Guimond S.R.,Ocean and Atmospheric Science |
Guimond S.R.,NASA |
Bourassa M.A.,Ocean and Atmospheric Science |
Reasor P.D.,Hurricane Research Division
Journal of the Atmospheric Sciences | Year: 2011
Despite the fact that latent heating in cloud systems drives many atmospheric circulations, including tropical cyclones, little is known of its magnitude and structure, largely because of inadequate observations. In this work, a reasonably high-resolution (2 km), four-dimensional airborne Doppler radar retrieval of the latent heat of condensation/evaporation is presented for rapidly intensifying Hurricane Guillermo (1997). Several advancements in the basic retrieval algorithm are shown, including 1) analyzing the scheme within the dynamically consistent framework of a numerical model, 2) identifying algorithm sensitivities through the use of ancillary data sources, and 3) developing a precipitation budget storage term parameterization. The determination of the saturation state is shown to be an important part of the algorithm for updrafts of;5 m s-1 or less. The uncertainties in the magnitude of the retrieved heating are dominated by errors in the vertical velocity. Using a combination of error propagation and Monte Carlo uncertainty techniques, biases are found to be small, and randomly distributed errors in the heating magnitude are;16% for updrafts greater than 5 m s-1 and;156% for updrafts of 1 m s-1. Even though errors in the vertical velocity can lead to large uncertainties in the latent heating field for small updrafts/downdrafts, in an integrated sense the errors are not as drastic. In Part II, the impact of the retrievals is assessed by inserting the heating into realistic numerical simulations at 2-kmresolution and comparing the generated wind structure to the Doppler radar observations of Guillermo. © 2011 American Meteorological Society.
Gurney L.J.,Ocean and Atmospheric Science |
Pakhomov E.A.,Ocean and Atmospheric Science |
Christensen V.,Fisheries Center
Ecological Modelling | Year: 2014
A model of an ecosystem provides a useful tool for the exploration of management options to achieve desired objectives. With the move to a more holistic approach to marine resource management, ecosystem models and the indicators that can be derived using them, are providing a means to move away from single species management and allow for the ecosystem effects of population dynamics to be explored. This work describes the construction of an ecosystem model of the Prince Edward archipelago. The archipelago consists of two islands, Marion and Prince Edward, which are situated southeast of the southern tip of Africa at 46°46'S, 37°51'E. The islands are host to millions of seabirds and seals that use the islands as a refuge for breeding and moulting. Using the Ecopath software, the ecosystem is described across three separate decades (1960s, 1980s, 2000s). All trophic links are described based on the rich published literature that exists for the islands. Local survey data for population estimates and trophic linkages were sourced for defining and quantifying the food web. The system is summarised into 37 functional groups which include 4 primary producer groups at the lower trophic spectrum, and 14 land based top predator groups (seals and seabirds) representing the majority of the higher trophic levels. Two detrital groups are included. The food web is compared across the three time periods with transfer efficiencies declining for the higher trophic levels through time, suggesting a decline in energetic coupling between groups. Comparison of the PEI ecosystem with eight other modeled sub Antarctic/Antarctic systems showed the ecosystem size (as measured in total biomass throughput per year, year-1) to be lower than all other systems and was found to be most similar to the Kerguelen Islands for the ecological metrics assessed. Future research priorities are highlighted based on an assessment of data availability, data gaps and sensitivity testing. The construction of this model provides a much needed tool for the advancement of management for the archipelago, which have both fisheries and conservation concerns. © 2014 Elsevier B.V.
Tortell P.D.,Ocean and Atmospheric Science |
Tortell P.D.,University of British Columbia |
Mills M.M.,Stanford University |
Payne C.D.,Ocean and Atmospheric Science |
And 7 more authors.
Marine Ecology Progress Series | Year: 2013
Physiological characteristics of inorganic C uptake were examined in Southern Ocean ice algae and phytoplankton assemblages. Ice algal and phytoplankton assemblages were largely dominated by diatoms and Phaeocystis antarctica, and showed a high capacity for HCO3 - utilization, with direct HCO3 - transport accounting for ~60% of total inorganic C uptake. Extracellular carbonic anhydrase (eCA) was detectable in all samples, but with significantly lower activity in sea ice algae. Neither HCO3 - transport nor eCA activity was related to the in situ partial pressure of CO2 (pCO2) or taxonomic composition of samples. The half-saturation constant (KS) for inorganic C ranged from ~100 to 5000 μM, and showed significantly more variability among sea ice algae than phytoplankton assemblages. For the phytoplankton assemblages, there were significant positive correlations between in situ pCO2 and KS (higher C substrate affinity in low pCO2 waters), and also between KS and maximum C uptake rates (Vmax). In contrast, KS and Vmax in sea-ice algal assemblages were not correlated to each other, or to any other measured variables. The C isotope composition of particulate organic carbon δ13C-POC) in the phytoplankton assemblages showed modest variability (range -30 to -24.6‰) and was significantly correlated to the ratio of inferred growth rates (derived from Vmax) and in situ CO2 concentrations, but not to any measured C uptake parameters. δ13C-POC in sea ice algal samples (range -25.7 to -12.9‰) was significantly heavier than in the phytoplankton assemblages, and not correlated to any other variables. Our results provide evidence for the widespread occurrence of carbon-concentrating mechanisms in Southern Ocean sea ice algae and phytoplankton assemblages. © Inter-Research 2013.