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Jin Z.-F.,Zhejiang Climate Center | Yang D.,Ningbo Meteorological Observatory | Yao Y.-P.,Zhejiang Climate Center | Li R.-Z.,Zhejiang Climate Center | Wang Z.-H.,Zhejiang Climate Center
Chinese Journal of Ecology | Year: 2016

Based on the meteorological data observed by 65 basic weather stations and statistical data of tea yield, the photosynthesis potential productivity (YQ), photo-thermal potential productivity (YT), and climatic potential productivity (YW) of tea in Zhejiang Province in the past 43 years were evaluated with successive correction analysis. The main factors influencing YW were explored by analyzing the spatial and temporal variation of potential productivity. The climate resource utilization (P) was also assessed by combining the YW with actual productivity (Ya). The results showed that, in the past 40 years, theYQ of tea in Zhejiang Province was 15.17 t•hm-2, with high value in north region and low value in the south region. The YT of tea was 11.27 t•hm-2, increasing gradually from Jinhua to the surrounding areas. The YW of tea was 8.39 t•hm-2, decreasing gradually from south to north. In the past 40 years, YQ, YT and YW all presented a decreased trend, with a climatic trend rate of -0.15, -0.45 and -0.40 t•hm-2•10 a-1, respectively. The variation speeds of YT and YW were more significant than that of YQ as the variation trend of heat and water resources was more obvious than that of solar radiation in the context of climate change. The P of tea in Zhejiang Province was 1.73%-35.12% (with an average of 11.90%) from 2009 to 2013. High P (>20%) was mainly distributed in the east of Hangzhou, Shaoxing, Ningbo, south of Huzhou, and middle of Jinhua. © 2016, Editorial Board of Chinese Journal of Ecology. All rights reserved. Source


Bao X.,Shanghai Typhoon Institute | Davidson N.E.,Shanghai Typhoon Institute | Yu H.,Shanghai Typhoon Institute | Hankinson M.C.N.,Monash University | And 5 more authors.
Monthly Weather Review | Year: 2015

Typhoon Fitow made landfall south of Shanghai, China, on 6 October 2013. During the following two days, precipitation in excess of 300 mm day-1 occurred 400 km to the north of the typhoon center. The rain-producing systems included (i) outward-spiraling rainbands, which developed in the storm's north sector in favorable environmental wind shear, and (ii) frontal cloud as a result of coastal frontogenesis. Over the rain area, in addition to enhanced ascent, there were increases in low-level moisture, convective instability, and midlevel relative vorticity. There is evidence of a preconditioning period prior to the rain when midlevel subsidence and boundary layer moistening occurred. From analysis of low-level equivalent potential temperature the following observations were made: (i) after landfall, a cold, dry airstream wrapped into Fitow's circulation from the north, limiting the inner-core rainfall and producing a cold-air boundary, and (ii) an extended warm, moist airstream from the east converged with the cold-air intrusion over the rain area. The heavy rain occurred as the large-scale flow reorganized. Major anticyclones developed over China and the North Pacific. At upper levels, a large-amplitude trough relocated over central China with the entrance to a southwesterly jet positioned near Shanghai. Back trajectories from the rain area indicate that four environmental interactions developed: (i) increasing midlevel injection of moist potential vorticity (PV) from Fitow's circulation; (ii) low-level warm, moist inflow from the east; (iii) midlevel inflow from nearby Typhoon Danas; and (iv) decreasing mid- to upper-level injection of PV from the midlatitude trough. The authors propose that the resultant PV structure change provided a very favorable environment for the development of rain systems. © 2015 American Meteorological Society. Source


Liu J.,Ningbo Meteorological Observatory | Yang S.,National Meteorological Center | Ma L.,Shanghai Typhoon Institute | Bao X.,Shanghai Typhoon Institute | And 2 more authors.
Journal of Applied Meteorology and Climatology | Year: 2013

A nudging scheme for humidity fields is implemented in the Advanced Hurricane Weather Research and Forecasting model (WRF) for tropical cyclone (TC) initialization. The scheme improves TC simulation by enhancing the TC humidity profile in deep-convection regions, where it uses satellite Fengyun 2 cloud-top brightness temperatures as a judging criterion. The impacts of the nudging on predicting TC intensity and structure are evaluated through the simulation of TC Khanun (2005) during its movement toward landfall at the coast of Zhejiang Province, China. During the nudging, the humidity distributions at the TC's inner core and along its outer spiral rainbands, where deep convections occur, are both enhanced. As a result, the intensity of the vortex is enhanced, being more consistent to the best-track data from the China Meteorological Administration. Specifically, the nudging modifies the simulated distribution of humidity according to convective activities captured by the satellite and therefore adjusts the development of deep convection in the model, which then influences the intensity and size of TC vortex through diabatic heating. During WRF simulation, the TC vortex initialized from the humidity nudging is dynamically and thermodynamically balanced with the background field, favoring a steady development of the vortex's intensity and structure. Because of the better simulation of TC inner core and outer spiral rainbands, theWRFsimulation skills of TC intensity and track are improved. © 2013 American Meteorological Society. Source


Shen S.,Nanjing University of Information Science and Technology | Yang D.,Ningbo Meteorological Observatory | Xiao W.,Nanjing University of Information Science and Technology | Liu S.,Nanjing University of Information Science and Technology | And 2 more authors.
Advances in Atmospheric Sciences | Year: 2014

Methane (CH4) emissions estimated with the Intergovernmental Panel on Climate Change (IPCC) inventory method at the city and regional scale are subject to large uncertainties. In this study, we determined the CH4:CO2 emissions ratio for both Nanjing and the Yangtze River Delta (YRD), using the atmospheric CH4 and CO2 concentrations measured at a suburban site in Nanjing in the winter. The atmospheric estimate of the CH4:CO2 emissions ratio was in reasonable agreement with that calculated using the IPCC method for the YRD (within 20%), but was 200% greater for the municipality of Nanjing. The most likely reason for the discrepancy is that emissions from unmanaged landfills are omitted from the official statistics on garbage production. © 2014, Chinese National Committee for International Association of Meteorology and Atmospheric Sciences, Institute of Atmospheric Physics, Science Press and Springer-Verlag Berlin Heidelberg. Source


Tu X.-P.,Ningbo Meteorological Observatory | Yao R.-S.,Ningbo Meteorological Observatory | Zhang C.-H.,Hainan Provincial Meteorological Observatory | Chen Y.-L.,Hainan Provincial Meteorological Observatory
Journal of Tropical Meteorology | Year: 2014

Based on the tropical cyclone data from the Central Meteorological Observatory of China, Japan Meteorological Agency, Joint Typhoon Warning Center and European Centre for Medium-Range Weather Forecasts (ECMWF) during the period of 2004 to 2009, three consensus methods are used in tropical cyclone (TC) track forecasts. Operational consensus results show that the objective forecasts of ECMWF help to improve consensus skill by 2%, 3%-5% and 3%-5%, decrease track bias by 2.5 km, 6-9 km and 10-12 km for the 24 h, 48 h and 72 h forecasts respectively over the years of 2007 to 2009. Analysis also indicates that consensus forecasts hold positive skills relative to each member. The multivariate regression composite is a method that shows relatively low skill, while the methods of arithmetic averaging and composite (in which the weighting coefficient is the reciprocal square of mean error of members) have almost comparable skills among members. Consensus forecast for a lead time of 96 h has negative skill relative to the ECMWF objective forecast. Source

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