The Leaf Area Index (LAI) is a measure of the amount of photosynthetic leaves and governs the canopy conductance to water vapor and carbon dioxide. Four different estimates of LAI were compared over ...France: two LAI products derived from satellite remote sensing, and two LAI simulations derived from land surface modelling. The simulated LAI was produced by the ISBA-A-gs model and by the ORCHIDEE model (developed by CNRM-GAME and by IPSL, respectively), for the 1994-2007 period. The two models were driven by the same atmospheric variables and used the same land cover map (SAFRAN and ECOCLIMAP-II, respectively). The MODIS and CYCLOPES satellite LAI products were used. Both products were available from 2000 to 2007 and this relatively long period allowed to investigate the interannual and the seasonal variability of monthly LAI values. In particular the impact of the 2003 and 2005 droughts were analyzed. The two models presented contrasting results, with a difference of one month between the average leaf onset dates simulated by the two models, and a maximum interannual variability of LAI simulated at springtime by ORCHIDEE and at summertime by ISBA-A-gs. The comparison with the satellite LAI products showed that, in general, the seasonality was better represented by ORCHIDEE, while ISBA-A-gs tended to better represent the interannual variability, especially for grasslands. While the two models presented comparable values of net carbon fluxes, ORCHIDEE simulated much higher photosynthesis rates than ISBA-A-gs (+70%), while providing lower transpiration estimates (-8%).
This study uses a variational data assimilation framework to simultaneously constrain a global ecosystem model with eddy covariance measurements of daily net ecosystem exchange (NEE) and latent heat ...(LE) fluxes from a large number of sites grouped in seven plant functional types (PFTs). It is an attempt to bridge the gap between the numerous site-specific parameter optimization works found in the literature and the generic parameterization used by most land surface models within each PFT. The present multisite approach allows deriving PFT-generic sets of optimized parameters enhancing the agreement between measured and simulated fluxes at most of the sites considered, with performances often comparable to those of the corresponding site-specific optimizations. Besides reducing the PFT-averaged model–data root-mean-square difference (RMSD) and the associated daily output uncertainty, the optimization improves the simulated CO2 balance at tropical and temperate forests sites. The major site-level NEE adjustments at the seasonal scale are reduced amplitude in C3 grasslands and boreal forests, increased seasonality in temperate evergreen forests, and better model–data phasing in temperate deciduous broadleaf forests. Conversely, the poorer performances in tropical evergreen broadleaf forests points to deficiencies regarding the modelling of phenology and soil water stress for this PFT. An evaluation with data-oriented estimates of photosynthesis (GPP – gross primary productivity) and ecosystem respiration (Reco) rates indicates distinctively improved simulations of both gross fluxes. The multisite parameter sets are then tested against CO2 concentrations measured at 53 locations around the globe, showing significant adjustments of the modelled seasonality of atmospheric CO2 concentration, whose relevance seems PFT-dependent, along with an improved interannual variability. Lastly, a global-scale evaluation with remote sensing NDVI (normalized difference vegetation index) measurements indicates an improvement of the simulated seasonal variations of the foliar cover for all considered PFTs.
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 polarization measurements achieved by the POLDER instrument on ADEOS‐1 are used for the remote sensing of aerosols over land surfaces. The key advantage of using polarized observations is their ...ability to systematically correct for the ground contribution, whereas the classical approach using natural light fails. The estimation of land surface polarizing properties from POLDER has been examined in a previous paper. Here we consider how the optical thickness δ0 and Ångstrom exponent α of aerosols are derived from the polarized light backscattered by the particles. The inversion scheme is detailed, and illustrative results are presented. Maps of the retrieved optical thickness allow for detection of large aerosol features, and in the case of small aerosols, the δ0 and α retrievals are consistent with correlative ground‐based measurements. However, because polarized light stems mainly from small particles, the results are biased for aerosol distributions containing coarser modes of particles. To overcome this limitation, an aerosol index defined as the product AI = δ0α is proposed. Theoretical analysis and comparison with ground‐based measurements suggest that AI is approximately the same when using δ0, and α is related to the entire aerosol size distribution or derived from the polarized light originating from the small polarizing particles alone. This invariance is specially assessed by testing the continuity of AI across coastlines, given the unbiased properties of aerosol retrieval over ocean. Although reducing the information concerning the aerosols, this single parameter allows a link between the POLDER aerosol surveys over land and ocean. POLDER aerosol index global maps enable the monitoring of major aerosol sources over continental areas.
Since 70 % of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate ...change. Yet, none of the land-surface models used in Earth system models, and therefore none of today's predictions of future climate, accounts for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrising a version of the ORCHIDEE land-surface model to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new branch called ORCHIDEE-CAN (SVN r2290) and the trunk version of ORCHIDEE (SVN r2243) are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes were introduced towards a better process representation for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrisation was revisited after introducing 12 new parameter sets that represent specific tree species or genera rather than a group of often distantly related or even unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy structure, gross primary production (GPP), albedo and evapotranspiration over Europe. For all tested variables, ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67 to 92 % chance to reproduce the spatial and temporal variability of the validation data.
To determine the location of the potential dust source regions and to evaluate the dust emission frequencies over the arid and semiarid areas of China and Mongolia (35.5°N–47°N; 73°E–125°E), we ...established a map of Z0 from the composition of protrusion coefficient (PC) derived from the POLDER‐1 bidirectional reflectance distribution function (BRDF). Using a ° × ° resolution Z0 data set, we derived a map of the 10‐m erosion threshold wind velocity for the Chinese and Mongolian deserts. The retrieved erosion thresholds range from 7 m s−1 in the sandy deserts (Taklimakan, Badain Jaran, and Tengger deserts) to up to 20 m s−1 in the Gobi desert. They are comparable to the minimum wind velocity measured in meteorological stations during dust storms in the Taklimakan (6–8 m s−1) and in the Gobi desert (11–20 m s−1). These erosion thresholds were combined with surface wind fields, soil moisture, and snow cover to simulate the dust emission frequencies of the eastern Asian deserts over 3 years (1997–1999). The simulations point out the Taklimakan desert and the deserts of northern China as the most frequent sources of dust emissions. The simulated seasonal cycle is characterized by a maximum in late spring and a minimum in late autumn and winter. The comparison with climatologic studies of dust storms derived from synoptic observations confirms the importance of these two source areas and the reliability of the simulated seasonal cycle. It reveals an underestimation of the dust emission frequency in the Gobi desert, because of a low frequency of high wind velocities. Our results also suggest that soil moisture and snow cover are not the main factors controlling the seasonal cycle or the interannual variability of the dust emission frequencies. We finally compared the simulated dust event frequencies to occurrences of Total Ozone Mapping Spectrometer (TOMS) Absorbing Aerosol Index (AAI) higher than 0.7 over the Taklimakan desert, where mineral dust is expected to be the dominant absorbing aerosol. A very good agreement is obtained between the simulated frequencies and the TOMS AAI frequencies on monthly and seasonal timescales.
This paper describes a new model for the calculation of daily, high-resolution (up to 1 km) fire emissions, developed in the framework of the APIFLAME (Analysis and Prediction of the Impact of Fires ...on Air quality ModEling) project. The methodology relies on the classical approach, multiplying the burned area by the fuel load consumed and the emission factors specific to the vegetation burned. Emissions can be calculated on any user-specified domain, horizontal grid, and list of trace gases and aerosols, providing input information on the burned area (location, extent), and emission factors of the targeted species are available. The applicability to high spatial resolutions and the flexibility to different input data (including vegetation classifications) and domains are the main strength of the proposed algorithm. The modification of the default values and databases proposed does not require any change in the core of the model. The code may be used for the calculation of global or regional inventories. However, it has been developed and tested more specifically for Europe and the Mediterranean area. A regional analysis of fire activity and the resulting emissions in this region is provided. The burning season extends from June to October in most regions, with generally small but frequent fires in eastern Europe, western Russia, Ukraine and Turkey, and large events in the Mediterranean area. The resulting emissions represent a significant fraction of the total yearly emissions (on average amounting to ~ 30% of anthropogenic emissions for PM2.5, ~ 20% for CO). The uncertainty regarding the daily carbon emissions is estimated at ~ 100% based on an ensemble analysis. Considering the large uncertainties regarding emission factors, the potential error on the emissions for the various pollutants is even larger. Comparisons with other widely used emission inventories show good correlations but discrepancies of a factor of 2–4 in the amplitude of the emissions, our results being generally on the higher end.
Two new remotely sensed leaf area index (LAI) and surface soil moisture (SSM) satellite-derived products are compared with two sets of simulations of the ORganizing Carbon and Hydrology In Dynamic ...EcosystEms (ORCHIDEE) and Interactions between Soil, Biosphere and Atmosphere, CO2-reactive (ISBA-A-gs) land surface models. We analyse the interannual variability over the period 1991–2008. The leaf onset and the length of the vegetation growing period (LGP) are derived from both the satellite-derived LAI and modelled LAI. The LGP values produced by the photosynthesis-driven phenology model of ISBA-A-gs are closer to the satellite-derived LAI and LGP than those produced by ORCHIDEE. In the latter, the phenology is based on a growing degree day model for leaf onset, and on both climatic conditions and leaf life span for senescence. Further, the interannual variability of LAI is better captured by ISBA-A-gs than by ORCHIDEE. In order to investigate how recent droughts affected vegetation over the Euro-Mediterranean area, a case study addressing the summer 2003 drought is presented. It shows a relatively good agreement of the modelled LAI anomalies with the observations, but the two models underestimate plant regrowth in the autumn. A better representation of the root-zone soil moisture profile could improve the simulations of both models. The satellite-derived SSM is compared with SSM simulations of ISBA-A-gs only, as ORCHIDEE has no explicit representation of SSM. Overall, the ISBA-A-gs simulations of SSM agree well with the satellite-derived SSM and are used to detect regions where the satellite-derived product could be improved. Finally, a correspondence is found between the interannual variability of detrended SSM and LAI. The predictability of LAI is less pronounced using remote sensing observations than using simulated variables. However, consistent results are found in July for the croplands of the Ukraine and southern Russia.
Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem ...models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high‐resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE‐CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE‐CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.
Key Points
The global ORCHIDEE ecosystem model is suitable for assimilating remotely sensed forest structure data to estimates AGB in tropical forests
The FOTO‐Pleiades products used for the assimilation system bear too large systematic errors to retrieve the fine‐scale structure of AGB
Most of the systematic errors related to ORCHIDEE‐CAN could be reduced by improving the allometric equations
In a previous paper, we described a procedure to correct the directional effects in AVHRR reflectance time series. The corrected measurements show much less high frequency variability than their ...original counterparts, which makes them suitable to study vegetation dynamics. The time series are used here to estimate the start and ending dates of the growing season for 18 years from 1982 to 1999. We focus on the interannual variations of these phenological parameters.A database of in situ phenology observations is used to quantify the accuracy of the satellite-based estimates. Although based on a limited sampling of the Northern mid and high latitudes, the comparison indicates that i) the satellite phenological product contains meaningful information on interannual onset anomalies; ii) there is a higher degree of consistency over regions covered by Broadleaf Forests, Grasses and cereal Crops than over those covered by Needleleaf Forests or Savannas; and iii) the satellite phenological product is of lower quality in regions with mountainous terrain. In favorable conditions, interannual variations of the onset are captured with an accuracy of a few days.As this satellite-derived product captures the interannual onset variability at ground-truth sites, we confidently use it to larger scales studies. Mapped at a continental scale, the onset anomalies show coherent patterns at the regional (≈ 1000 km) scale for the mid and high latitudes of the Northern hemisphere, which is consistent with a meteorological forcing. In the tropics, there is larger spatial heterogeneity, which suggests more complex controls of the phenology. The relation between vegetation phenology and climate is further investigated over Europe by comparing the variability of the satellite-derived vegetation onset and that of the winter North Atlantic Oscillation index, at a fine spatial scale. The strong correlations observed confirm that this climate forcing parameter explains most of the onset variability over a large fraction of Northern Europe (earlier onsets for positive winter NAO), with lower impact towards the south and opposite effects around the Mediterranean basin. The NAO has a predictive character as the January–February NAO index is strongly correlated with the vegetation onset that occurs around April in Northern Europe.
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