Abstract The river-lake transitional zone of Poyang Lake is a key water area connecting the Yangtze River and Poyang Lake. It is important to understand the relationship between fish communities, hydrological dynamics, and other water environment factors in these waters. This study examined the status of fish resources in the river-lake transitional zone of Poyang Lake, from 2021 to 2022. We collected 3,880 individual fish, belonging to 5 orders, 10 families, and 54 species. Cypriniformes comprised the largest number of fish species at 64.81% of the total number of species. Overall, the fish ecological types were dominated by carnivorous, demersal, resident and viscous egg fish. According to the relative importance index, there were eight dominant species (including Coilia brachygnathus and Megalobrama mantschuricus ). The fish community was more abundant and structure was more complex in downstream areas and in the flood season. This area showed significant regional differences in the fish community structure, whereas seasonal differences were not significant. Analysis showed that the water level and flow correlated significantly with the Margalef richness index and Shannon-Wiener diversity index. Redundancy analysis showed that pH, oxidation-reduction potential, dissolved oxygen and the water level were key environmental factors affecting the fish community structure and species spatio temporal distribution. Thus, high water levels in the flood season and in downstream waters are important to the river-lake transitional zone of Poyang Lake. Collectively, this survey of fish resources in the river-lake transitional zone will support the protection and management of aquatic biological resources in Poyang Lake.
Abstract. The modern instrumental record (1979–2006) is analyzed in an attempt to reveal the dynamical structure and origins of the major modes of interannual variability of East Asian summer monsoon (EASM) and to elucidate their fundamental differences with the major modes of seasonal variability. These differences are instrumental in understanding of the forced (say orbital) and internal (say interannual) modes of variability in EASM. We show that the leading mode of interannual variation, which accounts for about 39% of the total variance, is primarily associated with decaying phases of major El Nino, whereas the second mode, which accounts for 11.3% of the total variance, is associated with the developing phase of El Nino/La Nina. The EASM responds to ENSO in a nonlinear fashion with regard to the developing and decay phases of El Nino. The two modes are determined by El Nino/La Nina forcing and monsoon-warm ocean interaction, or essentially driven by internal feedback processes within the coupled climate system. For this internal mode, the intertropical convergence zone (ITCZ) and subtropical EASM precipitations exhibit an out-of-phase variations; further, the Meiyu in Yangtze River Valley is also out-of-phase with the precipitation in the central North China. In contrast, the annual cycle forced by the solar radiation shows an in-phase variation between the ITCZ and the subtropical EASM precipitation. Further, the seasonal march of precipitation displays a continental-scale northward advance of a southwest-northeastward tilted rainband from mid-May toward the end of July. This coherent seasonal advance between Indian and East Asian monsoons suggests that the position of the northern edge of the summer monsoon over the central North China may be an adequate measure of the monsoon intensity for the forced mode. Given the fact that the annual modes share the similar external forcing with orbital variability, the difference between the annual cycle and interannual variation may help to understand the differences in the EASM variability on the orbital time scale and in the modern records.
Five global monthly top-of-atmosphere (TOA) outgoing longwave radiation (OLR) products are evaluated in this study, including the products derived from the High-Resolution Infrared Radiation Sounder (HIRS), Clouds and the Earth’s Radiant Energy System (CERES), Advanced Very High Resolution Radiometer (AVHRR), the CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data (CLARA), and the Global Energy and Water Cycle EXchanges (GEWEX) project. Results show that overall there is good consistency among these five products. Larger differences are found between GEWEX and CERES (HIRS) after (before) 2000 (RMSE ~ 5 W/m2), particularly in the tropical regions. In terms of global mean values, GEWEX shows large differences with the other products from the year 1992 to 2002, and CLARA shows large differences from the year 1979 to 1981, which are more obvious in the global ocean values. Large discrepancies among these products exist at low latitudinal bands, particularly before the year 2000. Australia and Asia (mid–low latitude part) are two typical regions in which larger differences are found.
The time series of precipitation in flood season (May-September) at Wuhan Station, which is set as an example of the kind of time series with chaos characters, is split into two parts: One includes macro climatic timescale period waves that are affected by some relatively steady climatic factors such as astronomical factors (sunspot, etc.), some other known and/or unknown factors, and the other includes micro climatic timescale period waves superimposed on the macro one. The evolutionary modeling (EM), which develops from genetic programming (GP), is supposed to be adept at simulating the former part because it creates the nonlinear ordinary differential equation (NODE) based upon the data series. The natural fractals (NF) are used to simulate the latter part. The final prediction is the sum of results from both methods, thus the model can reflect multi-time scale effects of forcing factors in the climate system. The results of this example for 2002 and 2003 are satisfactory for climatic prediction operation. The NODE can suggest that the data vary with time, which is beneficial to think over short-range climatic analysis and prediction. Comparison in principle between evolutionary modeling and linear modeling indicates that the evolutionary one is a better way to simulate the complex time series with nonlinear characteristics.
A Local Ensemble Transform Kalman Filter assimilation system has been implemented into an aerosol-coupled global nonhydrostatic model to simulate the aerosol mass concentration and aerosol optical properties of 3 desert sites (Ansai, Fukang, Shapotou) in northwestern China. One-month experiment results of April 2006 reveal that the data assimilation can correct the much overestimated aerosol surface mass concentration, and has a strong positive effect on the aerosol optical depth (AOD) simulation, improving agreement with observations. Improvement is limited with the Ångström Exponent (AE) simulation, except for much improved correlation coefficient and model skill scores over the Ansai site. Better agreement of the AOD spatial distribution with the independent observations of Terra (Deep Blue) and Multi-angle Imaging Spectroradiometer (MISR) AODs is obtained by assimilating the Moderate Resolution Imaging Spectroradiometer (MODIS) AOD product, especially for regions with AODs lower than 0.30. This study confirms the usefulness of the remote sensing observations for the improvement of global aerosol modeling.
Abstract The precipitation over the eastern Tibetan Plateau (ETP, here defined as 29°–38°N, 91°–103°E) usually exhibits significant subseasonal variation during boreal summer. As the hot spot of land‐air interaction, the influences of ETP surface soil temperature ( T soil ) on the local precipitation through subseasonal land‐air interaction are still unclear but urgently needed for improving subseasonal prediction. Based on station and reanalysis datasets of 1979–2018, this study identifies the evident quasi‐biweekly (QBW) (9–30 days) periodic signal of ETP surface T soil variation during the early summer (May–June), which results from the anomalies of southeastward propagating mid‐latitude QBW waves in the mid‐to‐upper troposphere. The observational results further show that the maximum positive anomaly of precipitation over the ETP lags the warmest surface T soil by one phase at the QBW timescale, indicating that the warming surface T soil could enhance the subseasonal precipitation. The numerical experiments using the WRF model further demonstrate the effect of warming surface T soil on enhancing the local cyclonic and precipitation anomaly through increasing upward sensible heat flux, the ascending motion, and water vapor convergence at the QBW timescale. In contrast, the effect of soil moisture over the ETP is much weaker than T soil at the subseasonal timescale. This study confirms the importance of surface T soil over the ETP in regulating the precipitation intensity, which suggests better simulating the land thermal feedback is crucial for improving the subseasonal prediction.
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