Enric Valor

Mapping land surface emissivity from NDVI: Application to European, African, and South American areas

Thermal infrared emissivity is an important parameter both for surface characterization and for atmospheric correction methods. Mapping the emissivity from satellite data is therefore a very important question to solve. The main problem is the coupling of the temperature and emissivity effects in the thermal radiances. Several methods have been developed to obtain surface emissivity from satellite data. In this way we propose a theoretical model that relates the emissivity to the NDVI (normalized difference vegetation index) of a given surface and explains the experimental behavior observed by van de Griend and Owe. We can use it to obtain the emissivity in any thermal channel, but in this work we have focused on the 10.5- to 12.5-μm region, where most thermal sensors on board satellites work at present. The model is applicable to areas with several soil and vegetation types and where the vegetation cover changes. From the theoretical model we have developed an operational methodology to obtain the effective emissivity combining satellite images and field measurements. The error of the methodology ranges from 0.5% (due to the experimental limitations of the field methods) to 2% (considering the case in which we have no information about the studied area). To check the general validity of the model, we have validated and applied it in different atmospheric environments and in areas with a different degree of roughness, i.e., from midlatitude (France, Argentina) to tropical (Sahel, Botswana) atmospheres, and from flat (La Mancha, Spain) to rough (Valencia, Spain) surfaces, and we have obtained an error of estimate of 0.6% on the emissivity.

CO2 Prices, Energy and Weather

One of the main objectives of the European Union Emission Trading Scheme is the establishment of a market price level for allowances that show to European CO2 emitting installations the environmental impact of their polluting activities. The aim of this paper is to focus on the daily price changes during 2005 in an attempt to examine the underlying rationality of pricing behaviour. Specifically, we study the effect of those weather and non-weather variables that academic and market agents consider as the major determinants of the of CO2 price levels. The results show that the energy sources are the principal factors in the determination of CO2 price levels, and that only extreme temperatures influence them.

Temperature and seasonality influences on Spanish electricity load

Abstract Deregulation of the Spanish electricity market in 1998 and the possible listing of electricity or weather derivative contracts have encouraged the study of the relationship between electricity demand and weather in Spain. In this paper, a transfer function intervention model is developed for forecasting daily electricity load from cooling and heating degree–days. The influence of weather and seasonality is proved, and is significant even when the autoregressive effects and the dynamic specification of the temperature are taken into account. The estimated general model shows a high predictive power. The results and information presented in this paper could be of interest for current users and potential traders in the deregulated Spanish electricity market.

Daily Air Temperature and Electricity Load in Spain

Abstract Weather has a significant impact on different sectors of the economy. One of the most sensitive is the electricity market, because power demand is linked to several weather variables, mainly the air temperature. This work analyzes the relationship between electricity load and daily air temperature in Spain, using a population-weighted temperature index. The electricity demand shows a significant trend due to socioeconomic factors, in addition to daily and monthly seasonal effects that have been taken into account to isolate the weather influence on electricity load. The results indicate that the relationship is nonlinear, showing a “comfort interval” of ±3°C around 18°C and two saturation points beyond which the electricity load no longer increases. The analysis has also revealed that the sensitivity of electricity load to daily air temperature has increased along time, in a higher degree for summer than for winter, although the sensitivity in the cold season is always more significant than in th...

On the atmospheric dependence of the split-window equation for land surface temperature

Abstract A split-window equation is derived for land surface temperature, yielding T = T4 + A(T4 − T5) + B(e), where T is the true surface temperature, T4 and T5 are the brightness temperatures measured in AVHRR channels 4 and 5, A is a coefficient related to the atmospheric transmittances in AVHRR channels 4 and 5, being dependent on the atmosphere type and independent on surface emissivity, and B(e) takes into account the emissivity effect, which depends on both the channel surface emissivities (e4 and e5) and the atmosphere type. The atmospheric dependence of split-window coefficients, A and B(e), is discussed by means of satellite measurements simulations and in situ data. It is shown that linear, global-scale algorithms can produce inaccurate estimates of surface temperature when they are applied to areas of reduced atmospheric variability. A simple, non-linear split-window algorithm has been proposed, in which A = a0+ a1(T4− T5). The constants a0and a1 have been calculated from a set of in situ and ...

Land surface emissivity and temperature determination in the whole HAPEX-Sahel area from AVHRR data

Most of the developed methods for land surface temperature retrieval have been derived for mid-latitude atmospheres and their application in tropical areas is very limited. The aim of this paper is to discuss the applicability of a global split-window method, developed by the authors, in a tropical environment as well as to analyse the accuracy in determining LST in tropical areas. The accuracy of this split-window method is about 2degK, which is a reasonable value taking into account the large atmospheric attenuation in tropical environments. We have performed this study in the framework of the Hydrologic Atmospheric Pilot Experiment in the Sahel (HAPEX-Sahel), showing the results for the whole HAPEX-Sahel area (13 -14 N; 2-3 E). To complete the study, an intercomparison of the existing split-window methods has also been carried out in this area.

Spanish Stock Returns: Where is the Weather Effect?

Psychological studies support the existence of an influence of weather on mood. Saunders (1993) and Hirshleifer and Shumway (2001) argue that the weather could affect the behaviour of market traders and, therefore, it should be reflected in the stock returns. This paper investigates the possible relation between weather and market index returns in the context of the Spanish market. In 1989, this market changed its open outcry trading system into a computerised and decentralised trading system. Therefore, it is possible to check the influence of weather variables (sunshine hours and humidity levels) on index returns in an open outcry trading system, and to compare it with a screen traded environment. The empirical evidence indicates that, independently of the trading system, there is no influence of weather on stock prices. Thus, these findings do not contest the notion of efficient markets.

An Atmospheric Radiosounding Database for Generating Land Surface Temperature Algorithms

A database of global, cloud-free, and atmospheric radiosounding profiles was compiled with the aim of simulating radiometric measurements from satellite-borne sensors in the thermal infrared. The objective of the simulated data is to generate split-window (SW) and dual-angle (DA) algorithms for the retrieval of land surface temperature (LST) from Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) and Envisat/Advanced Along Track Scanning Radiometer (AATSR) data. The database contains 382 radiosounding profiles acquired over land, with nearly uniform distribution of precipitable water between 0.02 and 5.5 cm. Radiative transfer calculations were performed with the MODTRAN 4 code for six viewing angles between 0deg and 60deg. The resulting radiance spectra were convoluted with the response filter functions of MODIS bands 31 and 32 and AATSR channels at 11 and 12 mum. By using the simulation database, the SW algorithms adapted for MODIS and AATSR data and the DA algorithms for AATSR data were developed. Both types of algorithms are quadratic in the brightness temperature difference and depend explicitly on the land surface emissivity. The SW and DA algorithms were validated with actual ground measurements of LST collected concurrently to MODIS and AATSR observations in a site located close to the city of Valencia, Spain, in a large, flat, and thermally homogeneous area of rice crops. The results obtained have no bias and a standard deviation around plusmn0.5 K for the SW algorithms at nadir for both sensors. The SW algorithm used in the forward view results in a bias of 0.6 K and a standard deviation of plusmn0.8 K. The worst results are obtained in the other algorithms with a bias close to -1.0 K and a standard deviation close to plusmn1.1 K in the case of the DA algorithms.

Soil Moisture Effect on Thermal Infrared (8–13-μm) Emissivity

Thermal infrared (TIR) emissivities of soils with different textures were measured for several soil moisture (SM) contents under controlled conditions using the Box method and a high-precision multichannel TIR radiometer. The results showed a common increase of emissivity with SM at water contents lower than the field capacity. However, this dependence is negligible for higher water contents. The highest emissivity variations were observed in sandy soils, particularly in the 8-9-μm range due to water adhering to soil grains and decreasing the reflectance in the 8-9-μm quartz doublet region. Thus, in order to model the emissivity dependence on soil water content, different approaches were studied according to the a priori soil information. Soil-specific relationships were provided for each soil texture and different spectral bands between 8 and 13 μm, with determination coefficients up to 0.99, and standard estimation errors in emissivity lower than ± 0.014. When considering a general relationship for all soil types, standard estimation errors up to ±0.03 were obtained. However, if other soil properties (i.e., organic matter, quartz, and carbonate contents) were considered, along with soil water content, the general relationship predicted TIR emissivities with a standard estimation error of less than ±0.008. Furthermore, the study showed the possibility of retrieving SM from TIR emissivities with a standard estimation error of about ±0.08 m3 . m-3.

Mapping land surface emissivity using AVHRR data application to La Mancha, Spain

Abstract Land surface temperature can be determined applying the split‐window technique to the AVHRR channels 4 and 5. However, for this purpose the knowledge of land surface emissivities in the AVHRR channels 4 and 5 is essential. The paper proposes a simple method for mapping the difference between channels 4 and 5 surface emissivities (?? = ?4 ‐ ?5) at the AVHRR spatial scale. The method is based on the availability of radiosounding data coincident to the NOAA overpass for the study area and on the knowledge of the mean value of the land surface emissivity for channels 4 and 5 (? = (?4 + ?5)/2). Therefore, two simple methods for measuring and mapping the mean value of emissivity are also proposed, which use a reference calibrated sand and the normalized difference vegetation index (NDVI), respectively. And finally, a complete example of application of the methodology developed on the La Mancha region, Spain, is shown.