The Applicability of the Distribution Coefficient, KD, Based on Non-Aggregated Particulate Samples from Lakes with Low Suspended Solids Concentrations

Separate phases of metal partitioning behaviour in freshwater lakes that receive varying degrees of atmospheric contamination and have low concentrations of suspended solids were investigated to determine the applicability of the distribution coefficient, KD. Concentrations of Pb, Ni, Co, Cu, Cd, Cr, Hg and Mn were determined using a combination of filtration methods, bulk sample collection and digestion and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Phytoplankton biomass, suspended solids concentrations and the organic content of the sediment were also analysed. By distinguishing between the phytoplankton and (inorganic) lake sediment, transient variations in KD were observed. Suspended solids concentrations over the 6-month sampling campaign showed no correlation with the KD (n = 15 for each metal, p > 0.05) for Mn (r2 = 0.0063), Cu (r2 = 0.0002, Cr (r2 = 0.021), Ni (r2 = 0.0023), Cd (r2 = 0.00001), Co (r2 = 0.096), Hg (r2 = 0.116) or Pb (r2 = 0.164). The results implied that colloidal matter had less opportunity to increase the dissolved (filter passing) fraction, which inhibited the spurious lowering of KD. The findings conform to the increasingly documented theory that the use of KD in modelling may mask true information on metal partitioning behaviour. The root mean square error of prediction between the directly measured total metal concentrations and those modelled based on the separate phase fractions were ± 3.40, 0.06, 0.02, 0.03, 0.44, 484.31, 80.97 and 0.1 μg/L for Pb, Cd, Mn, Cu, Hg, Ni, Cr and Co respectively. The magnitude of error suggests that the separate phase models for Mn and Cu can be used in distribution or partitioning models for these metals in lake water

High Impact Weather Forecasts and Warnings with the GOES-R Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. A major advancement over the current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM). The GLM will operate continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Science Team and Algorithm Working Group Lightning Applications Team have begun to develop cal/val performance monitoring tools and new applications using the GLM alone, in conjunction with other instruments, and merged or blended integrated observing system products combining satellite, radar, in-situ and numerical models. Proxy total lightning data from the NASA Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional ground-based lightning networks are being used to develop the pre-launch algorithms, test data sets, and applications, as well as improve our knowledge of thunderstorm initiation and evolution. In this presentation we review the planned implementation of the instrument and suite of operational algorithms

GOES-R AWG GLM Val Tool Development

We are developing tools needed to enable the validation of the Geostationary Lightning Mapper (GLM). In order to develop and test these tools, we have need of a robust, high-fidelity set of GLM proxy data. Many steps have been taken to ensure that the proxy data are high quality. LIS is the closest analog that exists for GLM, so it has been used extensively in developing the GLM proxy. We have verified the proxy data both statistically and algorithmically. The proxy data are pixel (event) data, called Level 1B. These data were then clustered into flashes by the Lightning Cluster-Filter Algorithm (LCFA), generating proxy Level 2 data. These were then compared with the data used to generate the proxy, and both the proxy data and the LCFA were validated. We have developed tools to allow us to visualize and compare the GLM proxy data with several other sources of lightning and other meteorological data (the so-called shallow-dive tool). The shallow-dive tool shows storm-level data and can ingest many different ground-based lightning detection networks, including: NLDN, LMA, WWLLN, and ENTLN. These are presented in a way such that it can be seen if the GLM is properly detecting the lightning in location and time comparable to the ground-based networks. Currently in development is the deep-dive tool, which will allow us to dive into the GLM data, down to flash, group and event level. This will allow us to assess performance in comparison with other data sources, and tell us if there are detection, timing, or geolocation problems. These tools will be compatible with the GLM Level-2 data format, so they can be used beginning on Day 0

Preliminary Assessment of Detection Efficiency for the Geostationary Lightning Mapper Using Intercomparisons with Ground-Based Systems

As part of the calibration/validation (cal/val) effort for the Geostationary Lightning Mapper (GLM) on GOES-16, we need to assess instrument performance (detection efficiency and accuracy). One major effort is to calculate the detection efficiency of GLM by comparing to multiple ground-based systems. These comparisons will be done pair-wise between GLM and each other source. A complication in this process is that the ground-based systems sense different properties of the lightning signal than does GLM (e.g., RF vs. optical). Also, each system has a different time and space resolution and accuracy. Preliminary results indicate that GLM is performing at or above its specification

The GOES-R GeoStationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved capability for the Advanced Baseline Imager (ABI). The Geostationary Lighting Mapper (GLM) will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency among a number of potential applications. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms (environmental data records), cal/val performance monitoring tools, and new applications using GLM alone, in combination with the ABI, merged with ground-based sensors, and decision aids augmented by numerical weather prediction model forecasts. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. An international field campaign planned for 2011-2012 will produce concurrent observations from a VHF lightning mapping array, Meteosat multi-band imagery, Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) overpasses, and related ground and in-situ lightning and meteorological measurements in the vicinity of Sao Paulo. These data will provide a new comprehensive proxy data set for algorithm and application development

The GOES-R Series Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), which will have just completed Critical Design Review and move forward into the construction phase of instrument development. The GLM will operate continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (an engineering development unit and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional ground-based lightning networks are being used to develop the pre-launch algorithms, test data sets, and applications, as well as improve our knowledge of thunderstorm initiation and evolution. In this presentation we review the planned implementation of the instrument and suite of operational algorithm

The Goes-R Geostationary Lightning Mapper (GLM): Algorithm and Instrument Status

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved capability for the Advanced Baseline Imager (ABI). The Geostationary Lighting Mapper (GLM) will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. A joint field campaign with Brazilian researchers in 2010-2011 will produce concurrent observations from a VHF lightning mapping array, Meteosat multi-band imagery, Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) overpasses, and related ground and in-situ lightning and meteorological measurements in the vicinity of Sao Paulo. These data will provide a new comprehensive proxy data set for algorithm and application development

ASSESSMENT OF STRATEGIES TEACHERS USE TO ENHANCE SOCIAL INTERACTION SKILLS OF AUTISTIC PUPILS IN SPECIAL SCHOOLS FOR THE INTELLECTUALLY DISABLED

The study assessed strategies teachers used to enhance social interaction skills of autistic pupils in some selected special schools for the intellectually disabled in the Northern part of Ghana. Descriptive research design was adopted and a total sample of 50 respondents were involved. Purposive sampling technique was used to select the schools and the respondents for the study. Questionnaire was the main instrument used for data collection. Data was analysed using tables, frequencies and percentages. The findings showed that the teachers used modeling, physical prompts, visual cues, reinforcement, social stories, direct instruction skills and social skills training in groups and peer support as strategies to enhance social interaction skills of autistic pupils in the school. The strategies used by the teachers were also proven to be effective in enhancing social interaction skills of autistic pupils in the school. It was established that even though some support services were available to help enhance the social interaction skills of the autistic pupils, professionals like occupational therapists, physical therapists and the multi-disciplinary team were absent in the three special schools selected for the study. It was recommended that the requisite support services should be provided in the selected special schools which have autistic pupils in order to help enhance the social interaction skills. In addition, periodic workshops, symposia as well as refresher courses should be organized for special teachers and their aides to update their knowledge and skills in the strategies used to enhance social interaction skills of these pupils with autism.  Article visualizations