Fraction Of Absorbed Photosynthetically Active Radiation Research Articles

Intercomparison and quality assessment of MERIS, MODIS and SEVIRI FAPAR products over the Iberian Peninsula

The fraction of absorbed photosynthetically active radiation (FAPAR) is a key variable in productivity and carbon cycle models. The variety of available FAPAR satellite products from different space agencies leads to the necessity of assessing the existing differences between them before using into models. Discrepancies of four FAPAR products derived from MODIS, SEVIRI and MERIS (TOAVEG and MGVI algorithms), covering the Iberian Peninsula from July 2006 to June 2007 are here analyzed. The assessment is based on an intercomparison involving the spatial and temporal consistency between products and a statistical analysis across land cover types. In general, significant differences are found over the Iberian Peninsula concentrated on the temporal variation and absolute values. The MODIS and MERIS/MGVI FAPAR products clearly show the highest and lowest absolute values, respectively, along with the lowest intra-annual variation. When considering individual land cover types, the largest FAPAR disagreements among the analyzed products were found between MODIS-MERI/MGVI and MERIS/TOAVEG-MERIS/MGVI over broadleaf and needleaf forests, with discrepancies quantified by RMSE higher than 0.30 and absolute bias higher than 0.25. These discrepancies can lead to relative gross primary production differences up to 65%.

Consistent assimilation of MERIS FAPAR and atmospheric CO<sub>2</sub> into a terrestrial vegetation model and interactive mission benefit analysis

Abstract. The terrestrial biosphere is currently a strong sink for anthropogenic CO2 emissions. Through the radiative properties of CO2, the strength of this sink has a direct influence on the radiative budget of the global climate system. The accurate assessment of this sink and its evolution under a changing climate is, hence, paramount for any efficient management strategies of the terrestrial carbon sink to avoid dangerous climate change. Unfortunately, simulations of carbon and water fluxes with terrestrial biosphere models exhibit large uncertainties. A considerable fraction of this uncertainty reflects uncertainty in the parameter values of the process formulations within the models. This paper describes the systematic calibration of the process parameters of a terrestrial biosphere model against two observational data streams: remotely sensed FAPAR (fraction of absorbed photosynthetically active radiation) provided by the MERIS (ESA's Medium Resolution Imaging Spectrometer) sensor and in situ measurements of atmospheric CO2 provided by the GLOBALVIEW flask sampling network. We use the Carbon Cycle Data Assimilation System (CCDAS) to systematically calibrate some 70 parameters of the terrestrial BETHY (Biosphere Energy Transfer Hydrology) model. The simultaneous assimilation of all observations provides parameter estimates and uncertainty ranges that are consistent with the observational information. In a subsequent step these parameter uncertainties are propagated through the model to uncertainty ranges for predicted carbon fluxes. We demonstrate the consistent assimilation at global scale, where the global MERIS FAPAR product and atmospheric CO2 are used simultaneously. The assimilation improves the match to independent observations. We quantify how MERIS data improve the accuracy of the current and future (net and gross) carbon flux estimates (within and beyond the assimilation period). We further demonstrate the use of an interactive mission benefit analysis tool built around CCDAS to support the design of future space missions. We find that, for long-term averages, the benefit of FAPAR data is most pronounced for hydrological quantities, and moderate for quantities related to carbon fluxes from ecosystems. The benefit for hydrological quantities is highest for semi-arid tropical or sub-tropical regions. Length of mission or sensor resolution is of minor importance.

Characteristics and drivers of global NDVI‐based FPAR from 1982 to 2006

Fraction of Absorbed Photosynthetically Active Radiation (FPAR) is a state parameter in most ecosystem productivity models and is also the key terrestrial product. In this study, Normalized Difference Vegetation Index (NDVI) from Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) was used to estimate FPAR from 1982 to 2006, using an intermediate model. Our research focused on the analysis of long‐term global FPAR interannual trend patterns and driving forces involving climate and land cover changes. Results showed that interannual trend and spatial distribution patterns of global FPAR were independent of the changes in AVHRR instruments, and differed by season dynamics and vegetation types. Compared with other seasons, the period during JJA (June–August) exhibited more areas with decreasing FPAR and greater reduction range. For FPAR interannual trend, a wholly different correlation pattern was observed between temperature and precipitation, especially for arid and semi‐arid regions. A significant influence of extreme droughts such as those associated with El Nino/Southern Oscillation (ENSO) on FPAR variability was found. The result also revealed the increasing and decreasing interannual trend of FPAR corresponding to the afforestation in the Three North Shelterbelts Program in China and deforestation in tropical forests in Southeast Asia. Driving factor analysis indicated that the climate and land cover changes had an interactive effect on the FPAR annual anomalous variation.

Comparing spatiotemporal patterns in Eurasian FPAR derived from two NDVI-based methods

A long-term, consistent Fraction of Absorbed Photosynthetically Active Radiation (FPAR) product is necessary to study the spatial and temporal patterns of vegetation dynamics associated with climatic changes and human activities. In this study, Eurasia was selected as the study area. The relationship between FPAR and simple infrared/red ratio relationship (SR FPAR), and that between Moderate Resolution Imaging Spectroradiometer (MODIS) FPAR and a Normalised Difference Vegetation Index (NDVI) look-up table (LUT FPAR) were employed to estimate FPAR from 1982 to 2006 by different land cover types, focusing on the comparisons of spatiotemporal FPAR patterns between the two FPAR datasets. The results showed high agreement between MODIS standard FPAR and estimated FPAR in seasonal dynamics with peak values in July. The LUT FPAR was close to MODIS standard FPAR and larger than SR FPAR. The SR and LUT FPAR showed the same spatial distribution and inter-annual variation patterns and were primarily determined by land cover types. An overall increasing trend in FPAR was observed from 1982 to 2006, with reductions from 1991 to 1994 and 2000 to 2002. The inter-annual dynamics in evergreen broadleaf forests showed a decreasing trend over 25 years, while non-forest vegetation FPAR values had slow, stable growth in inter-annual variation.

基于遥感的光合有效辐射吸收比率(FPAR) 估算方法综述

Fraction of Absorbed Photosynthetically Active Radiation(FPAR) is an important biophysical factor for monitoring vegetation growth,as well as a critical parameter in the terrestrial ecosystem modeling and a key indicator for studying global climate change.Remote sensing technology has been proved to be an effective tool in estimating FPAR at regional and global scales,because satellite data can provide a spatially and periodic,comprehensive view of vegetation growing status.Many methods have been developed in estimating FPAR with remote sensing,which can be generally grouped into two categories.The first category of approaches are the empirical statistics models based on the relationships between vegetation indices,derived from reflectance at canopy level,and FPAR.These models are easy to use with high efficiency and much more suitable for detecting within-field spatial variability,yet they may lead to inaccurate results when applied over another place or broad scale with different land cover types.Another category of approaches for FPAR retrieval are to invert canopy reflectance models based on the BRDF(Bi-Directional Reflectance Distribution Functions) models such as the radiative transfer model and geometrical optics model,which describe the transfer and interaction of radiation inside the canopy based on physical mechanism between FPAR and vegetation canopy reflectance.These models have strong applicability and are taken as the algorithm bases among most widely used FPAR products.However,the inversion process is ill-posed due to the complexity of these physical models;the parameters and prior knowledge required by these models are hard to acquire over large areas.At the same time,other methods such as the method based on the concept of effective FPAR,which is FPAR absorbed by chlorophyll,and the method based on the airbome lidar data which is useful to characterize spatial variability of canopy structure,bring significant improvement to the two categories of methods.Due to the complexity of FPAR itself and its influencing factors,as well as the quality of remote sensing data,plenty of uncertainties existed in satellite based FPAR estimation.For statistical model,most vegetation indices are easily affected by soil background,saturation problem,atmospheric condition,and so on.These factors bring much uncertainty in the relationship between FPAR and vegetation indices.For physical models,problems including top-of-atmosphere radiance uncertainties and errors in land cover mapping are hard or even impossible to avoid.In order to deal with these uncertainties and meet the requirements of further research for terrestrial ecological process,future research focuses on FRAR retrieval based on satellite will be: further research on theoretical mechanism of FPAR estimation,seeking to minimize noise effects on vegetation indices for more accurate estimation of FPAR,improvement of the inversion methods for physically-bases models,acquisition and accumulation of prior knowledge in FPAR estimation based on systematic observation network,construction of long-term FPAR dataset based on multi-source remote sensing data,and algorithm for deriving FPAR with both high spatial and high temporal resolutions.

Estimativa da radiação fotossinteticamente ativa absorvida pela cultura da soja através de dados do sensor Modis

O objetivo deste trabalho foi testar um método de geração de informações da distribuição espacial e temporal da radiação fotossinteticamente ativa absorvida (RFAa), pela cultura da soja, a partir da quantificação da relação entre o índice de vegetação por diferença normalizada (NDVI) e a fração da radiação fotossinteticamente ativa absorvida (FRFAa) pela cultura. O estudo abrangeu o município de Cruz Alta, um dos grandes produtores de soja do Rio Grande do Sul, durante duas safras: 2008/2009 e 2009/2010. Os dados de radiação fotossinteticamente ativa incidente (RFAi) foram monitorados em área experimental e os dados orbitais, provenientes de duas plataformas: Landsat/TM e Terra/MODIS, ambos com distribuição gratuita, mas com características distintas. Foi estabelecida uma relação linear simples entre o NDVI das imagens MODIS e a FRFAa obtida em dois períodos importantes do ciclo, semeadura e máximo desenvolvimento das plantas. Pelos resultados, observou-se que existe associação entre o NDVI e FRFAa, a qual pode, portanto, ser usada na geração de informações da RFAa pela cultura da soja ao longo do ciclo de desenvolvimento, permitindo, assim, um monitoramento temporal deste elemento.

Evaluation of a Global Vegetation Model using time series of satellite vegetation indices

Abstract. Atmospheric CO2 drives most of the greenhouse effect increase. One major uncertainty on the future rate of increase of CO2 in the atmosphere is the impact of the anticipated climate change on the vegetation. Dynamic Global Vegetation Models (DGVM) are used to address this question. ORCHIDEE is such a DGVM that has proven useful for climate change studies. However, there is no objective and methodological way to accurately assess each new available version on the global scale. In this paper, we submit a methodological evaluation of ORCHIDEE by correlating satellite-derived Vegetation Index time series against those of the modeled Fraction of absorbed Photosynthetically Active Radiation (FPAR). A perfect correlation between the two is not expected, however an improvement of the model should lead to an increase of the overall performance. We detail two case studies in which model improvements are demonstrated, using our methodology. In the first one, a new phenology version in ORCHIDEE is shown to bring a significant impact on the simulated annual cycles, in particular for C3 Grasses and C3 Crops. In the second case study, we compare the simulations when using two different weather fields to drive ORCHIDEE. The ERA-Interim forcing leads to a better description of the FPAR interannual anomalies than the simulation forced by a mixed CRU-NCEP dataset. This work shows that long time series of satellite observations, despite their uncertainties, can identify weaknesses in global vegetation models, a necessary first step to improving them.

Monitoring carbon assimilation in South America's tropical forests: Model specification and application to the Amazonian droughts of 2005 and 2010

Net primary production (NPP) is a key variable for monitoring and understanding the impacts of environmental change on ecosystems and for generating realistic global and regional carbon budgets. In this paper we present a regional algorithm (RATE) for automatically monitoring the rate of carbon fixation (as measured by NPP) of tropical forests in South America. The algorithm is based on a modification of the SITE ecosystem model and uses data obtained from the procedures for aggregation and correction of data from the MOD12Q1 and MOD15A2 products and meteorological data from the National Centers for Environmental Prediction (NCEP). A correction procedure for the MOD15A2 Leaf area index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) used by the RATE algorithm produced satisfactory LAI and FAPAR estimates when compared against observed values. The algorithm was successfully validated in eight field sites from two types of tropical forests in South America (Amazon rainforest and the Atlantic forest), producing an average error of only 4.72%. When applied to Amazonia, RATE indicates that NPP showed little variation in the 2005 and 2010 drought years (NPP = 1.28 kg-C m − 2 year − 1 ) in comparison to non-drought years (NPP = 1.31 kg-C m − 2 year − 1 ). RATE also provides some limited evidence for small decreasing trends in Amazonia carbon assimilation during the period 2001–2010.

Seasonal dynamic pattern analysis on global FPAR derived from AVHRR GIMMS NDVI

The purpose of this paper is to develop Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modelling and Mapping Studies (GIMMS) Normalised Difference Vegetation Index (NDVI; AVHRR GIMMS NDVI for short) based fraction of absorbed photosynthetically active radiation (FPAR) from 1982 to 2006 and focus on their seasonal and spatial patterns analysis. The available relationship between FPAR and NDVI was used to calculate FPAR values from 1982 to 2006 and validated by Moderate-resolution Imaging Spectroradiometer (MODIS) FPAR product. Then, the seasonal dynamic patterns were analysed, as well as the driving force of climatic factors. Results showed that there was an agreement between FPAR values from this study and those of the MODIS product in seasonal dynamic, and the spatial patterns of FPAR vary with vegetation type distribution and seasonal cycles. The time series of average FPAR revealed a strong seasonal variation, regular periodic variations from January 1982 to December 2006, and opposite patterns between the Northern and Southern Hemispheres. Evergreen vegetation FPAR values were close to 0.7. A clear single-peak curve was observed between 30°N and 80°N – an area covered by deciduous vegetation. In the Southern Hemisphere, the time series fluctuations of FPAR averaged by 0.7° latitude zones were not clear compared to those in the Northern Hemisphere. A significant positive correlation (P<0.01) was observed between the seasonal variation of temperature and precipitation and FPAR over most other global meteorological sites.

Application of two remote sensing GPP algorithms at a semiarid grassland site of North China

Aims Estimation of gross primary production (GPP) from remote sensing data is an important approach to study regional or global carbon cycle. However, for a given algorithm, it usually has its limitation on applications to a wide range of vegetation types and/or under diverse environmental conditions. This study was conducted to compare the performance of two remote sensing GPP algorithms, the MODIS GPP and the vegetation photosynthesis model (VPM), in a semiarid temperate grassland ecosystem. Methods The study was conducted at a typical grassland site in Ujimuqin of Inner Mongolia, North China, over 2 years in 2006 and 2007. Environmental controls on GPP measured by the eddy covariance (EC) technique at the study site were first investigated with path analysis of meteorological and soil moisture data at a daily and 8-day time steps. The estimates of GPP derived from the MODIS GPP and the VPM with site-specific inputs were then compared with the values of EC measurements as ground truthing at the site. Site-specific emax (a) was estimated by using rectangular hyperbola function based on the 7-day flux data at 30-min intervals over the peak period of the growing season (May to September). Important Findings Between the two remote sensing GPP algorithms and various estimates of the fraction of absorbed photosynthetic active radiation (FPAR), the VPM based on FPAR derived from the enhanced vegetation index (EVI) works the best in predicting GPP against the ground truthing of EC GPP. A path analysis indicates that the EC GPP in this semiarid temperate grassland ecosystem is controlled predominantly by both soil water and temperature. The site water condition is slightly better simulated by the moisture multiplier in the VPM than in the MODIS GPP algorithm, which is a most probable explanation for a better performance of the VPM than MODIS GPP algorithm in this semiarid grassland ecosystem.

Downscaling real-time vegetation dynamics by fusing multi-temporal MODIS and Landsat NDVI in topographically complex terrain

Canopy phenology is an important factor driving seasonal patterns of water and carbon exchange between land surface and atmosphere. Recent developments of real-time global satellite products (e.g., MODIS) provide the potential to assimilate dynamic canopy measurements with spatially distributed process-based ecohydrological models. However, global satellite products usually are provided with relatively coarse spatial resolutions, averaging out important spatial heterogeneity of both terrain and vegetation. Therefore, bias can result from lumped representation of ecological and hydrological processes especially in topographically complex terrain. Successful downscaling of canopy phenology to high spatial resolution would be indispensable for catchment-scale distributed ecohydrological modeling, aiming at understanding complex patterns of water, carbon and nutrient cycling in mountainous watersheds. Two downscaling approaches are developed in this study to overcome this issue by fusing multi-temporal MODIS and Landsat TM data in conjunction with topographic information to estimate high spatio-temporal resolution biophysical parameters over complex terrain. MODIS FPAR (fraction of absorbed photosynthetically active radiation) is used to provide medium spatial resolution phenology, while the variability of vegetation within a MODIS pixel is characterized by Landsat NDVI. The algorithms depend on the scale-invariant linear relationship between FPAR and NDVI, which is verified in this study. Downscaled vegetation dynamics are successfully validated both temporally and spatially with ground-based continuous FPAR and leaf area index measurements. Topographic correction during the downscaling process has a limited effect on downscaled FPAR products except for the period around the winter solstice in the study area.

Carbon cycle data assimilation with a generic phenology model

Photosynthesis by terrestrial plants is the main driver of the global carbon cycle, and the presence of actively photosynthesizing vegetation can now be observed from space. However, challenges remain when translating remotely sensed data into carbon fluxes. One reason is that the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), which documents the presence of photosynthetically active vegetation, relates more directly to leaf development and leaf phenology than to photosynthetic rates. Here, we present a new approach for linking FAPAR and vegetation‐to‐atmosphere carbon fluxes through variational data assimilation. The scheme extends the Carbon Cycle Data Assimilation System (CCDAS) by a newly developed, globally applicable and generic leaf phenology model, which includes both temperature and water‐driven leaf development. CCDAS is run for seven sites, six of them included in the FLUXNET network. Optimization is carried out simultaneously for all sites against 20 months of daily FAPAR from the Medium Resolution Imaging Spectrometer on board the European Space Agency's ENVISAT platform. Fourteen parameters related to phenology and 24 related to photosynthesis are optimized simultaneously, and their posterior uncertainties are computed. We find that with one parameter set for all sites, the model is able to reproduce the observed FAPAR spanning boreal, temperate, humid‐tropical, and semiarid climates. Assimilation of FAPAR has led to reduced uncertainty (by &gt;10%) of 10 of the 38 parameters, including one parameter related to photosynthesis, and a moderate reduction in net primary productivity uncertainty. The approach can easily be extended to regional or global studies and to the assimilation of further remotely sensed data.

On the bias of instantaneous FAPAR estimates in open-canopy forests

Global products of the fraction of absorbed photosynthetically active radiation (FAPAR) are operationally available from a variety of space agencies. A proper validation of these products is essential and hinges on the acquisition of accurate ground-based FAPAR estimates of the vegetation contained within the field of view of the space sensor at the time of satellite overpass. Often remotely sensed FAPAR products are defined with respect to theoretical rather than ambient illumination conditions which complicates in situ validation efforts. Similarly, the spatial complexity and substantial heights of certain plant environments may prevent the reliable sampling of certain radiation fluxes. As a consequence, many field campaigns are carried out on agricultural crops or within young tree plantations where canopy height is not an issue. This contribution compares different approaches for estimating instantaneous FAPAR in tall, open-canopy forest stands under a variety of architectural, spectral and illumination related conditions. The bias associated with these estimations is separated into a sampling error and a transfer bias. The former relates to the impact of both the number and location of the measurements whereas the latter addresses the quality of the theory that relates these measurements to the actual canopy FAPAR. Among the various methods tested it was the 2-flux FAPAR estimator (1 − T PAR) that performs best in open forest canopies under typical summer conditions. The quality of the 1 − T PAR canopy FAPAR estimator changes, however, with illumination conditions, foliage colour and especially with the background brightness. Similarly, the smaller the size of the area for which the FAPAR is to be estimated the larger the variability of the bias is going to be (and this irrespective of the choice of in situ estimation techniques). Evidence is provided that working under overcast sky conditions will reduce the sampling error but may well increase the transfer bias when compared to clear sky conditions. A parametric relationship is developed that allows to predict the instantaneous canopy FAPAR for arbitrary diffuse-to-total-incident-radiation ratios (at any given solar zenith angle). This approach has a similar transfer bias as the 1 − T PAR method when the forest floor is dark but dramatically outperforms the 2-flux approach under snowy background conditions (RMSE = 0.9934 versus 0.5801, respectively). The number of samples acquired was found to be crucial in reducing the variability of the bias of a given FAPAR estimator. Both random and grid-based sampling schemes result in similar FAPAR biases but do not lend themselves easily to the acquisition of hundreds of data points needed for reliable estimations under direct-only illumination conditions. Transect sampling—which is shown to deliver best results if carried out at ninety degrees to the solar azimuth angle—appears ideally suited to acquire the necessary numbers of samples enabling the generation of accurate quasi-instantaneous FAPAR estimates in open-canopy forests.

Monitoring biosphere vegetation 1998–2009

Earth Observation from space offers the opportunity to produce time‐series of geophysical products that can be used to assess the state and changes of land surfaces. The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is used to monitor the state and evolution of terrestrial vegetation, and also constitutes a state variable in advanced Earth system models that contain a detailed enough description of the terrestrial biosphere. This present study reports a 12‐year (1998–2009) time series of FAPAR derived from the combination of two satellite‐based sensors. We find that FAPAR exhibits large‐scale inter‐annual variations and multi‐year trends. The fraction of land grid cells showing positive anomalies, as computed by the deviation from the 12‐year climatology, shows a rapid decrease in the early part of the analysis period (until 2004). Large negative anomalies can be associated with previously reported large‐scale climate events, such as global land drying associated with El Niño Southern Oscillation 2000–2003, or the European drought of 2003 or recent Australian droughts The present analysis demonstrates that FAPAR is an important global variable suitable for large‐scale monitoring of climate impacts on the terrestrial biosphere.

Estimation of LAI and FAPAR by constraining the leaf and soil spectral characteristics in a radiative transfer model

We evaluated the estimation of the leaf area index (LAI) and the fraction of absorbed photosynthetically active radiation (FAPAR) of green plant canopies from top-of-the-canopy (TOC) spectral indices by using the PROSAIL model under the possible constraints of leaf and soil spectra. For the LAI estimation, the ratios (B1 – B3)/(B1 + B3) and B1/B3 provided fewer estimation errors than (B4 – B3)/(B4 + B3) or B4/B3 when the variation in the soil spectral reflectance was small or LAI was large. Here, B1, B3 and B4 denote the blue, red and near-infrared bands of Landsat ETM+, respectively. For the FAPAR estimation, the ratios (B5 – B7)/(B5 + B7) and B5/B7 provided fewer estimation errors than (NIR – R)/(NIR + R) or NIR/R for a FAPAR value of 0.3–0.7 when the variation in the soil spectral reflectance was large. Here, B5 and B7 denote the bands with wavelengths 1.55–1.75 and 2.09–2.35 μm, respectively. These were maintained for various conditions of the solar incident zenith angle (θs), leaf angle distribution (LAD), canopy hotspot parameter (s 1) and clumping index (Ω).

Comparison of four global FAPAR datasets over Northern Eurasia for the year 2000

The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) has been identified as one of several key satellite-derived biophysical datasets. With multiple global FAPAR datasets now available and a lack of in-situ measurements and comparison studies in the far north, this study attempts to provide the reader with an indication of the performance of four global FAPAR datasets (MODIS, CYCLOPES, JRC and GLOBCARBON) over Northern Eurasia in the year 2000 via comparison. Within the year 2000 growing season, both the MODIS and CYCLOPES datasets recorded on average similar but substantially higher values than the JRC and GLOBCARBON datasets. Among three of the four datasets, a high level of agreement in deciduous broadleaf forests and croplands was observed. Largest disagreement occurred among needleleaf forests and grassland/shrubland. Potential reasons for discrepancies among the datasets include different retrieval methods, use of LAI and land cover, snow effects and others. Findings from this study and other published results suggest that overall, JRC best captures FAPAR over northern Eurasia in the year 2000. However, when considering individual landcover types, any one or more of the four products may be suitable. There exists a real need for more in-situ measurements in this region — the lack of such measurements makes evaluation extremely difficult. It appears that areas north of 60° urgently require further investigation.

Strong links between teleconnections and ecosystem exchange found at a Pacific Northwest old‐growth forest from flux tower and MODIS EVI data

AbstractVariability in three Pacific teleconnection patterns are examined to see if net carbon exchange at a low‐elevation, old‐growth forest is affected by climatic changes associated with these periodicities. Examined are the Pacific Decadal Oscillation (PDO), Pacific/North American Oscillation (PNA) and El Niño‐Southern Oscillation (ENSO). We use 9 years of eddy covariance CO2, H2O and energy fluxes measured at the Wind River AmeriFlux site, Washington, USA and 8 years of tower‐pixel remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to address this question. We compute a new Composite Climate Index (CCI) based on the three Pacific Oscillations to divide the measurement period into positive‐ (2003 and 2005), negative‐ (1999 and 2000) and neutral‐phase climate years (2001, 2002, 2004, 2006 and 2007). The forest transitioned from an annual net carbon sink (NEP=+217 g C m−2 yr−1, 1999) to a source (NEP=−100 g C m−2 yr−1, 2003) during two dominant teleconnection patterns. Net ecosystem productivity (NEP), water use efficiency (WUE) and light use efficiency (LUE) were significantly different (P&lt;0.01) during positive (NEP=−0.27 g C m−2 day−1, WUE=4.1 mg C g−1 H2O, LUE=0.94 g C MJ−1) and negative (NEP=+0.37 g C m−2 day−1, WUE=3.4 mg C g−1 H2O, LUE=0.83 g C MJ−1) climate phases. The CCI was linked to variability in the MODIS Enhanced Vegetation Index (EVI) but not to MODIS Fraction of absorbed Photosynthetically Active Radiation (FPAR). EVI was highest during negative climate phases (1999 and 2000) and was positively correlated with NEP and showed potential for using MODIS to estimate teleconnection‐driven anomalies in ecosystem CO2 exchange in old‐growth forests. This work suggests that any increase in the strength or frequency of ENSO coinciding with in‐phase, low frequency Pacific oscillations (PDO and PNA) will likely increase CO2 uptake variability in Pacific Northwest conifer forests.

Remote Sensing Retrieval of FAPAR: Model and Analysis

FAPAR(Fraction of Absorbed Photosynthetically Active Radiation) is an important parameter for remote sensing monitoring plants net primary productivity(NPP) of land ecosystem.It is crucial that the calculated value approximates the actual value of canopy absorbed photosynthetically active radiation.The calculation accuracy directly influences the estimation of NPP and carbon cycle.The model in this paper is derived by analyzing the interaction processes between the photons and the canopy.It considers parameters like soil reflectance,canopy structure and solar zenith angle,etc.The relationship between these parameters and FAPAR is analyzed.The comparison results with Monte Carlo simulations and the validation results using field measurements prove the model to be accurate.We further choose Yingke,Zhangye City,Gansu province as study area,and retrieve LAI and FAPAR from hyperspectral and multi-angle PROBA-CHIRIS.Field data is also used to validate the retrieval result.

Long term precipitation chemistry and wet deposition in a remote dry savanna site in Africa (Niger)

Abstract. Long-term precipitation chemistry have been recorded in the rural area of Banizoumbou (Niger), representative of a semi-arid savanna ecosystem. A total of 305 rainfall samples ~90% of the total annual rainfall) were collected from June 1994 to September 2005. From ionic chromatography, pH major inorganic and organic ions were detected. Rainwater chemistry is controlled by soil/dust emissions associated with terrigeneous elements represented by SO42−, Ca2+, Carbonates, K+ and Mg2+. It is found that calcium and carbonates represent ~40% of the total ionic charge. The second highest contribution is nitrogenous, with annual Volume Weighed Mean (VWM) for NO3− and NH4+ concentrations of 11.6 and 18.1 μeq.l−1, respectively. This is the signature of ammonia sources from animals and NOx emissions from savannas soil-particles rain-induced. The mean annual NH3 and NO2 air concentration are of 6 ppbv and 2.6 ppbv, respectively. The annual VWM precipitation concentration of sodium and chloride are both of 8.7 μeq.l−1 which reflects the marine signature of monsoonal and humid air masses. The median pH value is of 6.05. Acidity is neutralized by mineral dust, mainly carbonates, and/or dissolved gases such NH3. High level of organic acidity with 8μeq.l−1 and 5.2 μeq.l−1 of formate and acetate were also found. The analysis of monthly Black Carbon emissions and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) values show that both biogenic emission from vegetation and biomass burning could explain the rainfall organic acidity content. The interannual variability of the VWM concentrations around the mean (1994–2005) is between ±5% and ±30% and mainly due to variations of sources strength and rainfall spatio-temporal distribution. From 1994 to 2005, the total mean wet deposition flux in the Sahelian region is of 60.1 mmol.m−2.yr−1 ±25%. Finally, Banizoumbou measurements are compared to other long-term measurements of precipitation chemistry in the wet savanna of Lamto (Côte d'Ivoire) and in the forested zone of Zoétélé (Cameroon). The total chemical loading presents a maximum in the dry savanna and a minimum in the forest (from 143.7, 100.2 to 86.6 μeq.l−1), associated with the gradient of terrigeneous sources. The wet deposition fluxes present an opposite trend, with 60.0 mmol.m−2.yr−1 in Banizoumbou, 108.6 mmol.m−2.yr−1 in Lamto and 162.9 mmol.m−2.yr−1 in Zoétélé, controlled by rainfall gradient along the ecosystems transect.

Can a satellite-derived estimate of the fraction of PAR absorbed by chlorophyll (FAPAR chl) improve predictions of light-use efficiency and ecosystem photosynthesis for a boreal aspen forest?

We used daily MODerate resolution Imaging Spectroradiometer (MODIS) imagery obtained over a five-year period to analyze the seasonal and inter-annual variability of the fraction of absorbed photosynthetically active radiation (FAPAR) and photosynthetic light use efficiency (LUE) for the Southern Old Aspen (SOA) flux tower site located near the southern limit of the boreal forest in Saskatchewan, Canada. To obtain the spectral characteristics of a standardized land area to compare with tower measurements, we scaled up the nominal 500 m MODIS products to a 2.5 km × 2.5 km area (5 × 5 MODIS 500 m grid cells). We then used the scaled-up MODIS products in a coupled canopy-leaf radiative transfer model, PROSAIL-2, to estimate the fraction of absorbed photosynthetically active radiation (APAR) by the part of the canopy dominated by chlorophyll (FAPAR chl) versus that by the whole canopy (FAPAR canopy). Using the additional information provided by flux tower-based measurements of gross ecosystem production (GEP) and incident PAR, we determined 90-minute averages for APAR and LUE (slope of GEP:APAR) for both the physiologically active foliage (APAR chl, LUE chl) and for the entire canopy (APAR canopy, LUE canopy). The flux tower measurements of GEP were strongly related to the MODIS-derived estimates of APAR chl ( r 2 = 0.78) but only weakly related to APAR canopy ( r 2 = 0.33). Gross LUE between 2001 and 2005 for LUE chl was 0.0241 µmol C µmol − 1 PPFD whereas LUE canopy was 36% lower. Time series of the 5-year normalized difference vegetation index (NDVI) were used to estimate the average length of the core growing season as days of year 152–259. Inter-annual variability in the core growing season LUE chl (µmol C µmol − 1 PPFD) ranged from 0.0225 in 2003 to 0.0310 in 2004. The five-year time series of LUE chl corresponded well with both the seasonal phase and amplitude of LUE from the tower measurements but this was not the case for LUE canopy. We conclude that LUE chl derived from MODIS observations could provide a more physiologically realistic parameter than the more commonly used LUE canopy as an input to large-scale photosynthesis models.