Verification of a scattering-based algorithm for estimating rainfall over the open ocean

Summary An algorithm for estimating rainfall (based upon scattering of upwelling radiation at 85 GHz) using the Special Sensor Microwave Imager (SSM/I) 85 GHz sensor data has recently been developed at the National Oceanographic and Atmospheric Administration's Office of Research and Applications (NOAA ORA). Spatial and temporal variability in the differences between simple areal-averaged rainfall estimates from a raingage and satellite-derived estimates are examined. These initial comparisons provide insight into the nature of the differences; however, due to substantial amounts of spatial sampling error in the raingage spatial averages, this approach is ineffective at identifying statistically significant differences.Thus, rainfall estimates for this algorithm are examined over the tropical Pacific using a statistical technique, called the noncontiguous raingage method (NCR), which minimizes spatial sampling error so that the statistical significance of relationships may be determined. The results indicate that, adjusted with calibration coefficients, the ORA algorithm could produce unbiased estimates of areal rainfall for the tropical Pacific region examined in this study.With 8 Figures     

A New Algorithm for Sea Fog／Stratus Detection Using GMS-5 IR Data

A new algorithm for the detection of fog/stratus over the ocean from the GMS-5 infrared (IR) channel data is presented. The new algorithm uses a clear-sky radiance composite map (CSCM) to compare the hourly observations of the IR radiance. The feasibility of the simple comparison is justified by the theoretical simulations of the fog effect on the measured radiance using a radiative transfer model. The simulation results show that the presence of fog can be detected provided the visibility is worse than 1 km and the background clear-sky radiances are accurate enough with known uncertainties. For the current study, an accurate CSCM is constructed using a modified spatial and temporal coherence method, which takes advantage of the high temporal resolution of the GMS-5 observations. The new algorithm is applied for the period of 10-12 May 1999, when heavy sea fog formed near the southwest coast of the Korean Peninsula. Comparisons of the fog/stratus index, defined as the difference between the measured and clear-sky brightness temperature, from the new algorithm to the results from other methods, such as the dual channel difference of NOAA/AVHRR and the earth albedo method, show a good agreement. The fog/stratus index also compares favorably with the ground observations of visibility and relative humidity. The general characteristics of the fog/stratus index and visibility are relatively well matched, although the relationship among the absolute values, the fog/stratus index, visibility, and relative humidity, varies with time. This variation is thought to be due to the variation of the atmospheric conditions and the characteristics of fog/stratus, which affect the derived fog/stratus index.     

基于神经网络算法的Sentinel-1和Sentinel-2遥感数据联合反演土壤湿度研究

以西班牙萨拉曼卡地区为研究区域,联合Sentinel-1后向散射系数和入射角信息、Sentinel-2光学数据提取的植被指数以及地面实测数据,构建了BP神经网络土壤湿度反演模型,并将该模型应用于试验区土壤湿度反演.结果 表明:1)基于Sentinel-1卫星VV和VH极化雷达后向散射系数、雷达入射角和Sentinel-...     

使用物理方法反演中国陆地雨强和水凝物垂直结构

使用MM5模式模拟了11个降水个例,获得中国陆地的降水廓线,由蒙特卡罗辐射传输模式计算其上行辐射亮温,构成初始云一辐射数据库.采用对照表方法从中获得Db_ml和Db_m2两个数据集,作为GPROF反演算法的先验数据集.对2007年7月的3次强降水过程的地面雨强进行反演,与微波成像仪(TMI)及NESDIS、GSCAT、...     

Estimation of Indian summer monsoon rainfall using Kalpana-1 VHRR data and its validation using rain gauge and GPCP data

In the present study, an attempt has been made to estimate and validate the daily and monthly rainfall during the Indian summer monsoon seasons of 2008 and 2009 using INSAT (Indian National Satellite System) Multispectral Rainfall Algorithm (IMSRA) technique utilizing Kalpana-1 very high resolution radiometer (VHRR) measurements. In contrary to infrared (IR), microwave (MW) rain rates are based on measurements that sense precipitation in clouds and do not rely merely on cloud top temperature. Geostationary satellites provide broad coverage and frequent refresh measurements but microwave measurements are accurate but sparse. IMSRA technique is the combination of the infrared and microwave measurements which make use of the best features of both IR- and MW-based rainfall estimates. The development of this algorithm included two major steps: (a) classification of rain-bearing clouds using proper cloud classification scheme utilizing Kalpana-1 IR and water vapor (WV) brightness temperatures (Tb) and (b) collocation of Kalpana-1 IR brightness temperature with Tropical Rainfall Measuring Mission (TRMM)-Precipitation Radar (PR) surface rain rate and establishment of a regression relation between them. In this paper, the capability of IMSRA as an operational algorithm has been tested for the two monsoon seasons 2008 and 2009. For this, IMSRA has been used to estimate daily and monthly rainfall and has been intercompared on daily and monthly scales with TRMM Multisatellite Precipitation Analysis (TMPA)-3B42 V6 product and Global Precipitation Climatology Project (GPCP) rain product during these two monsoon years. The daily and monthly IMSRA rainfall has also been validated against ground-based observations from Automatic Weather Station (AWS) Rain Gauge and Buoy data. The algorithm proved to be in good correlation with AWS data over land up to 0.70 for daily rain estimates except orographic regions like North-East and South-West India and 0.72 for monthly rain estimates. The validation with Buoys gives the reasonable correlation of 0.49 for daily rain estimates and 0.66 for monthly rain estimates over Tropical Indian Ocean.     

A statistical retrieval algorithm for root zone soil moisture

An algorithm for the estimation of root zone soil moisture is presented. Global fields of the soil moisture within the uppermost metre of soil are derived with a temporal resolution of 10 days. For calibration, long-term soil moisture observations from the former Soviet Union are used. The variance of the measurements is largely dominated by the spatial variability of the long-term mean soil moisture, while the temporal variability gives comparatively small contribution. Consequently, the algorithm is organised into two steps. The first step concentrates on the retrieval of the spatial variance of the long-term means, which comprises more than 85% of the total soil moisture variability. A major part of the spatial variance can be explained by four easily available fields: the climatological precipitation, land use, soil texture, and terrain slope. The second step of the algorithm is dedicated to the local temporal variability. This part of variability is recovered by using passive microwave data from scanning multichannel microwave radiometre (SMMR) supported by monthly averaged fields of air temperature and precipitation. The 6-GHz channel of SMMR is shown to be severely disturbed by radio frequency interference, so that information from the 10-GHz channel is used instead. The algorithm provides reasonable soil moisture fields which is confirmed by a comparison with independent measurements from Illinois.     

AMSU-B微波资料反演对流云中冰粒子含量

微波遥感可以穿透云顶直接探测云内的冰粒子分布,NOAA系列卫星微波湿度计(AMSU-B)的3个水汽吸收波段对冰粒子含量的变化有着很好的响应,受冰粒子的强烈散射衰减作用,亮温随冰粒子的增加而降低.因此,可以利用3个水汽通道亮温变化判断云中冰粒子的含量.根据模拟实验结果,确定了对流云状态下各水汽通道对冰粒子的响应高度,冰粒...     

A synergic algorithm for retrieval of aerosol optical depth over land

In this paper, a novel algorithm for aerosol optical depth(AOD) retrieval with a 1 km spatial resolution over land is presented using the Advanced Along Track Scanning Radiometer (AATSR) dual-view capability at 0.55, 0.66 and 0.87 μm, in combination with the Bi-directional Reflectance Distribution Function (BRDF) model, a product of the Moderate Resolution Imaging Spectroradiometer (MODIS). The BRDF characteristics of the land surface, i.e. prior input parameters for this algorithm, are computed by extracti...     

Analysis of sky condition using solar radiation data at Kwangju and Seoul, South Korea and Ile-Ife, Nigeria

Summary ?Daily global and diffuse radiation measurements have been used to characterize the atmosphere optical conditions at Kwangju (Lat.35.13N, Long.126.53E) and Seoul (Lat.37.57N, Long.126.98E) in South Korea and Ile-Ife (Lat.7.14N, Long.4.56E) in Nigeria. The clearness index, (CI) which gives the percentage depletion by the sky of the incoming global radiation and the diffuse ratio, (D_R) which represents the effectiveness of the sky in scattering incoming radiation have been analyzed in this study. Results show an average clearness index value of 0.57 for the year 1999 with maximum values occurring during the wet seasons at Ile-Ife. The average clearness indexes for Kwangju and Seoul from 1998–2000 was 0.48 and 0.34, respectively, with both stations having maximum clearness indexes in the winter seasons. The diffuse ratio was higher at Kwangju and Seoul than at Ile-Ife due to heavy dust pollution from the Gobi desert in the Korea peninsula in spring, and high biomass burning at Kwangju in the fall. Department of Physics, Obafemi Awolowo University, Ile-Ife, Nigeria Received May 7, 2001; Revised November 24, 2001     

Improved multisite stochastic weather generation with applications to historical data in South Korea

In this paper, we propose an improved multisite weather generation with applications to the historical data in South Korea. The proposed method improve the algorithm of Wilks (1998, 1999) by automatically selecting an optimal model that represents precipitation amounts and by providing a procedure to obtain a symmetric positive definite estimate for the covariance matrix. The proposed method is computationally fast, and hence, it can be feasible to handle a massive data. We apply the proposed method to the precipitation and temperature data collected 170 stations in South Korea for the period 1976–2005 which are given by the Korea Meteorological Administration (KMA). Results of the proposed method demonstrate the promising performance in terms of spatial correlation and long-term variation as compared with those of the multisite method of Wilks (1998) and the single-site weather generator.     

Validating infrared-based rainfall retrieval algorithms with 1-minute spatially dense raingage measurements over Korean peninsula

Summary ?This study compares and contrasts six infrared-based satellite rain estimation techniques and their validation during a 2-month period from June 20–August 20, 1998 over the Korean peninsula. Two probability matching techniques (PMM1, PMM2), a look-up table technique (LUT), a convective-stratiform technique (CST), the Negri-Adler-Wetzel technique (NAWT), and the Arkin technique (ARKT) are applied to hourly infrared GMS imagery. Retrieved rainrates are compared against one-minute reporting raingage observations from the dense Automated Weather Station (AWS) network of Korea. The high spatial resolution and fine temporal resolution of the AWS measurements provide a unique and effective means to validate rain estimates derived from instantaneous space measurements, which is a main scientific focus of this study. Validation results indicate that all techniques exhibit better performance for more evenly spread rain events while exhibiting lesser performance for weak and sporadic rains for which validation sampling becomes more of a problem. Validation statistics show that climatologically-local techniques such as the PMM and LUT algorithms perform better than techniques developed in climatologically different regimes, indicating the well-known dependence of rain physics on the immediate environment. Nevertheless, the validation results suggest how the rain determination parameters including attributed rain and threshold brightness temperature could be optimized locally before application. As others have found, the most difficult problem with satellite infrared techniques is in the detection and quantification of heavy rainfall events arising from uncertainties in discriminating non-precipitating anvil clouds from convective clouds. However, for the set of algorithms under examination here, given the sharp resolution of the validation measurements, it is evident that the CST algorithm exhibits superior performance in differentiating between non-precipitating anvil and heavy rain. Received January 4, 2002; revised March 11, 2002     

GPS资料同化中一种快速优化算法

GPS资料同化最终归结为一个大规模的无约束优化问题。由于问题的维数很高，使得寻找到一种快速且节约存储的优化算法成为GPS资料同化能否满足在业务数值天气预报上的要求的关键。提出了一种新的优化算法。该方法把L-BFGS和HFN两种方法动态的结合起来，同时利用有限差分技术和截去技术，使算法在存储和计算量适合当前设备的前提下，较大的提高了算法的收敛速度。数值试验表明，该方法的计算效率与L-BFGS方法相比有十分明显的改善。     

Numerical simulations of heavy rainfall over central Korea on 21 September 2010 using the WRF model

On 21 September 2010, heavy rainfall with a local maximum of 259 mm d-1occurred near Seoul, South Korea. We examined the ability of the Weather Research and Forecasting(WRF) model in reproducing this disastrous rainfall event and identified the role of two physical processes: planetary boundary layer(PBL) and microphysics(MPS) processes. The WRF model was forced by 6-hourly National Centers for Environmental Prediction(NCEP) Final analysis(FNL) data for 36 hours form 1200 UTC 20 to 0000 UTC 22 September 2010. Twenty-five experiments were performed, consisting of five different PBL schemes—Yonsei University(YSU), Mellor-Yamada-Janjic(MYJ), Quasi Normal Scale Elimination(QNSE),Bougeault and Lacarrere(Bou Lac), and University of Washington(UW)—and five different MPS schemes—WRF SingleMoment 6-class(WSM6), Goddard, Thompson, Milbrandt 2-moments, and Morrison 2-moments. As expected, there was a specific combination of MPS and PBL schemes that showed good skill in forecasting the precipitation. However, there was no specific PBL or MPS scheme that outperformed the others in all aspects. The experiments with the UW PBL or Thompson MPS scheme showed a relatively small amount of precipitation. Analyses form the sensitivity experiments confirmed that the spatial distribution of the simulated precipitation was dominated by the PBL processes, whereas the MPS processes determined the amount of rainfall. It was also found that the temporal evolution of the precipitation was influenced more by the PBL processes than by the MPS processes.     

A simple approach for improving spatial interpolation of rainfall using ANN

The spatiotemporal features of tropical cyclone strikes from 1949 to 2008 at 49 coastal cities of China are investigated in this study. The cities in Hainan, Guangdong, and Taiwan have high strike frequencies, with the severest and most frequent average strikes found in Taiwan. In Hainan, strike clusters appear in the mid-1950s, the early 1960s and 1970s, and the late 1980s, with relative inactive frequencies from the mid-1990s to 2008, and the clusters of strikes in Guangdong are found during the 1970s. In Taiwan, the most active strikes are found during the period 1956–1963. The return periods for all typhoons are either 1 or 2 years at the coastal cities of Taiwan in contrast to 2–5 and 4–8 years at the cities of Guangdong and Fujian, respectively. Super typhoons affect Taiwan with a frequency of once every 12–30 years on average. A tropical cyclone hazard index is also created to investigate the vulnerability at these cities.     

星载双频云雷达的云微物理参数反演算法研究

使用星载雷达模拟器输出的模拟数据,为星载双频云雷达选择了最佳的频点组合,并开展了双频联合反演云微物理参数的算法研究。结果表明:（1）在位于大气窗口的6组频点组合中,94/220 GHz的组合对滴谱参数的微小变化较为敏感,有利于进行双频的联合反演。综合考虑不同频点的探测能力、衰减以及工业部门的制造水平后,认为94/220 GHz可以作为未来星载双频测云雷达的探测频点。（2）双频反演中最核心的双波长比（DWR）和体积中值直径（D₀）的关系与冰晶粒子密度相关。当密度随着粒子直径变化时,DWR随着D₀单调递增,当粒子密度固定不变时,DWR-D₀曲线可能会出现非单调变化,从而使得固定密度时的反演比变密度时更加复杂。（3）后向迭代的双频反演算法同样适用于94/220 GHz进行云微物理参数的反演,并且对模拟数据的反演精度较高。此外,反演精度受到系统噪声以及定标精度的影响,为了满足反演精度的要求,系统噪声和定标误差应该控制在1 dBz以内。      

Long-range prediction of Indian summer monsoon rainfall using data mining and statistical approaches

This paper presents a hybrid model to better predict Indian summer monsoon rainfall. The algorithm considers suitable techniques for processing dense datasets. The proposed three-step algorithm comprises closed itemset generation-based association rule mining for feature selection, cluster membership for dimensionality reduction, and simple logistic function for prediction. The application of predicting rainfall into flood, excess, normal, deficit, and drought based on 36 predictors consisting of land and ocean variables is presented. Results show good accuracy in the considered study period of 37years (1969–2005).     

Projections of high resolution climate changes for South Korea using multiple-regional climate models based on four RCP scenarios. Part 2: precipitation

Precipitation changes over South Korea were projected using five regional climate models (RCMs) with a horizontal resolution of 12.5 km for the mid and late 21st century (2026-2050, 2076- 2100) under four Representative Concentration Pathways (RCP) scenarios against present precipitation (1981-2005). The simulation data of the Hadley Centre Global Environmental Model version 2 coupled with the Atmosphere-Ocean (HadGEM2-AO) was used as boundary data of RCMs. In general, the RCMs well simulated the spatial and seasonal variations of present precipitation compared with observation and HadGEM2-AO. Equal Weighted Averaging without Bias Correction (EWA_NBC) significantly reduced the model biases to some extent, but systematic biases in results still remained. However, the Weighted Averaging based on Taylor’s skill score (WEA_Tay) showed a good statistical correction in terms of the spatial and seasonal variations, the magnitude of precipitation amount, and the probability density. In the mid-21st century, the spatial and interannual variabilities of precipitation over South Korea are projected to increase regardless of the RCP scenarios and seasons. However, the changes in area-averaged seasonal precipitation are not significant due to mixed changing patterns depending on locations. Whereas, in the late 21st century, the precipitation is projected to increase proportionally to the changes of net radiative forcing. Under RCP8.5, WEA_Tay projects the precipitation to be increased by about +19.1, +20.5, +33.3% for annual, summer and winter precipitation at 1-5% significance levels, respectively. In addition, the probability of strong precipitation (≥ 15 mm d^-1) is also projected to increase significantly, particularly in WEA_Tay under RCP8.5.     

Design of an inversion-based precipitation proflie retrieval algorithm using an explicit cloud model for initial guess microphysics

Summary This paper describes the design and validation of the FSU precipitation profile retrieval algorithm for applications with SSM/I passive microwave measurements. The algorithm employs the principles of multifrequency inversion based on forward radiative transfer modeling. A Sobolev 2-stream solution to the radiative transfer equation (RTE) is used as the forward RTE model and is described herein. The method is shown to be very accurate, retaining the same degree of computational efficiency inherent to simpler 2-stream flux models. Tests of the model against more detailed multistream, adding-doubling models demonstrate that the Sobolev solution produces radiance accuracies of approximately 1%. An advantage of the Sobolev approach is that the intensity field can be expanded in a mathematically consistent fashion, an essential feature in applications with the off-nadir SSM/I microwave measurements. A 4-dimensional non-hydrostatic cloud model provides the microphysical underpinnings of the algorithm, and is used to generate the initial guess profiles for the inversion procedure. The various stages of the algorithm are described, as well as two different methods of computational implementation for storm-scale and global-scale applications. The paper also summarizes a number of different rainrate validation analyses that have been carried out at the two scales, as well as examining the capabilities of the algorithm in diagnosing the vertical latent heating structure. The validation results represent a mixture of quantitative comparisons to radar and raingage datasets, and more qualitative comparisons to the numerical modeling results of other investigators. Because of known uncertainties in the validation data in terms of their accuracy and representativeness, and the underlying problems with time-space matching of the comparisons, it is not yet possible to place absolute confidence limits on the retrievals. However, taken as a whole, the rainrate validation analyses and the estimated latent heating profiles present solid evidence that the profile approach is returning credible rainfall estimates whose uncertainnes are commensurate with those of current validation data.With 12 Figures