Estimation of Regional Evapotranspiration by Combining Aircraftand Ground-Based Measurements

Two methods are examined for combining measurements from instrumented aircraftand towers to estimate regional scale evapotranspiration. Aircraft data provided spatially averaged values of properties of the surface, the evaporative fraction and maximum stomatal conductance. These quantities are less sensitive to meteorological conditions than the turbulent fluxes of heat and water vapour themselves. The methods allowed aircraft data collected over several days to be averaged and thus to reduce the random error associated with the temporal under-sampling inherent in aircraft measurements. Evaporative fraction is estimated directly from the aircraft data, while maximum stomatal conductance is estimated by coupling the Penman–Monteith equation to a simple model relating surface conductance to the incoming shortwave radiation and specific humidity saturation deficit. The spatial averages of evaporative fraction and maximum stomatal conductance can then be used with routine tower data to estimate the regional scale evapotranspiration. Data from aircraft flights and six ground based sites during the OASIS field campaign in south–east New South Wales in 1995 have been used to check the methods. Both the evaporative fraction and the maximum stomatal conductance derived from the aircraft data give information on the spatial variability of the surface energy budget at scales from 10 to 100 km. Daily averaged latent heat fluxes estimated using these methods for the OASIS study region agree with the available observations in quasi-stationary conditions or in weakly non-stationary conditions when the data from several aircraft flights are averaged to reduce the impact of short term imbalances in the surface energy budget.     

Groundwater Discharge as a Source of Dissolved Carbon and Greenhouse Gases in a Subtropical Estuary

Groundwater may be highly enriched in dissolved carbon species, but its role as a source of carbon to coastal waters is still poorly constrained. Exports of deep and shallow groundwater-derived dissolved carbon species from a small subtropical estuary (Korogoro Creek, Australia, latitude ?31.0478°, longitude 153.0649°) were quantified using a radium isotope mass balance model (²³³Ra and ²²⁴Ra, natural groundwater tracers) under two hydrological conditions. In addition, air-water exchange of carbon dioxide and methane in the estuary was estimated. The highest carbon inputs to the estuary were from deep fresh groundwater in the wet season. Most of the dissolved carbon delivered by groundwater and exported from the estuary to the coastal ocean was in the form of dissolved inorganic carbon (DIC; 687 mmol m^?2 estuary day^?1; 20 mmol m^?2 catchment day^?1, respectively), with a large export of alkalinity (23 mmol m^?2 catchment day^?1). Average water to air flux of CO₂ (869 mmol m^?2 day^?1) and CH₄ (26 mmol m^?2 day^?1) were 5- and 43-fold higher, respectively, than the average global evasion in estuaries due to the large input of CO₂- and CH₄-enriched groundwater. The groundwater discharge contribution to carbon exports from the estuary for DIC, dissolved organic carbon (DOC), alkalinity, CO₂, and CH₄ was 22, 41, 3, 75, and 100 %, respectively. The results show that CO₂ and CH₄ evasion rates from small subtropical estuaries surrounded by wetlands can be extremely high and that groundwater discharge had a major role in carbon export and evasion from the estuary and therefore should be accounted for in coastal carbon budgets.     

Estimating the expansion of urban areas and urban heat islands (UHI) in Ghana: a case study

Natural Hazards - This research is focused on identifying urban sprawl pattern and extent in two rapidly growing major Ghanaian cities (Accra and Kumasi) and how urban expansion affected heat...     

A Trophic Flow Model of the Caeté Mangrove Estuary (North Brazil) with Considerations for the Sustainable Use of its Resources

The Caeté Estuary lies within the world's second largest mangrove region, 200 km south-east of the Amazon delta. It has an extension of about 220 km²and is subjected to a considerable human impact through intensive harvest of mangrove crabs (Ucides cordatus) and logging of mangroves. In order to integrate available information on biomass, catches, food spectrum and dynamics of the main species populations of the system, a trophic steady state model of 19 compartments was constructed using the ECOPATH II software (Christensen & Pauly, 1992). Ninety-nine percent of total system biomass is made up by mangroves (Rhizophora mangle, Avicennia germinans andLaguncularia racemosa ), which are assumed to cover about 45% of the total area and contribute about 60% to the system's primary production. The remaining biomass (132 g m⁻²) is distributed between the pelagic and benthic domains in proportions of 10% and 90% respectively. Through litter fall, mangroves inject the main primary food source into the system, which is either consumed directly by herbivores (principally land crabs, Ucides cordatus) or, when already metabolized by bacteria, by detritivors (principally fiddler crabs, Uca spp.). These two groups are prominent in terms of biomass (80 g and 14·5 g m⁻²), and food intake (1120 g m⁻² yr⁻¹and 1378 g m⁻² yr⁻¹respectively). According to the model estimates, energy flow through the fish and shrimp compartments is of relatively low importance for the energy cycling within the system, a finding which is contrary to the situation in other mangrove estuaries reported in the literature. The dominance of mangrove epibenthos is attributed to the fact that a large part of the system's production remains within the mangrove forest as material export to the estuary is restricted to spring tides, when the forest is completely indundated. This is also the reason for the low abundance of suspension feeders, which are restricted to a small belt along the Caeté River and the small creeks which are watered daily. Phytoplankton, temporarily refloating benthic diatoms, neritic zooplankton and small pelagic fish dominate the (low) pelagic biomass. Total system throughput (10 559 g m⁻² yr⁻¹) and mean transfer efficiency between trophic levels (9·8%) calculated by the model fit well into the range reported for other tropical coastal ecosystems. The very high gross efficiency of the fishery (catch/net primary production) of 8·6% and its low trophic level (2·1) is explained by a high harvesting rate of mangroves and the fact that the main animal resource in the system are the mangrove crabs (Ucides cordatus), which feed at the first trophic level. The model was balanced asuming a turnover rate for the land crabs of P/B=0·25 (P/B: production per unit of biomass) which is possibly too high. If this value was replaced by a (possibly more realistic) lower value, the model would not balance, suggesting a situation in which more biomass is being harvested than produced, which hints to an overexploitation of this resource A ranking of the various system components in terms of their contribution to the system function (ascendency sensu Ulanowicz, 1997) revealed that detritus and associated bacteria contribute 34%, mangroves 19%, fiddler crabs 13%, phytoplankton and microphytobenthos 10%, mangrove crabs 10%, and the remaining 14 groups 14% to the total ascendency. Summary statistics of the model are given and compared with those of other coastal ecosystems.     

MegaZ-LRG: a photometric redshift catalogue of one million SDSS luminous red galaxies

We describe the construction of MegaZ-LRG, a photometric redshift catalogue of over one million luminous red galaxies (LRGs) in the redshift range  0.4 < z < 0.7  with limiting magnitude   i < 20  . The catalogue is selected from the imaging data of the Sloan Digital Sky Survey (SDSS) Data Release 4. The 2dF-SDSS LRG and Quasar (2SLAQ) spectroscopic redshift catalogue of 13 000 intermediate-redshift LRGs provides a photometric redshift training set, allowing use of ann z, a neural network-based photometric-redshift estimator. The rms photometric redshift accuracy obtained for an evaluation set selected from the 2SLAQ sample is  σ _z = 0.049  averaged over all galaxies, and  σ _z = 0.040  for a brighter subsample  ( i < 19.0)  . The catalogue is expected to contain ∼5 per cent stellar contamination. The ann z code is used to compute a refined star/galaxy probability based on a range of photometric parameters; this allows the contamination fraction to be reduced to 2 per cent with negligible loss of genuine galaxies. The MegaZ-LRG catalogue is publicly available on the World Wide Web from http://www.2slaq.info .     

Health profiles of Hamilton: Spatial characterisation of neighbourhoods for health investigations

This paper is part of a larger research program which employs a mixed-methods approach to study the determinants of health at the local level using specific neighborhoods in Hamilton, Ontario, Canada. In this paper, multivariate, spatial statistical techniques and geographic information systems are used to address questions about the characterization of neighbourhoods, based on socioeconomic determinants of health and risk factors such as smoking. While neighbourhood characterization has been a component of public health surveillance for some time, geostatistical techniques can now be used to derive more accurate representation of neighbourhoods for use in subsequent analysis. We utilize principal components analysis to reduce the data and extract the components that represent the underlying local processes. Principal components are also overlayed on comparative mortality figures to visualize where the socio-demographic determinants of health correspond spatially with mortality patterns. Predicted values from the components are then analysed for spatial clustering using local indicators of spatial association. The findings reveal a pattern of distinct neighbourhoods that will be used in subsequent quantitative and qualitative stages in the larger research programme. The results can also be used to inform public health policy and to target public health interventions.     

Dynamical and microphysical characteristics of Arctic clouds using integrated observations collected over SHEBA during the April 1998 FIRE.ACE flights of the Canadian Convair

Summary The purpose of this study is to better understand the dynamical and microphysical processes within Arctic clouds, which occurred in April 1998 over the Surface Heat Budget of the Arctic Ocean (SHEBA) ship during the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment Arctic Cloud Experiment (FIRE.ACE). The observations from the four cases in the present study were collected by instruments mounted onboard the National Research Council (NRC) Convair, as well as, the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellite, the SHEBA surface based NOAA Doppler radar (35GHz, Ka-Band), and the NOAA depolarization lidar (0.523µm) measurements. The aircraft observations were collected at 32Hz (3-m scale). The Meteorological Services of Canada (MSC) lidar (1.064µm) was operated onboard the Convair-580. The AVHRR observations, representing a 5-km horizontal resolution, were used to estimate particle size, phase, and optical thickness. Constant altitude flight legs were made at about 100m over the ocean surface. Vertical air velocity (w), reflectivity and Doppler velocity, and backscatter and depolarization ratio values were used to define the size of the important dynamical structures. Ice crystal number concentration (N_i), ice water content (IWC), droplet number concentration (N_d), liquid water content (LWC) and characteristic particle size and shape were summarized for each case. The effective radius (r_eff) values for liquid clouds obtained from in-situ and AVHRR observations were found comparable. The large variability in IWC can be due to undetected ice crystals at small size ranges. Mixed phased conditions in the AVHRR retrievals complicated the comparisons with in-situ data. N_i was found to be directly related to the history of the air-parcel dynamics e.g., w. The variability and differences in the parameters obtained from various platforms can be attributed to their instrumental capabilities, resolution, as well as the cloud development.