Assimilation of INSAT data in the simulation of the recent tropical Cyclone Aila

The atmospheric motion vectors (AMVs) from the operational geostationary Indian National Satellite Kalpana-1 are now regularly available at the Space Applications Centre, Indian Space Research Organization (ISRO). ISRO also provides a large number of near real-time surface observations, such as winds, temperature, relative humidity, pressure, etc., from automatic weather stations (AWS) at various locations in India under the Prediction of Regional Weather with Observational Meso-Network and Atmospheric Modeling (PRWONAM) project. A series of experimental forecasts are attempted here to evaluate the impact of AMVs derived from Kalpana-1 and AWS surface observations for the track and intensity prediction of the recent Bay of Bengal Cyclone Aila using the Advanced Research Weather Research Forecast model (ARW-WRF). The insertion of AMVs using Cressman objective analysis techniques has had some positive, though not significant, impact in the initial position errors and track forecasts when compared with the corresponding control experiments. However, no significant improvement is noticed in the simulations of cyclone intensities, that is, minimum sea-level pressure and maximum surface winds forecasts when satellite winds are used for assimilation. Moreover, the model performance is also evaluated by repeating the same sets of experiments using AMV, AWS surface observations and upper-air radiosonde data together for assimilation. The simulation of initial position errors, track and intensity forecasts from all experiments are comparable. Though these results are preliminary with respect to the Kalpana-1 AMV, the present study can provide some insight for WRF model users over the Indian Ocean region.     

Inter-comparison of INSAT-3D atmospheric motion vectors height with cloud-base height from a Ceilometer

ABSTRACT

The atmospheric motion vectors (AMV) are derived by tracking cloud and moisture features in the subsequent images of geostationary as well as polar satellites. The heights of the AMVs are nothing but the height of cloud tracers used during the retrieval process for tracking. This height is derived using different complex techniques. In this study, a detailed comparison has been performed with the use of ground-based cloud-base height (CBH) measurements from ceilometer CL31, installed at Ahmedabad (23.03°N, 72.54°E), India and height assigned to AMVs which are retrieved from INSAT-3D satellite images. Six months CBH measurement over Ahmedabad from ceilometer CL31 has been used to inter-compare the co-located AMV heights. Although both ground-based and satellite-based techniques have their own limitations, however, it is found from this study that the ceilometer is an excellent instrument to precisely detect low- and mid-level clouds and height-assignments technique of AMVs retrieved from INSAT-3D satellite provides all high-, mid- and low-levels cloud information over this region. As an example, it is found that AMVs height of INSAT-3D is about 867.92, 750.00 and 465.09 hPa on 26 May 2014, 7 July 2014 and 29 October 2014, respectively, which matches very closely with ceilometer-measured CBH of about 873.15, 769.16 and 507.44 hPa, respectively. However, in case multi-level clouds present on rainy days, CBH measurements from ceilometer are differing from INSAT-3D AMV cloud tracer heights.     

Comparison of Oceansat-2 scatterometer- to buoy-recorded winds and spatial distribution over the Arabian Sea during the monsoon period

For this wind resource assessment (WRA) study, wind speed and direction are the fundamental inputs. Also, these studies are data driven and require large historical wind speed data sets available on the site. This work explores the application of space-based scatterometer winds for assimilation into WRA studies towards the development of offshore wind energy. This article focuses on estimating the performance of Oceansat-2 scatterometer (OSCAT)-derived wind vector using in situ data from buoys at different locations in the Arabian Sea. A comparative study between three methods for estimating the equivalent neutral winds (ENW) for buoys is carried out. OSCAT winds were closest to ENW estimated by the Liu–Katsaros–Businger (LKB) method. The spatial and temporal windows for comparison were 0.5° and ±60 minutes, respectively. The monsoon months (June–September) of 2011 were selected for study. The root mean square deviation for wind speed is less than 2.5 m s^?1 and wind direction is less than 20°, and a small positive bias is observed in the OSCAT wind values. From the analysis, the OSCAT wind values are consistent with in situ-observed values. Furthermore, wind atlas maps were developed with OSCAT winds, representing the spatial distribution of winds at a height of 10 m over the Arabian Sea.     

红外云图晴空区导风风矢高度指定方案与检验

在静止卫星红外云图上,用实际大气廓线的响应权重取代标准大气的响应权重,对利用时间序列差分法反演出的晴空区风矢,进行高度重新指定。然后对台风个例高度重新指定前、后的晴空区风矢进行了误差统计检验和分析,最后利用三维中尺度同化系统WRF\|3DVAR进行了敏感性试验。结果表明:利用实际大气廓线的权重响应进行高度指定优于标准热带大气廓线,晴空风矢高度主要分布在600~900 hPa之间;经高度重新指定后各高度层上的晴空区风矢的均方根差和标准差明显减小,风速偏差集中。同化经过高度重新指定的晴空区风矢能够减小台风路径预报误差。因此,对晴空区风矢进行高度重新指定能够改善晴空风矢产品的质量。     

Cloud fraction retrieval using data from Indian geostationary satellites and validation

ABSTRACT

Cloud fraction (CF) is known as the dominant modulator of Earth’s radiation budget, thus regarded as Essential Climate Variable. CF is retrieved using Indian geostationary satellites Kalpana-1 and Indian National Satellite System (INSAT-3D) by calculating the fraction of area covered by the clouds in a given pixel divided by the total area of the pixel. The technique uses multi-channel thresholding for three channels in Kalpana-1, that is, thermal, visible, and water vapour, and four channels in INSAT-3D with mid-infrared channel in addition to the three mentioned for Kalpana-1. A 2-year record of CF at 30-min intervals was generated for the Indian region using the Kalpana-1 and INSAT-3D data. The retrieved CF data were compared against Moderate Resolution Imaging Spectroradiometer (MODIS) CF product in the near vicinity of simultaneous data availability (i.e., within ±15 min interval). This product agrees with MODIS (correlation coefficient 80%) with a root mean square error (RMSE) of 0.30, in spite of ±15 min of time difference between both the satellites. In addition, ground-based Total Sky Imager (TSI-440) retrieved data over Pune is used to validate the satellite retrieved CF over the same region. The probability of detection between retrieved CF and ground-based data is relatively more for range of CF between 0.00 and 0.25, that is, 90% and more than 20% for CF greater than 0.50. In view of the close agreement between retrieved CF from Kalpana-1 and INSAT-3D with MODIS and TSI-440, this product is operational and is being made available through National Information System for Climate and Environment Studies portal for use in better understanding of climate.     

Assessing solar energy potential using diurnal remote-sensing observations from Kalpana-1 VHRR and validation over the Indian landmass

A spectrally integrated clear-sky and three-layer cloudy-sky models were developed to determine atmospheric transmittances and instantaneous surface insolation. Half-hourly observations at 8 km spatial resolution in optical and thermal infrared bands from an Indian geostationary satellite (Kalpana-1) Very High Resolution Radiometer (VHRR) sensor were used to provide inputs to these models in addition to global 8 day aerosol optical depth and columnar ozone. Sensitivity analysis of the clear-sky model showed a higher influence of aerosol on global insolation, diffuse insolation, and its fraction as compared with water vapour and ozone. The root mean square error (RMSE) of insolation estimates of the daily integral was found to be 2.05 MJ m^?2 (～11.2% of measured mean) with a high correlation coefficient (r?=?0.93) when compared with in situ measurements during 1 August 2008 to 31 March 2010 over six locations in India. The errors were found to reduce to 7.5% over 3 to 5 day averages. The comparison of annual estimates and equivalent reanalysis fields showed a mean difference of the order of ±1.7 MJ m^?2 over the majority of the Indian landmass.     

A geometrical optics model based on the non-Gaussian probability density distribution of sea surface slopes for wind speed retrieval at low incidence angles

In this study, a large amount of data from precipitation radar (PR) and National Data Buoy Center (NDBC) buoys are collocated for the development and validation of a Geometrical Optics Model, in order to retrieve wind speed at small incidence angles. The omni-directional model is developed based on the combination of the quasi-specular scattering theory and non-Gaussian probability density distribution of ocean surface slope, and can be applied at incidence angles as high as 15°. There are four parameters included in the proposed model: the effective Fresnel reflection coefficient, the mean square slope, and the two coefficients associated with the kurtosis of the sea surface slope distribution. Using one half of the collocated data, the dependence of the four parameters on the in situ wind speed is acquired. The results show that the effective Fresnel reflection coefficient has a decrease relative to that obtained in previous studies. We combine the proposed model with the maximum-likelihood estimation (MLE) technique to retrieve the ocean surface wind speed at the 10 m height. The retrieved wind speeds are then validated against those measured by the NDBC buoys. The comparison shows that the root mean square error (RMSE) and bias between the model retrievals and buoy observations are 1.54 m s^–1 and 0.1 m s^–1, respectively, revealing high agreements in the wind speed estimations. The results of this study indicate that the proposed model and the PR measurements at low incidence angles can provide reasonably accurate estimates of the surface wind speeds within the range of 0–20 m s^–1.     

船测资料与智利外海QuikSCAT风场比较分析

利用大洋渔船在智利外海观测的风场资料与QuikSCAT 10 m散射风原始轨道资料L3产品进行了比较分析。两种资料的偏差统计特征显示:①智利外海船测风速总体上高于QuikSCAT风速,船测风向总体上偏于QuikSCAT风向的左侧;②智利外海船测风场资料与QuikSCAT散射风的风速偏差集中分布在-1~1 m/s之间;风向偏差主要集中分布于-60°~-10°之间,其次为10°~60° 和-10°~10°段;③智利外海白天的风速偏差特征值均小于夜晚,昼、夜风向平均偏差数值差别很大,但昼、夜风向平均绝对偏差、均方根偏差数值相差不大;④2008年智利外海船测风场资料与QuikSCAT散射风的偏差大于其他年份的整体平均值,在高风速段风速偏差尤为明显。     

Inter-comparison of wind profiles in the tropical boundary layer remotely sensed from GPS radiosonde and Doppler wind lidar

Winds play a very important role in the dynamics of the lower atmosphere, and there is a need to obtain vertical distribution of winds at high spatio-temporal resolution for various observational and modelling applications. Profiles of wind speed and direction obtained at two tropical Indian stations using a Doppler wind lidar during the Indian southwest monsoon season were inter-compared with those obtained simultaneously from GPS upper-air sounding (radiosonde). Mean wind speeds at Mahbubnagar (16.73° N, 77.98° E, 445 m above mean sea level) compare well in magnitude for the entire height range from 100 m to 2000 m. The mean difference in wind speed between the two techniques ranged from ?0.81 m s^?1 to +0.41 m s^?1, and the standard deviation of wind speed differences ranged between 1.03 m s^?1 and 1.95 m s^?1. Wind direction by both techniques compared well up to about 1200 m height and then deviated slightly from each other at heights above, with a standard deviation in difference of 19°–48°. At Pune (18^○32′ N, 73^○51′ E, 559 m above mean sea level), wind speed by both techniques matched well throughout the altitude range, but with a constant difference of about 1 m s^?1. The root mean square deviation in wind speed ranged from 1.0 to 1.6 m s^?1 and that in wind direction from 20° to 45°. The bias and spread in both wind speed and direction for the two stations were computed and are discussed. The study shows that the inter-comparison of wind profiles obtained by the two independent techniques is very good under conditions of low wind speeds, and they show larger deviation when wind speeds are large, probably due the drift of the radiosonde balloon away from the location.     

Use of an optimum interpolation method to construct a high-resolution global ocean surface vector wind dataset from active scatterometers and passive radiometers

This study presents a new 0.25° gridded 6-hourly global ocean surface wind vector dataset from 2000 to 2015 produced by blending satellite wind retrievals from five active scatterometers (QuikSCAT, ASCAT-A, ASCAT-B, OSCAT, and HY-2A), nine passive radiometers (four SSM/I sensors, two SSMIS sensors, TMI, AMSR-E, and AMSR2) and one polarimetric radiometer (WindSat) with reanalysis from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) employing an optimum interpolation method (OIM). The accuracy of this wind product is determined through various comparisons with buoy measurements, NCEP/NCAR reanalysis and the cross-calibrated multi-platform (CCMP) winds. The comparisons indicate that OIM winds agree well with buoys, showing a root-mean-squared difference of 1.32 m s^?1 for wind speed and 24.73° for wind direction over 0–30 m s^?1 wind speed range. And the quality of OIM winds is improved significantly relative to NCEP/NCAR reanalysis and can be comparable with CCMP winds. Furthermore, OIM winds can reveal abundant small-scale features that are not visible in reanalysis data. In addition, the wind speed and direction retrievals of most satellites are proved to play an important role in generating the high-quality product, but the procedure for including HY-2A winds and WindSat wind directions should be further explored.     

Estimating clear-sky land surface longwave upwelling radiation from MODIS data using a hybrid method

Surface longwave upwelling radiation (LWUP) is one of the four components for calculating the earth’s surface radiation budget. Under the general framework of the hybrid method, we developed linear models for estimating the global 1-km instantaneous clear-sky LWUP from the top-of-atmosphere (TOA) radiance of the Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared channels 29, 31, and 32. Extensive radiative transfer simulations were conducted to produce a large number of representative samples, from which the linear model was derived. The derived hybrid model was first evaluated using ground measurements collected at 15 sites from two networks (SURFRAD and ASRCOP). According to the validation results, the average bias and root mean square error (RMSE) of ?0.55 and 15.76 W m^?2, respectively, were obtained by averaging the mean bias and RMSE for the two networks. Compared to a hybrid method developed by a previous study and the temperature-emissivity method, our linear model had a superior performance.     

The impact of assimilation of satellite derived wind observations for the prediction of a monsoon depression over India using a mesoscale model

The Penn State/NCAR mesoscale model (MM5) has been used in this study to ingest and assimilate the INSAT‐CMV (Indian National Satellite System‐Cloud Motion Vector) wind observations using analysis nudging (four‐dimensional data assimilation, FDDA) to improve the prediction of a monsoon depression which occurred over the Bay of Bengal, India during 28 July 2005 to 31 July 2005. To determine the impact of assimilation of INSAT‐CMV winds on the prediction of a monsoon depression, three sets of numerical experiments (NOFDDA, FDDA and FDDA CMV) were designed. While the FDDA CMV run assimilated satellite derived winds only, the FDDA run assimilated both satellite and conventional observations. The NOFDDA run used neither satellite nor conventional observations. The results of the study indicate that the simulated sea level pressure field from the FDDA run is more consistent with the sea level pressure field from NCEP‐FNL compared to the FDDA CMV and NOFDDA runs. The highest correlation and lowest rms error of the sea level pressure field are associated with the FDDA run, and this provides a quantitative verification of the improvement due to the assimilation of satellite derived winds and the conventional upper air observations for the prediction of monsoon depression. All the three model simulated winds are in good agreement with the analysis winds at 850 hPa, 500 hPa and 200 hPa levels. The simulated structure of the spatial precipitation pattern for the assimilation experiments (FDDA and FDDA CMV) are closer to the TRMM observations with more rainfall simulated over the east coast regions in the assimilation experiments. The rms errors of the wind speed for the FDDA run show lower values at 500 hPa for all the three model runs, with a reduction in all three levels of up to 0.8–1.4 m s^?1 for the FDDA run and 0.5–1.9 m s^?1 for the FDDA CMV run with respect to the NOFDDA run. The statistical significance of the sea level pressure and the precipitation differences between the FDDA and the NOFDDA as well as the differences between the FDDA CMV and the NOFDDA have been calculated using the two‐tailed Student's t‐test and were found to be statistically significant. The influence of varying the nudging coefficients in the FDDA experiment has been studied.     

Preliminary validation of ocean surface vector winds estimated from China’s HY-2A scatterometer

The microwave scatterometer on the Haiyang-2A (HY-2A) satellite is designed to provide global sea surface wind field data. The accuracy of HY-2A scatterometer wind retrievals is determined through various comparisons with moored buoys and the European Centre for Medium Range Weather Forecasting (ECMWF) reanalysis data. These comparisons were made in wide regions, including open sea and coastal areas, over a four-month period from January to March 2012 and August 2012. The retrieved wind speed results agree well with in situ observations and model data with respective biases ?0.19 m s^?1 and 0.01 m s^?1 and root mean square error 2.02 m s^?1 and 1.81 m s^?1. However, the wind direction errors are a little higher. The overall bias and root mean square deviation of wind direction are ?2.24°, 1.74°, and 40.28°, 38.56°, respectively. The wind speed and direction residuals are higher in low- and high-wind speed ranges. In addition, the wind speed and direction are relatively more accurate for open sea than those in coastal regions.     

Multisatellite observations and numerical simulation of an along‐coast cumulus cloud line induced by sea‐breeze circulation

A coastal cumulus cloud‐line formation along the east coast of the USA was observed on a National Oceanic and Atmospheric Administration (NOAA) Polar Orbiting Environmental Satellite (POES) Advanced Very High Resolution Radiometer (AVHRR) satellite image from 17 August 2001. The cloud line starts to form at about 16:00 UTC (local 12:00 noon) and follows the coastline from Florida to North Carolina. The length and width of the cloud line are about 850 km and 8.5 km, respectively. A 15‐min interval sequence of NOAA Geostationary Operational Environmental Satellite (GOES) images shows that the cloud line maintains the shape of the coastline and penetrates inland for more than 20 km over the next 6‐h timespan. Model simulation with actual atmospheric conditions as inputs shows that the cloud line is formed near the land–sea surface temperature (SST) gradient. The synoptic flow at all model levels is in the offshore direction prior to 16:00 UTC whereas low‐level winds (below 980 hPa) reverse direction to blow inland after 16:00 UTC. This reversal is due to the fact that local diurnal heating over the land takes place on shorter time‐scales than over the ocean. The vertical wind at these levels becomes stronger as the land–SST increases during the summer afternoon, and the leading edge of the head of the inland wind ascends from 920 hPa to about 850 hPa in the 3 h after 16:00 UTC. Model simulation and satellite observations show that the cloud line becomes very weak after 21:00 UTC when the diurnal heating decreases.     

Comparison of total ozone column observations from space-borne Ozone Monitoring Instrument with ground-based Dobson Ozone Spectrophotometer measurements at an urban location in Indo-Gangetic Basin

This article presents a comparison analysis of OMIT (Ozone Monitoring Instrument retrieved overpass total ozone column (TOC)), and DOST (Dobson Ozone Spectrophotometer observed TOC) over Delhi during a period from October 2004 to June 2011. Megacity Delhi, located in Indo-Gangetic Basin, is an important site for comparison of ground-based and satellite retrieved TOCs due to significant anthropogenic emissions of ozone precursors, large shift in seasons, and large-scale crop residue burning in the region. DOST and OMIT data show an overall bias of 3.07% and significant correlation with coefficient of determination R² = 0.73. Large seasonal fluctuations in the biases and correlations have been observed ranging from 2.46% (winter) to 3.82% (spring), and R² = 0.84 (winter) to R² = 0.09 (summer), respectively. The large biases are attributed to changes in temperature, cloud cover, pollutants emissions from urban area, and crop-residue burning events. We also find notable variations in correlations between the datasets due to the varying burden of absorbing aerosols from open field crop-residue burning. The R² has changed from 0.67 (for aerosol optical depth, AOD 1.5–3.5) to 0.77 (for AOD 0–0.99). The dependence of the bias on solar zenith angle, cloud fraction, and satellite distance is also discussed. A simple linear regression analysis is applied to check the linkage between DOST and OMIT. The influence of atmospheric air temperature and relative humidity on OMIT at different pressure levels between 1000 and 20 hPa has been discussed.     

Radiative effects of elevated aerosol layer in Central Himalayas

Systematic observations of light detection and ranging (LIDAR) to detect elevated aerosol layer were carried out at Manora Peak (29.4° N, 79.5° E, ～1960 m a.s.l), Nainital, in the Central Himalayas during January–May 2008. In spite of being a remote, high-altitude site, an elevated aerosol layer is observed quite frequently in the altitude range of 2460–4460 m a.s.l with a width of ～2 km during the observation period. We compare these profiles with the vertical profiles observed over Gadanki (13.5° N, 79.2° E, ～370 m a.s.l), a tropical station, where no such elevated aerosol layer was found. Further, there is a steady increase in aerosol optical depth (AOD) from January (winter) to May (summer) from 0.043 to 0.742, respectively, at Manora Peak, indicating aerosol loading in the atmosphere. Our observations show north-westerly winds indicating the convective lifting of aerosols from far-off regions followed by horizontal long-range transport. The presence of strongly absorbing and scattering aerosols in the elevated layer resulted in a relatively large diurnal mean aerosol surface radiative forcing efficiency (forcing per unit optical depth) of about??65 and??63 W m^?2 and the corresponding mean reduction in the observed net solar flux at the surface (cooling effect) is as high as??22 and??30 W m^?2. The reduction of radiation will heat the lower atmosphere by redistributing the radiation with heating rate of 1.13 and 1.31 K day^?1 for April and May 2008, respectively, in the lower atmosphere.     

Comparison of wind data from QuikSCAT and buoys in the Indian Ocean

The performance of QuikSCAT‐derived wind vectors is evaluated using in‐situ data from moored buoys over the Indian Ocean. The results show that the mean differences for wind speed and wind direction are 0.37 ms^?1 and 5.8°, root mean square deviations are 1.57 ms^?1 and 44.1° and corresponding coefficients of correlation are 0.87 and 0.75, respectively. The matching between in‐situ and satellite estimates seems to be better in the North Indian Ocean than in the Equatorial Indian Ocean. The effects of sea surface temperature and air–sea temperature difference on wind residuals were also investigated. In general, QuikSCAT is found to overestimate the winds. It is speculated that low wind speed during rain‐free conditions and high wind speed, normally associated with rain, may be the reason for the less accurate estimation of the wind vector from QuikSCAT over the Indian Ocean.     

Estimated time of arrival and debiasing the time saving bias

The time saving bias predicts that the time saved when increasing speed from a high speed is overestimated, and underestimated when increasing speed from a slow speed. In a questionnaire, time saving judgements were investigated when information of estimated time to arrival was provided. In an active driving task, an alternative meter indicating the inverted speed was used to debias judgements. The simulated task was to first drive a distance at a given speed, and then drive the same distance again at the speed the driver judged was required to gain exactly 3 min in travel time compared with the first drive. A control group performed the same task with a speedometer and saved less than the targeted 3 min when increasing speed from a high speed, and more than 3 min when increasing from a low speed. Participants in the alternative meter condition were closer to the target. The two studies corroborate a time saving bias and show that biased intuitive judgements can be debiased by displaying the inverted speed.     

Development of polarization ratio model for sea surface wind field retrieval from TerraSAR-X HH polarization data

In this article, the polarization ratio (PR) of TerraSAR-X (TS-X) vertical–vertical (VV) and horizontal–horizontal (HH) polarization data acquired over the ocean is investigated. Similar to the PR of C-band synthetic aperture radar (SAR), the PR of X-band SAR data also shows significant dependence on incidence angle. The normalized radar cross-section (NRCS) in VV polarization data is generally larger than that in HH polarization for incidence angles above 23°. Based on the analysis, two PR models proposed for C-band SAR were retuned using TS-X dual-polarization data. A new PR model, called X-PR hereafter, is proposed as well to convert the NRCS of TS-X in HH polarization to that in VV polarization. By using the developed geophysical model functions of XMOD1 and XMOD2 and the tuned PR models, the sea surface field is retrieved from the TS-X data in HH polarization. The comparisons with in situ buoy measurements show that the combination of XMOD2 and X-PR models yields a good retrieval with a root mean square error (RMSE) of 2.03 m s^–1 and scatter index (SI) of 22.4%. A further comparison with a high-resolution analysis wind model in the North Sea is also presented, which shows better agreement with RMSE of 1.76 m s^–1 and SI of 20.3%. We also find that the difference between the fitting of the X-PR model and the PR derived from TS-X dual-polarization data is close to a constant. By adding the constant to the X-PR model, the accuracy of HH polarization sea surface wind speed is further improved with the bias reduced by 0.3 m s^–1. A case acquired at the offshore wind farm in the East China Sea further demonstrates that the improvement tends to be more effective for incidence angles above 40°.     

A study on the use of computerized concept mapping to assist ESL learners’ writing

This study aims to examine the effect of using computerized concept maps during the pre-writing phase on learners’ writing performance. The research questions were: (1) What are the impacts of different computerized concept mapping treatments (no-mapping, individual-mapping, and cooperative-mapping) on writing performance for learners of different writing proficiencies (high-level, middle-level, and low-level)? (2) Does the quality of the concept maps constructed cooperatively exceed the quality of the concept maps constructed individually? (3) Does the map quality correlate to the learner’s writing performance?