A comparison of global estimates of marine primary production from ocean color

The third primary production algorithm round robin (PPARR3) compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models. Here we compare the global primary production fields corresponding to eight months of 1998 and 1999 as estimated from common input fields of photosynthetically-available radiation (PAR), sea-surface temperature (SST), mixed-layer depth, and chlorophyll concentration. We also quantify the sensitivity of the ocean-color-based models to perturbations in their input variables. The pair-wise correlation between ocean-color models was used to cluster them into groups or related output, which reflect the regions and environmental conditions under which they respond differently. The groups do not follow model complexity with regards to wavelength or depth dependence, though they are related to the manner in which temperature is used to parameterize photosynthesis. Global average PP varies by a factor of two between models. The models diverged the most for the Southern Ocean, SST under 10 degrees C, and chlorophyll concentration exceeding 1 mg Chlm(-3). Based on the conditions under which the model results diverge most, we conclude that current ocean-color-based models are challenged by high-nutrient low-chlorophyll conditions, and extreme temperatures or chlorophyll concentrations. The GCM-based models predict comparable primary production to those based on ocean color: they estimate higher values in the Southern Ocean, at low SST, and in the equatorial band, while they estimate lower values in eutrophic regions (probably because the area of high chlorophyll concentrations is smaller in the GCMs). Further progress in primary production modeling requires improved understanding of the effect of temperature on photosynthesis and better parameterization of the maximum photosynthetic rate. (c) 2006 Elsevier Ltd. All rights reserved.

Applying GIS tools for analysing urban thermal environment

A methodology for analyzing the solar access and its influence on both air temperature and thermal comfort of the urban environment was here developed by applying the potentiality of GIS tools. Urban canyons in a specific area of a Brazilian medium sized city were studied. First, a computational algorithm was applied in order to allow the determination of sky view factors (SVF) and sun-paths in urban canyons. Then, air temperatures in 40 measurement points were collected within the study area. Solar radiation values of these canyons were determined and subsequently stored in a GIS database. The creation of thermal maps for the whole neighbourhood was possible due to a statistical treatment of the data, by promoting the interpolation of values. All data could then be spatially cross-examined. In addition, thermal comfort maps for summer and winter periods were generated. The methodology allowed the identification of thermal tendencies within the neighbourhood, what can be useful in the conception of guidelines for urban planning purposes.

Biomass burning fuel consumption rates: a field measurement database

Landscape fires show large variability in the amount of biomass or fuel consumed per unit area burned. Fuel consumption (FC) depends on the biomass available to burn and the fraction of the biomass that is actually combusted, and can be combined with estimates of area burned to assess emissions. While burned area can be detected from space and estimates are becoming more reliable due to improved algorithms and sensors, FC is usually modeled or taken selectively from the literature. We compiled the peerreviewed literature on FC for various biomes and fuel categories to understand FC and its variability better, and to provide a database that can be used to constrain biogeochemical models with fire modules. We compiled in total 77 studies covering 11 biomes including savanna (15 studies, average FC of 4.6 t DM (dry matter) ha 1 with a standard deviation of 2.2), tropical forest (n = 19, FC = 126 +/- 77), temperate forest (n = 12, FC = 58 +/- 72), boreal forest (n = 16, FC = 35 +/- 24), pasture (n = 4, FC = 28 +/- 9.3), shifting cultivation (n = 2, FC = 23, with a range of 4.0-43), crop residue (n = 4, FC = 6.5 +/- 9.0), chaparral (n = 3, FC = 27 +/- 19), tropical peatland (n = 4, FC = 314 +/- 196), boreal peatland (n = 2, FC = 42 [42-43]), and tundra (n = 1, FC = 40). Within biomes the regional variability in the number of measurements was sometimes large, with e. g. only three measurement locations in boreal Russia and 35 sites in North America. Substantial regional differences in FC were found within the defined biomes: for example, FC of temperate pine forests in the USA was 37% lower than Australian forests dominated by eucalypt trees. Besides showing the differences between biomes, FC estimates were also grouped into different fuel classes. Our results highlight the large variability in FC, not only between biomes but also within biomes and fuel classes. This implies that substantial uncertainties are associated with using biome-averaged values to represent FC for whole biomes. Comparing the compiled FC values with co-located Global Fire Emissions Database version 3 (GFED3) FC indicates that modeling studies that aim to represent variability in FC also within biomes, still require improvements as they have difficulty in representing the dynamics governing FC.

A survey of radiographic measurement estimation in assessment of dental implant length.

The aim of this study is to survey radiographic measurement estimation in the assessment of dental implant length according to dentists' confidence. A 19-point questionnaire with closed-ended questions was used by two graduate students to interview 69 dentists during a dental implant meeting. Included were 12 questions related to over- and underestimation in three radiographic modalities: panoramic (P), conventional tomography (T), and computerized tomography (CT). The database was analyzed by Epi-Info 6.04 software and the values from two radiographic modalities, P and T, were compared using a chi2 test. The results showed that 38.24% of the dentists' confidence was in the overestimation of measurements in P, 30.56% in T, and 0% in CT. On the other hand, considering the underestimated measurements, the percentages were 47.06% in P, 33.33% in T, and 1.92% in CT. The frequency of under- and overestimation were statistically significant (chi2 = 6.32; P = .0425) between P and T. CT was the radiographic modality with higher measurement precision according to dentists' confidence. In conclusion, the interviewed dentists felt that CT was the best radiographic modality when considering the measurement estimation precision in preoperative dental implant assessment.

Modeling approach based on experimental results for prediction of measurement errors in energy meters

This paper presents a general modeling approach to investigate and to predict measurement errors in active energy meters both induction and electronic types. The measurement error modeling is based on Generalized Additive Model (GAM), Ridge Regression method and experimental results of meter provided by a measurement system. The measurement system provides a database of 26 pairs of test waveforms captured in a real electrical distribution system, with different load characteristics (industrial, commercial, agricultural, and residential), covering different harmonic distortions, and balanced and unbalanced voltage conditions. In order to illustrate the proposed approach, the measurement error models are discussed and several results, which are derived from experimental tests, are presented in the form of three-dimensional graphs, and generalized as error equations. © 2009 IEEE.

Specialist tool for monitoring the measurement degradation process of induction active energy meters

This paper presents a methodology and a specialist tool for failure probability analysis of induction type watt-hour meters, considering the main variables related to their measurement degradation processes. The database of the metering park of a distribution company, named Elektro Electricity and Services Co., was used for determining the most relevant variables and to feed the data in the software. The modeling developed to calculate the watt-hour meters probability of failure was implemented in a tool through a user friendly platform, written in Delphi language. Among the main features of this tool are: analysis of probability of failure by risk range; geographical localization of the meters in the metering park, and automatic sampling of induction type watt-hour meters, based on a risk classification expert system, in order to obtain information to aid the management of these meters. The main goals of the specialist tool are following and managing the measurement degradation, maintenance and replacement processes for induction watt-hour meters. © 2011 IEEE.