A GCM Study on the Mechanism of Seasonal Abrupt Changes

ＡＧＣＭＳｔｕｄｙｏｎｔｈｅＭｅｃｈａｎｉｓｍｏｆＳｅａｓｏｎａｌＡｂｒｕｐｔＣｈａｎｇｅｓＷａｎｇＨｕｉｊｕｎ（王会军）ａｎｄＺｅｎｇＱｉｎｇｃｕｎ（曾庆存）（ＬＡＳＧ，ＩｎｓｔｉｔｕｔｅｏｆＡｔｍｏｓｐｈｅｒｉｃＰｈｙｓｉｃｓ，ＣｈｉｎｅｓｅＡｃ...     

Sensitivity Study of Nonlocal Turbulence ClosureScheme in Local Circulation

Ｓｅｎｓｉｔｉｖｉｔｙ　Ｓｔｕｄｙ　ｏｆ　Ｎｏｎｌｏｃａｌ　Ｔｕｒｂｕｌｅｎｃｅ　ＣｌｏｓｕｒｅＳｃｈｅｍｅ　ｉｎ　Ｌｏｃａｌ　ＣｉｒｃｕｌａｔｉｏｎＣｈｅｎＭｉｎｇａｎｄＨｏｎｅＺｈｏｎｇｘｉａｎｇ（ＩｎｓｔｉｔｕｔｅｏｆＡｔｍｏｓｐｈｅｒｉｃＰｈ...     

The Effect of Weak Shear－induced Motion on Brownian Coagulation of Aerosol Particles

ＴｈｅＥｆｆｅｃｔｏｆＷｅａｋＳｈｅａｒ－ｉｎｄｕｃｅｄＭｏｔｉｏｎｏｎＢｒｏｗｎｉａｎＣｏａｇｕｌａｔｉｏｎｏｆＡｅｒｏｓｏｌＰａｒｔｉｃｌｅｓＷｉｎｊｉｎｇｓｏｎｓ（Ｃ．Ｓ．Ｗｉｎ）（温景嵩）（Ｄｅｐａｒｔｍｅｎｔｏｆｐｈｙｓｉｃｓ，Ｎａｎｋａｉ...     

Effect of the Interaction of Different Scale Vortices on the Structure and Motion of Typhoons

ＥｆｆｅｃｔｏｆｔｈｅＩｎｔｅｒａｃｔｉｏｎｏｆＤｉｆｆｅｒｅｎｔＳｃａｌｅＶｏｒｔｉｃｅｓｏｎｔｈｅＳｔｒｕｃｔｕｒｅａｎｄＭｏｔｉｏｎｏｆＴｙｐｈｏｏｎｓＣｈｅｎＬｉａｎｓｈｏｕ（陈联寿）（ＣｈｉｎｅｓｅＡｃａｄｅｍｙｏｆＭｅｔ６ｏｒｏｌｏｇｉｃ...     

Monsoons over China

ＭｏｎｓｏｏｎｓｏｖｅｒＣｈｉｎａ￥ｂｙＤｉｎｇＹｉｈｕｉ（ＣｈｉｎｅｓｅＡｃａｄｅｍｙｏｆＭｅｔｅｏｒｏｌｏｇｉｃａｌＳｃｉｅｎｃｅｓ，Ｂｅｉｇｕｇ，Ｃｈｉｎａ）ＡＴＭＯＳＰＨＥＲＩＣＳＣＩＥＮＣＥＳＬＩＢＲＡＲＹ，１６Ｔｈｅｍｏｎｓｏｏｎｏｖｅｒ...     

The Quasi-Decadal Oscillation of Air-Sea System in the Northwestern Pacific Region

ＴｈｅＱｕａｓｉ－ＤｅｃａｄａｌＯｓｃｉｌａｔｉｏｎｏｆＡｉｒ－ＳｅａＳｙｓｔｅｍｉｎｔｈｅＮｏｒｔｈｗｅｓｔｅｒｎＰａｃｉｆｉｃＲｅｇｉｏｎ①ＬｉＣｈｏｎｇｙｉｎ（李崇银）ＬＡＳＧ,ＩｎｓｔｉｔｕｔｅｏｆＡｔｍｏｓｐｈｅｒｉｃＰｈｙｓｉｃｓ,Ｃｈｉ...     

Numerical Simulation for the Impact of Deforestation on Climate in China and Its Neighboring Regions

ＮｕｍｅｒｉｃａｌＳｉｍｕｌａｔｉｏｎｆｏｒｔｈｅＩｍｐａｃｔｏｆＤｅｆｏｒｅｓｔａｔｉｏｎ　ｏｎ　Ｃｌｉｍａｔｅ　ｉｎ　ＣｈｉｎａａｎｄＩｔｓＮｅｉｇｈｂｏｒｉｎｇ　ＲｅｇｉｏｎｓＳｏｎｇＹｕｋｕａｎ（宋玉宽）；ＣｈｅｎＬｏｎｇｘｕｎ（陈隆勋）ａｎ...     

ALow-order Model of Two-dimensional Fluid Dynamics on the Surface of a Sphere

ＡＬｏｗ－ｏｒｄｅｒＭｏｄｅｌｏｆＴｗｏ－ｄｉｍｅｎｓｉｏｎａｌＦｌｕｉｄＤｙｎａｍｉｃｓｏｎｔｈｅＳｕｒｆａｃｅｏｆａＳｐｈｅｒｅＭｏｚｈｅｎｇＷｅｉ（ＣＲＣｆｏｒＳｏｕｔｈｅｒｎＨｅｍｉｓｐｈｅｒｅＭｅｔｅｏｒｏｌｏｇｙ，ＣＳＩＲＯＤｉｖｉｓｉｏ...     

Some Aspects of the Characteristics of Monsoon Disturbances Using a Combined Barotropic－Baroclinic Model

ＳｏｍｅＡｓｐｅｃｔｓｏｆｔｈｅＣｈａｒａｃｔｅｒｉｓｔｉｃｓｏｆＭｏｎｓｏｏｎＤｉｓｔｕｒｂａｎｃｅｓＵｓｉｎｇａＣｏｍｂｉｎｅｄＢａｒｏｔｒｏｐｉｃ－ＢａｒｏｃｌｉｎｉｃＭｏｄｅｌ￥Ｎ．Ｒ．ＰａｒｉｊａａｎｄＳ．Ｋ．Ｄａｓｈ（ＣｅｎｔｒｅｆｏｒＡ...     

Impacts of Land Surface on Climate of July and On set of Summer Monsoon:A Study with an AGCM plus SSiB

ＩｍｐａｃｔｓｏｆＬａｎｄＳｕｒｆａｃｅｏｎＣｌｉｍａｔｅｏｆＪｕｌｙａｎｄＯｎｓｅｔｏｆＳｕｍｍｅｒＭｏｎｓｏｏｎ：ＡＳｔｕｄｙｗｉｔｈａｎＡＧＣＭｐｌｕｓＳＳｉＢ①ＬｉｕＨｕｉ（刘辉）ａｎｄＷｕＧｕｏｘｉｏｎｇ（吴国雄）ＳｔａｔｅＫｅｙＬａｂｏｒ...     

Use of total precipitable water classification of a priori error and quality control in atmospheric temperature and water vapor sounding retrieval

This study investigates the use of dynamic a priori error information according to atmospheric moistness and the use of quality controls in temperature and water vapor profile retrievals from hyperspectral infrared (IR) sounders. Temperature and water vapor profiles are retrieved from Atmospheric InfraRed Sounder (AIRS) radiance measurements by applying a physical iterative method using regression retrieval as the first guess. Based on the dependency of first-guess errors on the degree of atmospheric moistness, the a priori first-guess errors classified by total precipitable water (TPW) are applied in the AIRS physical retrieval procedure. Compared to the retrieval results from a fixed a priori error, boundary layer moisture retrievals appear to be improved via TPW classification of a priori first-guess errors. Six quality control (QC) tests, which check non-converged or bad retrievals, large residuals, high terrain and desert areas, and large temperature and moisture deviations from the first guess regression retrieval, are also applied in the AIRS physical retrievals. Significantly large errors are found for the retrievals rejected by these six QCs, and the retrieval errors are substantially reduced via QC over land, which suggest the usefulness and high impact of the QCs, especially over land. In conclusion, the use of dynamic a priori error information according to atmospheric moistness, and the use of appropriate QCs dealing with the geographical information and the deviation from the first-guess as well as the conventional inverse performance are suggested to improve temperature and moisture retrievals and their applications.     

Atmospheric profile retrieval with AIRS data and validation at the ARM CART site

The physical retrieval algorithm of atmospheric temperature and moisture distribution from the Atmospheric InfraRed Sounder （AIRS） radiances is presented. The retrieval algorithm is applied to AIRS clear-sky radiance measurements. The algorithm employs a statistical retrieval followed by a subsequent nonlinear physical retrieval. The regression coefficients for the statistical retrieval are derived from a dataset of global radiosonde observations （RAOBs） comprising atmospheric temperature, moisture, and ozone profiles. Evaluation of the retrieved profiles is performed by a comparison with RAOBs from the Atmospheric Radiation Measurement （ARM） Program Cloud And Radiation Testbed （CART） in Oklahoma, U. S. A.. Comparisons show that the physically-based AIRS retrievals agree with the RAOBs from the ARM CART site with a Root Mean Square Error （RMSE） of 1K on average for temperature profiles above 850 hPa, and approximately 10% on average for relative humidity profiles. With its improved spectral resolution, AIRS depicts more detailed structure than the current Geostationary Operational Environmental Satellite （GOES） sounder when comparing AIRS sounding retrievals with the operational GOES sounding products.     

利用AIRS卫星资料反演大气廓线Ⅰ.特征向量统计反演法

引进美国威斯康星大学的IMAPP（International MODIS／AIRS Preprocessing Package）软件包，介绍了利用高光谱分辨率大气红外探测器AIRS（Atmospheric Infrared Sounder）观测辐射值，用特征向量统计法反演大气温度、湿度等垂直廓线的算法，采用亮度温度分类和扫描角分类回归后，减小了反演误差。并将其应用到中国地区，通过与无线电探空值及欧洲中期天气预报中心ECMWF（European Center of Medium-range Weather Forecasts）客观分析场的比较，结果表明：该方法所获得的温度、水汽反演结果与探空观测及ECMWF大气廓线分布一致，且AIRS因其高光谱分辨率（即高垂直空间分辨率）显示了精细的大气结构。     

A Study on Retrieving Atmospheric Profiles from EOS/AIRS Observations

1. IntroductionThe development of global climate and weathermodels requires accurate monitoring of atmospherictemperature and moisture profiles, as well as the con-tents of trace gases and aerosols. It is quite difficultto monitor continuously these parameters on a globalscale.Until recently. AIRS (Atmospheric InfraredSounder) offers a new opportunity to improve globalmonitoring of temperature, moisture, and ozone distri-butions and changes therein. The high spectral resolu-tion (v/Δv ? 12…     

Optimal Use of High Resolution Infrared Sounder Channels in Atmospheric Prof

ＯｐｔｉｍａｌＵｓｅｏｆＨｉｇｈＲｅｓｏｌｕｔｉｏｎＩｎｆｒａｒｅｄＳｏｕｎｄｅｒＣｈａｎｎｅｌｓｉｎＡｔｍｏｓｐｈｅｒｉｃＰｒｏｆｉｌｅＲｅｔｒｉｅｖａｌ￥ＬｉＪｕｎ（李俊）ａｎｄＨｕａｎｇＨｕｎｇ－Ｌｕｎｇ（黄鸿荣）（Ｐｅｒｍａｎｅｎｔａｆｆｉｌ...     

Ensemble retrieval of atmospheric temperature profiles from AIRS

ABSTRACT Satellite-based observations provide great opportunities for improving weather forecasting. Physical retrieval of atmo spheric profiles from satellite observations is sensitive to the uncertainty of the first guess and other factors. In order to improve the accuracy of the physical retrieval, an ensemble methodology was developed with an emphasis on perturbing the first guess. In the methodology, a normal probability density function （PDF） is used to select the optimal profile from the ensemble retrievals. The ensemble retrieval algorithm contains four steps： （1） regression retrieval for original first guess; （2） perturbation of the original first guess to generate new first guesses （ensemble first guesses）; （3） using the ensemble first guesses and nonlinear iterative physical retrieval to generate ensemble physical results; and （4） the final optimal profile is selected from the ensemble physical results by using PDE Temperature eigenvectors （EVs） were used to generate the pertur- bation and generate the ensemble first guess. Compared with the regular temperature profile retrievals from the Atmospheric InfraRed Sounder （AIRS）, the ensemble retrievals RMSE of temperature profiles selected by the PDF was reduced between 150 and 320 hPa and below 400 hPa, with a maximum improvement of 0.3 K at 400 hPa. The bias was also reduced in many layers, with a maximum improvement of 0.69 K at 460 hPa. The combined optimal （CombOpt） profile and a mean optimal （MeanOpt） profile of all ensemble physical results were improved below 150 hPa. The MeanOpt profile was better than the CombOpt profile, and was regarded as the final optimal （FinOpt） profile. This study lays the foundation for improving temperature retrievals from hyper-spectral infrared radiance measurements.     

Ozone Profile Retrieval from Satellite Observation Using High Spectral Resolution Infrared Sounding Instrument

I. IntroductionOzone p1ays a very 1mportant ro1e in globa1 climate change. This is particularly true inthe stratosphere, where ultra--v1olet solar radiation is strongly absorbed by ozone, leading tosubstantlal change in the earths atmospheric thermal, physical and chemical structure. Al-though the troposphere contains only about l0% of the total atmospheric ozone, the varia-tlon of tropospheric ozone may have more significant cllmatic effect than stratospheric ozoneon the earth's surface temP…     

红外高光谱资料模拟大气廓线反演对云的敏感性

用不同云顶高度和不同有效云量时的星载红外高光谱观测值,模拟大气温湿垂直廓线反演对云参数的敏感性。用特征向量统计反演法按照云顶高度和有效云量分类反演了大气温湿廓线,统计了不同云高（200,300,500,700和850hPa）及云高有50hPa误差时温度、水汽混合比反演的均方根误差随有效云量的变化。结果表明,随着有效云量的增大,云顶以下各高度层上的温度、水汽混合比反演误差都明显增大。云高有50hPa误差较准确已知而言,温度和水汽混合比的反演误差增大,但温度反演对云高误差的敏感性比水汽反演要高。     

应用ATOVS资料反演大气温湿廓线

本文用牛顿迭代的方法反演NOAA-15极轨气象卫星ATOVS资料，求解大气温度廓线和水汽廓线，本文利用一阶变分原理从辐射传输方程中得到了大气温度、水汽权重函数的解析形式，并改进了传统使用的线性迭代方法，利用牛顿非线性迭代方法求解大气表层温度，大气温度廓线及大气水汽廓线，并根据大气参量的自相关性，将大气温度廓线、大气水汽廓线用经验正交函数（EOF）的线性组合表示，减少了要反演的参数，提高了反演稳定性和迭代速度。     

人工神经网络法反演晴空大气湿度廓线的研究

高光谱分辨率大气红外探测器AIRS(Atmospheric Infrared Sounder)作为第一个超高光谱大气红外探测仪,开辟了卫星大气探测的新时代.以无线电探空值与SARTA(Stand-Alone Radiative Transfer Algorithm辐射传输模式)v1.05版的前向模式模拟出的AIRS辐射...