A modification of the most popular two-equation (E-ϕ) models, taking into account the plant drag, is proposed. Here E is the turbulent kinetic energy (TKE) and ϕ is any of the following variables: El (product of E and the mixing length l), ε (dissipation rate of TKE), and ω (specific dissipation of TKE, ω = ε/E). The proposed modification is due to the fact that the model constants estimated experimentally for 'free-air' flow do not allow for adequate reconstruction of the ratio between the production and dissipation rates of TKE in the vegetation canopy and have to be adjusted. The modification is universal, i.e. of the same type for all E-ϕ models considered. The numerical experiments carried out for both homogeneous and heterogeneous plant canopies with E-ϕ models (and with the E-l model taken as a kind of reference) show that the modification performs well. They also suggest that E-ε and E-ω schemes are more promising than the E-El scheme for canopy flow simulation since they are not limited by the need to use a wall function.In addition, a new parameterization for enhanced dissipation within the plant canopy is derived. It minimizes the model sensitivity to C μ , the key parameter for two-equation schemes, and whose estimates unfortunately vary considerably from experiment to experiment. The comparison of results of new modified E-ε and E -ω models with observations from both field and wind-tunnel experiments shows that the proposed parameterization is quite robust. However, because of uncertainties with the turbulence Prandtl and Schmidt numbers for the E-ε model within the canopy, the E-ω model is recommended for future implementation, with the suggested modifications.

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Abstract. In order to quantify the effects of forests to oil palm conversion occurring in the tropics on land–atmosphere carbon, water and energy fluxes, we develop a new perennial crop sub-model CLM-Palm for simulating a palm plant functional type (PFT) within the framework of the Community Land Model (CLM4.5). CLM-Palm is tested here on oil palm only but is meant of generic interest for other palm crops (e.g., coconut). The oil palm has monopodial morphology and sequential phenology of around 40 stacked phytomers, each carrying a large leaf and a fruit bunch, forming a multilayer canopy. A sub-canopy phenological and physiological parameterization is thus introduced so that each phytomer has its own prognostic leaf growth and fruit yield capacity but with shared stem and root components. Phenology and carbon and nitrogen allocation operate on the different phytomers in parallel but at unsynchronized steps, separated by a thermal period. An important phenological phase is identified for the oil palm – the storage growth period of bud and "spear" leaves which are photosynthetically inactive before expansion. Agricultural practices such as transplanting, fertilization and leaf pruning are represented. Parameters introduced for the oil palm were calibrated and validated with field measurements of leaf area index (LAI), yield and net primary production (NPP) from Sumatra, Indonesia. In calibration with a mature oil palm plantation, the cumulative yields from 2005 to 2014 matched notably well between simulation and observation (mean percentage error = 3 %). Simulated inter-annual dynamics of PFT-level and phytomer-level LAI were both within the range of field measurements. Validation from eight independent oil palm sites shows the ability of the model to adequately predict the average leaf growth and fruit yield across sites and sufficiently represent the significant nitrogen- and age-related site-to-site variability in NPP and yield. Results also indicate that seasonal dynamics of yield and remaining small-scale site-to-site variability of NPP are driven by processes not yet implemented in the model or reflected in the input data. The new sub-canopy structure and phenology and allocation functions in CLM-Palm allow exploring the effects of tropical land-use change, from natural ecosystems to oil palm plantations, on carbon, water and energy cycles and regional climate.

The present study is based on the assumption that vegetation in Indonesia is significantly affected by climate anomalies that are related to El Niñ o-Southern Oscillation (ENSO) warm phases (El Niñ o) during the past decades. The analysis builds upon a monthly time series from the normalized difference vegetation index (NDVI) gridded data from the Advanced Very High Resolution Radiometer (AVHRR) and two ENSO proxies, namely, sea surface temperature anomalies (SSTa) and Southern Oscillation index (SOI), and aims at the analysis of the spatially explicit dimension of ENSO impact on vegetation on the Indonesian archipelago. A time series correlation analysis between NDVI anomalies and ENSO proxies for the most recent ENSO warm events showed that, in general, anomalies in vegetation productivity over Indonesia can be related to an anomalous increase of SST in the eastern equatorial Pacific and to decreases in SOI, respectively. The net effect of these variations is a significant decrease in NDVI values throughout the affected areas during the ENSO warm phases. The 1982/83 ENSO warm episode was rather short but-in terms of ENSO indices-the most extreme one within the study period. The 1997/98 El Niñ o lasted longer but was weaker. Both events had significant impact on vegetation in terms of negative NDVI anomalies. Compared to these two major warm events, the other investigated events (1987/88, 1991/92, 1994/95, and 2002/03) had no significant effect on vegetation in the investigated region. The land cover-type specific sensitivity of vegetation to ENSO anomalies revealed thresholds of vegetation response to ENSO warm events. The results for the 1997/98 ENSO warm event confirm the hypothesis that the vulnerability of vegetated tropical land surfaces to drought conditions is considerably affected by land use intensity. In particular, it could be shown that natural forest areas are more resistant to drought stress than degraded forest areas or cropland. Comparing the spatially explicit patterns of El Niñ o-related vegetation variation during the major El Niñ o phases, the spatial distribution of affected areas reveals distinct core regions of ENSO drought impact on vegetation for Indonesia that coincide with forest conversion and agricultural intensification hot spots.

Abstract. Models of gross primary production (GPP) are currently parameterized with vegetation-specific parameter sets and therefore require accurate information on the distribution of vegetation to drive them. Can this parameterization scheme be replaced with a vegetation-invariant set of parameter that can maintain or increase model applicability by reducing errors introduced from the uncertainty of land cover classification? Based on the measurements of ecosystem carbon fluxes from 150 globally distributed sites in a range of vegetation types, we examined the predictive capacity of seven light use efficiency (LUE) models. Two model experiments were conducted: (i) a constant set of parameters for various vegetation types and (ii) vegetation-specific parameters. The results showed no significant differences in model performances to simulate GPP while using both sets of parameters. These results indicate that a universal set of parameters, which is independent of vegetation cover type and characteristics can be adopted in prevalent LUE models. Availability of this well tested and universal set of parameters would help to improve the accuracy and applicability of LUE models in various biomes and geographic regions.

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