors in climate models often make finding the source of a systematic error difficult. In this paper, it is shown how model development can benefit from the use of the same model across a range of temporal and spatial scales. Two particular systematic errors are examined: tropical circulation and precipitation distribution, and summer land surface temperature and moisture biases over Northern Hemisphere continental regions. Each of these errors affects the model performance on time scales ranging from a few days to several decades. In both cases, the characteristics of the long-time-scale errors are found to develop during the first few days of simulation, before any large-scale feedbacks have taken place. The ability to compare the model diagnostics from the first few days of a forecast, initialized from a realistic atmospheric state, directly with observations has allowed physical deficiencies in the physical parameterizations to be identified that, when corrected, lead to improvements across the full range of time scales. This study highlights the benefits of a seamless prediction system across a wide range of time scales.

scholarly journals Validation of Noah-Simulated Soil Temperature in the North American Land Data Assimilation System Phase 2

2013 ◽  
Vol 52 (2) ◽  
pp. 455-471 ◽  
Author(s):  
Youlong Xia ◽  
Michael Ek ◽  
Justin Sheffield ◽  
Ben Livneh ◽  
Maoyi Huang ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Time Scales ◽  
Land Surface ◽  
Phase 2 ◽  
Soil Layers ◽  
The North ◽  
Weather And Climate ◽  
Soil Temperatures ◽  
Land Data Assimilation

AbstractSoil temperature can exhibit considerable memory from weather and climate signals and is among the most important initial conditions in numerical weather and climate models. Consequently, a more accurate long-term land surface soil temperature dataset is needed to improve weather and climate simulation and prediction, and is also important for the simulation of agricultural crop yield and ecological processes. The North American Land Data Assimilation phase 2 (NLDAS-2) has generated 31 years (1979–2009) of simulated hourly soil temperature data with a spatial resolution of ⅛°. This dataset has not been comprehensively evaluated to date. Thus, the purpose of this paper is to assess Noah-simulated soil temperature for different soil depths and time scales. The authors used long-term (1979–2001) observed monthly mean soil temperatures from 137 cooperative stations over the United States to evaluate simulated soil temperature for three soil layers (0–10, 10–40, and 40–100 cm) for annual and monthly time scales. Short-term (1997–99) observed soil temperatures from 72 Oklahoma Mesonet stations were used to validate simulated soil temperatures for three soil layers and for daily and hourly time scales. The results showed that the Noah land surface model generally matches observed soil temperature well for different soil layers and time scales. At greater depths, the simulation skill (anomaly correlation) decreased for all time scales. The monthly mean diurnal cycle difference between simulated and observed soil temperature revealed large midnight biases in the cold season that are due to small downward longwave radiation and issues related to model parameters.

scholarly journals Global Meteorological Drought: A Synthesis of Current Understanding with a Focus on SST Drivers of Precipitation Deficits

2016 ◽  
Vol 29 (11) ◽  
pp. 3989-4019 ◽  
Author(s):  
Siegfried D. Schubert ◽  
Ronald E. Stewart ◽  
Hailan Wang ◽  
Mathew Barlow ◽  
Ernesto H. Berbery ◽  
...  
Keyword(s):  
Time Scales ◽  
Land Surface ◽  
General Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
Meteorological Drought ◽  
Current Understanding ◽  
Northern Eurasia ◽  
Eastern Canada

Abstract Drought affects virtually every region of the world, and potential shifts in its character in a changing climate are a major concern. This article presents a synthesis of current understanding of meteorological drought, with a focus on the large-scale controls on precipitation afforded by sea surface temperature (SST) anomalies, land surface feedbacks, and radiative forcings. The synthesis is primarily based on regionally focused articles submitted to the Global Drought Information System (GDIS) collection together with new results from a suite of atmospheric general circulation model experiments intended to integrate those studies into a coherent view of drought worldwide. On interannual time scales, the preeminence of ENSO as a driver of meteorological drought throughout much of the Americas, eastern Asia, Australia, and the Maritime Continent is now well established, whereas in other regions (e.g., Europe, Africa, and India), the response to ENSO is more ephemeral or nonexistent. Northern Eurasia, central Europe, and central and eastern Canada stand out as regions with few SST-forced impacts on precipitation on interannual time scales. Decadal changes in SST appear to be a major factor in the occurrence of long-term drought, as highlighted by apparent impacts on precipitation of the late 1990s “climate shifts” in the Pacific and Atlantic SST. Key remaining research challenges include (i) better quantification of unforced and forced atmospheric variability as well as land–atmosphere feedbacks, (ii) better understanding of the physical basis for the leading modes of climate variability and their predictability, and (iii) quantification of the relative contributions of internal decadal SST variability and forced climate change to long-term drought.

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