Bernard Seguin

Meteorology and climatology

Abstract. One of the first disciplines in which remote sensing has had obvious applications is in meteorology. The main applications, which have been developed for using satellite data in manual and short term forecasting and for numerical weather prediction models, are described. Some examples arc also given to illustrate these applications. Meteorological applications require the data in near real time but if the data are processed and archived a useful data set for climatologica! research is also produced. Some examples of the application of satellite data to climatology are given. Finally some promising future developments in the use of satellite data in meteorology and climatology during the next ten years are briefly outlined.

Use of meteorological satellites for water balance monitoring in Sahelian regions

Abstract This study represents part of an EEC research programme to monitor crop water conditions during the south Saharan rainy season using satellite data. Primarily focused on the Senegalese area, it was mainly performed using Meteosat daytime thermal infrared data. The purpose was to establish a relationship between the satellite-derived land surface temperatures (Ts ) and the actual evapotranspiration (ET). After a preliminary study based on data from 1979 and 1983, the emphasis was put on the summers of 1984 and 1985. About thirty dates were selected for cloud-free conditions for each rainy season. Resulting surface temperatures were compared to measured rainfall and computed ET from the IRAT water-balance model for ten agrometeorological stations on a north-south transect depicting a steep water-balance gradient. The linear relationship obtained between Σ Ts and the cumulative rainfall is shown and the possible applications to rainfall mapping are discussed. This methodology is shown to be feasible...

NOAA AVHRR and its uses for rainfall and evapotranspiration monitoring

Abstract NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) Global Vegetation Indices (GVI) were used during the 1986 rainy season (June-September) over Senegal to monitor rainfall. The satellite data were used in conjunction with ground-based measurements so as to derive empirical relationships between rainfall and GVI. The regression obtained was then used to map the total rainfall corresponding to the growing season, yielding good results. Normalized Difference Vegetation Indices (NDVI) derived from High Resolution Picture Transmission (HRJT) data were also compared with actual evapotranspiration (ET) data and proved to be closely correlated with it with a time lapse of 20 days.

Including Croplands in a Global Biosphere Model: Methodology and Evaluation at Specific Sites

Abstract There is a strong international demand for quantitative estimates of both carbon sources/sinks, and water availability at the land surface at various spatial scales (regional to global). These estimates can be derived (and usually are) from global biosphere models, which simulate physiological, biogeochemical, and biophysical processes, using a variety of plant functional types. Now, the representation of the large area covered with managed land (e.g., croplands, grasslands) is still rather basic in these models, which were first designed to simulate natural ecosystems, while more and more land is heavily disturbed by man (crops cover ∼35% and grasslands ∼30%–40% of western Europes area as a result of massive deforestation mainly in the Middle Ages). In this paper a methodology is presented that combines the use of a dynamic global vegetation model (DGVM) known as Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) and a generic crop model [the Simulateur Multidisciplinaire pour les...

Surface temperature and evapotranspiration: Application of local scale methods to regional scales using satellite data

Abstract Remotely sensed surface temperatures have proven useful for monitoring evapotranspiration (ET) rates and crop water use because of their direct relationship with sensible and latent energy exchange processes. Procedures for using the thermal infrared (IR) obtained with hand-held radiometers deployed at ground level are now well established and even routine for many agricultural research and management purposes. The availability of IR from meteorological satellites at scales from 1 km (NOAA-AVHRR) to 5 km (METEOSAT) permits extension of local, ground-based approaches to larger scale crop monitoring programs. Regional observations of surface minus air temperature (i.e., the stress degree day) and remote estimates of daily ET were derived from satellite data over sites in France, the Sahel, and North Africa and summarized here. Results confirm that similar approaches can be applied at local and regional scales despite differences in pixel size and heterogeneity. This article analyzes methods for obtaining these data and outlines the potential utility of satellite data for operational use at the regional scale.

The assessment of regional crop water conditions from meteorological satellite thermal infrared data

Abstract Meteorological satellites (mainly NOAA AVHRR) have been extensively used these last years to monitor vegetation and crop conditions on a regional scale, using vegetation index NDVI data. Recent work with Nimbus-7 passive microwave measurements has also shown the complementary potential of that spectral domain. On the other hand, the thermal infrared channels, in spite of their well-known ability to detect water stress (as established by ground studies at a local scale), are less studied for the same purpose of long-term monitoring. This paper intends to demonstrate their capabilities in assessing crop water conditions on a regional scale and estimating the actual evapotranspiration (ET) to be used in agrometeorological models. A brief analysis of past studies justifies the use of the cumulative Σ(Ts − Ta) (difference between the midafternoon surface temperature by satellite and the maximum air temperature obtained from the meteorological ground network), named stress-degree-day by Jackson et al. (1977) which may be related to ET by a simplified linear relationship. This criterion, already tested in Sahelian regions (Seguin et al., 1989), is applied to France on a large scale, corresponding to the entire country, using 5-day syntheses from Meteosat, calibrated by NOAA AVHRR on selected dates, for 3 years (1985–1987). Values of Σ(Ts − Ta) may be considered as climatological data. They reveal both spatial differences in regional climates and the main features of each year. The use of the linear relationship, derived from ET values computed from a coupled energy budget-water balance model, allows one to estimate and map regional evaporation on a monthly to 6-month time basis. The variations obtained along a latitudinal transect display the relations between ET and potential evapotranspiration (PET), also leading to an indirect estimation of PET from remote sensing data. Σ(Ts − Ta)/Rn is proposed as an index of regional water stress, which may be derived from satellite data and appears as complementary to the integrated NDVI, with the advantage of a more physically established relationship with ET.

Agrometeorological soil water balance for crop simulation models

Abstract The use of crop simulation models on a large scale for agrometeorological purposes is often limited by their inputs being non-routinely collected data, especially with regard to their soil water balance compartment. The objective of this study is to develop a water balance sub-model which can be run with readily available inputs. The model predicts water use, soil evaporation and crop transpiration throughout the growing season. Physiological reduction factors, as influenced by water stress, are derived from the soil water availability. This is achieved by using empirical relationships such as the reservoir analogy to assess water availability in relation to root development. The framework of applicable conditions is assessed by sensitivity analyses performed on inputs: the model can be run with a time step of ten days and using soil information given by soil maps, i.e. soil texture and depth, which fit agrometeorological purposes. Moreover, the model is shown to describe realistically soil water depletion, crop evapotranspiration and rooting depth. However, wetting processes are not correctly simulated, especially when large amounts of water are supplied. This limitation is emphasized for ten day time steps. Therefore incorporating effective rainfall simulation, i.e. both runoff and rainfall interception by the canopy, would improve the model.

IRSUTE : A MINISATELLITE PROJECT FOR LAND SURFACE HEAT FLUX ESTIMATION FROM FIELD TO REGIONAL SCALE

Abstract Thermal infrared remote sensing has proved its usefulness in various environmental applications, including the evaluation of surface heat fluxes exchanged between the continental biosphere and the lower atmosphere. The concept of a minisatellite, IRSUTE, has been evaluated. It is designed to allow the derivation of accurate (±50 W m −2 or ±0.8 mm/d water evaporation) estimates of surface heat flux at the field scale (near 40 m). Such estimates will be useful for meteorological, hydrological, and agricultural studies. The instrument will also be useful for environmental monitoring, for example, frost mapping, forest fires, volcano activity, thermal pollution, etc. The IRSUTE concept has been further elaborated by conducting scientific studies (modeling canopy radiative temperature, method for flux estimation, ergodicity problem, emissivity of natural surfaces, correction of atmospheric effect), by analyzing methodological aspects (definition of pixel size, overpass time, time repeat cycle, analysis of angular effects) and system specification (superposition error and MTF effects assessment). These studies have resulted in the definition of a feasible instrument corresponding to the minisatellite category (95 kg), with a high spatial resolution (40 m), four bands in the thermal infrared domain (3.5–4.0 μm and three bands between 8.2 μm and 11.0 μm, with two options), a 1-day revisit, corresponding to an orbite altitude of 540 km. The narrow ground swath (40 km) precludes a global coverage; as a result IRSUTE will focus on a set of test-sites. The phase A study is now complete. The main elements of IRSUTE are defined. This article describes the IRSUTE mission characteristics and the main experimental results which led to the chosen specifications.

Teledetection et bilan hydrique: Utilisation combinee d'un modele agrometeorologique et des donnees de l'IR thermique du satellite NOAA-AVHRR

Abstract The monitoring of water balance from satellite thermal infra-red data is limited by the frequency of clear days necessary to obtain images: interpolation between precise data is therefore possible only by the modelling of crop energy and water balance. The agrometeorological model of Choisnel is improved in order to get a better estimation of hourly surface temperature of a short crop (grass ...). It is then compared to thermal infra-red data of NOAA satellite on South-East of France. This remote sensing and modelling approach permits the study of the spatial variability of soil water holding capacity, the estimation of irrigation water supply in a homogeneous area and the drawing of a first map of the daily evapotranspiration in the lower Rhone Valley.

Frost mapping using NOAA AVHRR data in the Pampean region, Argentina

Abstract On 4 November 1992, the southern and western parts of the Pampean region, Argentina were affected by a frost that caused serious damage to crops and particularly to the wheat in flowering. Frosts were also reported for 5 and 23 November in the northeast and the southeast parts, respectively. In order to assess the frost affected areas, brightness temperatures recorded around 03:00 am from the NOAA-AVHRR sensor were examined for the three dates and the whole area (500 000 km 2 ). Qualitatively, the temperature spatial distribution derived from AVHRR data agreed with the reports on the affected areas. To retrieve the actual surface temperature, in theory more appropriate than minimum air temperature ( T n ) for frost mapping, 12 split-window algorithms were performed. However, the uncertainties on the surface temperatures retrieved on the one hand and the non-optimal overpass time of the satellite on the other led us to examine how well AVHRR temperatures could predict the T n registered by the meteorological network. The objective was hence to interpolate T n taking advantage of AVHRR spatial coverage. The split-window algorithms did not significantly improve the T n prediction obtained using brightness temperatures. Regressions of brightness temperatures against T n gave correlations of 0.81, 0.44 and 0.90 and standard deviations of 1.4, 1.9 and 1.7°C for 4, 5 and 23 November, respectively (using 41, 31 and 21 stations). Apart from the interdate variability, these correlations are satisfactory if we consider the different ‘nature’ of both temperatures and also the size of the study area. The introduction of geographical variables (latitude, longitude and altitude) did not significantly improve the correlations found. The posterior examination of AVHRR NDVI time profiles over affected and non affected areas permitted to confirm and complete the mapping of the damaged area.