NOAA's National Climatic Data Center
Veach-Baley Federal Building
151 Patton Avenue
Asheville, NC 28801-5001
Telephone: +1 828.257.3007
Dr. Pierre Guillevic received a Ph.D. in Radiative Transfer and Land Surface Modeling from Paul Sabatier University, Toulouse, France, in 1999. During his postdoctoral work with the Hydrological Sciences branch at NASA Goddard Space Flight Center in Greenbelt, MD, he participated in the NASA Seasonal to Interannual Prediction Project (NSIPP) and studied the influence of the interannual variability of vegetation parameters derived from satellite observations on seasonal climate prediction. In 2003, he joined the Laboratoire Central des Ponts et Chaussées (LCPC) (French Government research laboratory on public works) in France, as a research scientist. He conducted research on water and energy balance of urban surface for applications in road safety and urban hydrology, including field experiments and modeling approach. From 2007 and 2010, he developed new skills, mostly management and financial related, as a business engineer at VINCI, a major player in Europe’s construction, environment, energy and information technology services. His main research interests are the retrieval of land biophysical parameters from satellite remotely sensed observations with a focus on land surface temperature, and the calibration and validation of satellite products.
Dr. Guillevic joined CICS-NC as a senior scientist on July 1, 2010.
This task focuses on the development and use of a new validation methodology to estimate the quantitative uncertainty in the Land Surface Temperature (LST) Environmental Data Record (EDR( derived from Suomi NPP/VIIRS, and contribute to improving the retrieval algorithm. It employs a land surface model to scaling up point LST measurements currently made operationally at NOAA’s Climate Reference Network.
This task is part of the ongoing NPP/JPSS VIIRS Land Product Validation Plan (v. 1.0; 16 January 2009) for validation of the Land Environmental Data Records (EDRs) produced from the Visible Infrared Imager Radiometer Suite (VIIRS) of the Suomi National Polar-orbiting Partnership (NPP) and/or the Joint Polar Satellite System (JPSS). Suomi NPP/JPSS is a satellite system used to monitor global environmental conditions, and collect and disseminate data related to the atmosphere, oceans, land and the near-space environment.
NOAA will soon transition VIIRS on JPSS as its primary polar-orbiting satellite imager. Employing a near real-time processing system, NOAA will generate a series of EDRs from VIIRS data. For example, the VIIRS Land Surface Temperature (LST) EDR will estimate the surface skin temperature over all global land areas and provide key information for monitoring Earth surface energy and water fluxes. Since both VIIRS and its processing algorithms are new, NOAA is conducting a rigorous calibration and validation program to understand and improve product quality. This task represents a new validation methodology to estimate the quantitative uncertainty in the LST EDR, and contribute to improving the retrieval algorithm. It employs the SETHYS land surface model to scaling up point LST measurements currently made operationally at many field and weather stations around the world, e.g. NOAA’s Climate Reference Network (CRN). The scaling method consists of the merging information collected at different spatial resolutions within a land surface model to fully characterize large area (km x km scale) satellite products. The approach is used to explore scaling issues over terrestrial surfaces spanning a large range of climate regimes and land cover types, including forests and mixed vegetated areas.
This work represents a continuation and enhancement of previous activities.
The parameterizations of energy and water transfers used in the SEtHyS land surface model (Coudert et al., 2006) are conceptual and involve a set of parameters that cannot be routinely measured at ground level. For a given application, several parameters and initial conditions need to be estimated in order to obtain reliable simulated LST.
Suomi NPP VIIRS Land Surface Temperature (LST) and Climate Reference Network (CRN)
Figure 1: Representation of the scaling issue when using the NOAA’s Climate Reference Network (CRN) to validate LST EDR from Suomi NPP VIIRS. The approach combines point field data and fine resolution imagery in the SETHYS land surface model to characterize the LST over moderate resolution scales (750 meters).
Here, model calibration and data assimilation scheme consist of the minimization of a cost function expressing the divergence between model outputs and observations. To achieve a robust model calibration, we use the multi-objective calibration iterative process (MCIP; Demarty et al., 20052). Based on a stochastic Monte Carlo approach, MCIP represents the reduction of an initial parameter space by the optimization of one or several model outputs against observations, here LST. We fully implemented and tested the MCIP algorithm that is now integrated in the LST EDR validation scheme.
First, the validation methodology was tested successfully with NASA/MODIS data as proxy for NPP/VIIRS, at a mixed agricultural site located near Bondville, IL. Results indicate an absolute error for MODIS LST products of 2.0 K when accounting for scaling, and higher than 3 K without scaling. The VIIRS LST EDR requires a 1.5 K measurement accuracy and 2.5 K measurement precision. Ultimately, this validation approach should lead to an accurate and continuously assessed VIIRS LST products suitable to support weather forecast, hydrological applications, or climate studies. It is readily adaptable to other moderate resolution satellite systems.
Preliminary validation results indicate a bias of -0.3K and precision of 1.9K of the VIIRS LST EDR when using 13 clear-sky VIIRS granules over Bondville, IL (Fig. 1).
Characterization of LST spatial variability using airborne satellite and ground based data
NOAA/NCDC and CICS-NC are collaborating with the NOAA/ATDD and the University of Tennessee Space Institute's (UTSI) Aviation Systems and Flight Research Department in Tullahoma, TN, to utilize aircraft for performing measurements of LST over selected U.S. Climate Reference Network (USCRN) sites in the continental U.S. The goal is to provide data to quantify the spatial variability and representativeness of the single-point skin temperature measurement being recorded at USCRN sites. A secondary goal is to provide additional ground-truth data to validate scaling methodology used to validate VIIRS LST EDR over mixed vegetated areas.
Guillevic P., Privette J., Coudert B., Palecki M. A., Demarty J., Ottlé C. and Augustine J. A. (2012). Land Surface Temperature product validation using NOAA’s surface climate observation networks – Scaling methodology for the Visible Infrared Imager Radiometer Suite (VIIRS). Submitted to Remote Sensing of Environment.
1Coudert B., C. Ottlé, B. Boudevillain, J. Demarty, and P. Guillevic (2006), Contribution of thermal infrared remote sensing data in multiobjective calibration of a dual-source SVAT model. Journal of Hydrometeorology, 7, 404-420.
2Demarty J., Ottlé, C., Braud, I., Olioso, A., Gupta, H. V., & Bastidas, L. A. (2005). Constraining a physically based Soil–Vegetation–Atmosphere Transfer model with surface water content and thermal infrared brightness temperature measurements using a multiobjective approach. Water Resources Research, 41.