Evaluation of MODIS water vapour products over China using radiosonde data

Radiosonde data collected from 83 stations in China from January to December 2012 were used to evaluate Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared (NIR) and thermal infrared (IR) total precipitable water vapour (PWV) products. The results indicate that MODIS NIR PWV products shows better agreement with radiosonde data than with IR PWV products, with the correlation coefficients up to 0.95. The root mean square errors (RMSEs) of NIR PWV range from 2 to 8 mm with different stations, which shows significant regional differences over China. The mean RMSE is about 5.03 mm (~35%) with a positive deviation of 2.56 mm (~18%), indicating the occurrence of a slight overestimation. Moreover, MODIS IR PWV during night-time has a better agreement with radiosonde PWV than that during daytime. The mean RMSE of IR PWV during daytime was ~6.02 mm (~42%), with a positive deviation of 1.54 mm (~11%). The mean RMSE of IR PWV during night-time was ~5.81 mm (~40%), with a negative deviation of approximately ?0.04 mm (~0.25%). Both the NIR and IR PWV products during daytime tend to be higher than radiosonde PWV.     

Measurement of atmospheric water vapour content over a tropical location by dual frequency microwave radiometry

Atmospheric water vapour was measured over a tropical location, Calcutta, by deploying dual frequency microwave radiometers operating at 22.235 and 31.4 GHz. Simultaneous measurements of brightness temperature and hence attenuation in the presence of thin cloud were made for the purpose. An algorithm was developed to exclude the effect of non-precipitating liquid water during the measurement of water vapour. The experimental results are supported by the corresponding radiosonde data analysis. Dual frequency radiometric measurements are shown to improve the rms accuracy, over the single frequency inversion technique, for the measurement of water vapour.     

Spatio-temporal analysis of precipitable water vapour over northwest china utilizing MERSI/FY-3A products

Northwest China is considered as the arid and semi-arid temperate continental climate, where the precipitation is closely related to precipitable water vapour (PWV) content. In this paper, the Medium-Resolution Spectral Imager (MERSI) water vapour products were first used to study the spatial and temporal characteristics of water vapour over Northwest China, which were developed by the National Satellite Meteorological Center of China from the Chinese second-generation polar orbit Meteorological Satellite Fengyun 3A (FY-3A). In order to utilize the MERSI water vapour products, the MERSI 5 min water vapour product is compared respectively with global positioning system (GPS), Aerosol Robotic Network (AERONET) and Radiosonde water vapour data in situ datasets. The results show that the water vapour values of the MERSI product are a slightly lower than referenced data, and the accuracy of MERSI product compared with GPS water vapour is the most agreeable, with a mean absolute percentage error (MAPE) of 22.83%. The PWV content displays a typical spatial distribution pattern in Northwest China that it is the highest in the southeast, the second for the northwest and the lowest in the south-centre. The water vapour content over each province in a descending order is Shaanxi, Ningxia, west of Inner Mongolia, Xinjiang, Gansu and Qinghai. The seasonal variation of water vapour content over Northwest China appears to be lowest in winter, followed by spring, then for autumn, and highest in summer. The PWV content of each province in Northwest China shows the periodic inner-annual variation, that is, the PWV content is lowest in January, and gradually increases with time till it peaks in July, and then decreases monthly afterwards, which agrees with the quadratic polynomial model by months. The standard deviation of the water vapour content in summer is 0.533–1.027 mm, while that in winter is 0.262–0.527 mm.     

Satellite remote sensing of atmospheric water vapour

Abstract

The Advanced Very High Resolution Radiometer (AVHRR-2) has two channels in the 10-13/mi window region. These channels are used for remote sensing of the sea surface temperature corrected for atmospheric absorption. The brightness temperature difference between the channels can be directly related to the atmospheric absorption due to water vapour. The problem of water-vapour retrieval from satellite data is examined in detail. The best evaluation of the water-vapour content is obtained from the spectrometric data of the Infrared Interferometer Spectrometer (IRIS), with an error of about + 3kg/m². It is, however, feasible to obtain the water-vapour content from AVHRR data with an algorithm derived from radiative transfer model simulations. The retrieved water vapour has an error of ±5kg/m² when compared with ship data. It is possible to use the remotely sensed water vapour for the inference of the boundary-layer structure. The information is, however, limited for water vapour contained near the surface.     

Integrated water vapour content by scanning radiometry

Abstract

Radiometry at the water vapour line with a scanning antenna beam from horizon to horizon through the zenith, in the vertical plane, was shown to be useful in estimating the integrated water vapour content from the zenith angle variation of radiometric temperature. The beam scanning may be made at a rate slower than the radiometer time constant using a Dicke type radiometer. Alternatively, a fast scanning beam may be used in a total power radiometer with a synchronous detection of the radiometer output at the scanning frequency to obtain a space domain Dicke switching for the measurements. A simultaneous scanning beam with 22.235 and 31.4GHz radiometers would allow us to separate the liquid water, if any, from the integrated water vapour content. Theoretical studies of the scanning beam radiometer performance in the estimation of integrated water vapour content from radiosonde data is presented and some typical results of Dicke type scanning beam radiometers at 22.235 and 31.4 GHz are also presented in this paper.     

Retrieval and analysis of precipitable water vapour based on GNSS,AIRS, and reanalysis models over Nigeria

Precipitable water vapour (PWV) retrieved from ground-based Global Navigation Satellite System (GNSS) stations over Nigeria from 2013 to 2014 is compared with PWV from a satellite remote-sensing technique (Atmospheric Infrared Sounder [AIRS]) and a global reanalysis model (ERA-Interim) over Nigeria. The PWV for AIRS and ERA-Interim was obtained from the respective data providers. PWV estimates from the different techniques were grouped into daily estimates and were matched and re-grouped into monthly and seasonal averages. The performance of the PWV techniques was evaluated using recommended indices by the World Meteorological Organization. All datasets gave a reasonable estimate of PWV when compared against GNSS at daily, monthly, and seasonal scales, the agreement between the various techniques was better at monthly and seasonal scales. In terms of bias, precision, accuracy, fitness, and reliability of measurement, ERA-Interim outperformed the other technique and could possibly be a complementary data source to GNSS PWV, although as a reanalysis, it cannot be used for meteorology. The AIRS night-time (or descending) retrieval was ranked next to the ERA-Interim; AIRS daytime (or ascending) retrieval agreed less with GNSS PWV when compared with ERA Interim and night-time AIRS. These results indicate that GNSS PWV as observed over the study area represents a remarkable dataset for further evaluation studies and serves as a useful source of humidity information to improve the water cycle in numerical weather models for varying applications in the region.     

Ground-based single-frequency microwave radiometric measurement of water vapour

The integrated water vapour content of the atmosphere is measured by a ground-based radiometer at 22.234 GHz at the Instituto Nacional de Pesquisas Espaciais (INPE), Brazil. The data set has been partitioned into two sets: one for no cloud and the other for cloudy conditions. The attenuation (dB) under the no cloud condition was always found to vary within 1.0–1.5 dB, except at around 1400 hrs (local time) through 1800 hrs (local time), and it reached a value of more than 1.5 dB with a maximum at 1700. This is in conformity with the theoretically calculated values of water vapour density over the same location. An effort has been made to get the regression relation between the measured and calculated water vapour content, for which the RMS error was found to be 0.49 kg m^?2.     

Validation of satellite and model aerosol optical depth and precipitable water vapour observations with AERONET data over Pune,India

ABSTRACT

The present work concerns with a detailed study of the validation of the Moderate Resolution Imaging Spectroradiometer (MODIS) and model products, and investigates the spatial and temporal variations in the correlation coefficient of the validation results obtained from the analysis of Aerosol Robotic Network (AERONET) sun–sky radiometer data archived at Pune during 2005–2015. Combining the confidence intervals and prediction levels, the ground-based AERONET aerosol optical depth (AOD) at 550 nm and precipitable water vapour (PWV) have been used to validate the MODIS, model AOD (550 nm), and PWV (cm) observations. The correlation coefficients (r) of AOD for the linear regression fits are 0.73, 0.75, and 0.79, and of PWV are 0.88, 0.89, and 0.97 for Terra, Aqua, and model simulations, respectively. Month-to-month/seasonal variation of AOD (550 nm) and PWV observations of satellite and model observations are also compared with AERONET observations. Additionally, various statistical metrics, including the root mean square error, mean absolute error, and root mean bias values were calculated using AERONET, satellite, and model simulations data. Furthermore, a frequency distribution of AOD (550 nm) and PWV observations are studied from AERONET, satellite, and model data. The study emphasizes that the globally distributed AERONET observations help to improve the satellite retrievals and model predictions to enrich our knowledge of aerosols and their impact on climate, the hydrological cycle, and air quality.     

流媒体在Ad Hoc网络中的多路径传输

提出了Ad Hoc 网络上多路径传输流媒体的框架,在Ad Hoc 网络中多路径同时传输流媒体以提高吞吐量并减小传输延迟。在发送端,采用部分解压缩算法对图像进行自适应分割,并通过多径源路由(MSR)协议根据负载均衡算法选择多条路由传输被拆分的数据;在接收端对数据进行缓存、图像重建恢复、JPEG解压缩及实时显示。实验表明,流媒体多路径传输实现了较好的图像传输质量和实时性。     

In place merging of satellite based atmospheric water vapour measurements

Atmospheric water vapour plays a key role in the climatology of the Earth. It has traditionally been measured using radiosondes for reasons of instrumental simplicity but these offer limited opportunities for spatial and continuous measurements of dynamic water vapour changes over large areas of the Earth's atmosphere. Efforts have recently turned to using satellite remote sensing instruments with different spectral and spatial capabilities to derive measurements of total water vapour content in atmospheric columns or simply precipitable water. The merging of remote sensing data with different spectral and spatial capabilities can result in large biases when independent measurements are not nested correctly to produce the final product. Consequently, such merging of data must take into account the intrinsic time dynamics of measured parameters. In this paper, the impact of atmospheric water vapour dynamics on the merging of satellite-based retrieval of precipitable water estimates is investigated by comparing independent measurements obtained at different spatial resolutions from the High Resolution Infrared Sounder (HIRS) and the Advanced Very High Resolution Radiometer (AVHRR). Correlations are used to infer optimal merging parameters depending on the observational conditions. The authors conclude that the merging technique reproduces HIRS-based retrievals in cloud-free and partly cloudy locations from AVHRR soundings.     

Studies of precipitable water vapour characteristics on a global scale

Atmospheric water vapour plays an important role in hydrological, global climate change, atmospheric, and meteorological processes. In this study, precipitable water vapour (PWV) data set for 2004–2017 was first estimated with an average accuracy of about 1.28 mm globally using the products provided by the International Global Navigation Satellite System Service and Global Geodetic Observation System Atmosphere and then the spatio-temporal trends of PWV variation were characterized. Periodic signals of the annual, semi-annual, and seasonal variations of PWV time series were detected based on the Lomb–Scargle periodogram and analysed by dividing the whole world into five geographical zones. From a global perspective, the average PWV has an increasing trend, which may be caused by global warming effects and anthropogenic activities. Analysis of different PWV amplitudes also shows that the main component of the PWV is annual amplitude except in low latitude zones. In addition, the PWV differences between weekends and weekdays for four seasons are also analysed globally, and the result indicates that the weekend effects caused by anthropogenic activity depend on season and region     

Surface temperature and water vapour retrieval from MODIS data

This paper gives operational algorithms for retrieving sea (SST), land surface temperature (LST) and total atmospheric water vapour content (W) using Moderate Resolution Imaging Spectroradiometer (MODIS) data. To this end, the MODTRAN 3.5 radiative transfer program was used to predict radiances for MODIS channels 31, 32, 2, 17, 18 and 19. To analyse atmospheric effects, a simulation with a set of radiosonde observations was used to cover the variability of surface temperature and water vapour concentration on a worldwide scale. These simulated data were split into two sets (DB1 and DB2), the first one (DB1) was used to fit the coefficients of the algorithms, while the second one (DB2) was used to test the fitted coefficients. The results show that the algorithms are capable of producing SST and LST with a standard deviation of 0.3 K and 0.7 K if the satellite data are error free. The LST product has been validated with in situ data from a field campaign carried out in the Mississippi (USA), the results show for the LST algorithm proposed a root mean square error lower than 0.5K. Regarding water vapour content, a ratio technique is proposed, which is capable of estimating W from the absorbing channels at 0.905, 0.936, and 0.94,µm, and the atmospheric window channel at 0.865,µm, with a standard deviation (in the comparison with radiosonde observations) of 0.4 g cm^?2.     

Inter annual,spatial, seasonal,and diurnal variability of precipitable water vapour over northeast India using GPS time series

We present multi-scale variability of GPS-derived column integrated precipitable water vapour (PWV) estimated over five continuous GPS sites of northeast India from 2004 to 2012. PWV is estimated from GPS-derived zenith total delay using observed surface pressure and temperature from collocated meteorological sensors as well as obtained by interpolating European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis project (ERA-Interim) global reanalysis dataset. PWV estimated using ERA-Interim-derived parameters compare well with the PWV estimated using observed meteorological parameters with bias of less than ± 0.1 mm and highest root mean square error of 0.56 mm. The average PWV for the study period is about 17 mm at Bomdila in the Eastern Himalayas, about 20 mm at Shillong in Shillong plateau, about 31 mm at Lumami in Arokan-Yoma Hill ranges, and about 43 mm at Guwahati and Tezpur in Assam valley. The high altitude sites show low annual PWV variability (around 49%) than the low altitude sites (around 63–67%). Seasonal PWV value coincides with the monsoon with maximum in summer and minimum in the winter. However, percentage seasonal PWV variability is found to be almost same (around 68%) for all the five sites. The Assam valley sites do not show a distinct diurnal cycle whereas the high altitude sites indicate a distinct diurnal cycle coinciding with the daily solar cycle. Insights in to GPS PWV variability and rainfall are presented for the study period.     

Radiometric Transfer: Example‐based Radiometric Linearization of Photographs

We present an example‐based approach for radiometrically linearizing photographs that takes as input a radiometrically linear exemplar image and a target regular uncalibrated image of the same scene, possibly from a different viewpoint and/or under different lighting. The output of our method is a radiometrically linearized version of the target image. Modeling the change in appearance of a small image patch seen from a different viewpoint and/or under different lighting as a linear 1D subspace, allows us to recast radiometric transfer in a form similar to classic radiometric calibration from exposure stacks. The resulting radiometric transfer method is lightweight and easy to implement. We demonstrate the accuracy and validity of our method on a variety of scenes.     

Retrieval of atmospheric water vapour using a ground-based single-channel microwave radiometer

Estimates of the amount of atmospheric water vapour derived from algorithms for a ground-based single-channel (21.0 GHz) microwave radiometer have been investigated. Ten datasets covering 44 days were used to derive the methods and two other sets (in total 32 days) were used to assess the quality of these. It is shown how the rms estimation error can be reduced by recognizing the rapid variations in sky brightness temperatures during periods when cloud liquid is present. Data was either discarded, guided by the variability, or an adaptive Kalman filter was applied with different parameter values for different degrees of variability. The resulting estimates were compared to the estimates obtained from a dual-channel algorithm (21.0 and 31.4 GHz), which were used as reference. The amount of water vapour was represented as the ‘wet delay’, the excess radio path length due to the atmospheric water vapour. Applying the Kalman filter to the single-frequency estimates reduced the wet delay rms error from 20 mm to 9 and 14 mm for the two datasets. Further reduction of the rms error was achieved by the removal of data in periods with high variability; discarding about 40% of the data led to rms errors of 5 and 7 mm for the two datasets.     

Radiometric measurements over bare and vegetated fields at 1.4-GHz and 5-GHz frequencies

Results of radiometric measurements over bare and vegetated fields with dual-polarized microwave radiometers at 1.4-GHz and 5-GHz frequencies are presented. The measured brightness temperatures over bare fields are shown to compare favorably with those calculated from radiative transfer theory with two constant parameters characterizing surface roughness effect. The presence of vegetation cover is found to reduce the sensitivity to soil moisture variation. This sensitivity reduction is generally more pronounced the denser the vegetation cover and the higher the frequency of observation. The effect of vegetation cover is also examined with respect to the measured polarization factor at both frequencies. With the exception of dry corn fields, the measured polarization factor over vegetated fields is found appreciably reduced compared to that over bare fields. A much larger reduction in this factor is found at 5 GHz than at 1.4 GHz.     

Sensitivity of near infrared total water vapour estimate to calibration errors

Analysis of satellite data to estimate the precipitable water (also called the columnar water vapour) amount often leads to systematic errors in deduced precipitable water (PW). The causes of systematic errors are likely to be instrumental calibration errors rather than variability of atmospheric parameters. We use the MODTRAN 4.0 radiative transfer code to model effects of various calibration errors on the Multi-spectral Thermal Imager (MTI) daytime total water vapour estimate. From the considered sources of calibration errors (spectral band centre error, spectral bandwidth error and radiometric calibration error) the radiometric calibration error has the largest influence on the accuracy of total water vapour estimate. When the radiometric calibration error between 1% and 5% is combined with the estimated spectral band centre error of 1 nm and the bandwidth error of 0.5 nm, the total systematic error of the columnar water vapour estimate is expected to be between 8% and 26%. The accuracy of the retrieved PW using the MTI imagery over the NASA Stennis site and Oklahoma DOE (Department of Energy) ARM (Atmospheric Radiation Measurement program) site is about 17%, well within the estimated range due to calibration errors. A similarity between the MTI and the MODIS (Moderate Resolution Imaging Spectral-Radiometer) bands used for water vapour estimate suggests that a similar error analysis may be valid for the MODIS sensor. However, the narrow band instruments (with bandwidth around 10 nm) are much more sensitive to the band centre calibration error.     

Study of aerosol optical depth,ozone, and precipitable water vapour content over Sinhagad,a high-altitude station in the Western Ghats

This article reports the results of a study related to variations in columnar aerosol optical depth (AOD), total column ozone (TCO), and precipitable water content (PWC) over a high-altitude station, Sinhagad (18° 21′ N, 73° 45′ E, 1450 m above mean sea level (AMSL)), employing a microprocessor-based total ozone portable spectrometer, MICROTOPS-II, comprising both a sun photometer and ozonometer, during November 2009–April 2010. The aerosol optical depth at 500 nm (AOD_{500 nm}) portrayed seasonal variation with higher values (0.39) in summer and lower values (0.15) in winter. The TCO and PWC also exhibited lower values in winter and started increasing by the pre-monsoon season. The Ångström wavelength exponent, α, was found to be high (1.79) during February, indicating the relative dominance of accumulation-mode particles. During the summer season, the lower value (0.94) of the Ångström wavelength exponent indicates the relative dominance of coarse-mode particles. The ground-based observations from MICROTOPS-II revealed good correlation with satellite observations of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI). The observed short-wave solar flux at the bottom of the atmosphere decreased due to aerosol extinction and was found to be 19 and 78 W m^–2 for the winter and pre-monsoon seasons, respectively. This implies that greater concentrations of accumulation-mode particles – which are due to local anthropogenic sources – affected the down-welling radiation than those from natural sources – which are due to long-range transport processes – over the experimental location.