A quantitative analysis of KALPANA-1 derived water vapor winds and its impact on NWP model

The coverage of satellite derived winds over the Indian region including Indian Ocean has improved by the operation of India’s first dedicated satellite for meteorology, KALPANA-1 since 12 September 2002. Atmospheric motion vectors (AMVs) are being derived at the India Meteorological Department (IMD), New Delhi on a routine operational basis. The AMV is recognized as an important source of information for numerical weather prediction (NWP) and is particularly suited for tracking the low and middle level clouds mainly because of the good contrast in albedo between target and background, whereas the upper level moisture pattern can be better tracked by water vapor winds (WVW) using water vapor (WV) channel (5.7–7.1 μm). The WVWs proved to be a very useful wind product for predicting the future track position of cyclones, well marked low pressure areas or heavy rainfall warnings in advance and so, often these types of weather systems are steered by the upper level winds. In the present study, the quantitative as well as qualitative analyses of KALPANA-1 WVW have been carried out. The primary change introduced is making use of first guess (FG) forecast fields obtained from National Center for Environmental Prediction (NCEP) and Global Forecast System (GFS), at a resolution of 1° × 1° with T-382/L64 instead of forecasts of operational limited area model (LAM) of IMD. The overall results showed a consistent improvement after using improved FG wind fields from NCEP instead of LAM with a significantly increasing number of good qualities of KALPANA-1 derived WVWs. The quantitative error analysis has also been carried out for the validation of WVWs using collocated radiosonde observations for the period from May 2008 to December 2009 and the available mid-upper level winds derived from METEOSAT-7 data for the period from October to December 2008. The analysis shows that after modification, the RMSE and bias of KALPANA-1 WVWs have reduced considerably. Further, to assess the impact of these winds, a high resolution mesoscale model WRF 3DVAR system is used in the present study for the analysis of tropical cyclone ‘Sidr’. The results show that the wind assimilation experiments (analysis at 200 hPa) using upper level KALPANA-1 WVW have great potential for improving the NWP analysis. The impact of additional wind data in the model is found to be positive and beneficial.     

A Study on Height Reassignment for the AMV Products of the FY-2C Satellite

A method for using height reassignment to improve the quality of satellite-derived atmospheric motion vectors (AMVs) is presented. The rationale underlying height reassignment is explored, and the technical details are studied by applying three height reassignment schemes that use NCEP reanalysis winds. The quality of the AMVs is generally improved following reassignment, although the magnitude of the improvement differs according to the scheme applied. Scheme 3 provides the best quality and stability, followed by Scheme 1 and Scheme 2. The negative biases in the zonal components of the AMVs decrease from [-5,-4] m s-1to <-1 m s-1following reassignment. The meridional components also improve. The AMVs derived from the infrared and water vapor channels improve by 58.7% and 25%, respectively. The feasibility of using Scheme 3 in the operational derivation of AMVs is studied by incorporating the forecast wind field predicted by a T511 medium-range numerical weather prediction (NWP) system. Incorporating the 120-h forecast reduces the negative biases in zonal winds and positive biases in meridional winds retrieved from the water vapor channel, improving the overall quality of the AMVs by 26.7%. Extending the validity period of the forecast field linearly reduces the improvement in retrieved AMVs, but the magnitude of this reduction is small. Incorporating the 120-h forecast field still results in a 13% improvement, although it may eliminate a larger number of AMVs of good quality.     

Characteristics of Fengyun-4A Satellite Atmospheric Motion Vectors and Their Impacts on Data Assimilation

The high observation efficiency, scanning speed and observation frequency of the Fengyun-4A (FY-4A) satellite indicates the progress of Chinese geostationary meteorological satellites. The characteristics of FY-4A atmospheric motion vectors (AMVs) derived from the high-level water vapor (WV-High) channel, mid-level water vapor (WV-Mid) channel, and infrared (IR) channel of FY-4A are analyzed, and their corresponding observation errors estimated. Then, the impacts of single-channel and multi-channel FY-4A AMVs on RMAPS-ST (the Rapid-refresh Multi-scale Analysis and Prediction System—Short Term) are evaluated based on one-month data assimilation cycling and forecasting experiments. Results show that the observation errors of FY-4A AMVs from the three channels have an explicit vertical structure. Results from the cycling experiments indicate that the assimilation of AMVs from WV-High produces more apparent improvement of the wind in the upper layer, while a more positive effect in the lower layer is achieved by the assimilation of AMVs from IR. Furthermore, the assimilation of AMVs from IR is more skillful for medium and moderate precipitation than from other channels owing to the good quality of data in the lower layer in the AMVs from IR. Assimilation of FY-4A AMVs from the three channels could combine the advantages of assimilation from each individual channel to improve the wind in the upper, middle and lower layers simultaneously.     

Impact of assimilation of INSAT-3D retrieved atmospheric motion vectors on short-range forecast of summer monsoon 2014 over the South Asian region

The Weather Research and Forecasting (WRF) model and its three-dimensional variational data assimilation system are used in this study to assimilate the INSAT-3D, a recently launched Indian geostationary meteorological satellite derived from atmospheric motion vectors (AMVs) over the South Asian region during peak Indian summer monsoon month (i.e., July 2014). A total of four experiments were performed daily with and without assimilation of INSAT-3D-derived AMVs and the other AMVs available through Global Telecommunication System (GTS) for the entire month of July 2014. Before assimilating these newly derived INSAT-3D AMVs in the numerical model, a preliminary evaluation of these AMVs is performed with National Centers for Environmental Prediction (NCEP) final model analyses. The preliminary validation results show that root-mean-square vector difference (RMSVD) for INSAT-3D AMVs is ～3.95, 6.66, and 5.65 ms^?1 at low, mid, and high levels, respectively, and slightly more RMSVDs are noticed in GTS AMVs (～4.0, 8.01, and 6.43 ms^?1 at low, mid, and high levels, respectively). The assimilation of AMVs has improved the WRF model of produced wind speed, temperature, and moisture analyses as well as subsequent model forecasts over the Indian Ocean, Arabian Sea, Australia, and South Africa. Slightly more improvements are noticed in the experiment where only the INSAT-3D AMVs are assimilated compared to the experiment where only GTS AMVs are assimilated. The results also show improvement in rainfall predictions over the Indian region after AMV assimilation. Overall, the assimilation of INSAT-3D AMVs improved the WRF model short-range predictions over the South Asian region as compared to control experiments.     

Assimilation of the multisatellite data into the WRF model for track and intensity simulation of the Indian Ocean tropical cyclones

Weather Research and Forecasting (WRF-ARW) model and its three-dimensional variational data assimilation (3D-Var) system are used to investigate the impact of the Quick Scatterometer (QuikSCAT) near surface winds, Special Sensor Microwave/Imager (SSM/I)-derived Total Precipitable Water (TPW), and Meteosat-7-derived Atmospheric Motion Vectors (AMVs) on the track and intensity prediction of tropical cyclones over the North Indian Ocean. The case of tropical cyclone, Gonu (June 2007; Arabian Sea), is first tested and the results show significant improvements particularly due to the assimilation of QuikSCAT winds. Three other cases, cyclone Mala (April 2006; Bay of Bengal), Orissa super cyclone (October 1999; Bay of Bengal), and Very Severe Cyclonic storm (October 1999; Bay of Bengal), are then examined. The prediction of cyclone tracks improved significantly with the assimilation of QuikSCAT winds. The track improvement resulted from the relocation of the initial cyclonic vortices after the assimilation of QuikSCAT wind vectors. After the assimilation of QuikSCAT winds, the mean (for four cyclone cases) track errors for first, second, and third day forecasts are reduced to 72, 101, and 166?km, respectively, from 190, 250, and 381?km of control (without QuikSCAT winds) runs. The assimilation of QuikSCAT winds also shows positive impact on the intensity (in terms of maximum surface level winds) prediction particularly for those cyclones, which are at their initial stages of the developments at the time of data assimilation. The assimilation of SSM/I TPW has significant influence (negative and positive) on the cyclone track. In three of the four cases, the assimilation of the SSM/I TPW resulted in drying of lower troposphere over cyclonic region. This decrease of moisture in TPW assimilation experiment resulted in reduction of cyclonic intensity. In three of the four cyclones, the assimilation of Meteosat-7 AMVs shows negative impact on the track prediction.     

GNSS/PWV与风云四号A星GIIRS水汽廓线融合应用研究

中国新一代地球静止气象卫星风云四号A星（FY-4A）搭载的干涉式大气垂直探测仪（Geostationary Interferometric Infrared Sounder, GIIRS）以红外高光谱干涉分光方式探测三维大气温湿结构,取得了在静止轨道上探测大气的突破性进展。地基全球导航卫星系统（Global Navigation Satellite System,GNSS）是一种连续监测大气可降水量（Precipitable Water Vapor,PWV）的有效手段,基于2018年6—8月中国地基GNSS站监测的PWV和FY-4A/GIIRS水汽廓线的业务产品以及常规无线电探空资料,开展GNSS/PWV与FY-4A/GIIRS水汽廓线快速融合应用,以提高卫星资料反演大气水汽廓线的精度。结果表明:与常规无线电探空相比,FY-4A/GIIRS水汽廓线产品在大气低层均方根误差（Root Mean Square Error,RMSE）为4.5 g/kg,700 hPa为2.4 g/kg,500 hPa以上因水汽含量较低RSME小于1.5 g/kg。GNSS/PWV与FY-4A/GIIRS水汽廓线融合后,FY-4A/GIIRS水汽廓线误差整层RMSE减小20%,从近地层到600 hPa RMSE平均减小20%—25%,尤其是850—700 hPa改善最明显,极大改善了卫星水汽反演资料的可用性。对一次多系统影响的暴雨天气过程应用分析表明,GNSS/PWV和FY-4A/GIIRS融合产品可获得高时、空密度的大气水汽廓线,对强降水的临近预报有非常重要的支撑作用。      

Validation of IASI-Retrieved Atmospheric Water Vapor Data over the Tibetan Plateau Region

The Infrared Atmospheric Sounding Interferometer (IASI) is a new-generation ultraspectral atmospheric sounding instrument mounted on the MetOp-A, the first operational polar-orbiting satellite developed by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). It is an ultrahigh spectral-resolution atmospheric detector which can detect atmospheric chemical composition, temperature, and humidity profiles with high accuracy and resolution. In the present study, through comparative analyses of the similarities and differences between the IASI and the radiosonde observation (RAOB) water vapor data, and between the IASI and the Aqua-AIRS water vapor retrievals, a detailed and systematic assessment of the credibility of the IASI water vapor retrievals over the plateau region was made. A comparison of the IASI retrievals with the AIRS retrievals and the RAOB measurements over the Tibetan Plateau revealed that the IASI retrieval data are reliable and can be used for conducting further studies.     

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.     

FY-4A卫星云导风观测误差优化及同化效果影响研究

为了推进FY-4A卫星资料在数值模式中的实际应用,本研究选择云导风产品作为研究对象,首先统计了FY-4A高层水汽通道和红外通道云导风的观测误差,进一步基于WRFDA(Weather Research and Forecasting model Data Assimilation system)系统,利用默认观测误差和新...     

L波段高空气象探测系统测风算法改进探讨

对我国高空气象观测业务中的平均风计算方法及其存在的问题进行了分析和探讨,提出了完全采用矢量平均风算法来求取高空规定层风的业务流程改进方案;用锡林浩特站和阳江站同球施放的RS92GPS探空仪与L波段雷达-GTS1探空仪的对比观测数据集,对20~200s时间窗口下的各种矢量平均风计算方案及其规定风层计算结果进行了分析比对,提出未来改进的L波段高空气象观测系统可以测试使用时间窗口为30~45s的矢量平均风、使得计算风层达到每150~350m高程一个,以便进一步提高与GPS测风结果的一致性、更好地满足预报服务部门对高空风垂直分辨率的应用需求。     

CYGNSS海表风场观测数据验证及其可能的应用

海表面风场可以用于获取许多大气和海洋现象的信号,高质量、高时空分辨率的海表面风场数据产品将有利于海洋-大气动力过程的研究.本文使用全球热带系泊浮标阵列计划（Global Tropical Moored Array Programs）的锚定浮标风场数据和西沙通量塔气象观测资料验证了Cyclone Global Navigation Satellite System （CYGNSS）的35°N~35°S海面遥感风场观测数据.结果表明,CYGNSS海表面风场与实测资料存在着2.17 m/s左右的平均均方根误差（RMSD）,它可能源于观测数据和卫星遥感资料的观测误差,以及两者在空间和时间上未严格匹配而引起的代表性误差.另外,CYGNSS海表面风速的时间演变与实测资料非常一致,展现了CYGNSS在研究海洋-大气能量和动量交换过程方面的潜在应用价值.本文使用Madden-Julian Oscillation （MJO）和赤道东部印度洋上升流事件作为两个个例,说明了CYGNSS海表面风场资料的潜在应用价值.     

Intra-seasonal variability in Oceansat-2 scatterometer sea-surface winds over the Indian summer monsoon region

In September 2009, the Indian Space Research Organisation launched a Ku-band microwave scatterometer (OSCAT) onboard the polar orbiting satellite ‘Oceansat-2’. In this article, the capabilities of the newly available OSCAT sea-surface winds are demonstrated by studying the monsoon intra-seasonal variabilities during the 2010 summer monsoon season. A preliminary validation of OSCAT surface winds with European Centre for Medium Range Weather Forecasting (ECMWF) analysis surface winds carried out during June to August 2010 suggests that the quality of the OSCAT winds are able to meet the mission specifications. The observed mean monthly features of the Indian summer monsoon in July and August 2010 from OSCAT match well with those of ECMWF reanalysis winds. The OSCAT winds capture the known characteristics of the Indian summer monsoon, such as the northward propagation of a low level jet, and its preferred locations during active and break monsoon conditions, reasonably well. The Morlet wavelet transform is used for time series analysis. The OSCAT measured sea-surface winds were found to possess two dominant modes of variability during the 2010 monsoon season: one with a periodicity between 32 and 64?days, and another with a periodicity between 8 and 16?days. Rainfall activity over the Indian summer monsoon region is closely associated with the phases of the two above-mentioned dominant intra-seasonal variabilities. This study demonstrates that the OSCAT winds can be used very well and with confidence for meteorological studies.     

Prediction of tropical cyclogenesis in North Indian Ocean using Oceansat-2 scatterometer (OSCAT) winds

India’s polar orbiting satellite Oceansat-2 was launched by Indian Space Research Organisation on 23 September 2009 for applications pertaining to ocean studies and meteorology. The wind scatterometer aboard the Oceansat-2 satellite (OSCAT) covers 90 % of the global ocean within a day. In the present study, the OSCAT-derived wind fields are used to predict the genesis of tropical cyclones over the North Indian Ocean using a new technique based on data mining. The technique is based on the premise that there is some degree of similarity in low-level wind circulation among developing systems, which can be utilized to distinguish them from non-developing systems. This similarity of wind patterns has been measured quantitatively by computing the “matching index” between the given wind pattern and the wind signatures of developing systems available from the past observations. The algorithm is used to predict the tropical cyclogenesis of cyclones formed during the period 2009–11 in the North Indian Ocean. All the tropical disturbances that developed into tropical storms during the above period (2009–11), viz. PHYAN, WARD, LAILA, BANDU, PHET, GIRI, JAL, KEILA, FOUR, FIVE and THANE were predicted using the proposed method. The mean prediction lead time of the technique was 63 h. Probability of detection of the technique was 100 %, while the false alarm ratio was 2 %.     

卫星风推导和应用综述

该文介绍了卫星风推导和应用的进展, 包括卫星风的算法, 卫星风在数值天气预报中的应用, 卫星风在天气分析和预报中的应用以及卫星风的研究工作动向。目前各个卫星数据处理中心卫星风的算法大体一致和稳定。风矢量的追踪用相关匹配法, 而风矢量的高度指定依靠双通道物理方法。卫星风的质量是从图像定位和定标开始的许多工作阶段的综合结果, 确保每个工作段的高质量对于风矢量的计算都十分重要。卫星风的高度指定仍然是最有挑战性的课题。因为物理定高方法进展不明显, 近期内尤其要重视几何定高技术的研究和使用。静止气象卫星的风对数值预报的影响在热带和南半球是正反馈; 由于在极地地区各种资料都十分匮乏, 极地卫星风对数值天气预报有非常明显的正反馈。卫星风与云图叠合显示, 在主要雨带、副热带高压、强对流和热带气旋的诊断、分布、预报中十分有用。     

Derivation of Cloud-Free-Region Atmospheric Motion Vectors from FY-2E Thermal Infrared Imagery

The operational cloud-motion tracking technique fails to retrieve atmospheric motion vectors(AMVs) in areas lacking cloud; and while water vapor shown in water vapor imagery can be used, the heights assigned to the retrieved AMVs are mostly in the upper troposphere. As the noise-equivalent temperature difference(NEd T) performance of FY-2E split window(10.3–11.5 μm, 11.6–12.8 μm) channels has been improved, the weak signals representing the spatial texture of water vapor and aerosols in cloud-free areas can be strengthened with algorithms based on the difference principle, and applied in calculating AMVs in the lower troposphere. This paper is a preliminary summary for this purpose, in which the principles and algorithm schemes for the temporal difference, split window difference and second-order difference(SD) methods are introduced. Results from simulation and cases experiments are reported in order to verify and evaluate the methods, based on comparison among retrievals and the "truth". The results show that all three algorithms, though not perfect in some cases,generally work well. Moreover, the SD method appears to be the best in suppressing the surface temperature influence and clarifying the spatial texture of water vapor and aerosols. The accuracy with respect to NCEP 800 h Pa reanalysis data was found to be acceptable, as compared with the accuracy of the cloud motion vectors.     

Construction of vertical wind profile from satellite-derived winds for objective analysis of wind field

During summer Monex-79, a variety of observing systems viz. research ships, research aircrafts, constant pres-sure balloons and geostationary satellite etc. were deployed, besides the regular conventional observations The pur-pose of these additional systems was to make the best possible data for the studies on various aspects of monsoon cir-culation. The present study is aimed at the construction of vertical wind profile using cloud motion vectors obtained from GOES (I-O) satellite and to examine whether the constructed wind profiles improves the representation of the monsoon system, flow pattern etc. in the objective analysis. For this purpose, climatological normals of the wind field are considered as the initial guess and the objective analyses of the wind field are made with, first using only data from conventional observations over land areas, subsequently including the constructed winds from cloud motion vectors. These analyses are then compared with the standard analyses of wind field obtained from Quick Look Atlas by T. N. Krishnamurti et al. (1979).It is inferred that satellite estimated mean wind profiles show good agreement with the mean wind profiles of the research ships with RMS errors less than 5 mps below 500 hPa and less than 8 mps above 500 hPa. It is further infer-red that the inclusion of constructed winds shows a positive impact on the objective analysis and improvement is seen to be more marked in the data-sparse region of the Arabian sea. Analyses which include the constructed winds show better agreement with the standard analysis, than the analyses obtained using only conventional winds. Thus, results of our study suggest that the wind profiles constructed using cloud motion vectors are of potential use in objective analysis to depict the major circulation features over the Indian region.     

Satellite- and radar-based investigations of heavy precipitation systems on the southern side of the European Alps

Summary In autumn 1999 during the field phase of the Mesoscale Alpine Programme (MAP), the geostationary satellite Meteosat-6 performed 5-minute rapid scan imagery over central Europe. The rapid scan data of 11 heavy precipitation events are investigated by analyzing the spatial and temporal characteristics of cloud top structures. The objectives are to separate convective from stratiform cloud regions by satellite data alone and to gain insight into the life cycle of heavy precipitation systems. For verification of the satellite-based results, radar data from the operational Mt. Lema C-band radar is interpolated on the spatial grid of the infrared and visible Meteosat images. The interpolated radar data of each single grid cell is then classified by a convective-stratiform algorithm and compared to the analysed rapid scan imagery.The satellite- and radar-based approaches do only rarely produce matching classifications concerning the identification of convective areas. Since convection during the field phase of MAP occurred mostly embedded within stratiform cloud regions, no temporal and spatial characteristics of convective activity within clouds can be systematically derived from satellite imagery. This lack of characteristic cloud top structures prevented the unambiguous identification of typical cloudiness associated with stratiform precipitation. It is one of the major findings of this study, that in several cases being classified as stratiform by radar, strong cloud development is observed in satellite imagery. The preferred area of strong cloud development is located ahead of the Alpine barrier in a precipitation-free atmosphere. Two contrasting examples of life cycles of heavy precipitation systems are given based on the complementary information extracted from satellite and radar data.     

L波段探空系统高空风平滑计算方法探讨

在分析现行业务L波段探空系统测风原理的基础上,提出改进高空测风数据的平滑计算方法.首先比较了业务分钟风与滑动平均风两种高空测风数据的平滑计算办法,并与GPS RS92测风数据进行了对比分析和批统计处理,特别是对业务L波段雷达在1～21、22～42和43分钟及以后采取不同的时间隔计算风的规定给出了分时段以及低仰角、远距离和小风速的统计分析.结果显示,滑动平均法在选取合适的滑动平均窗口的条件下,其计算的高空风与GPS RS92测风结果一致性更好且动态误差小.建议未来改进业务L波段探空系统的高空风平滑计算方法时,采用窗口为1分钟的滑动平均方式或者前20分钟采用30秒,以后采用1分钟的分段滑动平均方法.     

Mesoscale Structure of Trade Wind Convection over Puerto Rico: Composite Observations and Numerical Simulation

We examine the mesoscale structure of the atmospheric boundary layer (ABL), low-level circulation, and trade wind convection over the sub-tropical island of Puerto Rico in mid-summer. Shallow afternoon thunderstorms are frequently seen over the western plains of the island. Observational data include automatic weather station measurements, radiosonde profiles, infrared satellite images, and mesoscale reanalysis data with a focus on the summer of 2006. Satellite microwave radar data (TRMM and CloudSat) indicate that island clouds typically extend just above the −20°C level during afternoon hours with reflectivity values reaching 50 dBz. A singular value decomposition of 3-hourly high resolution satellite rainfall maps reveals an island mode. From this a composite is constructed for a group of ten cases. With a Froude number ≈1 the trade winds pass over the mountains and standing vortices and gravity waves are trapped in the meandering wake. The Weather and Research Forecasting (WRF) model at 1-km resolution with 51 vertical layers is used to simulate the short-lived thunderstorms for two cases: 27 June and 20 July 2006. The model correctly locates the convective cells that develop between 1400 and 1700 LST. The shallow afternoon thunderstorms are triggered by surface heat fluxes, confluent sea breezes and a mountain wake. Recommendations for enhanced observations are given.     

Precipitable water vapor estimation in India from GPS-derived zenith delays using radiosonde data

One of the most recent applications of global positioning system (GPS) is the estimation of precipitable water vapor (PWV). It requires proper modeling to extract PWV from zenith wet delay (ZWD). The existing global models take no account of latitudinal and seasonal variation of meteorological parameters in the atmosphere. In fact, they ignore the atmospheric conditions at a specific location. Therefore, site-specific PWV models have been developed for five stations spread over the Indian subcontinent, using 3-year (2006–2008) radiosonde data from each of these stations. Furthermore, a similar regional PWV model is also developed for the Indian region. The purpose of the developed site-specific as well as regional model was to convert ZWDs into PWV without using surface meteorological parameters. It has been found that the developed regional and site-specific PWV models show about mm-level accuracy in estimating PWV using derived ZWD from radiosonde as input. The developed site-specific, regional models were also used to extract PWV from GPS-derived ZWD at Bangalore and New Delhi. The accuracy of the developed site-specific and regional model is of the same level. The PWV accuracy obtained with the developed regional model is about 6.28, 6.6 mm in comparison to radiosonde PWV at Bangalore and New Delhi, respectively.