Search results for "Atmospheric model"
showing 10 items of 104 documents
Generation of global vegetation products from EUMETSAT AVHRR/METOP satellites
2020
We describe the methodology applied for the retrieval of global LAI, FAPAR and FVC from Advanced Very High Resolution Radiometer (AVHRR) onboard the Meteorological-Operational (MetOp) polar orbiting satellites also known as EUMETSAT Polar System (EPS). A novel approach has been developed for the joint retrieval of three parameters (LAI, FVC, and FAPAR) instead of training one model per parameter. The method relies on multi-output Gaussian Processes Regression (GPR) trained over PROSAIL EPS simulations. A sensitivity analysis is performed to assess several sources of uncertainties in retrievals and maximize the positive impact of modeling the noise in training simulations. We describe the ma…
Automatic emulator and optimized look-up table generation for radiative transfer models
2017
This paper introduces an automatic methodology to construct emulators for costly radiative transfer models (RTMs). The proposed method is sequential and adaptive, and it is based on the notion of the acquisition function by which instead of optimizing the unknown RTM underlying function we propose to achieve accurate approximations. The Automatic Gaussian Process Emulator (AGAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the good capabilities of the method in toy examples and for the construction of an…
Multioutput Automatic Emulator for Radiative Transfer Models
2018
This paper introduces a methodology to construct emulators of costly radiative transfer models (RTMs). The proposed methodology is sequential and adaptive, and it is based on the notion of acquisition functions in Bayesian optimization. Here, instead of optimizing the unknown underlying RTM function, one aims to achieve accurate approximations. The Automatic Multi-Output Gaussian Process Emulator (AMO-GAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the promising capabilities of the method for the const…
Vicarious Calibration of the Landsat 7 Thermal Infrared Band and LST Algorithm Validation of the ETM+ Instrument Using Three Global Atmospheric Profi…
2017
Due to problems in the thermal infrared sensor on-board the Landsat-8 satellite, Landsat-7 (L7) can be an interesting alternative source of thermal data because it is the only source of well-calibrated, free, high-resolution data. To contribute to the quality of thermal data, a vicarious calibration (VC) of the enhanced thematic mapper instrument and a validation of the single-channel general equation and the water vapor approach algorithm in conjunction with an inversion of the radiative transfer equation (RTE) have been performed during 2013–2015 over two Spanish test sites. For this purpose, three global atmospheric profile data sets were used to better characterize the error due to atmo…
Top-of-Atmosphere Retrieval of Multiple Crop Traits Using Variational Heteroscedastic Gaussian Processes within a Hybrid Workflow.
2021
In support of cropland monitoring, operational Copernicus Sentinel-2 (S2) data became available globally and can be explored for the retrieval of important crop traits. Based on a hybrid workflow, retrieval models for six essential biochemical and biophysical crop traits were developed for both S2 bottom-of-atmosphere (BOA) L2A and S2 top-of-atmosphere (TOA) L1C data. A variational heteroscedastic Gaussian process regression (VHGPR) algorithm was trained with simulations generated by the combined leaf-canopy reflectance model PROSAILat the BOA scale and further combined with the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) atmosphere model at the TOA scale. Establishe…
On the Dependence of Cirrus Parametrizations on the Cloud Origin
2019
<p>Particle size distributions (PSDs) for cirrus clouds are important for both climate models as well as many remote sensing retrieval methods. Therefore, PSD parametrizations are required. This study presents parametrizations of Arctic cirrus PSDs. The dataset used for this purpose originates from balloon-borne measurements carried out during winter above Kiruna (Sweden), i.e. north of the Arctic circle. The observations are sorted into two types of cirrus cloud origin, either in-situ or liquid. The cloud origin describes the formation pathway of the ice particles. At temperatures below −38 °C, ice particles form in-situ from solution or ice nuclea…
Oxygen transmittance correction for solar-induced chlorophyll fluorescence measured on proximal sensing: Application to the NASA-GSFC fusion tower
2017
Since oxygen (O 2 ) absorption of light becomes more pronounced at higher pressure levels, even a few meters distance between the target and the sensor can strongly affect canopy-leaving Solar-Induced chlorophyll Fluorescence (SIF) retrievals. This study was conducted to quantify the consequent error propagation and the impact of ignoring oxygen absorption effects on proximal sensing SIF measurements based on the O 2 -A absorption band with field-acquired and simulated data. It was demonstrated that the uncorrected oxygen transmittance between target and sensor distance of 10 m can lead to SIF relative errors ranging from 66% to higher than 100% when using a Spectral Fitting (SF) technique …
Nonlinear statistical retrieval of surface emissivity from IASI data
2017
Emissivity is one of the most important parameters to improve the determination of the troposphere properties (thermodynamic properties, aerosols and trace gases concentration) and it is essential to estimate the radiative budget. With the second generation of infrared sounders, we can estimate emissivity spectra at high spectral resolution, which gives us a global view and long-term monitoring of continental surfaces. Statistically, this is an ill-posed retrieval problem, with as many output variables as inputs. We here propose nonlinear multi-output statistical regression based on kernel methods to estimate spectral emissivity given the radiances. Kernel methods can cope with high-dimensi…
Quantification of LAI interannual anomalies by adjusting climatological patterns
2011
International audience; Scaling variations and shifts in the timing of seasonal phenology are central features of global change research. In this study, we propose a novel climatology fitting approach to quantify inter-annual anomalies in LAI seasonality. A consistent archive of daily LAI estimates was first derived from historical AVHRR satellite data for the 1981-2000 period over a globally representative sample of sites. The climatology values were then computed by averaging multi-year LAI profiles, gap filling and smoothing to eliminate possible high temporal frequency residual artifacts. The inter-annual variations in LAI were finally quantified by scaling and shifting the seasonal cli…
Atmospheric water vapor content over land surfaces derived from the AVHRR data: application to the Iberian Peninsula
1999
A study has been carried out using simulated NOAA/advanced very high resolution radiometer (AVHRR) data at 11 and 12 /spl mu/m (with LOWTRAN-7, MODTRAN 2.0, and the TIGR database), AVHRR images of the Iberian Peninsula and the Palma de Mallorca Island, radiosonde observations at seven meteorological stations, and the AVISO database provided by Meteo France to describe, compare, and analyze two different approaches for estimating the total atmospheric water vapor content (W) over land surfaces from AVHRR data. These two techniques are: 1) the split-window covariance-variance ratio (SWCVR), based on a quadratic relationship between W and the ratio of the spatial covariance and variance of bri…