Cristian Mattar

Record-breaking warming and extreme drought in the Amazon rainforest during the course of El Niño 2015-2016.

The El Niño-Southern Oscillation (ENSO) is the main driver of interannual climate extremes in Amazonia and other tropical regions. The current 2015/2016 EN event was expected to be as strong as the EN of the century in 1997/98, with extreme heat and drought over most of Amazonian rainforests. Here we show that this protracted EN event, combined with the regional warming trend, was associated with unprecedented warming and a larger extent of extreme drought in Amazonia compared to the earlier strong EN events in 1982/83 and 1997/98. Typical EN-like drought conditions were observed only in eastern Amazonia, whilst in western Amazonia there was an unusual wetting. We attribute this wet-dry dipole to the location of the maximum sea surface warming on the Central equatorial Pacific. The impacts of this climate extreme on the rainforest ecosystems remain to be documented and are likely to be different to previous strong EN events.

Thermal remote sensing in the framework of the SEN2FLEX project: field measurements, airborne data and applications

A description of thermal radiometric field measurements carried out in the framework of the European project SENtinel‐2 and Fluorescence Experiment (SEN2FLEX) is presented. The field campaign was developed in the region of Barrax (Spain) during June and July 2005. The purpose of the thermal measurements was to retrieve biogeophysical parameters such as land surface emissivity (LSE) and temperature (LST) to validate airborne‐based methodologies and to characterize different surfaces. Thermal measurements were carried out using two multiband field radiometers and several broadband field radiometers, pointing at different targets. High‐resolution images acquired with the Airborne Hyperspectral Scanner (AHS) sensor were used to retrieve LST and LSE, applying the Temperature and Emissivity Separation (TES) algorithm as well as single‐channel (SC) and two‐channel (TC) methods. To this purpose, 10 AHS thermal infrared (TIR) bands (8–13 µm) were considered. LST and LSE estimations derived from AHS data were used to obtain heat fluxes and evapotranspiration (ET) as an application of thermal remote sensing in the context of agriculture and water management. To this end, an energy balance equation was solved using the evaporative fraction concept involved in the Simplified Surface Energy Balance Index (S‐SEBI) model. The test of the different algorithms and methods against ground‐based measurements showed root mean square errors (RMSE) lower than 1.8 K for temperature and lower than 1.1 mm/day for daily ET.

Temporal analysis of normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters to detect changes in the Iberian land cover between 1981 and 2001

In past decades, the Iberian Peninsula has been shown to have suffered vegetation changes such as desertification and reforestation. Normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters, estimated from data acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensor onboard the National Oceanic and Atmospheric Administration (NOAA) satellite series, are particularly adapted to assess these changes. This work presents an application of the yearly land-cover dynamics (YLCD) methodology to analyse the behaviour of the vegetation, which consists of a combined multitemporal study of the NDVI and LST parameters on a yearly basis. Throughout the 1981–2001 period, trend analysis of the YLCD parameters emphasizes the areas that have endured the greatest changes in their vegetation. This result is corroborated by results from previous studies.

Emissivity mapping over urban areas using a classification-based approach: Application to the Dual-use European Security IR Experiment (DESIREX)

Abstract In this work a methodology to provide an emissivity map of an urban area is presented. The methodology is applied to the city of Madrid (Spain) using data provided by the Airborne Hyperspectral Scanner (AHS) in 2008. From the data a classification map with twelve different urban materials was created. Each material was then characterized by a different emissivity, whose values were obtained from the application of the TES algorithm to in situ measurements and values extracted from the ASTER spectral library. This new emissivity map could be used as a basis for determining the temperature of the city and to understand the urban heat island effect in terms of spatial distribution and size.

Evaluation of the surface urban heat island effect in the city of Madrid by thermal remote sensing

The surface urban heat island (SUHI) effect is defined as the increased surface temperatures in urban areas in contrast to cooler surrounding rural areas. In this article, the evaluation of the SUHI effect in the city of Madrid (Spain) from thermal infrared (TIR) remote-sensing data is presented. The data were obtained from the framework of the Dual-use European Security IR Experiment (DESIREX) campaign that was carried out during June and July 2008 in Madrid. The campaign combined the collection of airborne hyperspectral and in situ measurements. Thirty spectral and spatial high-resolution images were acquired with the Airborne Hyperspectral Scanner (AHS) sensor in a 11, 21, and 4 h UTC scheme. The imagery was used to retrieve the SUHI effect by applying the temperature and emissivity separation (TES) algorithm. The results show a nocturnal SUHI effect with a highest value of 5 K. This maximum value agrees within 1 K with the highest value of the urban heat island (UHI) observed using air temperature data (AT). During the daytime, this situation is reversed and the city becomes a negative heat island.

Soil emissivity and reflectance spectra measurements.

We present an analysis of the laboratory reflectance and emissivity spectra of 11 soil samples collected on different field campaigns carried out over a diverse suite of test sites in Europe, North Africa, and South America from 2002 to 2008. Hemispherical reflectance spectra were measured from 2.0 to 14 microm with a Fourier transform infrared spectrometer, and x-ray diffraction analysis (XRD) was used to determine the mineralogical phases of the soil samples. Emissivity spectra were obtained from the hemispherical reflectance measurements using Kirchhoffs law and compared with in situ radiance measurements obtained with a CIMEL Electronique CE312-2 thermal radiometer and converted to emissivity using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) temperature and emissivity separation algorithm. The CIMEL has five narrow bands at approximately the same positions as the ASTER. Results show a root mean square error typically below 0.015 between laboratory emissivity measurements and emissivity measurements derived from the field radiometer.

A Combined Optical–Microwave Method to Retrieve Soil Moisture Over Vegetated Areas

A simple approach for correcting for the effect of vegetation in the estimation of the surface soil moisture (wS) from L-band passive microwave observations is presented in this study. The approach is based on semi-empirical relationships between soil moisture and the polarized reflectivity including the effect of the vegetation optical depth which is parameterized as a function of the normalized vegetation difference index (NDVI). The method was tested against in situ measurements collected over a grass site from 2004 to 2007 (SMOSREX experiment). Two polarizations (horizontal/vertical) and five incidence angles (20°, 30°, 40°, 50°, and 60°) were considered in the analysis. The best wS estimations were obtained when using both polarizations at an angle of 40°. The average accuracy in the soil moisture retrievals was found to be approximately 0.06 m3/m3, improving the estimations by 0.02 m3/m3 with respect to the case in which the vegetation effect is not considered. The results indicate that information on vegetation (through a vegetation index such as NDVI) is useful for the estimation of soil moisture through the semi-empirical regressions.

Evaluation of the DART 3D model in the thermal domain using satellite/airborne imagery and ground-based measurements

This work provides an evaluation of the discrete anisotropy radiative transfer (DART) three-dimensional (3D) model in assessing the simulation of directional brightness temperatures (T b) at both sensor and surface levels. Satellite imagery acquired with the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), airborne imagery acquired with the Airborne Hyperspectral Scanner (AHS) sensor and ground-based measurements collected over an agricultural area were used to evaluate the DART model at nadir views. Directional radiometric temperatures measured with a goniometric system at ground level were also used to evaluate modelling results at different view angles. The DART model was evaluated over three homogeneous plots: bare soil (BS), green grass (GG) and sand (NS). The results show good agreement between the simulations and the satellite, airborne and ground-based measurements, with root mean square errors (RMSEs) less than 2.0 K. However, three major discrepancies were found: (1) differences greater than 4.0 K over BS when comparing DART and ASTER, attributed to turbulence-induced temperature fluctuations, (2) higher differences in sensor-level than in surface-level comparisons when using AHS due to thermal heterogeneity of the selected regions of interest in the image and also to differences in atmospheric correction performed over the imagery and the correction included in the DART model, especially for bands located in the lowest atmospheric transmissivity regions and (3) RMSEs greater than 2.0 K when comparing DART results and ground measurements over the NS plot, due to the strong emissivity correction in the 8.0–9.0 μm bands, where the measured emissivity was below 0.75. Despite these discrepancies, we show that the DART model is a useful tool for simulating remotely sensed thermal images over different landscapes. Finally, new versions of this model are continuously being released to solve technical problems and improve the simulation results.

A database for the monitoring of thermal anomalies over the Amazon forest and adjacent intertropical oceans.

Advances in information technologies and accessibility to climate and satellite data in recent years have favored the development of web-based tools with user-friendly interfaces in order to facilitate the dissemination of geo/biophysical products. These products are useful for the analysis of the impact of global warming over different biomes. In particular, the study of the Amazon forest responses to drought have recently received attention by the scientific community due to the occurrence of two extreme droughts and sustained warming over the last decade. Thermal Amazoni@ is a web-based platform for the visualization and download of surface thermal anomalies products over the Amazon forest and adjacent intertropical oceans using Google Earth as a baseline graphical interface (http://ipl.uv.es/thamazon/web). This platform is currently operational at the servers of the University of Valencia (Spain), and it includes both satellite (MODIS) and climatic (ERA-Interim) datasets. Thermal Amazoni@ is composed of the viewer system and the web and ftp sites with ancillary information and access to product download.

Evaluation of Terra/MODIS atmospheric profiles product (MOD07) over the Iberian Peninsula: a comparison with radiosonde stations

Remote sensing techniques are a useful tool for continuous observation of the Earth at global scale. However, products derived from remote sensing data require a rigorous validation using in situ data. Moderate Resolution Imaging Spectroradiometer (MODIS) is not really a sounding instrument, but it does have 16 infrared bands (bands 20–36 covering the spectral range from 3 µm to 14 µm) that allow the retrieval of temperature and moisture profiles as well as total column integrated magnitudes. In this paper we show the results obtained in the evaluation of MOD07 daytime and nighttime products over the Iberian Peninsula during the decade from 2000 to 2010 using nine radiosonde stations. Although MODIS limitations in comparison with other sounding instruments, the validation provided satisfactory results, with bias (MOD07 minus radiosonde) < 0.3 cm and a standard deviation of 0.5 cm for the total column water vapor, and bias around 1 K on average with standard deviations between 2 K and 3 K for air temperature at different pressure levels. On average, bias was positive and below 2 K with standard deviations around 5 K for the dew point temperature case. Large errors were found in this case for pressure levels higher than 50 hPa.