Rudiger C.,Monash University |
Walker J.P.,Monash University |
Kerr Y.H.,CNRS Center for the Study of the Biosphere from Space |
Kim E.J.,NASA |
And 4 more authors.
IEEE Transactions on Geoscience and Remote Sensing | Year: 2014
The Soil Moisture and Ocean Salinity (SMOS) satellite marks the commencement of dedicated global surface soil moisture missions, and the first mission to make passive microwave observations at L-band. On-orbit calibration is an essential part of the instrument calibration strategy, but on-board beam-filling targets are not practical for such large apertures. Therefore, areas to serve as vicarious calibration targets need to be identified. Such sites can only be identified through field experiments including both in situ and airborne measurements. For this purpose, two field experiments were performed in central Australia. Three areas are studied as follows: 1) Lake Eyre, a typically dry salt lake; 2) Wirrangula Hill, with sparse vegetation and a dense cover of surface rock; and 3) Simpson Desert, characterized by dry sand dunes. Of those sites, only Wirrangula Hill and the Simpson Desert are found to be potentially suitable targets, as they have a spatial variation in brightness temperatures of <4 K under normal conditions. However, some limitations are observed for the Simpson Desert, where a bias of 15 K in vertical and 20 K in horizontal polarization exists between model predictions and observations, suggesting a lack of understanding of the underlying physics in this environment. Subsequent comparison with model predictions indicates a SMOS bias of 5 K in vertical and 11 K in horizontal polarization, and an unbiased root mean square difference of 10 K in both polarizations for Wirrangula Hill. Most importantly, the SMOS observations show that the brightness temperature evolution is dominated by regular seasonal patterns and that precipitation events have only little impact. © 2013 IEEE.
Lee J.-Y.,University of Hawaii at Manoa |
Wang B.,University of Hawaii at Manoa |
Kang I.-S.,Seoul National University |
Shukla J.,George Mason University |
And 10 more authors.
Climate Dynamics | Year: 2010
Given observed initial conditions, how well do coupled atmosphere-ocean models predict precipitation climatology with 1-month lead forecast? And how do the models' biases in climatology in turn affect prediction of seasonal anomalies? We address these questions based on analysis of 1-month lead retrospective predictions for 21 years of 1981-2001 made by 13 state-of-the-art coupled climate models and their multi-model ensemble (MME). The evaluation of the precipitation climatology is based on a newly designed metrics that consists of the annual mean, the solstitial mode and equinoctial asymmetric mode of the annual cycle, and the rainy season characteristics. We find that the 1-month lead seasonal prediction made by the 13-model ensemble has skills that are much higher than those in individual model ensemble predictions and approached to those in the ERA-40 and NCEP-2 reanalysis in terms of both the precipitation climatology and seasonal anomalies. We also demonstrate that the skill for individual coupled models in predicting seasonal precipitation anomalies is positively correlated with its performances on prediction of the annual mean and annual cycle of precipitation. In addition, the seasonal prediction skill for the tropical SST anomalies, which are the major predictability source of monsoon precipitation in the current coupled models, is closely link to the models' ability in simulating the SST mean state. Correction of the inherent bias in the mean state is critical for improving the long-lead seasonal prediction. Most individual coupled models reproduce realistically the long-term annual mean precipitation and the first annual cycle (solstitial mode), but they have difficulty in capturing the second annual (equinoctial asymmetric) mode faithfully, especially over the Indian Ocean (IO) and Western North Pacific (WNP) where the seasonal cycle in SST has significant biases. The coupled models replicate the monsoon rain domains very well except in the East Asian subtropical monsoon and the tropical WNP summer monsoon regions. The models also capture the gross features of the seasonal march of the rainy season including onset and withdraw of the Asian-Australian monsoon system over four major subdomains, but striking deficiencies in the coupled model predictions are observed over the South China Sea and WNP region, where considerable biases exist in both the amplitude and phase of the annual cycle and the summer precipitation amount and its interannual variability are underestimated. © 2010 Springer-Verlag.
Bocaniov S.A.,Helmholtz Center for Environmental Research |
Bocaniov S.A.,University of Waterloo |
Smith R.E.H.,University of Waterloo |
Spillman C.M.,Bureau of Meteorology Research Center |
And 3 more authors.
Hydrobiologia | Year: 2014
Dreissenid mussels have been hypothesized to cause selective decreases of phytoplankton in nearshore areas (nearshore shunt hypothesis) as well as the near-complete loss of the offshore phytoplankton spring bloom in some Laurentian Great Lakes. To evaluate whether mussels can reasonably be expected to mediate such changes, we extended the three-dimensional hydrodynamic-ecological model (ELCOM-CAEDYM) to include mussels as a state variable and applied it to Lake Erie (USA-Canada). Mussel-mediated decreases in mean phytoplankton biomass were highly sensitive to the assigned mussel population size in each basin. In the relatively deep east basin, mussels were predicted to decrease phytoplankton in both nearshore and offshore zones, even during periods of thermal stratification but especially during the spring phytoplankton maximum. Spatially, impacts were associated with mussel distributions but could be strong even in areas without high mussel biomass, consistent with advection from areas of higher mussel biomass. The results supported the nearshore shunt hypothesis that mussel impacts on phytoplankton should be greater in nearshore than offshore waters and also supported suggestions about the emerging importance of deep water offshore mussels. The results of this study provide an important insight into ecological role of mussels in lowering plankton productivity in some world's largest lakes. © 2013 Springer Science+Business Media Dordrecht.
Cai W.,CSIRO |
Cowan T.,CSIRO |
Arblaster J.M.,U.S. National Center for Atmospheric Research |
Arblaster J.M.,Bureau of Meteorology Research Center |
Geophysical Research Letters | Year: 2010
Trends in global oceanic heat content (OHC) over the late 20th century as simulated by climate models that incorporate all radiative forcing factors are smaller than the observed, but the causes are not clear. Given the cooling effect associated with increasing anthropogenic aerosols and natural forcing (i.e., volcanic aerosols), we examine their respective roles in the simulated global OHC trend and the associated ocean temperature structure, using targeted experiments from two models, designed to separate the individual impacts of these forcing components. We show that it is more likely that the indirect effect of aerosols, not volcanic aerosols alone, is the reason for the bulk of weaker modelled OHC trends. Further, anthropogenic aerosols are essential for simulating the structure of the observed temperature changes, including a concentrated cooling in the Southern Hemisphere subtropical latitudes, consistent with a more stable global Conveyer, a greater strengthening of the subtropical gyre circulation, and a stronger Southern Annular Mode trend in targeted experiments with anthropogenic aerosol forcing. © 2010 by the American Geophysical Union.
Oke P.R.,CSIRO |
Sakov P.,Bureau of Meteorology Research Center |
Cahill M.L.,CSIRO |
Dunn J.R.,CSIRO |
And 5 more authors.
Ocean Modelling | Year: 2013
The generation and evolution of eddies in the ocean are largely due to instabilities that are unpredictable, even on short time-scales. As a result, eddy-resolving ocean reanalyses typically use data assimilation to regularly adjust the model state. In this study, we present results from a second-generation eddy-resolving ocean reanalysis that is shown to match both assimilated and with-held observations more closely than its predecessor; but involves much smaller adjustments to the model state at each assimilation. We compare version 2 and 3 of the Bluelink ReANalysis (BRAN) in the Australian region. Overall, the misfits between the model fields in BRAN3 and observations are 5-28% smaller than the misfits for BRAN2. Specifically, we show that for BRAN3 (BRAN2) the sea-level, upper ocean temperature, upper-ocean salinity, and near-surface velocity match observations to within 7.7. cm (9.7. cm), 0.68. °C (0.95. °C), 0.16. psu (0.18. psu), and 20.2. cm/s (21.3. cm/s) respectively. We also show that the increments applied to BRAN3 - the artificial adjustments applied at each assimilation step - are typically 20-50% smaller than the equivalent adjustments in BRAN2. This leads us to conclude that the performance of BRAN3 is more dynamically consistent than BRAN2, rendering it more suitable for a range of applications, including analysis of ocean variability, extreme events, and process studies. © 2013 Elsevier Ltd.