Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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    Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice : the Larcform 1 single column model intercomparison
    Pithan, Felix ; Ackerman, Andrew ; Angevine, Wayne M. ; Hartung, Kerstin ; Ickes, Luisa ; Kelley, Maxwell ; Medeiros, Brian ; Sandu, Irina ; Steeneveld, Gert Jan ; Sterk, H.A.M. - \ 2016
    Journal of Advances in Modeling Earth Systems 8 (2016)3. - ISSN 1942-2466 - p. 1345 - 1357.
    Arctic - boundary-layer - intercomparison - inversion - mixed-phase clouds - models

    Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modeled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: some models lack the cloudy state of the boundary layer due to the representation of mixed-phase microphysics or to the interaction between micro- and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behavior.

    The Role of the Mean State of Arctic Sea Ice on Near-Surface Temperature Trends
    Linden, E.C. van der; Bintanja, R. ; Hazeleger, W. ; Katsman, C.A. - \ 2014
    Journal of Climate 27 (2014)8. - ISSN 0894-8755 - p. 2819 - 2841.
    climate model sensitivity - albedo feedback - amplification - future - predictability - variability - inversion - thickness - extent - gcm
    Century-scale global near-surface temperature trends in response to rising greenhouse gas concentrations in climate models vary by almost a factor of 2, with greatest intermodel spread in the Arctic region where sea ice is a key climate component. Three factors contribute to the intermodel spread: 1) model formulation, 2) control climate state, and 3) internal climate variability. This study focuses on the influence of Arctic sea ice in the control climate on the intermodel spread in warming, using idealized 1% yr(-1) CO2 increase simulations of 33 state-of-the-art global climate models, and combining sea ice-temperature relations on local to large spatial scales. On the Arctic mean scale, the spread in temperature trends is only weakly related to ice volume or area in the control climate, and is probably not dominated by internal variability. This suggests that other processes, such as ocean heat transport and meteorological conditions, play a more important role in the spread of long-term Arctic warming than control sea ice conditions. However, on a local scale, sea ice-warming relations show that in regions with more sea ice, models generally simulate more warming in winter and less warming in summer. The local winter warming is clearly related to control sea ice and universal among models, whereas summer sea ice-warming relations are more diverse, and are probably dominated by differences in model formulation. To obtain a more realistic representation of Arctic warming, it is recommended to simulate control sea ice conditions in climate models so that the spatial pattern is correct.
    Role of the residual layer and large-scale subsidence on the development and evolution of the convective boundary layer
    Blay-Carreras, E. ; Pino, D. ; Vilà-Guerau de Arellano, J. ; Boer, A. van de; Coster, O. de; Darbieu, C. ; Hartogensis, O.K. ; Lohou, F. ; Lothon, M. ; Pietersen, H.P. - \ 2014
    Atmospheric Chemistry and Physics 14 (2014). - ISSN 1680-7316 - p. 4515 - 4530.
    large-eddy-simulation - morning transition - carbon-dioxide - mixed-layer - water-vapor - order-jump - part i - turbulence - entrainment - inversion
    Observations, mixed-layer theory and the Dutch Large-Eddy Simulation model (DALES) are used to analyze the dynamics of the boundary layer during an intensive operational period (1 July 2011) of the Boundary Layer Late Afternoon and Sunset Turbulence campaign. Continuous measurements made by remote sensing and in situ instruments in combination with radio soundings, and measurements done by remotely piloted aircraft systems and two manned aircrafts probed the vertical structure and the temporal evolution of the boundary layer during the campaign. The initial vertical profiles of potential temperature, specific humidity and wind, and the temporal evolution of the surface heat and moisture fluxes prescribed in the models runs are inspired by some of these observations. The research focuses on the role played by the residual layer during the morning transition and by the large-scale subsidence on the evolution of the boundary layer. By using DALES, we show the importance of the dynamics of the boundary layer during the previous night in the development of the boundary layer at the morning. DALES numerical experiments including the residual layer are capable of modeling the observed sudden increase of the boundary-layer depth during the morning transition and the subsequent evolution of the boundary layer. These simulations show a large increase of the entrainment buoyancy flux when the residual layer is incorporated into the mixed layer. We also examine how the inclusion of the residual layer above a shallow convective boundary layer modifies the turbulent kinetic energy budget. Large-scale subsidence mainly acts when the boundary layer is fully developed, and, for the studied day, it is necessary to be considered to reproduce the afternoon observations. Finally, we also investigate how carbon dioxide (CO2) mixing ratio stored the previous night in the residual layer plays a fundamental role in the evolution of the CO2 mixing ratio during the following day.
    Bayesian object-based estimation of LAI and chlorophyll from a simulated Sentinel-2 top-of-atmosphere radiance image
    Laurent, V.C.E. ; Schaepman, M.E. ; Verhoef, W. ; Weyermann, J. ; Chavez Oyanadel, R.O. - \ 2014
    Remote Sensing of Environment 140 (2014). - ISSN 0034-4257 - p. 318 - 329.
    radiative-transfer models - high-spatial-resolution - remote-sensing data - red-edge bands - reflectance model - global products - leaf-area - inversion - canopy - vegetation
    Leaf area index (LAI) and chlorophyll content (Cab) are important vegetation variables which can be monitored using remote sensing (RS). Physically-based approaches have higher transferability and are therefore better suited than empirically-based approaches for estimating LAI and Cab at global scales. These approaches, however, require the inversion of radiative transfer (RT) models, which is an ill-posed and underdetermined problem. Four regularization methods have been proposed, allowing finding stable solutions: 1) model coupling, 2) using a priori information (e.g. Bayesian approaches), 3) spatial constraints (e.g. using objects), and 4) temporal constraints. For mono-temporal data, only the first three methods can be applied. In an earlier study, we presented a Bayesian object-based algorithm for inverting the SLC-MODTRAN4 coupled canopy-atmosphere RT model, and compared it with a Bayesian LUT inversion. The results showed that the object-based approach provided more accurate LAI estimates. This study, however, heavily relied on expert knowledge about the objects and vegetation classes. Therefore, in this new contribution, we investigated the applicability of the Bayesian object-based inversion of the SLC-MODTRAN4 model to a situation where no such knowledge was available. The case study used a 16 × 22 km2 simulated top-of-atmosphere image of the upcoming Sentinel-2 sensor, covering the area near the city of Zurich, Switzerland. Seven APEX radiance images were nadir-normalized using the parametric Li–Ross model, spectrally and spatially resampled to Sentinel-2 specifications, geometrically corrected, and mosaicked. The atmospheric effects between APEX flight height and top-of-atmosphere level were added based on two MODTRAN4 simulations. The vegetation objects were identified and delineated using a segmentation algorithm, and classified in four levels of brightness in the visible domain. The LAI and Cab maps obtained from the Bayesian object-based inversion of the coupled SLC-MODTRAN4 model presented realistic spatial patterns. The impact of the parametric Li–Ross nadir-normalization was evaluated by comparing 1) the angular signatures of the SLC-MODTRAN4 and Li–Ross models, and 2) the LAI and Cab maps obtained from a Li–Ross nadir-normalized image (using nadir viewing geometry) and from the original image (using the original viewing geometry). The differences in angular signatures were small but systematic, and the differences between the LAI and Cab maps increased from the center towards the edges of the across-track direction. The results of this study contribute to preparing the RS community for the arrival of Sentinel-2 data in the near future, and generalize the applicability of the Bayesian object-based approach for estimating vegetation variables to cases where no field data are available.
    Influence of boundary layer dynamics and isoprene chemistry on the organic aerosol budget in a tropical forest.
    Janssen, R.H.H. ; Vilà-Guerau de Arellano, J. ; Jimenez, J.L. ; Ganzeveld, L.N. ; Robinson, N.H. ; Allan, J.D. ; Coe, H. ; Pugh, T.A.M. - \ 2013
    Journal of Geophysical Research: Atmospheres 118 (2013)16. - ISSN 2169-897X - p. 9351 - 9366.
    rain-forest - atmospheric chemistry - soa formation - op3 project - oxidation - photooxidation - surface - inversion - campaign - impact
    We study the organic aerosol (OA) budget in a tropical forest by analyzing a case that is representative for the OP3 campaign at Borneo. A model is designed that combines the essential dynamical and chemical processes that drive the diurnal evolution of reactants in the atmospheric boundary layer (BL). In this way, the model simultaneously represents the effects and interactions of various dynamical and chemical factors on the OA budget. The model is able to reproduce the observed diurnal dynamics of the BL, including the evolution of most chemical species involved in secondary organic aerosol (SOA) formation. A budget analysis of the contributions of the dynamic and chemical processes reveals the significance of the entrainment process in the diurnal evolution of SOA. Further, we perform a series of sensitivity analyses to determine the effect of meteorological forcings and isoprene chemical pathways on the OA budget. Subsidence and advection of cool air have opposing effects on the OA concentration, although both suppress BL growth. Recycling of the OH radical in the oxidation of isoprene may affect the amount of SOA that is formed, but must be understood better before its impact can be definitely determined. SOA formation from isoprene is calculated for both the low- and high-NOx pathway, with the latter dominating the isoprene peroxy radical chemistry. Finally, we study the significance of SOA formation through the reactive uptake of isoprene epoxydiols on acidic sulfate aerosol. Despite the incorporation of these new pathways, the OA concentration is systematically underestimated by about a factor of 2.
    A Bayesian object-based approach for estimating vegetation biophysical and biochemical variables from APEX at-sensor radiance data
    Laurent, V.C.E. ; Verhoef, W. ; Damm, A. ; Schaepman, M.E. ; Clevers, J.G.P.W. - \ 2013
    Remote Sensing of Environment 139 (2013). - ISSN 0034-4257 - p. 6 - 17.
    radiative-transfer models - leaf-area index - sun-induced fluorescence - remote-sensing data - reflectance data - global products - brdf model - inversion - canopy - lai
    Vegetation variables such as leaf area index (LAI) and leaf chlorophyll content (Cab) are important inputs for vegetation growth models. LAI and Cab can be estimated from remote sensing data using either empirical or physically-based approaches. The latter are more generally applicable because they can easily be adapted to different sensors, acquisition geometries, and vegetation types. They estimate vegetation variables through inversion of radiative transfer models. Such inversions are ill-posed but can be regularized by coupling models, by using a priori information, and spatial and/or temporal constraints. Striving to improve the accuracy of LAI and Cab estimates from single remote sensing images, this contribution proposes a Bayesian object-based approach to invert at-sensor radiance data, combining the strengths of regularization by model coupling, as well as using a priori data and object-level spatial constraints. The approach was applied to a study area consisting of homogeneous agricultural fields, which were used as objects for applying the spatial constraints. LAI and Cab were estimated from at-sensor radiance data of the Airborne Prism EXperiment (APEX) imaging spectrometer by inverting the coupled SLC-MODTRAN4 canopy-atmosphere model. The estimation was implemented in two steps. In the first step, up to six variables were estimated for each object using a Bayesian optimization algorithm. In the second step, a look-up-table (WT) was built for each object with only LAI and Cab as free variables, constraining the values of all other variables to the values obtained in the first step. The results indicated that the Bayesian object-based approach estimated LAI more accurately (R-2 = 0.45 and RMSE = 1.0) than a LUT with a Bayesian cost function (LUT-BCF) approach (R-2 = 022 and RMSE = 2.1), and Cab with a smaller absolute bias (-9 versus -23 mu g/cm(2)). The results of this study are an important contribution to further improve the regularization of ill-posed RT model inversions. The proposed approach allows reducing uncertainties of estimated vegetation variables, which is essential to support various environmental applications. The definition of objects and a priori data in cases where less extensive ground data are available, as well as the definition of the observation covariance matrix, are critical issues which require further research. (C) 2013 Elsevier Inc All rights reserved.
    Analytical solution for the convectively-mixed atmospheric boundary layer
    Ouwersloot, H.G. ; Vilà-Guerau de Arellano, J. - \ 2013
    Boundary-Layer Meteorology 148 (2013)3. - ISSN 0006-8314 - p. 557 - 583.
    inversion - dynamics - cumulus - model
    Based on the prognostic equations of mixed-layer theory assuming a zeroth order jump at the entrainment zone, analytical solutions for the boundary-layer height evolution are derived with different degrees of accuracy. First, an exact implicit expression for the boundary-layer height for a situation without moisture is analytically derived without assuming any additional relationships or specific initial conditions. It is shown that to expand the solution to include moisture, only minor approximations have to be made. Second, for relatively large boundary-layer heights, the implicit representation is simplified to an explicit function. Third, a hybrid expression is proposed as a reasonable representation for the boundary-layer height evolution during the entire day. Subsequently, the analysis is extended to present the evolution of any boundary-layer averaged scalar, either inert or under idealized chemistry, as an analytical function of time and boundary-layer height. Finally, the analytical solutions are evaluated. This evaluation includes a sensitivity analysis of the boundary-layer height for the entrainment ratio, the free tropospheric lapse rate of the potential temperature, the time-integrated surface flux and the initial boundary-layer height and potential temperature jump.
    Interannual variability of carbon monoxide emission estimates over South America from 2006 to 2010
    Hooghiemstra, P.B. ; Krol, M.C. ; Leeuwen, T.T. van; Werf, G.R. van der; Novelli, P.C. ; Deeter, M.N. ; Aben, I. ; Rockmann, T. - \ 2012
    Journal of Geophysical Research: Atmospheres 117 (2012). - ISSN 2169-897X
    variational data assimilation - land-use change - climate-change - co emissions - amazon deforestation - brazilian amazon - fire emissions - model tm5 - mopitt - inversion
    We present the first inverse modeling study to estimate CO emissions constrained by both surface and satellite observations. Our 4D-Var system assimilates National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) surface and Measurements Of Pollution In The Troposphere (MOPITT) satellite observations jointly by fitting a bias correction scheme. This approach leads to the identification of a positive bias of maximum 5 ppb in MOPITT column-averaged CO mixing ratios in the remote Southern Hemisphere (SH). The 4D-Var system is used to estimate CO emissions over South America in the period 2006-2010 and to analyze the interannual variability (IAV) of these emissions. We infer robust, high spatial resolution CO emission estimates that show slightly smaller IAV due to fires compared to the Global Fire Emissions Database (GFED3) prior emissions. South American dry season (August and September) biomass burning emission estimates amount to 60, 92, 42, 16 and 93 Tg CO/yr for 2006 to 2010, respectively. Moreover, CO emissions probably associated with pre-harvest burning of sugar cane plantations in Sao Paulo state are underestimated in current inventories by 50-100%. We conclude that climatic conditions (such as the widespread drought in 2010) seem the most likely cause for the IAV in biomass burning CO emissions. However, socio-economic factors (such as the growing global demand for soy, beef and sugar cane ethanol) and associated deforestation fires, are also likely as drivers for the IAV of CO emissions, but are difficult to link directly to CO emissions.
    Comparing optimized CO emission estimates using MOPITT or NOAA surface network observations
    Hooghiemstra, P.B. ; Krol, M.C. ; Bergamaschi, P. ; Laat, A.T.J. de; Werf, G.R. van der; Novelli, P.C. ; Deeter, M.N. ; Aben, I. ; Rockmann, T. - \ 2012
    Journal of Geophysical Research: Atmospheres 117 (2012). - ISSN 2169-897X - 23 p.
    variational data assimilation - zoom model tm5 - carbon-monoxide - tropospheric chemistry - inversion - validation - sciamachy - algorithm - pollution - aircraft
    This paper compares two global inversions to estimate carbon monoxide (CO) emissions for 2004. Either surface flask observations from the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) or CO total columns from the Measurement of Pollution in the Troposphere (MOPITT) instrument are assimilated in a 4D-Var framework. Inferred emission estimates from the two inversions are consistent over the Northern Hemisphere (NH). For example, both inversions increase anthropogenic CO emissions over Europe (from 46 to 94 Tg CO/yr) and Asia (from 222 to 420 Tg CO/yr). In the Southern Hemisphere (SH), three important findings are reported. First, due to their different vertical sensitivity, the stations-only inversion increases SH biomass burning emissions by 108 Tg CO/yr more than the MOPITT-only inversion. Conversely, the MOPITT-only inversion results in SH natural emissions (mainly CO from oxidation of NMVOCs) that are 185 Tg CO/yr higher compared to the stations-only inversion. Second, MOPITT-only derived biomass burning emissions are reduced with respect to the prior which is in contrast to previous (inverse) modeling studies. Finally, MOPITT derived total emissions are significantly higher for South America and Africa compared to the stations-only inversion. This is likely due to a positive bias in the MOPITT V4 product. This bias is also apparent from validation with surface stations and ground-truth FTIR columns. Our results show that a combined inversion is promising in the NH. However, implementation of a satellite bias correction scheme is essential to combine both observational data sets in the SH.
    Characterization of a boreal convective boundary layer and its impact on atmospheric chemistry during HUMPPA-COPEC-2010
    Ouwersloot, H.G. ; Vilà-Guerau de Arellano, J. ; Nölscher, A.C. ; Krol, M.C. ; Ganzeveld, L.N. ; Breitenberger, C. ; Mammarella, I. ; Williams, J. ; Lelieveld, J. - \ 2012
    Atmospheric Chemistry and Physics 12 (2012). - ISSN 1680-7316 - p. 9335 - 9353.
    large-eddy simulation - aerosol formation - forest - model - entrainment - turbulence - evolution - inversion - emissions - exchanges
    We studied the atmospheric boundary layer (ABL) dynamics and the impact on atmospheric chemistry during the HUMPPA-COPEC-2010 campaign. We used vertical profiles of potential temperature and specific moisture, obtained from 132 radio soundings, to determine the main boundary layer characteristics during the campaign. We propose a classification according to several main ABL prototypes. Further, we performed a case study of a single day, focusing on the convective boundary layer, to analyse the influence of the dynamics on the chemical evolution of the ABL. We used a mixed layer model, initialized and constrained by observations. In particular, we investigated the role of large scale atmospheric dynamics (subsidence and advection) on the ABL development and the evolution of chemical species concentrations. We find that, if the large scale forcings are taken into account, the ABL dynamics are represented satisfactorily. Subsequently, we studied the impact of mixing with a residual layer aloft during the morning transition on atmospheric chemistry. The time evolution of NOx and O3 concentrations, including morning peaks, can be explained and accurately simulated by incorporating the transition of the ABL dynamics from night to day. We demonstrate the importance of the ABL height evolution for the representation of atmospheric chemistry. Our findings underscore the need to couple the dynamics and chemistry at different spatial scales (from turbulence to mesoscale) in chemistry-transport models and in the interpretation of observational data.
    Optimizing global CO emission estimates using a four-dimensional variational data assimilation system and surface network observations
    Hooghiemstra, P.B. ; Krol, M.C. ; Meirink, J.F. ; Bergamaschi, P. ; Werf, G.R. van der; Novelli, P.C. ; Aben, I. ; Röckmann, T. - \ 2011
    Atmospheric Chemistry and Physics 11 (2011)10. - ISSN 1680-7316 - p. 4705 - 4723.
    carbon-monoxide - tropospheric chemistry - fire emissions - model tm5 - inversion - mopitt - adjoint - forest - asia - algorithm
    We apply a four-dimensional variational (4D-VAR) data assimilation system to optimize carbon monoxide (CO) emissions for 2003 and 2004 and to reduce the uncertainty of emission estimates from individual sources using the chemistry transport model TM5. The system is designed to assimilate large (satellite) datasets, but in the current study only a limited amount of surface network observations from the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) is used to test the 4D-VAR system. By design, the system is capable to adjust the emissions in such a way that the posterior simulation reproduces background CO mixing ratios and large-scale pollution events at background stations. Uncertainty reduction up to 60 % in yearly emissions is observed over well-constrained regions and the inferred emissions compare well with recent studies for 2004. However, with the limited amount of data from the surface network, the system becomes data sparse resulting in a large solution space. Sensitivity studies have shown that model uncertainties (e.g., vertical distribution of biomass burning emissions and the OH field) and the prior inventories used, influence the inferred emission estimates. Also, since the observations only constrain total CO emissions, the 4D-VAR system has difficulties in separating anthropogenic and biogenic sources in particular. The inferred emissions are validated with NOAA aircraft data over North America and the agreement is significantly improved from the prior to posterior simulation. Validation with the Measurements Of Pollution In The Troposphere (MOPITT) instrument version 4 (V4) shows a slight improved agreement over the well-constrained Northern Hemisphere and in the tropics (except for the African continent). However, the model simulation with posterior emissions underestimates MOPITT CO total columns on the remote Southern Hemisphere (SH) by about 10 %. This is caused by a reduction in SH CO sources mainly due to surface stations on the high southern latitudes.
    The seasonal cycle amplitude of total column CO2: Factors behind the model-observation mismatch
    Basu, S. ; Houweling, S. ; Peters, W. ; Sweeney, C. ; Machida, T. ; Maksyutov, S. - \ 2011
    Journal of Geophysical Research: Atmospheres 116 (2011)D23. - ISSN 2169-897X - 14 p.
    carbon-dioxide exchange - in-situ observations - atmospheric co2 - lower stratosphere - transport - inversion - sinks - constraints - calibration - delta-c-13
    CO2 surface fluxes that are statistically consistent with surface layer measurements of CO2, when propagated forward in time by atmospheric transport models, underestimate the seasonal cycle amplitude of total column CO2 in the Northern temperate latitudes by 1-2 ppm (Yang et al, 2007). In this manuscript we verify the systematic nature of this underestimation at a number of TCCON stations by comparing their measurements with a number of transport models. In particular, at Park Falls, Wisconsin (USA) we estimate this mismatch to be 1.4 ppm, and try to attribute portions of this mismatch to different factors affecting the total column. We find that errors due to the averaging kernel and prior used in forward models, water vapor in the model atmosphere, incorrect vertical transport by transport models in the free troposphere, incorrect aging of air in transport models in the stratosphere, and airmass dependence in TCCON data can explain up to 1 ppm of this mismatch. The remaining 0.4 ppm mismatch is at the edge of the accuracy requirement on satellite measurements to improve on our current estimate of surface fluxes. Uncertainties in the biosphere fluxes driving the transport models could explain a part of the remaining mismatch, implying that with corrections to the factors behind the accounted-for 1 ppm underestimation, present inverse modeling frameworks could effectively assimilate satellite CO2 measurements.
    The role of boundary layer dynamics on the diurnal evolution of isoprene and the hydroxyl radical over tropical forests
    Vilà-Guerau de Arellano, J. ; Patton, E.G. ; Karl, T. ; Dries, K. van den; Barth, M.C. ; Orlando, J.J. - \ 2011
    Journal of Geophysical Research: Atmospheres 116 (2011)D7. - ISSN 2169-897X - 16 p.
    large-eddy simulation - atmospheric chemistry - stiff odes - fluxes - entrainment - emissions - scalars - model - hydrocarbons - inversion
    We investigate diurnal variability of isoprene and related chemical species in the Amazonian region. The dynamics and chemistry of an atmospheric boundary layer are studied with a large-eddy simulation code and a mixed-layer model which are guided by observations available for the same area. The main features of isoprene and related species are reproduced well, but their evolution raises questions regarding the physical and chemical processes responsible for the observed diurnal behaviors. To address these questions, we systematically examine the role of (1) the exchange of chemical species between the free troposphere and the atmospheric boundary layer (entrainment), (2) surface isoprene and nitric oxide emissions, and (3) new chemical pathways to recycle the hydroxyl radical. The entrainment flux of isoprene is shown to be equally important as surface isoprene emissions in determining the isoprene temporal evolution. Varying the relationship between the initial isoprene mixing ratio in the boundary layer and that in the overlying free troposphere in the early morning results in an 50% increase/decrease in isoprene mixing ratio or more within the atmospheric boundary layer at noon. Entrainment of free tropospheric nitrogen oxides creates changes of similar magnitude to the boundary layer isoprene mixing ratio. These effects of entrainment and surface emissions on isoprene are found for two different chemical regimes. The introduction of an OH recycling pathway in the chemical mechanism increases midday OH. Our findings show that atmospheric dynamics and chemistry are equally important for interpreting the diurnal observation of reactants and for including in regional-scale modeling efforts where turbulence is parameterized.
    Estimating forest variables from top-of-atmosphere radiance satellite measurements using coupled radiative transfer models
    Laurent, V.C.E. ; Verhoef, W. ; Clevers, J.G.P.W. ; Schaepman, M.E. - \ 2011
    Remote Sensing of Environment 115 (2011)4. - ISSN 0034-4257 - p. 1043 - 1052.
    leaf-area index - bidirectional reflectance - biophysical variables - global products - canopy - vegetation - inversion - validation - simulation - albedo
    Traditionally, it is necessary to pre-process remote sensing data to obtain top of canopy (TOC) reflectances before applying physically-based model inversion techniques to estimate forest variables. Corrections for atmospheric, adjacency, topography, and surface directional effects are applied sequentially and independently, accumulating errors into the TOC reflectance data, which are then further used in the inversion process. This paper presents a proof of concept for demonstrating the direct use of measured top-of-atmosphere (TOA) radiance data to estimate forest biophysical and biochemical variables, by using a coupled canopy–atmosphere radiative transfer model. Advantages of this approach are that no atmospheric correction is needed and that atmospheric, adjacency, topography, and surface directional effects can be directly and more accurately included in the forward modelling. In the case study, we applied both TOC and TOA approaches to three Norway spruce stands in Eastern Czech Republic. We used the SLC soil–leaf–canopy model and the MODTRAN4 atmosphere model. For the TOA approach, the physical coupling between canopy and atmosphere was performed using a generic method based on the 4-stream radiative transfer theory which enables full use of the directional reflectance components provided by SLC. The method uses three runs of the atmosphere model for Lambertian surfaces, and thus avoids running the atmosphere model for each new simulation. We used local sensitivity analysis and singular value decomposition to determine which variables could be estimated, namely: canopy cover, fraction of bark, needle chlorophyll, and dry matter content. TOC and TOA approaches resulted in different sets of estimates, but had comparable performance. The TOC approach, however, was at its best potential because of the flatness and homogeneity of the area. On the contrary, the capacities of the TOA approach would be better exploited in heterogeneous rugged areas. We conclude that, having similar performance, the TOA approach should be preferred in situations where minimizing the pre-processing is important, such as in data assimilation and multi-sensor studies.
    Understanding the daily cycle of evapotranspiration: a method to quantify the influence of forcings and feedbacks
    Heerwaarden, C.C. van; Vilà-Guerau de Arellano, J. ; Gounou, A. ; Guichard, F. ; Couvreux, F. - \ 2010
    Journal of Hydrometeorology 11 (2010)6. - ISSN 1525-755X - p. 1405 - 1422.
    convective boundary-layer - land-atmosphere interaction - diurnal time scales - soil-moisture - surface - model - evaporation - parameterization - entrainment - inversion
    A method to analyze the daily cycle of evapotranspiration over land is presented. It quantifies the influence of external forcings, such as radiation and advection, and of internal feedbacks induced by boundary layer, surface layer, and land surface processes on evapotranspiration. It consists of a budget equation for evapotranspiration that is derived by combining a time derivative of the Penman–Monteith equation with a mixed-layer model for the convective boundary layer. Measurements and model results for days at two contrasting locations are analyzed using the method: midlatitudes (Cabauw, Netherlands) and semiarid (Niamey, Niger). The analysis shows that the time evolution of evapotranspiration is a complex interplay of forcings and feedbacks. Although evapotranspiration is initiated by radiation, it is significantly regulated by the atmospheric boundary layer and the land surface throughout the day. In both cases boundary layer feedbacks enhance the evapotranspiration up to 20 W m-2 h-1. However, in the case of Niamey this is offset by the land surface feedbacks since the soil drying reaches -30 W m-2 h-1. Remarkably, surface layer feedbacks are of negligible importance in a fully coupled system. Analysis of the boundary layer feedbacks hints at the existence of two regimes in this feedback depending on atmospheric temperature, with a gradual transition region in between the two. In the low-temperature regime specific humidity variations induced by evapotranspiration and dry-air entrainment have a strong impact on the evapotranspiration. In the high-temperature regime the impact of humidity variations is less pronounced and the effects of boundary layer feedbacks are mostly determined by temperature variations
    Can we reconcile atmospheric estimates of the Northern terrestrial carbon sink with land-based accounting?
    Ciais, P. ; Canadell, J. ; Luyssaert, S. ; Chevallier, F. ; Shvidenko, A. ; Poussi, Z. ; Jonas, M. ; Peylin, P. ; King, A. ; Schulze, E.D. ; Piao, S. ; Rödenbeck, C. ; Peters, W. ; Bréon, F.M. - \ 2010
    Current Opinion in Environmental Sustainability 2 (2010)4. - ISSN 1877-3435 - p. 225 - 230.
    co2 sources - dioxide exchange - transport - inversion - balance - fluxes - sensitivity - emissions
    We estimate the northern hemisphere (NH) terrestrial carbon sink by comparing four recent atmospheric inversions with land-based C accounting data for six large northern regions. The mean NH terrestrial CO2 sink from the inversion models is 1.7 Pg C year-1 over the period 2000–2004. The uncertainty of this estimate is based on the typical individual (1-sigma) precision of one inversion (0.9 Pg C year-1) and is consistent with the min–max range of the four inversion mean estimates (0.8 Pg C year-1). Inversions agree within their uncertainty for the distribution of the NH sink of CO2 in longitude, with Russia being the largest sink. The land-based accounting estimate of NH carbon sink is 1.7 Pg C year-1 for the sum of the six regions studied. The 1-sigma uncertainty of the land-based estimate (0.3 Pg C year-1) is smaller than that of atmospheric inversions, but no independent land-based flux estimate is available to derive a ‘between accounting model’ uncertainty. Encouragingly, the top-down atmospheric and the bottom-up land-based methods converge to consistent mean estimates within their respective errors, increasing the confidence in the overall budget. These results also confirm the continued critical role of NH terrestrial ecosystems in slowing down the atmospheric accumulation of anthropogenic CO2
    A spectral directional reflectance model of row crops
    Zhao, F.J. ; Gu, X.F. ; Verhoef, W. ; Wang, Q. ; Yu, T. ; Liu, Q. ; Huang, H.A. ; Qin, W. ; Chen, Liangfu ; Zhao, H. - \ 2010
    Remote Sensing of Environment 114 (2010)2. - ISSN 0034-4257 - p. 265 - 285.
    canopy reflectance - bidirectional reflectance - radiative-transfer - leaf canopies - gap probability - plant canopy - vegetation - scattering - light - inversion
    A computationally efficient reflectance model for row planted canopies is developed in this paper through separating the contributions of incident direct and diffuse radiation scattered by row canopies. The row model allows calculating the reflectance spectrum in any given direction for the optical spectral region. The performance of the model is evaluated through comparisons with field measurements of winter wheat as well as with an established 3D computer simulation model. Especially the systematic comparisons with the computer simulation model demonstrate that the model can adequately simulate the characteristic distribution of directional reflectance factors of row canopies, which is shown in the polar map of reflectance as a high or low value stripe approximately parallel to the row orientation, besides the hotspot effect. Physical mechanisms causing the dynamics were proposed and supported by comparison studies. The features of reflectance distributions of row canopies, which are distinctively different from those of homogeneous canopy, imply that it is problematic to use one-dimensional radiation transfer model to interpret radiation data and estimate the structural or spectral parameters of row canopies from reflectance measurements. Finally, further improvements needed for the current model are briefly discussed
    A high-density SNP-based linkage map of the chicken genome reveals sequence features correlated with recombination rate
    Groenen, M.A.M. ; Wahlberg, O. ; Foglio, M. ; Cheng, H.H. ; Megens, H.J.W.C. ; Crooijmans, R.P.M.A. ; Besnier, F. ; Lathrop, A. ; Muir, W.M. ; Wong, G.K. ; Gut, I. ; Andersson, L. - \ 2009
    Genome Research 19 (2009). - ISSN 1088-9051 - p. 510 - 519.
    genetic maps - physical map - sex - chromosome - evolution - polymorphisms - frequencies - difference - inversion - markers
    The resolution of the chicken consensus linkage map has been dramatically improved in this study by genotyping 12,945 single nucleotide polymorphisms (SNPs) on three existing mapping populations in chicken: the Wageningen (WU), East Lansing (EL), and Uppsala (UPP) mapping populations. As many as 8599 SNPs could be included, bringing the total number of markers in the current consensus linkage map to 9268. The total length of the sex average map is 3228 cM, considerably smaller than previous estimates using the WU and EL populations, reflecting the higher quality of the new map. The current map consists of 34 linkage groups and covers at least 29 of the 38 autosomes. Sex-specific analysis and comparisons of the maps based on the three individual populations showed prominent heterogeneity in recombination rates between populations, but no significant heterogeneity between sexes. The recombination rates in the F1 Red Jungle fowl/White Leghorn males and females were significantly lower compared with those in the WU broiler population, consistent with a higher recombination rate in purebred domestic animals under strong artificial selection. The recombination rate varied considerably among chromosomes as well as along individual chromosomes. An analysis of the sequence composition at recombination hot and cold spots revealed a strong positive correlation between GC-rich sequences and high recombination rates. The GC-rich cohesin binding sites in particular stood out from other GC-rich sequences with a 3.4-fold higher density at recombination hot spots versus cold spots, suggesting a functional relationship between recombination frequency and cohesin binding
    CO2 budgeting at the regional scale using a Lagrangian experimental strategy and meso-scale modeling
    Sarrat, C. ; Noilhan, J. ; Lacarrere, P. ; Masson, P.J.H. ; Ceschia, E. ; Ciais, P. ; Dolman, H. ; Elbers, J.A. ; Gerbig, C. ; Jarosz, N. - \ 2009
    Biogeosciences 6 (2009). - ISSN 1726-4170 - p. 113 - 127.
    klimaatverandering - kooldioxide - modellen - bovenlagen - emissie - climatic change - carbon dioxide - models - surface layers - emission - hapex-mobilhy - atmospheric co2 - surface - parameters - resolution - inversion - database - fluxes
    An atmospheric Lagrangian experiment for regional CO2 budgeting with aircraft measurements took place during the CarboEurope Regional Experiment Strategy campaign (CERES) in south-west France, in June 2005. The atmospheric CO2 aircraft measurements taken upstream and downstream of an active and homogeneous pine forest revealed a CO2 depletion in the same air mass, using a Lagrangian strategy. This field experiment was analyzed with a meteorological meso-scale model interactively coupled with a surface scheme, with plant assimilation, ecosystem respiration, anthropogenic CO2 emissions and sea fluxes. First, the model was carefully validated against observations made close to the surface and in the atmospheric boundary layer. Then, the carbon budget was evaluated using the numerous CERES observations, by upscaling the surface fluxes observations, and using the modeling results, in order to estimate the relative contribution of each physical process. A good agreement is found between the two methods which use the same vegetation map: the estimation of the regional CO2 surface flux by the Eulerian meso-scale model budget is close to the budget deduced from the upscaling of the observed surface fluxes, and found a budget between -9.4 and -12.1 µmol.m-2.s-1, depending on the size of the considered area. Nevertheless, the associated uncertainties are rather large for the upscaling method and reach 50%. A third method, using Lagrangian observations of CO2 estimates a regional CO2 budget a few different and more scattered, (-16.8 µmol.m-2.s-1 for the small sub-domain and -8.6 µmol.m-2.s-1 for the larger one). For this budgeting method, we estimate a mean of 31% error, mainly arising from the time of integration between the two measurements of the Lagrangian experiment. The paper describes in details the three methods to assess the regional CO2 budget and the associated errors
    Quantitative forest canopy structure assessment using an inverted geometric-optical model and up-scaling
    Zeng, Y. ; Schaepman, M.E. ; Wu, B. ; Clevers, J.G.P.W. ; Bregt, A.K. - \ 2009
    International Journal of Remote Sensing 30 (2009)6. - ISSN 0143-1161 - p. 1385 - 1406.
    spectral mixture analysis - resolution image data - reflectance model - bidirectional reflectance - biophysical structure - solar-radiation - ground cover - inversion - site
    The physical-based geometric-optical Li-Strahler model can be inverted to retrieve forest canopy structural variables. One of the main input variables of the inverted model is the fractional component of sunlit background (K g). K g is calculated by using pure reflectance spectra (endmembers) of the viewed surface components. In this paper, the feasibility of up-scaling from high (Quickbird) to medium (Hyperion) spatial resolution data for extracting the required endmembers is demonstrated. Furthermore, the sensitivity of the endmembers used as input for inverting Li-Strahler model is evaluated. After validating the inverted model results, namely spatially explicit forest mean crown closure and crown diameter using field measurements, it can be concluded that the regional scaling-based endmembers derived from the linear unmixing model are the best ones to be used in combination with the inverted Li-Strahler model for quantitatively monitoring disturbance in forest canopy structure
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