Standard metabolic rates of Schlegels black rockfish with different body weights are determined in laboratory by using the flow-through respirometer at 11.2 ℃, 14.7℃ , 18.0 ℃ and 23.6 ℃ . The results indicate that...Standard metabolic rates of Schlegels black rockfish with different body weights are determined in laboratory by using the flow-through respirometer at 11.2 ℃, 14.7℃ , 18.0 ℃ and 23.6 ℃ . The results indicate that the standard metabolic rates increase with the increase of body weight at different temperatures. Relationship between them could be described as Rs = a ln W b. The mean of standard metabolic rate is significantly different among groups, but the b values are not. The standard metabolic rates of amended standard body weights decrease with the increase of temperature, and the mean of standard metabolic rate is also significantly different among groups when the standard body weights are 48.6 g, 147.9 g, and 243.1 g. Relationship between them could be described as Rsw = m e-b/T. The relations of standard metabolic rate ( Rs ) or relative metabolic rate ( Rs ) to body weight and temperature yield the following equations: Rs = 1.160 W 0.752 e -9.494/ T and Rs’= 1.160 W 0.254 e -9.494/ T.展开更多
Feeding growth experiments on black porgy, Sparus macrocephalus , were carried out at four ration levels from starvation to satiation and four temperatures ranging from 14.8° to 26.8℃. The energy budget was used...Feeding growth experiments on black porgy, Sparus macrocephalus , were carried out at four ration levels from starvation to satiation and four temperatures ranging from 14.8° to 26.8℃. The energy budget was used to calculate the metabolism in black porgy. Resting metabolism correlated significantly with body weight in power function at 24.4°, 20.1° and 14.8℃ ( R S=aW b ). The model predicting resting metabolism was obtained as: R S=0.0834W 0.8763 ·e 0.0319T . The feeding metabolism correlated linearly with ration level and food consumption. The predicting model of feeding metabolism is: R F=0.5631+0.0341·T-0.0013C·W·T+0.0010W ·T+0.0219C ·W-0.3335C. Using ln( RL+1 ), ln W , ln T and their interaction terms as independent variables, the prediction model of total daily metabolism was obtained by stepwise regression as: ln R T =-1.7328+0.3936ln W +1.1882ln( RL +1)-0.2823ln( RL +1)ln T +0.1555ln W ln T .展开更多
The effective temperature of the solar photosphere is usually obtained according to the solar constant, based on the Stefan-Boltzmann law. However its temperature distribution is not homogeneous. A hopeful way to obta...The effective temperature of the solar photosphere is usually obtained according to the solar constant, based on the Stefan-Boltzmann law. However its temperature distribution is not homogeneous. A hopeful way to obtain the area-temperature distribution of the solar photosphere is to solve the Black-body Radiation Inversion (BRI) problem. In this paper, a new practical solution method for BRI is developed. The theoretical analysis and numerical calculations show the low-temperature distribution difficulty of BRI is solved by this new method. Then the area-temperature distribution of the solar photosphere is obtained, according to the measured absolute solar spectral irradiance. It is the first realization of BRI for a real system after almost three decades of efforts. The results are comparable to that from the Stefan-Boltzmann law.展开更多
Using equivalent black body temperature （TBB） data retrieved from meteorological satellite GMS-5 during 1996-2002, the correlation between the circular symmetric/asymmetric component of TBB and the intensity of trop...Using equivalent black body temperature （TBB） data retrieved from meteorological satellite GMS-5 during 1996-2002, the correlation between the circular symmetric/asymmetric component of TBB and the intensity of tropical cyclone （TC） at various time lags from 0 to 48 h is analyzed for the Northwest Pacific （0^-50~N, 120%155~E）, excluding landed and near-coast samples. It is found that the total TBB near southeast of the eyewall, the circular symmetric component, and the sum of the amplitudes of tangential wave numbers 1-10 （SA10） of the TBB between the radii of 0.8^o and 1.7^o are significantly and negatively correlated with the TC intensity at various time lags from 0 to 48 h. Especially, the maximum 24-h lag correlation coefficients reach -0.52, -0.58, and -0.625, respectively. A statistical prediction scheme for TC intensity is developed based on climatic persistent, synoptic, and TBB factors by stepwise regression technique. It is found that the variance contribution of the averaged TBB over the ring between 1.0^o and 1.5^o from the TC center ranks the fourth in the equation for 12-h TC intensity prediction, and those of the total TBB near southeast of the eyewall and the difference between maximum and minimum TBB between 1.1^o and 1.5^o rank the third and fifth respectively in the 24-h forecast equation. It is also shown that, with TBB factors, the following predictions are improved compared to the scheme without TBB factors： 48-h prediction for severe tropical storm （STS）, 12-h prediction for TC with a weakening rate greater than 15 m s-1/12 h, 24-h intensity prediction for TC with almost no intensity change, and 48-h prediction for TC intensifying faster than 10 m s^-1/48 h.展开更多
利用2011—2015年安徽省自动气象站的降水观测资料和静止气象卫星FY-2E的黑体辐射温度(Black Body Temperature,TBB)资料,分析了安徽省不同地形条件下汛期短时强降水的时空分布特征及其与中尺度对流活动的关系,并对短时极端强降水的时...利用2011—2015年安徽省自动气象站的降水观测资料和静止气象卫星FY-2E的黑体辐射温度(Black Body Temperature,TBB)资料,分析了安徽省不同地形条件下汛期短时强降水的时空分布特征及其与中尺度对流活动的关系,并对短时极端强降水的时空特征进行了初步探讨。结果表明:2011—2015年不同地形条件下皖南山区为安徽省汛期短时强降水集中出现的区域,其次为大别山区和中东部丘陵地区,淮北平原发生最少。安徽省不同地形条件下汛期短时强降水发生次数月变化呈显著的单峰型,7月短时强降水发生最频繁,其他月份有所不同;候变化具有显著的多峰值—间断性发展的特点,主要集中出现在6月第1候至8月第6候之间,淮北平原变化最大,皖南山区则较均匀;日变化总体呈单峰型特征,午后15—19时最集中;皖南山区和中东部丘陵最明显;淮北平原和大别山区虽然仍以午后居多,但具有多峰值的特点,其中淮北平原除午后外,06—07时短时强降水发生较多;大别山区除午后外,02—03时和10时也为短时强降水发生的峰值。安徽省不同地形条件下汛期短时极端强降水分布较零散,没有明显的高发区,时间变化与短时强降水类似,具有一定的统计规律:皖南山区7月短时极端强降水发生最多,尤其是7月第5候;淮北平原8月短时极端强降水发生最多,尤其是8月第6候;中东部丘陵7月短时极端强降水发生最多,候变化相对均匀。皖南山区和中东部丘陵短时极端强降水集中出现在午后16—19时,其中大别山区02时还有一个峰值,淮北平原短时极端强降水日变化无显著峰值。展开更多
基金This paper is financially supported by the Major Program of National Natural Science Foundation (No.497901001)Key Basic Research and Development Program(No.G1999043710)of China
文摘Standard metabolic rates of Schlegels black rockfish with different body weights are determined in laboratory by using the flow-through respirometer at 11.2 ℃, 14.7℃ , 18.0 ℃ and 23.6 ℃ . The results indicate that the standard metabolic rates increase with the increase of body weight at different temperatures. Relationship between them could be described as Rs = a ln W b. The mean of standard metabolic rate is significantly different among groups, but the b values are not. The standard metabolic rates of amended standard body weights decrease with the increase of temperature, and the mean of standard metabolic rate is also significantly different among groups when the standard body weights are 48.6 g, 147.9 g, and 243.1 g. Relationship between them could be described as Rsw = m e-b/T. The relations of standard metabolic rate ( Rs ) or relative metabolic rate ( Rs ) to body weight and temperature yield the following equations: Rs = 1.160 W 0.752 e -9.494/ T and Rs’= 1.160 W 0.254 e -9.494/ T.
文摘Feeding growth experiments on black porgy, Sparus macrocephalus , were carried out at four ration levels from starvation to satiation and four temperatures ranging from 14.8° to 26.8℃. The energy budget was used to calculate the metabolism in black porgy. Resting metabolism correlated significantly with body weight in power function at 24.4°, 20.1° and 14.8℃ ( R S=aW b ). The model predicting resting metabolism was obtained as: R S=0.0834W 0.8763 ·e 0.0319T . The feeding metabolism correlated linearly with ration level and food consumption. The predicting model of feeding metabolism is: R F=0.5631+0.0341·T-0.0013C·W·T+0.0010W ·T+0.0219C ·W-0.3335C. Using ln( RL+1 ), ln W , ln T and their interaction terms as independent variables, the prediction model of total daily metabolism was obtained by stepwise regression as: ln R T =-1.7328+0.3936ln W +1.1882ln( RL +1)-0.2823ln( RL +1)ln T +0.1555ln W ln T .
基金supported by the National Natural Science Foundation of China (Grand Nos. 10675031, 10375012 and 19975009)supported in part by the Department of Education of Zhejiang Province (Grant No. Y200906911)
文摘The effective temperature of the solar photosphere is usually obtained according to the solar constant, based on the Stefan-Boltzmann law. However its temperature distribution is not homogeneous. A hopeful way to obtain the area-temperature distribution of the solar photosphere is to solve the Black-body Radiation Inversion (BRI) problem. In this paper, a new practical solution method for BRI is developed. The theoretical analysis and numerical calculations show the low-temperature distribution difficulty of BRI is solved by this new method. Then the area-temperature distribution of the solar photosphere is obtained, according to the measured absolute solar spectral irradiance. It is the first realization of BRI for a real system after almost three decades of efforts. The results are comparable to that from the Stefan-Boltzmann law.
基金Sponsored by the project from the Ministry of Science and Technology of the People's Republic of China under Grant No.2005DIB3J104the Generalized Project of CMAT under No.CMATG200TM17,Typhoon Research Foundation of Shanghai Meteorological Bureauthe Forecasting System Laboratory of NMC/CMA.
文摘Using equivalent black body temperature （TBB） data retrieved from meteorological satellite GMS-5 during 1996-2002, the correlation between the circular symmetric/asymmetric component of TBB and the intensity of tropical cyclone （TC） at various time lags from 0 to 48 h is analyzed for the Northwest Pacific （0^-50~N, 120%155~E）, excluding landed and near-coast samples. It is found that the total TBB near southeast of the eyewall, the circular symmetric component, and the sum of the amplitudes of tangential wave numbers 1-10 （SA10） of the TBB between the radii of 0.8^o and 1.7^o are significantly and negatively correlated with the TC intensity at various time lags from 0 to 48 h. Especially, the maximum 24-h lag correlation coefficients reach -0.52, -0.58, and -0.625, respectively. A statistical prediction scheme for TC intensity is developed based on climatic persistent, synoptic, and TBB factors by stepwise regression technique. It is found that the variance contribution of the averaged TBB over the ring between 1.0^o and 1.5^o from the TC center ranks the fourth in the equation for 12-h TC intensity prediction, and those of the total TBB near southeast of the eyewall and the difference between maximum and minimum TBB between 1.1^o and 1.5^o rank the third and fifth respectively in the 24-h forecast equation. It is also shown that, with TBB factors, the following predictions are improved compared to the scheme without TBB factors： 48-h prediction for severe tropical storm （STS）, 12-h prediction for TC with a weakening rate greater than 15 m s-1/12 h, 24-h intensity prediction for TC with almost no intensity change, and 48-h prediction for TC intensifying faster than 10 m s^-1/48 h.
文摘利用2011—2015年安徽省自动气象站的降水观测资料和静止气象卫星FY-2E的黑体辐射温度(Black Body Temperature,TBB)资料,分析了安徽省不同地形条件下汛期短时强降水的时空分布特征及其与中尺度对流活动的关系,并对短时极端强降水的时空特征进行了初步探讨。结果表明:2011—2015年不同地形条件下皖南山区为安徽省汛期短时强降水集中出现的区域,其次为大别山区和中东部丘陵地区,淮北平原发生最少。安徽省不同地形条件下汛期短时强降水发生次数月变化呈显著的单峰型,7月短时强降水发生最频繁,其他月份有所不同;候变化具有显著的多峰值—间断性发展的特点,主要集中出现在6月第1候至8月第6候之间,淮北平原变化最大,皖南山区则较均匀;日变化总体呈单峰型特征,午后15—19时最集中;皖南山区和中东部丘陵最明显;淮北平原和大别山区虽然仍以午后居多,但具有多峰值的特点,其中淮北平原除午后外,06—07时短时强降水发生较多;大别山区除午后外,02—03时和10时也为短时强降水发生的峰值。安徽省不同地形条件下汛期短时极端强降水分布较零散,没有明显的高发区,时间变化与短时强降水类似,具有一定的统计规律:皖南山区7月短时极端强降水发生最多,尤其是7月第5候;淮北平原8月短时极端强降水发生最多,尤其是8月第6候;中东部丘陵7月短时极端强降水发生最多,候变化相对均匀。皖南山区和中东部丘陵短时极端强降水集中出现在午后16—19时,其中大别山区02时还有一个峰值,淮北平原短时极端强降水日变化无显著峰值。
