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1.
Horizontal surface visibility range, one of the simplest measures of local atmospheric pollution, is critical for aviation, surface transport besides long-term impact on human health and climate. Long-term observations from multiple stations (including airports) across the world show statistically significant decline in visibility. We have studied climatology and trends of morning poor visibility days (PVD, visibility <4 km) and afternoon good visibility days (GVD, visibility >10 km) based on 279 surface meteorological stations well distributed over India for the period 1961–2008. During last 5 decades, all India averaged range of annual morning PVD has increased from 6.7 to 27.3 % days, while the range of afternoon GVD has decreased from 76.1 to 30.6 % days. Annually, the morning PVD increased significantly at 3.3 % days per decade, and the afternoon GVD declined significantly at ?8.6 % days per decade. Seasonally, the highest increase in morning PVD has occurred in winter (+4.3 % days per decade), while post-monsoon has the highest decrease in afternoon GVD (?9.2 % days per decade). In spatial distribution, visibility has decreased nationwide especially over Indo-Gangetic (IG) plains, central, east and northeast India which is due to increased wintertime fog, water vapor and aerosol loading. The IG plains suffer from increased fog or smog and aerosol loading during wintertime. Long-term visibility impairment over India is visible through increasing morning PVD (decreasing GVD) and decreasing afternoon GVD (increasing PVD) which are spatially well correlated with increasing relative humidity and decreasing wind speed (seasonal).  相似文献   

2.
Statistical bias correction methods for numerical weather prediction (NWP) forecasts of maximum and minimum temperatures over India in the medium-range time scale (up to 5 days) are proposed in this study. The objective of bias correction is to minimize the systematic error of the next forecast using bias from past errors. The need for bias corrections arises from the many sources of systematic errors in NWP modeling systems. NWP models have shortcomings in the physical parameterization of weather events and have the inability to handle sub-grid phenomena successfully. The statistical algorithms used for minimizing the bias of the next forecast are running-mean (RM) bias correction, best easy systematic estimator, simple linear regression and the nearest neighborhood (NN) weighted mean, as they are suitable for small samples. Bias correction is done for four global NWP model maximum and minimum temperature forecasts. The magnitude of the bias at a grid point depends upon geographical location and season. Validation of the bias correction methodology is carried out using daily observed and bias-corrected model maximum and minimum temperature forecast over India during July–September 2011. The bias-corrected NWP model forecast generally outperforms direct model output (DMO). The spatial distribution of mean absolute error and root-mean squared error for bias-corrected forecast over India indicate that both the RM and NN methods produce the best skill among other bias correction methods. The inter-comparison reveals that statistical bias correction methods improve the DMO forecast in terms of accuracy in forecast and have the potential for operational applications.  相似文献   

3.
In this study it is investigated how uncertainties in the magnitude of the drag coefficient translate into uncertainties in storm surge forecasts in the case of severe weather. A storm surge model is used with wind stress data from a numerical weather prediction (NWP) model, to simulate several recent storms over the North Sea. For a fixed wind speed, the wind stress is linear in the drag coefficient. However, in the NWP model the wind speed is not fixed and increasing the drag in the NWP model results into reduced wind speeds. The results from simulations show that for given increase in the drag coefficient, the weakening of the 10-m wind field reduces the increase in the stress considerably. When the Charnock parameter is increased in the NWP model, the resulting relative changes in the wind stress are almost independent of the wind speed. This is related to the fact that the depth of the surface boundary layer depends on the wind speed. The ratio between relative changes in the wind stress and relative changes in the drag coefficient depends on the wind speed. For 10-m wind speeds larger than 20?m?s?1 the ratio is 0.52; for lower wind speed criteria the ratio is somewhat larger (??0.60). Approximately 36% of the relative change in the drag coefficient translates into a relative change in the surge in stations at the Dutch coast. The relative increase in the storm surge is approximately 68% of the relative increase in the stress.  相似文献   

4.
The output from Global Forecasting System (GFS) T574L64 operational at India Meteorological Department (IMD), New Delhi is used for obtaining location specific quantitative forecast of maximum and minimum temperatures over India in the medium range time scale. In this study, a statistical bias correction algorithm has been introduced to reduce the systematic bias in the 24–120 hour GFS model location specific forecast of maximum and minimum temperatures for 98 selected synoptic stations, representing different geographical regions of India. The statistical bias correction algorithm used for minimizing the bias of the next forecast is Decaying Weighted Mean (DWM), as it is suitable for small samples. The main objective of this study is to evaluate the skill of Direct Model Output (DMO) and Bias Corrected (BC) GFS for location specific forecast of maximum and minimum temperatures over India. The performance skill of 24–120 hour DMO and BC forecast of GFS model is evaluated for all the 98 synoptic stations during summer (May-August 2012) and winter (November 2012–February 2013) seasons using different statistical evaluation skill measures. The magnitude of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) for BC GFS forecast is lower than DMO during both summer and winter seasons. The BC GFS forecasts have higher skill score as compared to GFS DMO over most of the stations in all day-1 to day-5 forecasts during both summer and winter seasons. It is concluded from the study that the skill of GFS statistical BC forecast improves over the GFS DMO remarkably and hence can be used as an operational weather forecasting system for location specific forecast over India.  相似文献   

5.
Almost every year in the winter months (December–February), the vast Indo-Gangetic Plain south of the Himalaya is affected by dense fog. This fog is considered as radiational fog, and sometime it becomes smog (when it mixes with smoke). The typical meteorological, topographic and increasing pollution conditions over the Indo-Gangetic Plain are perhaps the common contributing factors for fog formation. In the present study, the North Indian fog has been successfully mapped and analysed using NOAA-AVHRR satellite data. In the winter seasons of 2005–06, 2006–07 and 2007–08, the fog-affected area has been found to cover about 575,800 km2, 594,100 km2 and 478,000 km2, respectively. Less fog in 2007–08 may be the consequence of high fluctuations in the meteorological parameters like temperature, relative humidity and wind speed as related to the prevailing synoptic regime for that season. The dissipation and migration pattern of fog in the study area has also been interpreted on the basis of the analysis of both meteorological and satellite data. Further analysis of the fog-affected area allowed identifying more fog-prone regions. Analysis of past fog-affected days and corresponding meteorological conditions enabled us to identify favourable conditions for fog formation viz. air temperature 3–13°C, relative humidity >87%, wind speed <2 m/s and elevation <300 m. Based on the observations of past fog formation and corresponding governing parameters, fog for few selected days could be predicted in hind-sight and later verified with NOAA images.  相似文献   

6.
Performance of four mesoscale models namely, the MM5, ETA, RSM and WRF, run at NCMRWF for short range weather forecasting has been examined during monsoon-2006. Evaluation is carried out based upon comparisons between observations and day-1 and day-3 forecasts of wind, temperature, specific humidity, geopotential height, rainfall, systematic errors, root mean square errors and specific events like the monsoon depressions.It is very difficult to address the question of which model performs best over the Indian region? An honest answer is ‘none’. Perhaps an ensemble approach would be the best. However, if we must make a final verdict, it can be stated that in general, (i) the WRF is able to produce best All India rainfall prediction compared to observations in the day-1 forecast and, the MM5 is able to produce best All India rainfall forecasts in day-3, but ETA and RSM are able to depict the best distribution of rainfall maxima along the west coast of India, (ii) the MM5 is able to produce least RMSE of wind and geopotential fields at most of the time, and (iii) the RSM is able to produce least errors in the day-1 forecasts of the tracks, while the ETA model produces least errors in the day-3 forecasts.  相似文献   

7.
An accurate tropical cyclone track and intensity forecast is very important for disaster management. Specialized numerical prediction models have been recently used to provide high-resolution temporal and special forecasts. Hurricane Weather Research and Forecast (HWRF) model is one of the emerging numerical models for tropical cyclone forecasting. This study evaluates the performance of HWRF model during the post monsoon tropical cyclone Nilofar on the north Indian Ocean basin. The evaluation uses the best track data provided by the Indian Meteorological Department (IMD) and the Joint Typhoon Warning Centre (JTWC). Cyclone track, central pressure, and wind speed are covered on this evaluation. Generally, HWRF was able to predict the Nilofar track with track error less than 230 km within the first 66 h of forecast time span. HWRF predicted more intense tropical cyclone. It predicted the lowest central pressure to be 922 hPa while it reached 950 hPa according to IMD and 937 hPa according to JTWC. Wind forecast was better as it predicted maximum wind speed of 122 kt while it reached 110 and 115 kt according to IMD and JTWC, respectively.  相似文献   

8.
《Atmósfera》2014,27(3):287-303
Given the growing interest of the general public in accessing commercial weather forecasts through various media outlets and the available impetuses for promoting tourism in Saudi Arabia (SA), a first attempt is made to present a forecast skill comparison for surface temperature in four cities (Wejh, Yenbo, Jeddah, and Gizan) along the west coast of SA, for the 61-day transitional period (from January 16 to March 16) between the December-January-February (DJF) and the March-April-May (MAM) seasons. A simple skill score comparison method is used to assess the next-day city forecasts for surface temperature from six commercial weather forecast providers based on the operational numerical weather prediction (NWP) model outputs. All the NWP model forecast providers performed better than the respective daily climatology (Clm) for each station. Depending upon the station and the provider, the absolute average maximum daily surface temperature difference between the forecasts and the observations was less than 2 °C. Daily surface temperature forecasts from two versions of an atmospheric-ocean general circulation model are also compared to assess their performance for these coastal locations.  相似文献   

9.
The three dimensional variational data assimilation scheme (3D-Var) is employed in the recently developed Weather Research and Forecasting (WRF) model. Assimilation experiments have been conducted to assess the impact of Indian Space Research Organisation’s (ISRO) Automatic Weather Stations (AWS) surface observations (temperature and moisture) on the short range forecast over the Indian region. In this study, two experiments, CNT (without AWS observations) and EXP (with AWS observations) were made for 24-h forecast starting daily at 0000 UTC during July 2008. The impact of assimilation of AWS surface observations were assessed in comparison to the CNT experiment. The spatial distribution of the improvement parameter for temperature, relative humidity and wind speed from one month assimilation experiments demonstrated that for 24-h forecast, AWS observations provide valuable information. Assimilation of AWS observed temperature and relative humidity improved the analysis as well as 24-h forecast. The rainfall prediction has been improved due to the assimilation of AWS data, with the largest improvement seen over the Western Ghat and eastern India.  相似文献   

10.
India Meteorological Department (IMD) introduced the objective tropical cyclone (TC) intensity forecast valid for next 24 h over the north Indian Ocean (NIO) in 2003 and extended up to 72 h in 2009. In this study, an attempt is made to evaluate the TC intensity forecast issued by IMD during 2005–2011 (7 years) by calculating the absolute error (AE), root mean square error (RMSE) and skill in intensity forecast in terms of maximum sustained surface wind (MSW). The accuracy of TC intensity forecast has been analysed with respect to basin of formation (Bay of Bengal, Arabian Sea and NIO as whole), season of formation (pre-monsoon and post-monsoon seasons), intensity of TCs (cyclonic storm and severe cyclonic storm or higher intensities) and type of track of TCs (climatological/straight moving and recurving/looping type). The study shows that the average AE (RMSE) in intensity forecast is about 11(14), 14(19) and 20(26) knots, respectively, for 24-, 48- and 72-h forecasts over the NIO as a whole during 2009–2011. The skill of intensity forecast is about 44 %(48 %), 60 %(58 %) and 60 %(65 %) for 24-, 48- and 72-h forecasts during 2009–2011 with respect to AE (RMSE). There is no significant improvement in terms of reduction in AE and RMSE of MSW forecast over the NIO like that over the northwest Pacific and northern Atlantic Oceans during 2005–2011. However, the skill in intensity forecast compared to persistence method has significantly improved by about 6 %(10 %) and 9 %(8 %) per year, respectively, for 12- and 24-h forecasts considering the AE (RMSE) during 2005–2011. There is also significant increasing trend in percentage of 24-h intensity forecasts with error of 10 knots or less during 2005–2011.  相似文献   

11.
The disastrous effects of numerous winter storms on the marine environment in the North Sea and the Baltic Sea during the last decade show that wind waves generated by strong winds actually represent natural hazards and require high quality wave forecast systems as warning tools to avoid losses due to the impact of rough seas. Hence, the operational wave forecast system running at the German Weather Service including a regional wave model for the North Sea and the Baltic Sea is checked extensively whether it provides reasonable wave forecasts, especially for periods of extraordinary high sea states during winter storms. For two selected extreme storm events that induced serious damage in the area of interest, comprehensive comparisons between wave measurements and wave model forecast data are accomplished. Spectral data as well as integrated parameters are considered, and the final outcome of the corresponding comparisons and statistical analysis is encouraging. Over and above the capability to provide good short-term forecast results, the regional wave model is able to predict extreme events as severe winter storms connected with extraordinary high waves already about 2 days in advance. Therefore, it represents an appropriate warning tool for offshore activities and coastal environment.  相似文献   

12.
Usingin situ data collected during 1992–1997, under the Indian programme of Joint Global Ocean Flux Study (JGOFS), we show that the biological productivity of the Arabian Sea is tightly coupled to the physical forcing mediated through nutrient availability. The Arabian Sea becomes productive in summer not only along the coastal regions of Somalia, Arabia and southern parts of the west coast of India due to coastal upwelling but also in the open waters of the central region. The open waters in the north are fertilized by a combination of divergence driven by cyclonic wind stress curl to the north of the Findlater Jet and lateral advection of nutrient-rich upwelled waters from Arabia. Productivity in the southern part of the central Arabian Sea, on the other hand, is driven by advection from the Somalia upwelling. Surface cooling and convection resulting from reduced solar radiation and increased evaporation make the northern region productive in winter. During both spring and fall inter-monsoons, this sea remains warm and stratified with low production as surface waters are oligotrophic. Inter-annual variability in physical forcing during winter resulted in one-and-a-half times higher production in 1997 than in 1995.  相似文献   

13.
Balram Ambade 《Natural Hazards》2014,70(2):1535-1552
In the present work, chemical characterization and sources of fog water contaminants in the most polluted area of central India, Raipur, and its surroundings are described. The fog water (n = 22) was collected during 2010–2011 from six sites. The physical (i.e., pH, fog amount, electrical conductivity and TDS) and chemical (i.e., F?, Cl?, NO3 ?, SO4 2?, NH4 +, Na+, K+, Mg2+, Ca2+, Al, Mn, Fe, Cu, Zn, Pb and Hg) parameters of the fog water were investigated. The effect of meteorology, i.e., temperature, humidity and wind speed, on the precipitation of the fog water contaminants is discussed. The cluster and factor analysis are used to apportion the sources of the contaminants in the fog water.  相似文献   

14.
A tropical cyclone was formed over central northern Africa near Egypt, Libya and Crete, and it moved and deepened toward the north–northeast; meanwhile, the storm destroyed many regions in the west, southwest and central of Turkey. The cyclone carried huge dust from the north of Africa to Turkey and reduced the visibility to less than 1 km and raised the wind speed. As a result of severe storm, some meteorological stations have new extreme values that the strongest wind speed measured was 81 knots in the central region of Turkey. Medicane with wind speed 81 knots especially over Turkey is a rare event. This devastating cyclone carried exceptionally very strong winds (>80 kts) with favorable conditions to follow windstorm conceptual model. The cyclone caused adverse conditions such as excessive injuries, fatal incidents and forest fires. Mesoscale vortex formed and affected particularly the middle and western regions of Turkey. The vertical thermodynamic structure of storm is compared with April values of 40 years of datasets over Istanbul. Moreover, four different winds {measurement masts} of Istanbul Atatürk Airport are used for the microscale analysis of different meteorological parameters during deepened pressure level. In addition, divergence and vorticity of stormy weather are discussed in details during the effective time period of storm by solving equations and validated using ERA-40 reanalysis. We obtained many monitoring data sources such as ground base, radar, radiosonde and satellite display the values of the intensity of wind speed caused by cyclones of tropics have revealed similarities.  相似文献   

15.
The recent improvement of numerical weather prediction (NWP) models has a strong potential for extending the lead time of precipitation and subsequent flooding. However, uncertainties inherent in precipitation outputs from NWP models are propagated into hydrological forecasts and can also be magnified by the scaling process, contributing considerable uncertainties to flood forecasts. In order to address uncertainties in flood forecasting based on single-model precipitation forecasting, a coupled atmospheric-hydrological modeling system based on multi-model ensemble precipitation forecasting is implemented in a configuration for two episodes of intense precipitation affecting the Wangjiaba sub-region in Huaihe River Basin, China. The present study aimed at comparing high-resolution limited-area meteorological model Canadian regional mesoscale compressible community model (MC2) with the multiple linear regression integrated forecast (MLRF), covering short and medium range. The former is a single-model approach; while the latter one is based on NWP models [(MC2, global environmental multiscale model (GEM), T213L31 global spectral model (T213)] integrating by a multiple linear regression method. Both MC2 and MLRF are coupled with Chinese National Flood Forecasting System (NFFS), MC2-NFFS and MLRF-NFFS, to simulate the discharge of the Wangjiaba sub-basin. The evaluation of the flood forecasts is performed both from a meteorological perspective and in terms of discharge prediction. The encouraging results obtained in this study demonstrate that the coupled system based on multi-model ensemble precipitation forecasting has a promising potential of increasing discharge accuracy and modeling stability in terms of precipitation amount and timing, along with reducing uncertainties in flood forecasts and models. Moreover, the precipitation distribution of MC2 is more problematic in finer temporal and spatial scales, even for the high resolution simulation, which requests further research on storm-scale data assimilation, sub-grid-scale parameterization of clouds and other small-scale atmospheric dynamics.  相似文献   

16.
念青唐古拉山拉弄冰川气象要素变化特征   总被引：3，自引：2，他引：1  
利用在念青唐古拉山拉弄冰川垭口架设的自动气象站观测资料,分析了2006年9月1日至2007年8月31日的气温、气压、相对湿度和风等气象要素的日和季节变化特征.结果表明:拉弄冰川垭口气温日变化呈现升温快降温慢的特点,年平均气温为-8.1℃,最冷月为2月,最暖月为7月,其温度分别为-17.6℃和0.7℃;相对湿度日变化呈单峰单谷型,年平均相对湿度为53.4%,8月最大1月最小;气压日变化呈双峰双谷型,年均气压值为497.1hPa,9月值最大2月值最小,其气压分别为501.9hPa和489.9hPa;冬春季的风速日变化比夏秋季大,年均风速为4.2m.s-1,1月最大8月最小,其风速分别为7.5m.s-1和2.5m.s-1,全年盛行以偏南风和偏北风为主,约占全年盛行风向频率的75.2%.  相似文献   

17.
In this paper, we propose a framework for quantifying risks, including (1) the effects of forecast errors, (2) the ability to resolve critical grid features that are important to accurate site-specific forecasts, and (3) a framework that can move us toward performance-based/cost-based decisions, within an extremely fast execution time. A key element presently lacking in previous studies is the interrelationship between the effects of combined random errors and bias in numerical weather prediction (NWP) models and bias and random errors in surge models. This approach examines the number of degrees of freedom in present forecasts and develops an equation for the quantification of these types of errors within a unified system, given the number of degrees of freedom in the NWP forecasts. It is shown that the methodology can be used to provide information on the forecasts and along with the combined uncertainty due to all of the individual contributions. A potential important benefit from studies using this approach would be the ability to estimate financial and other trade-offs between higher-cost “rapid” evacuation methods and lower-cost “slower” evacuation methods. Analyses here show that uncertainty inherent in these decisions depends strongly on forecast time and geographic location. Methods based on sets of surge maxima do not capture this uncertainty and would be difficult to use for this purpose. In particular, it is shown that surge model bias can play a dominant role in distorting the forecast probabilities.  相似文献   

18.
Incorporation of cloud- and precipitation-affected radiances from microwave satellite sensors in data assimilation system has a great potential in improving the accuracy of numerical model forecasts over the regions of high impact weather. By employing the multiple scattering radiative transfer model RTTOV-SCATT, all-sky radiance (clear sky and cloudy sky) simulation has been performed for six channel microwave SAPHIR (Sounder for Atmospheric Profiling of Humidity in the Inter-tropics by Radiometry) sensors of Megha-Tropiques (MT) satellite. To investigate the importance of cloud-affected radiance data in severe weather conditions, all-sky radiance simulation is carried out for the severe cyclonic storm ‘Hudhud’ formed over Bay of Bengal. Hydrometeors from NCMRWF unified model (NCUM) forecasts are used as input to the RTTOV model to simulate cloud-affected SAPHIR radiances. Horizontal and vertical distribution of all-sky simulated radiances agrees reasonably well with the SAPHIR observed radiances over cloudy regions during different stages of cyclone development. Simulated brightness temperatures of six SAPHIR channels indicate that the three dimensional humidity structure of tropical cyclone is well represented in all-sky computations. Improved correlation and reduced bias and root mean square error against SAPHIR observations are apparent. Probability distribution functions reveal that all-sky simulations are able to produce the cloud-affected lower brightness temperatures associated with cloudy regions. The density scatter plots infer that all-sky radiances are more consistent with observed radiances. Correlation between different types of hydrometeors and simulated brightness temperatures at respective atmospheric levels highlights the significance of inclusion of scattering effects from different hydrometeors in simulating the cloud-affected radiances in all-sky simulations. The results are promising and suggest that the inclusion of multiple scattering radiative transfer models into data assimilation system can simulate the cloud-affected microwave radiance data which provide detailed information on three dimensional humidity structure of the atmosphere in the presence of cloud hydrometeors.  相似文献   

19.
A statistical model for predicting the intensity of tropical cyclones in the Bay of Bengal has been proposed. The model is developed applying multiple linear regression technique. The model parameters are determined from the database of 62 cyclones that developed over the Bay of Bengal during the period 1981–2000. The parameters selected as predictors are: initial storm intensity, intensity changes during past 12 hours, storm motion speed, initial storm latitude position, vertical wind shear averaged along the storm track, vorticity at 850 hPa, Divergence at 200 hPa and sea surface temperature (SST). When the model is tested with the dependent samples of 62 cyclones, the forecast skill of the model for forecasts up to 72 hours is found to be reasonably good. The average absolute errors (AAE) are less than 10 knots for forecasts up to 36 hours and maximum forecast error of order 14 knots occurs at 60 hours and 72 hours. When the model is tested with the independent samples of 15 cyclones (during 2000 to 2007), the AAE is found to be less than 13 knots (ranging from 5.1 to 12.5 knots) for forecast up to 72 hours. The model is found to be superior to the empirical model proposed by Roy Bhowmik et al (2007) for the Bay of Bengal.  相似文献   

20.
The characteristic features of the marine boundary layer (MBL) over the Bay of Bengal during the southwest monsoon and the factors influencing it are investigated. The Bay of Bengal and Monsoon Experiment (BOBMEX) carried out during July–August 1999 is the first observational experiment under the Indian Climate Research Programme (ICRP). A very high-resolution data in the vertical was obtained during this experiment, which was used to study the MBL characteristics off the east coast of India in the north and south Bay of Bengal. Spells of active and suppressed convection over the Bay were observed, of which, three representative convective episodes were considered for the study. For this purpose a one-dimensional multi-level PBL model with a TKE-ε closure scheme was used. The soundings, viz., the vertical profiles of temperature, humidity, zonal and meridional component of wind, obtained onboard ORV Sagar Kanya and from coastal stations along the east coast are used for the study. The temporal evolution of turbulent kinetic energy, marine boundary layer height (MBLH), sensible and latent heat fluxes and drag coefficient of momentum are simulated for different epochs of monsoon and monsoon depressions during BOBMEX-99.The model also generates the vertical profiles of potential temperature, specific humidity, zonal and meridional wind. These simulated values compared reasonably well with the observations available from BOBMEX.  相似文献   

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