191 research outputs found
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Do we (need to) care about canopy radiation schemes in DGVMs? Caveats and potential impacts
Dynamic global vegetation models (DGVMs) are an essential part of current state-of-the-art Earth system models. In recent years, the complexity of DGVMs has increased by incorporating new important processes like, e.g., nutrient cycling and land cover dynamics, while biogeophysical processes like surface radiation have not been developed much further. Canopy radiation models are however very important for the estimation of absorption and reflected fluxes and are essential for a proper estimation of surface carbon, energy and water fluxes.
The present study provides an overview of current implementations of canopy radiation schemes in a couple of state-of-the-art DGVMs and assesses their accuracy in simulating canopy absorption and reflection for a variety of different surface conditions. Systematic deviations in surface albedo and fractions of absorbed photosynthetic active radiation (faPAR) are identified and potential impacts are assessed.
The results show clear deviations for both, absorbed and reflected, surface solar radiation fluxes. FaPAR is typically underestimated, which results in an underestimation of gross primary productivity (GPP) for the investigated cases. The deviation can be as large as 25% in extreme cases. Deviations in surface albedo range between −0.15 ≤ Δα ≤ 0.36, with a slight positive bias on the order of Δα ≈ 0.04. Potential radiative forcing caused by albedo deviations is estimated at −1.25 ≤ RF ≤ −0.8 (W m−2), caused by neglect of the diurnal cycle of surface albedo.
The present study is the first one that provides an assessment of canopy RT schemes in different currently used DGVMs together with an assessment of the potential impact of the identified deviations. The paper illustrates that there is a general need to improve the canopy radiation schemes in DGVMs and provides different perspectives for their improvement
Consistent retrieval of land surface radiation products from EO, including traceable uncertainty estimates
Earth
observation (EO) land surface products have been demonstrated to provide a
constraint on the terrestrial carbon cycle that is complementary to the
record of atmospheric carbon dioxide. We present the Joint Research Centre
Two-stream Inversion Package (JRC-TIP) for retrieval of variables
characterising the state of the vegetation–soil system. The system provides a
set of land surface variables that satisfy all requirements for assimilation
into the land component of climate and numerical weather prediction models.
Being based on a 1-D representation of the radiative transfer
within the canopy–soil system, such as those used in the land surface
components of advanced global models, the JRC-TIP products are not only
physically consistent internally, but they also achieve a high degree of
consistency with these global models. Furthermore, the products are provided
with full uncertainty information. We describe how these uncertainties are
derived in a fully traceable manner without any hidden assumptions from the
input observations, which are typically broadband white sky albedo products.
Our discussion of the product uncertainty ranges, including the uncertainty
reduction, highlights the central role of the leaf area index, which describes
the density of the canopy. We explain the generation of products aggregated
to coarser spatial resolution than that of the native albedo input and
describe various approaches to the validation of JRC-TIP products, including the
comparison against in situ observations. We present a JRC-TIP processing
system that satisfies all operational requirements and explain how it
delivers stable climate data records. Since many aspects of JRC-TIP are
generic,
the package can serve as an example of a state-of-the-art system for
retrieval of EO products, and this contribution can help the user to
understand advantages and limitations of such products
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New Directions in Earth Observing: Scientific Applications ofMultiangle Remote Sensing
The physical interpretation of simultaneous multiangle observations represents a relatively new approach to remote
sensing of terrestrial geophysical and biophysical parameters. Multiangle measurements enable retrieval of physical scene
characteristics, such as aerosol type, cloud morphology and height, and land cover (e.g., vegetation canopy type), providing
improved albedo accuracies as well as compositional, morphological, and structural information that facilitates
addressing many key climate, environmental, and ecological issues. While multiangle data from wide field-of-view scanners
have traditionally been used to build up directional “signatures” of terrestrial scenes through multitemporal
compositing, these approaches either treat the multiangle variation as a problem requiring correction or normalization or
invoke statistical assumptions that may not apply to specific scenes. With the advent of a new generation of global imaging
spectroradiometers capable of acquiring simultaneous visible/near-IR multiangle observations, namely, the Along-
Track Scanning Radiometer-2, the Polarization and Directionality of the Earth’s Reflectances instrument, and the
Multiangle Imaging SpectroRadiometer, both qualitatively new approaches as well as quantitative improvements in
accuracy are achievable that exploit the multiangle signals as unique and rich sources of diagnostic information. This
paper discusses several applications of this technique to scientific problems in terrestrial atmospheric and surface geophysics
and biophysics
The state of the Martian climate
60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes
Global retrieval of bidirectional reflectance and albedo over land from EOS MODIS and MISR data: Theory and algorithm
This paper describes the theory and the algorithm to be used in producing a global bidirectional reflectance distribution function (BRDF) and albedo product from data to be acquired by the moderate resolution imaging spectroradiometer (MODIS) and the multiangle imaging spectroradiometer (MISR), both to be launched in 1998 on the AM-I satellite platform as part of NASA's Earth Observing System (EOS). The product will be derived using the kernel-driven semiempirical Ambrals BRDF model, utilizing five variants of kernel functions characterizing isotropic, volume and surface scattering. The BRDF and the albedo of each pixel of the land surface will be modeled at a spatial resolution of I km and once every 16 days in seven spectral bands spanning the visible and the near infrared. The BRDF parameters retrieved and recorded in the MODIS BRDF/albedo product will be intrinsic surface properties decoupled from the prevailing atmospheric state and hence suited for a wide range of applications requiring characterization of the directional anisotropy of Earth surface reflectance. A set of quality control flags accompanies the product. An initial validation of the Ambrals model is demonstrated using a variety of field-measured data sets for several different land cover types
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