Derivation of regression coefficients for sea surface temperature retrieval over East Asia

Among the regression-based algorithms for deriving SST from satellite measurements, regionally optimized algorithms normally perform better than the corresponding global algorithm. In this paper,three algorithms are considered for SST retrieval over the East Asia region (15°-55°N, 105°-170°E),including the multi-channel algorithm (MCSST), the quadratic algorithm (QSST), and the Pathfinder algorithm (PFSST). All algorithms are derived and validated using collocated buoy and Geostationary Meteorological Satellite (GMS-5) observations from 1997 to 2001. An important part of the derivation and validation of the algorithms is the quality control procedure for the buoy SST data and an improved cloud screening method for the satellite brightness temperature measurements. The regionally optimized MCSST algorithm shows an overall improvement over the global algorithm, removing the bias of about -0.13℃ and reducing the root-mean-square difference (rmsd) from 1.36℃ to 1.26℃. The QSST is only slightly better than the MCSST. For both algorithms, a seasonal dependence of the remaining error statistics is still evident. The Pathfinder approach for deriving a season-specific set of coefficients, one for August to October and one for the rest of the year, provides the smallest rmsd overall that is also stable over time.     

The Impact Cooling of the Storm-Induced SST on Hurricane Intensity

The effects of storm-induced sea surface temperature （SST） cooling on hurricane intensity are investigated using a 5-day cloud-resolving simulation of Hurricane Bonnie （1998）. Two sensitivity simulations are performed in which the storm-induced cooling is either ignored or shifted close to the modeled storm track. Results show marked sensitivity of the model-simulated storm intensity to the magnitude and relative position with respect to the hurricane track. It is shown that incorporation of the storm-induced cooling, with an average value of 1.3℃, causes a 25-hPa weakening of the hurricane, which is about 20 hPa per 1℃ change in SST. Shifting the SST cooling close to the storm track generates the weakest storm, accounting for about 47% reduction in the storm intensity. It is found that the storm intensity changes are well correlated with the air-sea temperature difference. The results have important implications for the use of coupled hurricane-ocean models for numerical prediction of tropical cyclones.     

A Relocation-based Initialization Scheme to Improve Track-forecasting of Tropical Cyclones简

A relocation procedure to initialize tropical cyclones was developed to improve the representation of the initial conditions and the track forecast for Panasonic Weather Solutions Tropical Operational Forecasts. This scheme separates the vortex perturbation and environment field from the first guess, then relocates the initial vortex perturbations to Lhe observed position by merging them with the environment field. The relationships of wind vector components with stream function and velocity potential are used for separating the vortex disturbance from first guess. For the separation of scalars, a low-pass Barnes filter is employed. The irregular-shaped relocation area corresponding to the specific initial conditions is determined by mapping the edge of the vortex radius in 36 directions.Then, the non-vortex perturbations in the relocation area are removed by a two-pass Barnes filter to retain the vortex perturbations, while the variable fields outside the perimeter of the modified vortex are kept ide.ntical to the original first guess. The potential impacts of this scheme on track forecasts were examined for three hurricane cases in the 2011-12 hurricane season. The experimental results demonstrate that the initialization scheme is able to effectively separate the vortex field from the environment field and maintain a relatively balanced and accurate relocated first guess. As the initial track error is reduced, the following track forecasts are considerably improved. The 72-h average track forecast error was redu,~ed by 32.6% for the cold-start cases, and by 38.4% when using the full-cycling data assimilation because of the accumulatedL improvements from the initialization scheme.     

Remote Sensing of Tropical Cyclone Thermal Structure from Satellite Microwave Sounding Instruments: Impacts of Background Profiles on Retrievals

A variational retrieval system often requires background atmospheric profiles and surface parameters in its minimization process. This study investigates the impacts of specific background profiles on retrievals of tropical cyclone(TC) thermal structure. In our Microwave Retrieval Testbed(MRT), the K-means clustering algorithm is utilized to generate a set of mean temperature and water vapor profiles according to stratiform and convective precipitation in hurricane conditions. The Advanced Technology Microwave Sounder(ATMS) observations are then used to select the profiles according to cloud type. It is shown that the cloud-based background profiles result in better hurricane thermal structures retrieved from ATMS observations. Compared to the Global Positioning System(GPS) dropsonde observations, the temperature and specific humidity errors in the TC inner region are less than 3 K and 2.5 g kg~(–1), respectively, which are significantly smaller than the retrievals without using the cloud-based profiles. Further experiments show that all the ATMS observations could retrieve well both temperature and humidity structures, especially within the inner core region. Thus, both temperature and humidity profiles derived from microwave sounding instruments in hurricane conditions can be reliably used for evaluation of the storm intensity with a high fidelity.     

Verification of Fengyun-3D MWTS and MWHS Calibration Accuracy Using GPS Radio Occultation Data

The newly launched Fengyun-3D(FY-3D) satellite carries microwave temperature sounder(MWTS) and microwave humidity sounder(MWHS), providing the global atmospheric temperature and humidity measurements. It is important to assess the in orbit performance of MWTS and MWHS and understand their calibration accuracy before using them in numerical weather prediction and many other applications such as hurricane monitoring. This study aims at quantifying the biases of MWTS and MWHS observations relative to the simulations from the collocated Global Positioning System(GPS) radio occultation(RO) data. Using the collocated FY-3C Global Navigation Satellite System Occultation Sounder(GNOS) RO data under clear-sky conditions as inputs to Community Radiative Transfer Model(CRTM), brightness temperatures and viewing angles are simulated for the upper level sounding channels of MWTS and MWHS. In order to obtain O – B statistics under clear sky conditions, a cloud detection algorithm is developed by using the two MWTS channels with frequencies at 50.3 and 51.76 GHz and the two MWHS channels with frequencies centered at 89 and 150 GHz. The analysis shows that for the upper air sounding channels,the mean biases of the MWTS observations relative to the GPS RO simulations are negative for channels 5–9, with absolute values 1 K, and positive for channels 4 and 10, with values 0.5 K. For the MWHS observations, the mean biases in brightness temperature are negative for channels 2–6, with absolute values 2.6 K and relatively small standard deviations. The mean biases are also negative for channels 11–13, with absolute values 1.3 K, but with relatively large standard deviations. The biases of both MWTS and MWHS show scan-angle dependence and are asymmetrical across the scan line. The biases for the upper air MWTS and MWHS sounding channels are larger than those previously derived for the Advanced Technology Microwave Sounder.     

Sensitivity Experiments of an Eastward-Moving Southwest Vortex to Initial Perturbations

Whether the initial conditions contain pronounced mesoscale signals is important to the simulation of the southwest vortex. An eastward-moving southwest vortex is simulated using the PSU/NCAR MM5. A modest degree of success is achieved, but the most serious failure is that the formation and displacement of the simulated vortex in its early phase are about fourteen hours later than the observed vortex. Considering the relatively sparse data on the mesoscale vortex and in an attempt to understand the cause of the forecast failure, an adjoint model is used to examine the sensitivity of the southwest vortex to perturbations of initial conditions. The adjoint sensitivity indicates how small perturbations of model variables at the initial time in the model domain can influence the vortex. A large sensitivity for zonal wind is located under 400 hPa, a large sensitivity for meridional wind is located under 500 hPa, a large sensitivity for temperature is located between 500 and 900 hPa, and almost all of the large sensitivity areas are located in the southwestern area. Based on the adjoint sensitivity results, perturbations are added to initial conditions to improve the simulation of the southwest vortex. The results show that the initial conditions with perturbations can successfully simulate the formation and displacement of the vortex; the wind perturbations added to the initial conditions appear to be a cyclone circulation under the middle level of the atmosphere in the southwestern area with an anticyclone circulation to its southwest; a water vapor perturbation added to initial conditions can strengthen the vortex and the speed of its displacement.     

Resolving SSM/I-ship radar rainfall discrepancies from AIP-3

The third algorithm intercomparison project （AIP-3） involved rain estimates from more than 50 satellite rainfall algorithms and ground radar measurements within the Intensive Flux Array （IFA） over the equatorial western Pacific warm pool region during the Tropical Ocean Global Atmosphere coupled Ocean-Atmosphere Response Experiment （TOGA COARE）. Early results indicated that there was a sys- tematic bias between rainrates from satellite passive microwave and ground radar measurements. The mean rainrate from radar measurements is about 50% underestimated compared to that from passive microwave-based retrieval algorithms. This paper is designed to analyze rain patterns from the Florida State University rain retrieval algorithm and radar measurements to understand physically the rain discrep- ancies. Results show that there is a clear range-dependent bias associated with the radar measurements. However, this range-dependent systematical bias is almost eliminated with the corrected radar rainrates. Results suggest that the effects from radar attenuation correction, calibration and beam filling are the major sources of rain discrepancies. This study demonstrates that rain retrievals based on satellite mea- surements from passive microwave radiometers such as the Special Sensor of Microwave Imager （SSM/I） are reliable, while rain estimates from ground radar measurements are correctable.     

Automated detection of contaminated radar image pixels in mountain areas

In mountain areas, radar observations are often contaminated （1） by echoes from high-speed moving vehicles and （2） by point-wise ground clutter under either normal propagation （NP） or anomalous propagation （AP） conditions. Level Ⅱ data are collected from KMTX （Salt Lake City, Utah） radar to analyze these two types of contamination in the mountain area around the Great Salt Lake. Human experts provide the ＂ground truth＂ for possible contamination of either type on each individual pixel. Common features are then extracted for contaminated pixels of each type. For example, pixels contaminated by echoes from high-speed moving vehicles are characterized by large radial velocity and spectrum width. Echoes from a moving train tend to have larger velocity and reflectivity but smaller spectrum width than those from moving vehicles on highways. These contaminated pixels are only seen in areas of large terrain gradient （in the radial direction along the radar beam）. The same is true for the second type of contamination - pointwise ground clutters. Six quality control （QC） parameters are selected to quantify the extracted features. Histograms are computed for each QC parameter and grouped for contaminated pixels of each type and also for non-contaminated pixels. Based on the computed histograms, a fuzzy logical algorithm is developed for automated detection of contaminated pixels. The algorithm is tested with KMTX radar data under different （clear and rainy） weather conditions.     

Retrieval of Liquid Water Path Inside Nonprecipitating Clouds Using TMI Measurements

Quantitative estimates of liquid water path （LWP） in clouds using satellite measurements are critical to understanding of cloud properties and the assessment of global climate change. In this paper, the relationship between microwave brightness temperature （TB） and LWP in the nonprecipitating clouds is studied by using satellite microwave measurements from the TRMM Microwave Imager （TMI） onboard the Tropical Rainfall Measuring Mission （TRMM）, together with a radiative transfer model for microwave radiance calculations. Radiative transfer modeling shows that the sensitivity is higher at both 37.0- and 85.5-GHz horizontal polarization channels for the LWP retrievals. Also, the differences between the retrieved values responding to TBs of various channels and the theoretical values are displayed by the model. Based upon above simulations, with taking into account the factor of resolution and retrieval bias for a single,channel, a nonprecipitating cloud LWP in the summer subtropical marine environment retrieval algorithm is formulated by the combination of the two TMI horizontal polarization channels, 37.0 and 85.5 GHz. Moreover,by using TMI measurements （1Bll）, this algorithm is applied to retrieving respectively LWPs for clear sky, nonprecipitating clouds, and typhoon precipitating clouds. In the clear sky case, the LWP cl~anges from -1 to 1 g m-2, and its mean value is about 10^-5 g m^-2. It indicates that, using this combination retrieval algorithm, there are no obvious systemic deviations when the LWP is low enough. The LWP values varying from 0 to 1000 g m^-2 in nonprecipitating clouds are reasonable, and its distribution pattern is very similar to the detected results in the visible channel of Visible and Infrared Scanner （VIRS） on the TRMM. In typhoon precipitating clouds, there is much more proportion of high LWP in the mature phase than the early stage. When surface rainfall rate is lower than 5 mm h^-1, the LWP increases with increasing rainfall rate.     

Applications of AMSR-E Measurements for Tropical Cyclone Predictions Part Ⅰ: Retrieval of Sea Surface Temperature and Wind Speed

Existing satellite microwave algorithms for retrieving Sea Surface Temperature(Sst)and wind(SSW)are applicable primarily for non-raining cloudy conditions.With the launch of the Earth Observing System (EOS)Aqua satellite in 2002,the Advanced Microwave Scanning Radiometer(AMSR-E)onboard provides some unique measurements at lower frequencies which are sensitive to ocean surface parameters under ad-verse weather conditions.In this study,a new algorithm is developed to derive SST and SSW for hurricane predictions such as hurricane vortex analysis from the AMSR-E measurements at 6.925 and 10.65 GHz.In the algorithm,the effects of precipitation emission and scattering on the measurements are properly taken into account.The algorithm performances are evaluated with buoy measurements and aircraft dropsonde data.It is found that the root mean square (RMS) errors for SST and SSW are about 1.8K and 1.9m s(-1),respectively,when the results are compared with the buoy data over open oceans under precipitating clouds (e.g.,its liquid water path is larger than 0.5 mm),while they are 1.1 K for SST and 2.0 ms(-1)for SSW,respectively,when the retrievals are validated against the dropsonde measurements over warm oceans.These results indicate that our newly developed algorithm catl provide some critical surface information for trop-ical cycle predictions.Currently,this newly developed algorithm has been implemented into the hybrid variational scheme for the hurricane vortex analysis to provide predictions of SST and SSW fields.     

基于AHI观测的全天气条件海表温度反演

基于搭载在日本新一代静止气象卫星Himawari-8上的先进葵花成像仪(Advanced Himawari Imager,AHI)观测资料,研究了高时空分辨率的、全天气条件的海表温度(Sea Surface Temperature,SST)反演算法。本算法包括两步:第一步,根据云检测算法划分晴空和云区,然后利用非线性SST(NLSST)方程由红外亮温估计晴空SST;第二步,在有云区,先由前5 d同一时刻的晴空SST进行初步补缺,然后再利用Barnes插值完善云区SST估计和进行异常点平滑。最终得到时间分辨率为10 min、空间分辨率为0.05°的全天气条件海温分布。利用移动浮标的观测SST验证,晴空区SST估计的均方根误差(Root Mean Square Error,RMSE)和平均误差(Mean Error,ME)分别为0.857 K和0.017 K。全天气条件SST估计的RMSE和ME分别为0.872 K和-0.005 K。     

Detection and Correction of AMSR-E Radio-Frequency Interference

Radio-frequency interference (RFI) affects greatly the quality of the data and retrieval products from space-borne microwave radiometry. Analysis of the Advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR-E) Aqua satellite observations reveals very strong and widespread RFI contam- inations on the C- and X-band data. Fortunately, the strong and moderate RFI signals can be easily identified using an index on observed brightness temperature spectrum. It is the weak RFI that is diffi- cult to be separated from the nature surface emission. In this study, a new algorithm is proposed for RFI detection and correction. The simulated brightness temperature is used as a background signal (B) and a departure of the observation from the background (O-B) is utilized for detection of RFI. It is found that the O-B departure can result from either a natural event (e.g., precipitation or flooding) or an RFI signal. A separation between the nature event and RFI is further realized based on the scattering index (SI). A positive SI index and low brightness temperatures at high frequencies indicate precipitation. In the RFI correction, a relationship between AMSR-E measurements at 10.65 GHz and those at 18.7 or 6.925 GHz is first developed using the AMSR-E training data sets under RFI-free conditions. Contamination of AMSR-E measurements at 10.65 GHz is then predicted from the RFI-free measurements at 18.7 or 6.925 GHz using this relationship. It is shown that AMSR-E measurements with the RFI-correction algorithm have better agreement with simulations in a variety of surface conditions.     

基于高空气球平台的下投探空:系统研发和青藏高原实验

为提高复杂地理环境和极端天气条件下的大气廓线探测能力,本文自主研发了基于平流层高空气球平台的下投探空系统,并在青藏高原开展探测评估实验.该系统主要由下投探空舱,携带降落伞的下投探空仪,下投施放装置,数据接收通讯天线和GPS模块等组成.下投探空仪测量数据通过卫星通信链路和无线电信号实时发送至数据接收机存储处理.2020年青藏高原实验中8枚下投探空仪全部成功施放,提供了合理有效的大气廓线探测数据.后续会进一步提高下投探空仪传感器性能,全面评估其探测准确性和精度.     

Evaluation and Preprocess of Chinese Fengyun-3A Sea Surface Temperature Experimental Product for Data Assimilation

Validated satellite-derived sea surface temperatures (SSTs) are widely used for climate monitoring and ocean data assimilation systems. In this study, the Fengyun-3A (FY-3A) SST experimental product is evaluated using Advanced Very High Resolution Radiometer (AVHRR)-merged and in situ SSTs. A comparison of AVHRR-merged SSTs reveals a negative bias of more than 2K in FY-3A SSTs in most of the tropical Pacific and low-latitude Indian and Atlantic Oceans. The error variance of FY-3A SSTs is estimated using three-way error analysis. FY-3A SSTs show regional error variance in global oceans with a maximum error variance of 2.2 K in the Pacific Ocean. In addition, a significant seasonal variation of error variance is present in FY-3A SSTs, which indicates that the quality of FY-3A SST could be improved by adjusting the parameters in the SST retrieval algorithm and by applying regional and seasonal algorithms, particularly in key areas such as the tropical Pacific Ocean. An objective analysis method is used to merge FY-3A SSTs with the drifter buoy data. The errors of FY-3A SSTs are decreased to-0.45K comparing with SST observations from GTSPP.     

Characteristics of sea surface temperature retrieved from MTSAT-1R and in-situ data

Multi-channel sea surface temperature (MCSST) data were retrieved from the Japanese geostationary satellite, MTSAT-1R, for East Asia in western North Pacific. The coefficients used to calculate the MCSST data were estimated by assuming a linear relationship between the brightness temperatures obtained from the satellite and the in-situ buoy SST. It is important to remove cloud contamination pixels to retrieve meaningful information from infrared data. Therefore, the cloud detection algorithm was improved by using a 10-day maximum or minimum composite map for infrared and visible channels. The RMSE of the MCSST in comparison with the two-year buoy SST was about 0.89oC. The error was the largest at mid-latitudes in summer. Additionally, the error between the two SSTs showed that diurnal variation had a positive bias during daytime and a negative bias during nighttime. Furthermore, in 2007, both SSTs showed seasonal and spatial diurnal variation. The magnitude of the daily variation in the MCSST was two times larger than that in the buoy SST, and this was attributed to diurnal heating with a weak surface wind speed.     

Stratospheric balloon-based dropsonde technology: Development and preliminary assessment over the Tibetan Plateau: 基于高空气球平台的下投探空:系统研发和青藏高原实验

To complement the atmospheric profile measurements under complex geographical environments and extreme weather conditions, a stratospheric balloon-based dropsonde technology, which is carried by a stratospheric balloon platform from the Earth's surface to the upper troposphere and lower stratosphere (UTLS) to release the dropsonde for measurements, is independently developed and preliminarily assessed over the Tibetan Plateau (TP) in this study. The dropsonde system is mainly composed of the dropsonde chamber, dropsonde with a parachute, data receiving and communication antennas, dropsonde-releasing device, and GPS (Global Positioning System) modules. The dropsonde measurements can be sent in real time through satellite communication links and by radio signals to a data receiver at the ground control center for storage and processing. A total of eight dropsondes aboard the stratospheric balloon were successfully released during the TP campaign in 2020. A preliminary assessment was conducted based on a case comparison between the dropsonde and radiosonde measurements, which indicated that the dropsonde technology we developed can generally provide reasonable atmospheric profiles. However, further efforts are still required to improve the detection performance of the dropsonde sensors after long-term locating in the UTLS and to assess the accuracy and precision of the detection technology more carefully.摘要为提高复杂地理环境和极端天气条件下的大气廓线探测能力, 本文自主研发了基于平流层高空气球平台的下投探空系统, 并在青藏高原开展探测评估实验.该系统主要由下投探空舱,携带降落伞的下投探空仪,下投施放装置,数据接收通讯天线和GPS模块等组成.下投探空仪测量数据通过卫星通信链路和无线电信号实时发送至数据接收机存储处理.2020年青藏高原实验中8枚下投探空仪全部成功施放, 提供了合理有效的大气廓线探测数据.后续会进一步提高下投探空仪传感器性能, 全面评估其探测准确性和精度.     

FY-3C/VIRR海表温度产品及质量检验

国家卫星气象中心FY-3C/VIRR（visible and infrared radiometer,可见光红外扫描辐射计）海表温度产品在云检测产品的基础上,采用多通道MCSST（multichannel SST）算法进行晴空区海温反演。该文详细介绍了海表温度产品算法、产品设计、质量控制及质量检验方法。FY-3C/VIRR海表温度产品包括5 min段原始投影海温和5 km全球等经纬度投影海温。设计逐像元的海温质量标识,将海温像元分为优、良、差3个等级,用户可根据应用目标选择海温的质量等级。与日最优插值海温OISST（optimum interpolation SST）相比,FY-3C/VIRR 2015年1月—2019年12月的5 min段海温质量检验结果表明:质量等级为优的海温,白天和夜间的偏差分别为-0.18℃和-0.06℃,均方根误差分别为0.85℃和0.8℃;白天海温均方根误差有季节性波动,夏季有的月份均方根误差大于1℃（如2015年7月、2016年7月和2019年7月）;在海温回归系数不变的条件下,夜间海温偏差的季节性波动与星上黑体温度相关显著。从一级数据质量、定位、业务运行状况等方面讨论引起海表温度产品异常的原因,为FY-3C/VIRR历史数据定位、定标和产品重处理及用户应用提供重要的参考信息。     

FY-3B/VIRR海表温度算法改进及精度评估

该文介绍了卫星观测海表温度 (SST) 算法的发展历程,给出了所用SST算法的回归模型,并在FY-3B/VIRR业务SST算法的基础上进行了改进。基于NOAA-19/AVHRR匹配数据集,进行多算法建模分析及精度评估,白天最优算法为非线性SST (NL) 算法,夜间最优算法为三通道SST (TC) 算法,最优算法的确定与NESDIS/STAR一致。建立2012年8月—2013年3月FY-3B/VIRR匹配数据集,并在此基础上进行多算法回归建模及精度评估,白天和夜间的最优均为NL算法,分析发现夜间TC算法采用匹配数据集版本2(MDB_V2) 时,3.7 μm通道存在类似百叶窗的条带现象。以2012年10—12月FY-3B/VIRR匹配数据集计算回归系数,以2013年1—3月独立样本进行精度评估,与浮标SST相比,NL算法白天和夜间的均方根误差分别为0.41℃和0.43℃。与日平均最优插值海温 (OISST) 相比,NL算法白天和夜间的均方根误差分别为1.45℃和1.5℃; 选择与OISST偏差在2℃以内的样本,NL算法白天和夜间均方根误差分别为0.82℃和0.84℃。