Ningbo Meteorological Bureau

Ningbo, China

Ningbo Meteorological Bureau

Ningbo, China
Time filter
Source Type

Sun L.,Chinese Academy of Agricultural Sciences | Sun L.,U.S. Department of Agriculture | Chen Z.,Chinese Academy of Agricultural Sciences | Gao F.,U.S. Department of Agriculture | And 5 more authors.
Computers and Geosciences | Year: 2017

Land surface temperature (LST) is a critical parameter in environmental studies and resource management. The MODIS LST data product has been widely used in various studies, such as drought monitoring, evapotranspiration mapping, soil moisture estimation and forest fire detection. However, cloud contamination affects thermal band observations and will lead to inconsistent LST results. In this study, we present a new Remotely Sensed DAily land Surface Temperature reconstruction (RSDAST) model that recovers clear sky LST for pixels covered by cloud using only clear-sky neighboring pixels from nearby dates. The reconstructed LST was validated using the original LST pixels. Model shows high accuracy for reconstructing one masked pixel with R2 of 0.995, bias of −0.02 K and RMSE of 0.51 K. Extended spatial reconstruction results show a better accuracy for flat areas with R2 of 0.72‒0.89, bias of −0.02–0.21 K, and RMSE of 0.92–1.16 K, and for mountain areas with R2 of 0.81–0.89, bias of −0.35–−1.52 K, and RMSE of 1.42‒2.24 K. The reconstructed areas show spatial and temporal patterns that are consistent with the clear neighbor areas. In the reconstructed LST and NDVI triangle feature space which is controlled by soil moisture, LST values distributed reasonably and correspond well to the real soil moisture conditions. Our approach shows great potential for reconstructing clear sky LST under cloudy conditions and provides consistent daily LST which are critical for daily drought monitoring. © 2017 Elsevier Ltd

Zhang T.-L.,Beijing Normal University | Zhang T.-L.,Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities | Sun R.,Beijing Normal University | Sun R.,Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities | And 5 more authors.
Chinese Journal of Ecology | Year: 2011

Using Biome-BGC model can simulate vegetation productivity through the coupling of water and CO2 exchange processes between vegetation, soil and atmosphere, but the soil water balance module is not perfect enough, leading to a large deviation between simulated and observed values under condition of a long time no precipitation. Aiming at this problem, this paper improved and adjusted the equation of stomatal conductance stressed by soil water, the calculation formula of evapotranspiration, and the process of soil water loss in Biome-BGC model. Using this improved model, the evapotranspiration and vegetation productivity in Harvard Forest area were simulated, and compared with field observations. The accuracy of simulated results by the improved model enhanced obviously, with the evapotranspiration R2 between simulated and observed values increased from 0.483 to 0.617, NEE R2 increased from 0.658 to 0.813, root mean square error (RMSE) of annual evapotranspiration decreased averagely by 48.7%, and annual sum squared error (ASSE) of NEE decreased averagely by 39.8%, which suggested that the simulated results by using the improved model were more close to the observed results.

Zhang T.-L.,Beijing Normal University | Zhang T.-L.,Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities | Sun R.,Beijing Normal University | Sun R.,Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities | And 3 more authors.
Chinese Journal of Ecology | Year: 2011

Ecological process model based on defined mechanism can well simulate the dynamic behaviors and features of terrestrial ecosystem, but could become a bottleneck in application because of numerous parameters needed to be confirmed. In this paper, simulated annealing algorithm was used to optimize the physiological and ecological parameters of Biome-BGC model. The first step was to choose some of these parameters to optimize, and then, gradually optimized these parameters. By using the optimized parameters, the model simulation results were much more close to the observed data, and the parameter optimization could effectively reduce the uncertainty of model simulation. The parameter optimization method used in this paper could provide a case and an idea for the parameter identification and optimization of ecological process models, and also, help to expand the application area of the models.

Feng L.,Beijing Normal University | Feng L.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | Sun R.,Beijing Normal University | Sun R.,Beijing Key Laboratory of Environmental Remote Sensing and City Digitalization | And 5 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2011

Carbon cycle of terrestrial ecosystem is one of the hot issues in global change science. And there are more difficult during study with agroecosystem because of the strong affect caused by human activities such as sowing, fertilizing and irrigation. In this study, a measurement is carried out in Guantao, Hebei Province, China, which is a typical argoecosystem station. In this paper, carbon dioxide fluxes in Guantao, were simulated by BIOME-BGC model as well, and the result was compared with the eddy covariance (EC) data. The result shows that the trend curves of simulated data and observation data were well matched in growing season of winter wheat in 2009. © 2011 IEEE.

Xu J.,Hangzhou Dianzi University | Huang X.,Ningbo Meteorological Bureau | Lu Y.,Ningbo Meteorological Bureau
Proceedings - NICOGRAPH International 2016, NicoInt 2016 | Year: 2016

In this study, an algorithm named EnergyTrend Constraint TREC (ET-TREC) that retrieves typhooncirculation field is proposed. Firstly, the radar reflectivity datais smoothed and interpolated into regular grids in preprocessingstage. Then for each grid at previous time step, acorresponding one with maximum correlation at current timestep is found under energy trend constraint, the collection ofthese computed grid pairs reflects the movement of circulationstructure and thus the wind field is obtained. Finally, a qualitycontrol is performed with total variation reconstruction tosmooth the global wind field by eliminating error data andfilling missing data points. Experimental result shows that thismethod more accurately reflects the characteristic of typhooncirculation structure in observation compared with traditionalTREC analysis, and more stable to be applied in Chinesetyphoon forecasting. © 2016 IEEE.

Hu B.,Ningbo Meteorological Bureau | Yan J.,Zhejiang Provincial Chunan Middle School | Ding Y.,Ningbo Meteorological Bureau | Huang H.,Ningbo Meteorological Bureau | Zhao W.,Ningbo Meteorological Bureau
Journal of Natural Disasters | Year: 2012

Typhoons happen frequently with serious consequences, so it is important to assess their risk. This paper takes Ningbo city as the example, draws the zoning map of typhoon disaster for the city using a risk zoning model, which was built on the basis of the membership function and natural disaster risk theory, while considering the hazard, exposure and vulnerability of typhoons, and applying the GIS technology. The effectiveness of the model was verified by disaster levels. The results show that, the overall risk indices of Ninghai, Yinzhou, Yuyao, Fenghua, Xiangshan and Cixi are relatively higher in counties and urban districts in Ningbo, while the indices of the old city (Haishu, Jiangdong, Jiangbei districts) , Zhenhai and Beilun are lower; the risk levels of typhoon disasters in the southeast coastal cities and towns and some mountain areas are high ; disaster level and risk index has a good correlation, with the coefficient of determination reaching 0.7181 and the confidence interval passed 0.01.

Tu X.,Ningbo Meteorological Bureau | Yao R.,Ningbo Meteorological Bureau | Yang H.,Ningbo Meteorological Bureau | Zhang C.,Ningbo Meteorological Bureau
Journal of Natural Disasters | Year: 2013

Based on the observation data over May 30 - 31, 2012 on the 370 meters tower constructed on Liangmaoshan Island of Ningbo City, analysis is done on an extro-tropical cyclone affecting the Zhejiang coastal areas. Results show that the extra-tropical cyclone is the main reason causing the disastrous heavy rainfalls across the north Zhejiang Province. Disastrous strong winds occur twice in turn. The first duration was caused by the extra-tropical cyclone blowing into the sea, with velocities keeping at the same pace at all tower levels and lasting for about 5 hours. Pressure gradient due to the cyclone system and weak cold air mass is blamed for the second strong wind duration, with wind force 7 originating in 199-232m, then stretching up and down, and lasting for only 1 hour at low levels. Both strong wind durations are accompanied with torrential rainfalls, but rainfalls are much more significant for the low pressure winds. Wind speed follows exponential law with different indices during different periods, about 0. 093, 0. 067 and 0. 041, respectively for before, during and after the strong wind periods. Wind standard deviations and turbulence intensities display differently at different levels. The stan dard deviation scattered vastly but turbulence intensity following a power law at 199 m and 232 m; while at the other levels, speed deviations follow a linear law, but no apparent tendency between turbulence intensities and speeds. Gust coefficients are less than 1.4 and intensities are less than 0.6 during strong wind durations. Successive power spectrum of instant speed shows no periodicity during strong wind.

Loading Ningbo Meteorological Bureau collaborators
Loading Ningbo Meteorological Bureau collaborators