Local feedback mechanisms of the shallow water region around the Maritime Continent

The focus of this study is the local-scale air-sea feedback mechanisms over the shallow shelf water region (water depth <200 m) of the Maritime Continent (MC). MC was selected as a pilot study site for its extensive shallow water coverage, geographic complexity, and importance in the global climate system. To identify the local-scale air-sea feedback processes, we ran numerical experiments with perturbed surface layer water temperature using a coupled ocean-atmosphere model and an uncoupled ocean model. By examining the responses of the coupled and uncoupled models to the water temperature perturbation, we identify that, at a local-scale, a negative feedback process through the coupled dynamics that tends to restore the SST from its perturbation could dominate the shallow water region of the MC at a short time scale of several days. The energy budget shows that 38% of initial perturbation-induced heat energy was adjusted through the air-sea feedback mechanisms within 2 weeks, of which 58% is directly transferred into the atmosphere by the adjustment of latent heat flux due to the evaporative cooling mechanism. The increased inputs of heat and moisture into the lower atmosphere then modifies its thermal structure and increases the formation of low-level clouds, which act as a shield preventing incoming solar radiation from reaching the sea surface, accounts for 38% of the total adjustment of surface heat fluxes, serving as the second mechanism for the negative feedback process. The adjustment of sensible heat flux and net longwave radiation play a secondary role. The response of the coupled system to the SST perturbation suggests a response time scale of the coupled feedback process of about 3–5 days. The two-way air-sea feedback tightly links the surface heat fluxes, clouds and SST, and can play an important role in regulating the short-term variability of the SST over the shallow shelf water regions

Polymorphism in Growth Hormone Gene and its Association with Growth Traits in Siniperca chuatsi

Growth hormone (GH) is a candidate gene for growth traits in fish. In this study, we assessed associations between single nucleotide polymorphisms (SNPs) in GH gene with growth traits in 357 Siniperca chuatsi individuals using high-resolution melting. Two SNPs were identified in GH gene, with one mutation in exon 5 (g.5045T>C), and one mutation in intron 5 (g.5234T>G). The corrections analysis of SNPs with the four growth traits was carried out using General Linear Model (GLM) estimation. Results showed that both of them were significantly associated with growth performance in S. chuatsi. For g.5234T>G, it was significantly associated with body weight (P＜0.01), body length (P＜0.05), body depth (P＜0.01), and body width (P＜0.01), and the individuals of genotype GG grew faster than those of genotypes TT and TG (P＜0.05). A further diplotype-trait association analysis confirmed that in fish with H3H2 (TC-GG) diplotype body weight, body length, and body width was greater than in those with other diplotypes (P＜0.05). These results demonstrated GH gene SNPs could be used as potential genetic markers in future marker assisted selection of S. chuatsi

Coupling of a regional atmospheric model (RegCM3) and a regional oceanic model (FVCOM) over the maritime continent

Climatological high resolution coupled climate model simulations for the maritime continent have been carried out using the regional climate model (RegCM) version 3 and the finite volume coastal ocean model (FVCOM) specifically designed to resolve regions characterized by complex geometry and bathymetry. The RegCM3 boundary forcing is provided by the EMCWF-ERA40 re-analysis. FVCOM is embedded in the Global MITgcm which provides boundary forcing. The domain of the coupled regional model covers the entire South China Sea with its through-flow, the entire Indonesian archipelago with the Indonesian through-flow (ITF) and includes a large region in the western Pacific and eastern Indian oceans. The coupled model is able to provide stable and realistic climatological simulations for a specific decade of atmospheric–oceanic variables without flux correction. The major focus of this work is on oceanic properties. First, the coupled simulation is assessed against ocean-only simulations carried out under two different sets of air–sea heat fluxes. The first set, provided by the MITgcm, is proved to be grossly deficient as the heat fluxes are evaluated by a two-dimensional, zonally averaged atmosphere and the simulated SST have anomalous cold biases. Hence the MITgcm fluxes are discarded. The second set, the NCEP re-analysis heat fluxes, produces a climatological evolution of the SST with an average cold bias of ~−0.8 °C. The coupling eliminates the cold bias and the coupled SST evolution is in excellent agreement with the analogous evolution in the SODA re-analysis data. The detailed comparison of oceanic circulation properties with the International Nusantara Stratification and Transport observations shows that the coupled simulation produces the best estimate of the total ITF transport through the Makassar strait while the transports of three ocean-only simulations are all underestimated. The annual cycle of the transport is also very well reproduced. The coupling also considerably improves the vertical thermal structure of the Makassar cross section in the upper layer affected by the heat fluxes. On the other hand, the coupling is relatively ineffective in improving the precipitation fields even though the coupled simulation captures reasonably well the precipitation annual cycle at three land stations in different latitudes.Singapore. National Research Foundation (Center for Environmental Sensing and Monitoring (CENSAM))Singapore-MIT Alliance for Research and Technology (SMART) programNational Natural Science Foundation (China) (NSFC, No. 41106003

An investigation of the thermal response to meteorological forcing in a hydrodynamic model of Lake Superior

Lake Superior, the largest lake in the world by surface area and third largest by volume, features strong spatiotemporal thermal variability due to its immense size and complex bathymetry. The objectives of this study are to document our recent modeling experiences on the simulation of the lake thermal structure and to explore underlying dynamic explanations of the observed modeling success. In this study, we use a three‐dimensional hydrodynamic model (FVCOM—Finite Volume Community Ocean Model) and an assimilative weather forecasting model (WRF—Weather Research and Forecasting Model) to study the annual heating and cooling cycle of Lake Superior. Model experiments are carried out with meteorological forcing based on interpolation of surface weather observations, on WRF and on Climate Forecast System Reanalysis (CFSR) reanalysis data, respectively. Model performance is assessed through comparison with satellite products and in situ measurements. Accurate simulations of the lake thermal structure are achieved through (1) adapting the COARE algorithm in the hydrodynamic model to derive instantaneous estimates of latent/sensible heat fluxes and upward longwave radiation based on prognostic surface water temperature simulated within the model as opposed to precomputing them with an assumed surface water temperature; (2) estimating incoming solar radiation and downward longwave radiation based on meteorological measurements as opposed to meteorological model‐based estimates; (3) using the weather forecasting model to provide high‐resolution dynamically constrained wind fields as opposed to wind fields interpolated from station observations. Analysis reveals that the key to the modeling success is to resolve the lake‐atmosphere interactions and apply appropriate representations of different meteorological forcing fields, based on the nature of their spatiotemporal variability. The close agreement between model simulation and observations also suggests that the 3‐D hydrodynamic model can provide reliable spatiotemporal estimates of heat budgets over Lake Superior and similar systems. Although there have been previous studies which analyzed the impact of the spatiotemporal variability of overwater wind fields on lake circulation, we believe this is the first detailed analysis of the importance of spatiotemporal variability of heat flux components on hydrodynamic simulation of 3‐D thermal structure in a lake.Key Points:Thermal response to meteorological forcing of Lake Superior is examinedKey to the modeling success is to resolve the lake‐air interactionsSpatiotemporal variability of surface meteorological components is importantPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113112/1/jgrc21314.pd