Air Force Meteorological Center

Beijing, China

Air Force Meteorological Center

Beijing, China
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Li Y.,Peking University | Zhu L.,State Oceanic Administration | Zhao X.,Peking University | Li S.,Peking University | Yan Y.,Air Force Meteorological Center
Journal of Climate | Year: 2013

The impact of urbanization on temperature trends in China was investigated with emphasis on two aspects of urbanization, land cover change, and human activity. A new station classification scheme was developed to incorporate these two aspects by utilizing land cover and energy consumption data. Observation temperature data of 274 stations and National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis temperature from 1979 to 2010 were used in conducting the observation minus reanalysis (OMR) method to detect urban influence. Results indicated that nearly half of the stations in the study area have been converted from nonurban to urban stations as a result of land cover change associated with urban expansion. It was determined that both land cover change and human activity play important roles in temperature change and contribute to the observed warming, particularly in urbanized stations, where the highest amount of warming was detected. Urbanized stations showed higher OMR temperature trends than those of unchanged stations. In addition, a statistically significant positive relationship was detected between human activity and temperature trends, which suggests that the observed warming is closely related to the intensity and spatial extent of human activity. In fact, the urbanization effect is strongly affected by specific characteristics of urbanization in local and regional scales. © 2013 American Meteorological Society.

Liu S.,Air Force Meteorological Center | Wang Q.,Air Force Meteorological Center | Liu H.,Air Force Meteorological Center
Jiefangjun Ligong Daxue Xuebao/Journal of PLA University of Science and Technology (Natural Science Edition) | Year: 2013

The schemes of Doppler radar reflectivity data 3D variational assimilation and hydrostatic balance in STMAS were introduced. The hydrostatic balance code was added into the STMAS cost function. The test shows that the reflectivity retrieved from the analysis field of STMAS is quite similar to that observed by doppler radar. Experiments using data from a typhoon case were conducted for comparing the different assimilation schemes. According to the experiments, the conclusions could be made that assimilating the reflectivity (STMAS scheme, test1)can result in a good performance, with the forecast of the rainfall area and cumulative precipitation improved, that adding hydrostatic balance penalty term and assimilating the reflectivity scheme together (HYDRO scheme, test1) can enhanced the total precipitation, but the maximal precipitation became smaller than sensitivity test 1, and that the forcast rainfall area and precipitation in HYDRO scheme and STMAS scheme were Improvement than control test.

Zheng Z.,Institute of Urban Meteorology | Zhang X.,Air Force Meteorological Center | Ding H.,Institute of Urban Meteorology
Journal of Natural Disasters | Year: 2012

Based on the daily meteorological observation station data from 1958 to 2008, the trends of extreme weather events in Beijing area were analyzed. Result shows that ( 1 ) All kinds of the extreme weather events have remarkable annual change on intensity and frequency. High temperature events and their intensities have a trend of increasing in the last 50 years, which means that, nowadays high temperature events are in a relatively highly-occurred period, while low temperature events are on the contrary. (2) The strong convection events such as rainstorm , hailstone and thunderstorm have no remarkable annual change, but weaken in intensity. Strong wind, sand storm and dense fog events decrease remarkably in the last 50 years. (3) The amount and intensity of the acid rain events increase significantly. (4) There are obvious differences in intensities and frequencies of extreme weather before and after abrupt weather warming, and the abrupt change of extreme temperature indices in the 1990s is 1 ∼2 years later than the abrupt temperature change. That is to say, the process of abrupt temperature change might be the intermediate of the extreme temperatures from one stationary period to another stationary one.

Dong H.-P.,Air force Meteorological Center | Li X.-W.,Chinese People's Liberation Army | Guo W.-D.,Air force Meteorological Center | Gao T.-C.,PLA University of Science and Technology
Journal of Tropical Meteorology | Year: 2013

Based on the newly developed Weather Research and Forecasting model (WRF) and its three-dimensional variational data assimilation (3DVAR) system, this study constructed twelve experiments to explore the impact of direct assimilation of different ATOVS radiance on the intensity and track simulation of super-typhoon Fanapi (2010) using a data assimilation cycle method. The result indicates that the assimilation of ATOVS radiance could improve typhoon intensity effectively. The average bias of the central sea level pressure (CSLP) drops to 18 hPa, compared to 42 hPa in the experiment without data assimilation. However, the influence due to different radiance data is not significant, which is less than 6 hPa on average, implying limited improvement from sole assimilation of ATOVS radiance. The track issue is studied in the following steps. First, the radiance from the same sensor of different satellites could produce different effect. For the AMSU-A, NOAA-15 and NOAA-18, they produce equivalent improvement, whereas NOAA-16 produces slightly poor effect. And for the AMSU-B, NOAA-15 and NOAA-16, they produce equivalent and more positive effect than that provided by the AMSU-A. Second, the assimilation radiance from different sensors of the identical satellites could also produce different effect. The assimilation of AMSU-B produces the largest improvement, while the ameliorating effect of HIRS/3 assimilation is inferior to that of AMSU-B assimilation, while the AMSU-A assimilation exhibits the poorest improvement. Moreover, the simultaneous assimilation of different radiance could not produce further improvement. Finally, the experiments of simultaneous assimilation radiance from multiple satellites indicate that such assimilation may lead to negative effect due to accumulative bias when adding various radiance data into the data assimilation system. Thus the assimilation of ATOVS radiance from a single satellite may perform better than that from two or three satellites.

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