Feasibility of using sea surface temperature imagery to mitigate cheloniid sea turtle–fishery interactions off the coast of northeastern USA

As sea turtles migrate along the Atlantic coast of the USA, their incidental capture in fisheries is a significant source of mortality. Because distribution of marine cheloniid turtles appears to be related, in part, to sea surface temperature (SST), the ability to predict water temperature over the continental shelf could be useful in minimizing turtle–fishery interactions. We analyzed 10 yr of advanced very high resolution radiometer (AVHRR) SST imagery to estimate the proportion of 18 spatial zones, nearshore and offshore of Hatteras, North Carolina, USA (35° N), to north of Cape Sable, Nova Scotia (44° N), at temperatures >10 to 15°C, by week. Detailed examples for 11°C, the temperature employed by some management actions in the study area, and for 14°C, the lowest temperature at which turtles were sighted by some studies in the area, demonstrate a predictable pattern of rapid warming in March and April, followed by rapid cooling in October and November, with nearshore waters warming more rapidly than those offshore. Of those loggerhead turtles Caretta caretta that stranded, were sighted, or were incidentally captured between Cape Hatteras, North Carolina, and Cape Cod, Massachusetts, those at lower latitudes occurred when 25% or more of the area reached a water temperature of 11°C, while those in the northern zones did not occur until 50% or more of the area had reached a water temperature of 14°C. This analysis provides a means of predicting marine cheloniid turtle presence, which can be helpful in regulating fisheries that seasonally interact with turtles.

NAVPRO 3.0: tutorial de instalação e utilização.

Este documento apresenta os procedimentos para instalação e utilização do sistema NAVPRO 3.0, desenvolvido para o processamento automático e geração de produtos de imagens do sensor Advanced Very High Resolution Radiometer (AVHRR) a bordo dos satélites da National Oceanic Atmospheric Administration (NOAA). O sistema NAVPRO foi criado pela Embrapa Informática Agropecuária em parceria com a Universidade Estadual de Campinas (Unicamp), que contou com o repasse do pacote computacional NAV (NAVigation), desenvolvido pelo Colorado Center for Astrodynamics Research (CCAR), da Universidade do Colorado, Boulder, EUA. O diferencial do sistema é seu método de georreferenciamento automático e preciso, capaz de gerar imagens com deslocamentos máximos de 1 pixel, valor aceito em aplicações envolvendo dados de baixa resolução espacial.

NAVLivre 1.0: Procedimentos de instalação e utilização.

Este documento apresenta os procedimentos para instalação e utilização do sistema NAVLivre 1.0, um software de código livre desenvolvido para o processamento automático de imagens do sensor Advanced Very High Resolution Radiometer (AVHRR) a bordo dos satélites da National Oceanic Atmospheric Administration (NOAA). O NAVLivre é uma derivação do sistema NAVPRO, criado pela Embrapa Informática Agropecuária em parceria com a Universidade Estadual de Campinas (Unicamp), que contou com o repasse do pacote computacional NAV (NAVigation), desenvolvido pelo Colorado Center for Astrodynamics Research (CCAR), da Universidade do Colorado, Boulder, EUA. O diferencial do NAVLivre é a ausência dos módulos desenvolvidos em Interactive Data Language (IDL), presentes no NAVPRO, e dependentes de softwares proprietários. O NAVLivre é um pacote totalmente livre, que realiza de forma automática as principais etapas do processamento das imagens NOAA, como a correção radiométrica, o georreferenciamento preciso e a geração da imagem final em formato GeoTIFF, compatível com os principais pacotes de processamento de imagens. O NAVLivre é executado em plataforma Linux e foi implementado em script c-shell e linguagem C. Seu uso é indicado aos usuários avançados de imagens NOAA, que demandam o processamento em lote de grandes volumes de dados. As rotinas e scripts aqui descritos são de domínio público, podendo ser alterados conforme necessidade do usuário.

Precisão posicional dos focos de queimadas no Estado de Mato Grosso.

Para estimar a precisão posicional dos pontos de queimadas, fornecidos pelo Inpe e identificados com auxilio das imagens National Oceanic and Atmospheric Administration (NOAA) e o Advanced Very High Resolution Radiometer (AVHRR), foram utilizados diferentes conjuntos de dados de queimadas, obtidos pela internet diretamente do site de queimadas do Inpe (INPE, 2007), imagens do satélite Landsat, composição colorida das bandas R5, G4 e B3, com data de aquisição situada até 30 dias posteriores à ocorrência dos focos de calor. O período máximo de defasagem entre a ocorrência e identificação dos pontos de calor pelo Inpe e a data de aquisição das imagens de satélite, de 30 dias, foi estabelecido com o objetivo de assegurar que as evidências da ocorrência das queimadas identificadas não fossem significativamente alteradas pela ação dos ventos ou das chuvas que transportam, lixiviam ou lavam as cinzas que são depositadas sobre o solo após a ocorrência de uma queimada.

Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009)

New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997-2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used maps of burned area derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997-2000) and estimates of plant productivity derived from Advanced Very High Resolution Radiometer (AVHRR) observations during the same period. Average global fire carbon emissions according to this version 3 of the Global Fire Emissions Database (GFED3) were 2.0 PgC year-1 with significant interannual variability during 1997-2001 (2.8 Pg Cyear-1 in 1998 and 1.6 PgC year-1 in 2001). Globally, emissions during 2002-2007 were rela-tively constant (around 2.1 Pg C year-1) before declining in 2008 (1.7 Pg Cyear-1) and 2009 (1.5 PgC year-1) partly due to lower deforestation fire emissions in South America and tropical Asia. On a regional basis, emissions were highly variable during 2002-2007 (e.g., boreal Asia, South America, and Indonesia), but these regional differences canceled out at a global level. During the MODIS era (2001-2009), most carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. Total carbon emissions were on average 13% lower than in our previous (GFED2) work. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 PgC year-1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series. © 2010 Author(s).

Space-borne study of seasonal, multi-year, and decadal phytoplankton dynamics in the Bay of Biscay

Seasonal and inter-annual variations in phytoplankton community abundance in the Bay of Biscay are studied. Preliminarily processed by the National Aeronautics and Space Administration (NASA) to yield normalized water-leaving radiance and the top-of-the-atmosphere solar radiance, Sea-viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Coastal Zone Color Scanner (CZCS) data are further supplied to our dedicated retrieval algorithms to infer the sought for parameters. By applying the National Oceanic and Atmospheric Administration's (NOAA's) Advanced Very High Resolution Radiometer (AVHRR) data, the surface reflection coefficient in the only band in the visible spectrum is derived and employed for analysis. Decadal bridged time series of variations of diatom-dominated phytoplankton and green dinoflagellate Lepidodinium chlorophorum within the shelf zone and the coccolithophore Emiliania huxleyi in the pelagic area of the Bay are documented and analysed in terms of impacts of some biogeochemical and geophysical forcing factors.

Deriving meteorological variables across Africa for the study and control of vector-borne disease:a comparison of remote sensing and spatial interpolation of climate

This paper presents the results of an investigation into the utility of remote sensing (RS) using meteorological satellites sensors and spatial interpolation (SI) of data from meteorological stations, for the prediction of spatial variation in monthly climate across continental Africa in 1990. Information from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration's (NOAA) polar-orbiting meteorological satellites was used to estimate land surface temperature (LST) and atmospheric moisture. Cold cloud duration (CCD) data derived from the High Resolution Radiometer (HRR) onboard the European Meteorological Satellite programme's (EUMETSAT) Meteosat satellite series were also used as a RS proxy measurement of rainfall. Temperature, atmospheric moisture and rainfall surfaces were independently derived from SI of measurements from the World Meteorological Organization (WMO) member stations of Africa. These meteorological station data were then used to test the accuracy of each methodology, so that the appropriateness of the two techniques for epidemiological research could be compared. SI was a more accurate predictor of temperature, whereas RS provided a better surrogate for rainfall; both were equally accurate at predicting atmospheric moisture. The implications of these results for mapping short and long-term climate change and hence their potential for the study anti control of disease vectors are considered. Taking into account logistic and analytical problems, there were no clear conclusions regarding the optimality of either technique, but there was considerable potential for synergy.

Diurnal cycle of land surface temperature in a desert encroachment zone as observed from satellites

Climate variability in the African Soudano-Sahel savanna zone has attracted much attention because of the persistence of anomalously low rainfall. Past efforts to monitor the climate of this region have focused on rainfall and vegetation conditions, while land surface temperature (LST) has received less attention. Remote sensing of LST is feasible and possible at global scale. Most remotely sensed estimates of LST are based on the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) that are limited in their ability to capture the full diurnal cycle. Although more frequent observations are available from past geostationary satellites, their spatial resolution is coarser than that of polar orbiting satellites. In this study, the improved capabilities of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the METEOSAT Second Generation (MSG) instrument are used to remotely sense the LST in the African Soudano-Sahel savanna zone at a resolution of 3 km and 15 minutes. In support of the Radiative Atmospheric Divergence using the ARM Mobile Facility (AMF), GERB and AMMA Stations (RADAGAST) project, African Monsoon Multidisciplinary Analyses (AMMA) project and the Department of Energy's Atmospheric Radiation Measurement (ARM) program, the ARM Mobile Facility was deployed during 2006 in this climatically sensitive region, thereby providing a unique opportunity to evaluate remotely sensed algorithms for deriving LST.

Validation of the GRAPE single view aerosol retrieval for ATSR-2 and insights into the long term global AOD trend over the ocean

The Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) project has produced a global data-set of cloud and aerosol properties from the Along Track Scanning Radiometer-2 (ATSR-2) instrument, covering the time period 1995�2001. This paper presents the validation of aerosol optical depths (AODs) over the ocean from this product against AERONET sun-photometer measurements, as well as a comparison to the Advanced Very High Resolution Radiometer (AVHRR) optical depth product produced by the Global Aerosol Climatology Project (GACP). The GRAPE AOD over ocean is found to be in good agreement with AERONET measurements, with a Pearson's correlation coefficient of 0.79 and a best-fit slope of 1.0±0.1, but with a positive bias of 0.08±0.04. Although the GRAPE and GACP datasets show reasonable agreement, there are significant differences. These discrepancies are explored, and suggest that the downward trend in AOD reported by GACP may arise from changes in sampling due to the orbital drift of the AVHRR instruments.

NOAA's sea surface temperature products from operational geostationary satellites

NOAA's National Environmental Satellite, Data, and Information Service (NESDIS) has generated sea surface temperature (SST) products from Geostationary Operational Environmental Satellite (GOES)-East (E) and GOES-West (W) on an operational basis since December 2000. Since that time, a process of continual development has produced steady improvements in product accuracy. Recent improvements extended the capability to permit generation of operational SST retrievals from the Japanese Multifunction Transport Satellite (MTSAT)-1R and the European Meteosat Second Generation (MSG) satellite, thereby extending spatial coverage. The four geostationary satellites (at longitudes of 75°W, 135°W, 140°E, and 0°) provide high temporal SST retrievals for most of the tropics and midlatitudes, with the exception of a region between 60° and 80°E. Because of ongoing development, the quality of these retrievals now approaches that of SST products from the polar-orbiting Advanced Very High Resolution Radiometer (AVHRR). These products from GOES provide hourly regional imagery, 3-hourly hemispheric imagery, 24-h merged composites, a GOES SST level 2 preprocessed product every 1/2 h for each hemisphere, and a match-up data file for each product. The MTSAT and the MSG products include hourly, 3-hourly, and 24-h merged composites. These products provide the user community with a reliable source of SST observations, with improved accuracy and increased coverage in important oceanographic, meteorological, and climatic regions.

Optimal estimation of sea surface temperature from split-window observations

Optimal estimation (OE) improves sea surface temperature (SST) estimated from satellite infrared imagery in the “split-window”, in comparison to SST retrieved using the usual multi-channel (MCSST) or non-linear (NLSST) estimators. This is demonstrated using three months of observations of the Advanced Very High Resolution Radiometer (AVHRR) on the first Meteorological Operational satellite (Metop-A), matched in time and space to drifter SSTs collected on the global telecommunications system. There are 32,175 matches. The prior for the OE is forecast atmospheric fields from the Météo-France global numerical weather prediction system (ARPEGE), the forward model is RTTOV8.7, and a reduced state vector comprising SST and total column water vapour (TCWV) is used. Operational NLSST coefficients give mean and standard deviation (SD) of the difference between satellite and drifter SSTs of 0.00 and 0.72 K. The “best possible” NLSST and MCSST coefficients, empirically regressed on the data themselves, give zero mean difference and SDs of 0.66 K and 0.73 K respectively. Significant contributions to the global SD arise from regional systematic errors (biases) of several tenths of kelvin in the NLSST. With no bias corrections to either prior fields or forward model, the SSTs retrieved by OE minus drifter SSTs have mean and SD of − 0.16 and 0.49 K respectively. The reduction in SD below the “best possible” regression results shows that OE deals with structural limitations of the NLSST and MCSST algorithms. Using simple empirical bias corrections to improve the OE, retrieved minus drifter SSTs are obtained with mean and SD of − 0.06 and 0.44 K respectively. Regional biases are greatly reduced, such that the absolute bias is less than 0.1 K in 61% of 10°-latitude by 30°-longitude cells. OE also allows a statistic of the agreement between modelled and measured brightness temperatures to be calculated. We show that this measure is more efficient than the current system of confidence levels at identifying reliable retrievals, and that the best 75% of satellite SSTs by this measure have negligible bias and retrieval error of order 0.25 K.

Observations of the Eastern Maine Coastal Current and Its Offshore Extensions in 1994

Cold surface temperatures, reflecting Scotian Shelf origins and local tidal mixing, serve as a tracer of the Eastern Maine Coastal Current and its offshore extensions, which appear episodically as cold plumes erupting from the eastern Maine shelf. A cold water plume emanating from the Eastern Maine Coastal Current in May 1994 was investigated using advanced very high resolution radiometer (AVHRR) imagery, shipboard surveys of physical and biochemical properties, and satellite-tracked drifters. Evidence is presented that suggests that some of the plume waters were entrained within the cyclonic circulation over Jordan Basin, while the major portion participated in an anticyclonic eddy at the distal end of the plume. Calculations of the nitrate transported offshore by the plume show that this feature can episodically export significant quantities of nutrients from the Eastern Maine Coastal Current to offshore regions that are generally nutrient depleted during spring-summer. A series of AVHRR images is used to document the seasonal along-shelf progression of the coastal plume separation point. We speculate on potential causes and consequences of plume separation from the coastal current and suggest that this feature may be an important factor influencing the patterns and overall biological productivity of the eastern Gulf of Maine.