Sources, sinks, and transatlantic transport of North African dust aerosol: a multimodel analysis and comparison with remote sensing data

This study evaluates model-simulated dust aerosols over North Africa and the North Atlantic from five global models that participated in the Aerosol Comparison between Observations and Models phase II model experiments. The model results are compared with satellite aerosol optical depth (AOD) data from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-viewing Wide Field-of-view Sensor, dust optical depth (DOD) derived from MODIS and MISR, AOD and coarse-mode AOD (as a proxy of DOD) from ground-based Aerosol Robotic Network Sun photometer measurements, and dust vertical distributions/centroid height from Cloud Aerosol Lidar with Orthogonal Polarization and Atmospheric Infrared Sounder satellite AOD retrievals. We examine the following quantities of AOD and DOD: (1) the magnitudes over land and over ocean in our study domain, (2) the longitudinal gradient from the dust source region over North Africa to the western North Atlantic, (3) seasonal variations at different locations, and (4) the dust vertical profile shape and the AOD centroid height (altitude above or below which half of the AOD is located). The different satellite data show consistent features in most of these aspects; however, the models display large diversity in all of them, with significant differences among the models and between models and observations. By examining dust emission, removal, and mass extinction efficiency in the five models, we also find remarkable differences among the models that all contribute to the discrepancies of model-simulated dust amount and distribution. This study highlights the challenges in simulating the dust physical and optical processes, even in the best known dust environment, and stresses the need for observable quantities to constrain the model processes.

Extension of the TAMSAT satellite-based rainfall monitoring over Africa and from 1983 to present

Tropical Applications of Meteorology Using Satellite Data and Ground-Based Observations (TAMSAT) rainfall monitoring products have been extended to provide spatially contiguous rainfall estimates across Africa. This has been achieved through a new, climatology-based calibration, which varies in both space and time. As a result, cumulative estimates of rainfall are now issued at the end of each 10-day period (dekad) at 4-km spatial resolution with pan-African coverage. The utility of the products for decision making is improved by the routine provision of validation reports, for which the 10-day (dekadal) TAMSAT rainfall estimates are compared with independent gauge observations. This paper describes the methodology by which the TAMSAT method has been applied to generate the pan-African rainfall monitoring products. It is demonstrated through comparison with gauge measurements that the method provides skillful estimates, although with a systematic dry bias. This study illustrates TAMSAT’s value as a complementary method of estimating rainfall through examples of successful operational application.

Predicted signatures of pulsed reconnection in ESR data

Early in 1996, the latest of the European incoherent-scatter (EISCAT) radars came into operation on the Svalbard islands. The EISCAT Svalbard Radar (ESR) has been built in order to study the ionosphere in the northern polar cap and in particular, the dayside cusp. Conditions in the upper atmosphere in the cusp region are complex, with magnetosheath plasma cascading freely into the atmosphere along open magnetic field lines as a result of magnetic reconnection at the dayside magnetopause. A model has been developed to predict the effects of pulsed reconnection and the subsequent cusp precipitation in the ionosphere. Using this model we have successfully recreated some of the major features seen in photometer and satellite data within the cusp. In this paper, the work is extended to predict the signatures of pulsed reconnection in ESR data when the radar is pointed along the magnetic field. It is expected that enhancements in both electron concentration and electron temperature will be observed. Whether these enhancements are continuous in time or occur as a series of separate events is shown to depend critically on where the open/closed field-line boundary is with respect to the radar. This is shown to be particularly true when reconnection pulses are superposed on a steady background rate.

Global burned-land estimation in Latin America using MODIS composite data

This paper presents results of the AQL2004 project, which has been develope within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLatif). The project intended to obtain monthly burned-land maps of the entire region, from Mexico to Patagonia, using MODIS (moderate-resolution imaging spectroradiometer) reflectance data. The project has been organized in three different phases: acquisition and preprocessing of satellite data; discrimination of burned pixels; and validation of results. In the first phase, input data consisting of 32-day composites of MODIS 500-m reflectance data generated by the Global Land Cover Facility (GLCF) of the University of Maryland (College Park, Maryland, U.S.A.) were collected and processed. The discrimination of burned areas was addressed in two steps: searching for "burned core" pixels using postfire spectral indices and multitemporal change detection and mapping of burned scars using contextual techniques. The validation phase was based on visual analysis of Landsat and CBERS (China-Brazil Earth Resources Satellite) images. Validation of the burned-land category showed an agreement ranging from 30% to 60%, depending on the ecosystem and vegetation species present. The total burned area for the entire year was estimated to be 153 215 km2. The most affected countries in relation to their territory were Cuba, Colombia, Bolivia, and Venezuela. Burned areas were found in most land covers; herbaceous vegetation (savannas and grasslands) presented the highest proportions of burned area, while perennial forest had the lowest proportions. The importance of croplands in the total burned area should be taken with reserve, since this cover presented the highest commission errors. The importance of generating systematic products of burned land areas for different ecological processes is emphasized.

Advances in the stochastic modelling of satellite-derived rainfall estimates using a sparse calibration dataset

As satellite technology develops, satellite rainfall estimates are likely to become ever more important in the world of food security. It is therefore vital to be able to identify the uncertainty of such estimates and for end users to be able to use this information in a meaningful way. This paper presents new developments in the methodology of simulating satellite rainfall ensembles from thermal infrared satellite data. Although the basic sequential simulation methodology has been developed in previous studies, it was not suitable for use in regions with more complex terrain and limited calibration data. Developments in this work include the creation of a multithreshold, multizone calibration procedure, plus investigations into the causes of an overestimation of low rainfall amounts and the best way to take into account clustered calibration data. A case study of the Ethiopian highlands has been used as an illustration.

Investigating the relationship between Eurasian snow and the Arctic Oscillation with data and models

Recent research suggests Eurasian snow-covered area (SCA) influences the Arctic Oscillation (AO) via the polar vortex. This could be important for Northern Hemisphere winter season forecasting. A fairly strong negative correlation between October SCA and the AO, based on both monthly and daily observational data, has been noted in the literature. While reproducing these previous links when using the same data, we find no further evidence of the link when using an independent satellite data source, or when using a climate model.

Collocating satellite-based radar and radiometer measurements — methodology and usage examples

Collocations between two satellite sensors are occasions where both sensors observe the same place at roughly the same time. We study collocations between the Microwave Humidity Sounder (MHS) on-board NOAA-18 and the Cloud Profiling Radar (CPR) on-board CloudSat. First, a simple method is presented to obtain those collocations and this method is compared with a more complicated approach found in literature. We present the statistical properties of the collocations, with particular attention to the effects of the differences in footprint size. For 2007, we find approximately two and a half million MHS measurements with CPR pixels close to their centrepoints. Most of those collocations contain at least ten CloudSat pixels and image relatively homogeneous scenes. In the second part, we present three possible applications for the collocations. Firstly, we use the collocations to validate an operational Ice Water Path (IWP) product from MHS measurements, produced by the National Environment Satellite, Data and Information System (NESDIS) in the Microwave Surface and Precipitation Products System (MSPPS). IWP values from the CloudSat CPR are found to be significantly larger than those from the MSPPS. Secondly, we compare the relation between IWP and MHS channel 5 (190.311 GHz) brightness temperature for two datasets: the collocated dataset, and an artificial dataset. We find a larger variability in the collocated dataset. Finally, we use the collocations to train an Artificial Neural Network and describe how we can use it to develop a new MHS-based IWP product. We also study the effect of adding measurements from the High Resolution Infrared Radiation Sounder (HIRS), channels 8 (11.11 μm) and 11 (8.33 μm). This shows a small improvement in the retrieval quality. The collocations described in the article are available for public use.

An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing

Satellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field. (C) 2010 Elsevier B.V. All rights reserved.

Exterior orientation of CBERS-2B imagery using multi-feature control and orbital data

The major contribution of this paper relates to the practical advantages of combining Ground Control Points (GCPs), Ground Control Lines (GCLs) and orbital data to estimate the exterior orientation parameters of images collected by CBERS-2B (China-Brazil Earth Resources Satellite) HRC (High-resolution Camera) and CCD (High-resolution CCD Camera) sensors. Although the CBERS-2B is no longer operational, its images are still being used in Brazil, and the next generations of the CBERS satellite will have sensors with similar technical features, which motivates the study presented in this paper. The mathematical models that relate the object and image spaces are based on collinearity (for points) and coplanarity (for lines) conditions. These models were created in an in-house developed software package called TMS (Triangulation with Multiple Sensors) with multi-feature control (GCPs and GCLs). Experiments on a block of four CBERS-2B HRC images and on one CBERS-2B CCD image were performed using both models. It was observed that the combination of GCPs and GCLs provided better bundle block adjustment results than conventional bundle adjustment using only GCPs. The results also demonstrate the advantages of using primarily orbital data when the number of control entities is reduced. © 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Comparisons between OMI SO2 data and ground-based SO2 measurements at Turrialba volcano

Turrialba is one of the largest and most active stratovolcanoes in the Central Cordillera of Costa Rica and an excellent target for validation of satellite data using ground based measurements due to its high elevation, relative ease of access, and persistent elevated SO2 degassing. The Ozone Monitoring Instrument (OMI) aboard the Aura satellite makes daily global observations of atmospheric trace gases and it is used in this investigation to obtain volcanic SO2 retrievals in the Turrialba volcanic plume. We present and evaluate the relative accuracy of two OMI SO2 data analysis procedures, the automatic Band Residual Index (BRI) technique and the manual Normalized Cloud-mass (NCM) method. We find a linear correlation and good quantitative agreement between SO2 burdens derived from the BRI and NCM techniques, with an improved correlation when wet season data are excluded. We also present the first comparisons between volcanic SO2 emission rates obtained from ground-based mini-DOAS measurements at Turrialba and three new OMI SO2 data analysis techniques: the MODIS smoke estimation, OMI SO2 lifetime, and OMI SO2 transect techniques. A robust validation of OMI SO2 retrievals was made, with both qualitative and quantitative agreements under specific atmospheric conditions, proving the utility of satellite measurements for estimating accurate SO2 emission rates and monitoring passively degassing volcanoes.

Digital processing and data compilation approach for using remotely sensed imagery to identify geological lineaments in hard-rock terrains : an application for groundwater explorations in Nicaragua

Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.

Observations of volcanic emissions using satellite remote sensing

Volcanoes pose a threat to the human population at regional and global scales and so efficient monitoring is essential in order to effectively manage and mitigate the risks that they pose. Volcano monitoring from space has been possible for over thirty years and now, more than ever, a suite of instruments exists with the capability to observe emissions of gas and ash from a unique perspective. The goal of this research is to demonstrate the use of a range of satellite-based sensors in order to detect and quantify volcanic sulphur dioxide, and to assess the relative performances of each sensor against one another. Such comparisons are important in order to standardise retrievals and permit better estimations of the global contribution of sulphur dioxide to the atmosphere from volcanoes for climate modelling. In this work, retrievals of volcanic sulphur dioxide from a number of instruments are compared, and the individual performances at quantifying emissions from large, explosive volcanic eruptions are assessed. Retrievals vary widely from sensor to sensor, and often the use of a number of sensors in synergy can provide the most complete picture, rather than just one instrument alone. Volcanic emissions have the ability to result significant economic loses by grounding aircraft due to the high risk associated with ash encountering aircraft. As sulphur dioxide is often easier to measure than ash, it is often used as a proxy. This work examines whether this is a reasonable assumption, using the Icelandic eruption in early 2010 as a case study. Results indicate that although the two species are for the most part collocated, separation can occur under some conditions, meaning that it is essential to accurately measure both species in order to provide effective hazard mitigation. Finally, the usefulness of satellite remote sensing in quantifying the passive degassing from Turrialba, Costa Rica is demonstrated. The increase in activity from 2005 – 2010 can be observed in satellite data prior to the phreatic phase of early 2010, and can therefore potentially provide a useful indication of changing activity at some volcanoes.

Lake surface water temperatures of European Alpine lakes (1989–2013) based on the Advanced Very High Resolution Radiometer (AVHRR) 1 km data set

Lake water temperature (LWT) is an important driver of lake ecosystems and it has been identified as an indicator of climate change. Consequently, the Global Climate Observing System (GCOS) lists LWT as an essential climate variable. Although for some European lakes long in situ time series of LWT do exist, many lakes are not observed or only on a non-regular basis making these observations insufficient for climate monitoring. Satellite data can provide the information needed. However, only few satellite sensors offer the possibility to analyse time series which cover 25 years or more. The Advanced Very High Resolution Radiometer (AVHRR) is among these and has been flown as a heritage instrument for almost 35 years. It will be carried on for at least ten more years, offering a unique opportunity for satellite-based climate studies. Herein we present a satellite-based lake surface water temperature (LSWT) data set for European water bodies in or near the Alps based on the extensive AVHRR 1 km data record (1989–2013) of the Remote Sensing Research Group at the University of Bern. It has been compiled out of AVHRR/2 (NOAA-07, -09, -11, -14) and AVHRR/3 (NOAA-16, -17, -18, -19 and MetOp-A) data. The high accuracy needed for climate related studies requires careful pre-processing and consideration of the atmospheric state. The LSWT retrieval is based on a simulation-based scheme making use of the Radiative Transfer for TOVS (RTTOV) Version 10 together with ERA-interim reanalysis data from the European Centre for Medium-range Weather Forecasts. The resulting LSWTs were extensively compared with in situ measurements from lakes with various sizes between 14 and 580 km2 and the resulting biases and RMSEs were found to be within the range of −0.5 to 0.6 K and 1.0 to 1.6 K, respectively. The upper limits of the reported errors could be rather attributed to uncertainties in the data comparison between in situ and satellite observations than inaccuracies of the satellite retrieval. An inter-comparison with the standard Moderate-resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature product exhibits RMSEs and biases in the range of 0.6 to 0.9 and −0.5 to 0.2 K, respectively. The cross-platform consistency of the retrieval was found to be within ~ 0.3 K. For one lake, the satellite-derived trend was compared with the trend of in situ measurements and both were found to be similar. Thus, orbital drift is not causing artificial temperature trends in the data set. A comparison with LSWT derived through global sea surface temperature (SST) algorithms shows lower RMSEs and biases for the simulation-based approach. A running project will apply the developed method to retrieve LSWT for all of Europe to derive the climate signal of the last 30 years. The data are available at doi:10.1594/PANGAEA.831007.

Lake ice phenology from AVHRR data for European lakes: An automated two-step extraction method

Several lake ice phenology studies from satellite data have been undertaken. However, the availability of long-term lake freeze-thaw-cycles, required to understand this proxy for climate variability and change, is scarce for European lakes. Long time series from space observations are limited to few satellite sensors. Data of the Advanced Very High Resolution Radiometer (AVHRR) are used in account of their unique potential as they offer each day global coverage from the early 1980s expectedly until 2022. An automatic two-step extraction was developed, which makes use of near-infrared reflectance values and thermal infrared derived lake surface water temperatures to extract lake ice phenology dates. In contrast to other studies utilizing thermal infrared, the thresholds are derived from the data itself, making it unnecessary to define arbitrary or lake specific thresholds. Two lakes in the Baltic region and a steppe lake on the Austrian–Hungarian border were selected. The later one was used to test the applicability of the approach to another climatic region for the time period 1990 to 2012. A comparison of the extracted event dates with in situ data provided good agreements of about 10 d mean absolute error. The two-step extraction was found to be applicable for European lakes in different climate regions and could fill existing data gaps in future applications. The extension of the time series to the full AVHRR record length (early 1980 until today) with adequate length for trend estimations would be of interest to assess climate variability and change. Furthermore, the two-step extraction itself is not sensor-specific and could be applied to other sensors with equivalent near- and thermal infrared spectral bands.

Satellite-Measured Chlorophyll and Temperature Variability Off Northern Chile During the 1996-1998 La Niña and El Niño

Time series of satellite measurements are used to describe patterns of surface temperature and chlorophyll associated with the 1996 cold La Nina phase and the 1997-1998 warm El Nino phase of the El Nino - Southern Oscillation cycle in the upwelling region off northern Chile. Surface temperature data are available through the entire study period. Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data first became available in September 1997 during a relaxation in El Nino conditions identified by in situ hydrographic data. Over the time period of coincident satellite data, chlorophyll patterns closely track surface temperature patterns. Increases both in nearshore chlorophyll concentration and in cross-shelf extension of elevated concentrations are associated with decreased coastal temperatures during both the relaxation in El Nino conditions in September-November 1997 and the recovery from EI Nino conditions after March 1998. Between these two periods during austral summer (December 1997 to March 1998) and maximum El Nino temperature anomalies, temperature patterns normally associated with upwelling were absent and chlorophyll concentrations were minimal. Cross-shelf chlorophyll distributions appear to be modulated by surface temperature frontal zones and are positively correlated with a satellite-derived upwelling index. Frontal zone patterns and the upwelling index in 1996 imply an austral summer nearshore chlorophyll maximum, consistent with SeaWiFS data from I 1998-1999, after the El Nino. SeaWiFS retrievals in the data set used here are higher than in situ measurements by a factor of 2-4; however, consistency in the offset suggests relative patterns are valid.