Retrieval and validation of aerosol optical depth using GF-1 WFV cameras data

Conventional AOD (Aerosol Optical Depth) retrieval is restricted to the global and regional scale due to the limited spatial resolution of satellites. This does not allow for aerosol monitoring at the city level. The Chinese GF-1 Wide Field of View (WFV) sensors have sufficiently fine resolution as a data source for AOD retrieval with fine spatial resolution and a 4-day revisit time. In this study, principles similar to those in the Deep Blue (DB) and Dark Target (DT) algorithms were used to retrieve AOD at 100 m spatial resolution from GF-1 WFV images supported by Moderate Resolution Imaging Spectraradiometer (MODIS) surface reflectance (SR) products (MOD09A1). The derived GF-1 WFV AOD were compared with a combination of MOD04_3K DT AOD and MOD04_L2 DB AOD (MODIS AOD) to find that they yield reasonable Spearman correlations (R_S > 0.82) over Taiwan and Beijing. The derived GF-1 WFV AOD were also validated against Aerosol Robotic Network (AERONET) AOD; the Spearman correlation values were R_S = 0.911 in Beijing and R_S = 0.858 in Taiwan.     

Seasonal variability of atmospheric aerosol over the North Indian region during 2005–2009

The Indo-Gangetic basin (IGB) extends 2000 km in length along NW–SE and has 400 km width, in the north the basin is bounded by towering Himalaya. High aerosol optical depth (AOD) is observed over the IGB throughout the year. The Himalaya restricts the transport of aerosols across Tibet and China. We have used ground based Kanpur and Gandhi College Aerosol Robotic Network (AERONET) stations and Multiangle Imaging SpectroRadiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) Terra level-3 AOD products for the years 2005–2009 to study the variability of aerosol over the Indo-Gangetic (IG) plains. An increase in both satellite-derived as well as ground observed aerosol loading during 2005–2009 has been found over major cities located in the IG plains. The correlation coefficients between AERONET and MISR data are found to be 0.70, 0.36 0.82, in contrast the correlation coefficients between AERONET and MODIS 0.49, 0.68, and 0.43, respectively during summer, winter and monsoon seasons. The AOD estimation using MISR is found to be close to AERONET data during summer and monsoon seasons, in contrast MODIS estimation is better during winter season.     

Synergetic retrieval of terrestrial AOD from MODIS images of twin satellites Terra and Aqua

Aerosol optical depth (AOD) is one of the most important indicators of atmospheric pollution. It can be retrieved from satellite imagery using several established methods, such as the dark dense vegetation method and the deep blue algorithm. All of these methods require estimation of surface reflectance prior to retrieval, and are applicable to a certain pre-designated type of surface cover. Such limitations can be overcome by using a synergetic method of retrieval proposed in this study. This innovative method is based on the fact that the ratio K of surface reflectance at different angles/geometries is independent of wavelength as reported by Flowerdew and Haigh (1995). An atmospheric radiative transfer model was then established and resolved with the assistance of the ratio K obtained from two Moderate Resolution Imaging Spectroradiometer (MODIS) spectral bands acquired from the twin satellites of Terra and Aqua whose overpass is separated by three hours. This synergetic method of retrieval was tested with 20 pairs of MODIS images. The retrieved AOD was validated against the ground observed AOD at the Taihu station of the AErosol RObotic NETwork (AERONET). It is found that they are correlated with the observations at a coefficient of 0.828 at 0.47 μm and 0.921 at 0.66 μm wavelengths. The retrieved AOD has a mean relative error of 25.47% at 0.47 μm and 24.3% at 0.66 μm. Of the 20 samples, 15 and 17 fall within two standard error of the line based observed AOD data on the ground at the 0.47 μm and 0.66 μm, respectively. These results indicate that this synergetic method can be used to reliably retrieve AOD from the twin satellites MODIS images, namely Terra and Aqua. It is not necessary to determine surface reflectance first.     

Validation of space-born Moderate Resolution Imaging Spectroradiometer remote sensors aerosol products using application of ground-based Multi-wavelength Radiometer

The measurements of aerosol optical properties were carried out during April 2006 to March 2011 over Mohal (31.9°N, 77.12°E) in the northwestern Indian Himalaya, using the application of ground-based Multi-wavelength Radiometer (MWR) and space-born Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensors. The average (±standard deviation) values of aerosol optical depth (AOD) at 500 nm, Ångström exponent and turbidity coefficient during the entire measurement period were 0.25 ± 0.09, 1.15 ± 0.42 and 0.12 ± 0.06 respectively. About 86% AOD values retrieved from MODIS remote sensor were found within an uncertainty limit (Δτ_pλ = ±0.05 ± 0.15τ_pλ). In general, the MWR derived AOD values were higher than that of MODIS retrieval with absolute difference ∼0.02. During the entire period of measurement space-born MODIS remote sensor and ground-based MWR observation showed good correspondence with significant correlation coefficient ∼0.78 and root mean square difference ∼0.06. For daily observations the relative difference between these two estimates stood less than 9%. However, satellite-based and ground-based observation showed good correspondence, but further efforts still needed to eliminate systematic errors in the existing MODIS algorithm.     

Satellite derived aerosol optical depth climatology over Bangalore,India

Climatological aerosol optical depths (AOD) over Bangalore, India have been examined to bring out the temporal heterogeneity in columnar aerosol characteristics. AOD values at 550 nm derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA’s Terra and Aqua satellites, for the period of 2002–2011 have been analyzed (independently) for the purpose. Frequency distributions of the AOD values are examined to infer the monthly mean values. Monthly and seasonal variations of AOD are investigated in the light of regional synoptic meteorology. Climatological monthly and seasonal mean Terra and Aqua AOD values exhibited similar temporal variation patterns. Monthly mean AOD values increased from January, peaks during May and thereafter (except for a secondary peak during July) fall off to reach a minimum during December. Monsoon season recorded the highest climatological seasonal mean AOD, while winter season recorded the lowest. AOD values show an overall increasing trend on a yearly basis, which was found mainly due to sustained increase in the seasonal averaged AOD during summer. The results obtained in the present study are compared with that of the earlier studies over the same location and also with AOD over various other Indian locations. Finally, the radiative and climatic impacts are discussed.     

Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data

Land surface temperature (LST) is an important factor in global change studies, heat balance and as control for climate change. A comparative study of LST over parts of the Singhbhum Shear Zone in India was undertaken using various emissivity and temperature retrieval algorithms applied on visible and near infrared (VNIR), and thermal infrared (TIR) bands of high resolution Landsat-7 ETM+ imagery. LST results obtained from satellite data of October 26, 2001 and November 2, 2001 through various algorithms were validated with ground measurements collected during satellite overpass. In addition, LST products of MODIS and ASTER were compared with Landsat-7 ETM+ and ground truth data to explore the possibility of using multi-sensor approach in LST monitoring. An image-based dark object subtraction (DOS3) algorithm, which is yet to be tested for LST retrieval, was applied on VNIR bands to obtain atmospheric corrected surface reflectance images. Normalized difference vegetation index (NDVI) was estimated from VNIR reflectance image. Various surface emissivity retrieval algorithms based on NDVI and vegetation proportion were applied to ascertain emissivities of the various land cover categories in the study area in the spectral range of 10.4–12.5 μm. A minimum emissivity value of about 0.95 was observed over the reflective rock body with a maximum of about 0.99 over dense forest. A strong correlation was established between Landsat ETM+ reflectance band 3 and emissivity. Single channel based algorithms were adopted for surface radiance and brightness temperature. Finally, emissivity correction was applied on ‘brightness temperature’ to obtain LST. Estimated LST values obtained from various algorithms were compared with field ground measurements for different land cover categories. LST values obtained after using Valor’s emissivity and single channel equations were best correlated with ground truth temperature. Minimum LST is observed over dense forest as about 26 °C and maximum LST is observed over rock body of about 38 °C. The estimated LST showed that rock bodies, bare soils and built-up areas exhibit higher surface temperatures, while water bodies, agricultural croplands and dense vegetations have lower surface temperatures during the daytime. The accuracy of the estimated LST was within ±2 °C. LST comparison of ASTER and MODIS with Landsat has a maximum difference of 2 °C. Strong correlation was found between LST and spectral radiance of band 6 of Landsat-7 ETM+. Result corroborates the fact that surface temperatures over land use/land cover types are greatly influenced by the amount of vegetation present.     

Monitoring spatio-temporal variations in aerosols and aerosol–cloud interactions over Pakistan using MODIS data

Clouds are important elements in climatic processes and interactions between aerosols and clouds are therefore a hot topic for scientific research. Aerosols show both spatial and temporal variations, which can lead to variations in the microphysics of clouds. In this research, we have examined the spatial and temporal variations in aerosol particles over Pakistan and the impact of these variations on various optical properties of clouds, using Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra satellite. We used the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model for trajectory analysis to reveal the origins of air masses, with the aim of understanding these spatial and temporal variabilities in aerosol concentrations. We also documented seasonal variations in patterns of aerosol optical depth (AOD) over Pakistan, for which the highest values occur during the monsoon season (June–August). We then analyzed the relationships between AOD and four other cloud parameters, namely water vapour (WV), cloud fraction (CF), cloud top temperature (CTT) and cloud top pressure (CTP). Regional correlation maps and time series plots for aerosol (AOD) and cloud parameters were produced to provide a better understanding of aerosol–cloud interaction. The analyses showed strong positive correlations between AOD and WV for all of the eight cities investigated. The correlation between AOD and CF was positive for those cities where the air masses were predominantly humid, but negative for those cities where the air masses were relatively dry and carried a low aerosol abundance. These correlations were clearly dependent on the meteorological conditions for all of the eight cities investigated. Because of the observed AOD–CF relationship, the co-variation of AOD with CTP and CTT may be attributable to large-scale meteorological variations: AOD showed a positive correlation with CTP and CTT in northern regions of Pakistan and a negative correlation in southern regions.     

基于DTW的HJ-1B卫星地表温度产品质量检验

HJ-1B卫星热红外数据应用广泛,但其地表温度反演产品的质量检验工作尚不完善。以黑河流域为研究区,利用普适性单通道算法得到HJ 1B地表温度,基于7个地面站点（下垫面为荒漠、沙漠、植被、农作物、雪地和湿地）同步观测资料和MODIS地表温度产品（MOD11A1）,引入动态时间规整方法（DTW）对站点处HJ 1B地表温度进行验证。试验结果表明：HJ 1B地表温度反演产品与地面观测值的偏差值在沙漠和荒漠站点为1K以内,均方根误差在05K左右;对于植被和农作物站点的偏差在2K以内,均方根误差为1~2K;基于DTW的验证对时序不匹配的数据评价结果与现有指标表现一致。HJ-1B地表温度反演产品与地面站点的相对偏差均低于其与MODIS地表温度反演产品的相对偏差。     

Evaluation of MODIS GPP over a complex ecosystem in East Asia: A case study at Gwangneung flux tower in Korea

Moderate Resolution Imaging Radiometer (MODIS) gross primary productivity (GPP) has been used widely to study the global carbon cycle associated with terrestrial ecosystems. The retrieval of the current MODIS productivity with a 1 × 1 km² resolution has limitations when presenting subgrid scale processes in terrestrial ecosystems, specifically when forests are located in mountainous areas, and shows heterogeneity in vegetation type due to intensive land use. Here, we evaluate MODIS GPP (MOD17) at Gwangneung deciduous forest KoFlux tower (deciduous forest; GDK) for 2006–2010 in Korea, where the forests comprise heterogeneous vegetation cover over complex terrain. The monthly MODIS GPP data overestimated the GDK measurements in a range of +15% to +34% and was fairly well correlated (R = 0.88) with the monthly variability at GDK during the growing season. In addition, the MODIS data partly represented the sharp GPP reduction during the Asian summer monsoon (June–September) when intensive precipitation considerably reduces solar radiation and disturbs the forest ecosystem. To examine the influence of subgrid scale heterogeneity on GPP estimates over the MODIS scale, the individual vegetation type and its area within a corresponding MODIS pixel were identified using a national forest type map (∼71-m spatial resolution), and the annual GPP in the same area as the MODIS pixel was estimated. This resulted in a slight reduction in the positive MODIS bias by ∼10%, with a high degree of uncertainty in the estimation. The MODIS discrepancy for GDK suggests further investigation is necessary to determine the MODIS errors associated with the site-specific aerodynamic and hydrological characteristics that are closely related to the mountainous topography. The accuracy of meteorological variables and the impact of the very cloudy conditions in East Asia also need to be assessed.     

ASAR imaging for coastal upwelling in the Baltic Sea

Analysis of Envisat Advanced Synthetic Aperture Radar (ASAR) and Aqua/Terra Moderate Imaging Spectrometer (MODIS) infrared (IR) imagery of coastal upwelling in the southeastern Baltic Sea is presented. It is found that upwelling features are well distinct in the SAR images, and the leading imaging mechanism appears to be the change of the marine atmospheric boundary layer (MABL) stratification over the sea surface temperature (SST) front. This finding is supported by model calculations of the MABL transformation supplemented with the SAR backscatter calculations based on the CMOD4 model. In addition an empirical dependence of the SAR contrasts over the upwelling region on the wind speed and the SST drop is suggested. Finally, surface slicks accumulated in the sea surface current convergence zones generate additional distinct features in SAR imagery. This effect is interpreted within the framework of the coastal current circulation model based on analysis of the SST snapshot.     

The use of MODIS 250 m bands to improve the MODIS 1 km ocean color atmospheric correction algorithm in turbid water

“Clear water” is a scale-dependent concept, so it is more likely to successfully find the “clear water” from images with smaller scale than that with larger scale data. In this study, an optimal spectral relationship of moderate-resolution imaging spectroradiometer (MODIS) 250 m and 1 km resolution data at near-infrared bands (OSRLM) is constructed for converting pseudo “clear water” reflectance at 859 nm to those at 748 and 869 nm. According to scale effects, the satellite-observed pseudo “clear water” reflectance is greater than 5.18%, larger than that derived from OSRLM model. An atmospheric correction model for MODIS 1km data using pseudo “clear water” reflectance of MODIS 250 m data (ACMM) was developed for improving the performance of traditional “clear water” atmospheric correction model (CWAC). The model validation results indicate that ACMM model has a better performance than CWAC model. By comparison, the uncertainty decreases by 19.18% in the use of ACMM model over CWAC model for deriving water-leaving reflectance in Taihu Lake, China. This uncertainty is significantly reduced in water-leaving reflectance estimation due to partial removal of scale effects on “clear water”. These findings imply that satellite-derived aerosol scattering contribution at smaller scale usually has a better performance than that at larger scale.     

Sensor calibration impacts on dust detection based on MODIS and VIIRS thermal emissive bands

Dust detection using remotely sensed measurements has been one of the challenging problems encountered by atmospheric scientists. MODerate Resolution Imaging Spectroradiometer (MODIS) on the Terra (T) and Aqua (A) platforms have been a versatile sensor for well over 21 and 18 years respectively, and have been extremely useful in the retrieval of aerosol information over the entire globe. The MODIS radiances from the Level 1B in general are expected to be within 5% accuracy in the reflective wavelengths and within 1% in the thermal emissive wavelengths. In this paper, we evaluate the sensitivity of previously developed dust detection technique based on thermal emissive wavelengths, which correspond to MODIS bands 20, 29, 31, and 32 respectively. The Thermal Emissive Dust Index (TEDI) performed very comparably to the traditional Aerosol Optical Thickness (AOT) retrievals by MODIS reflective channels. Since the MODIS Thermal Emissive Bands (TEB) are well calibrated on-orbit using a BlackBody (BB) source, the calibration of these long wave infrared bands is quite robust. As A-MODIS continues to perform well beyond its designed lifetime of 6 years, the instrument has undergone various levels of degradation during its mission time. As a consequence, it is imperative to check the impacts of calibration on the higher-level retrievals. In this paper, we rigorously analyze the sensitivity of TEDI due to the impact of calibration by the afore-mentioned TEB. The perturbation of the dominant (linear) calibration term demonstrated the following: first, there was a correlation in the sensitivity of the TEDI due to the uncertainty in the linear calibration term. Based on a perturbation in the linear calibration term for all aforementioned bands over a range of ±5% yielded the TEDI sensitivity to vary from approximately ?3.2% to about ?3.6%. When considering the uncertainty in each individual band significant changes were observed. The least change was observed for the perturbation in the calibration of band 20 with the TEDI sensitivity and the largest sensitivity in TEDI was observed in the perturbation of band 31 calibration. Thus, in the case of TEDI, noticeable sensitivity due to calibration uncertainty was observed in bands 29, 31, and 32, reiterating the importance of the TEB calibration in these bands. Also, the dust detection scheme based on A-MODIS was successfully transferred to the follow-on sensors such as Suomi (SNPP) and NOAA 20 (N20) VIIRS. The results presented in this paper would be extremely helpful in understanding impacts of calibration on the higher-level products for both current and future missions based on the MODIS heritage. Finally, the work also identifies the importance of radiometric fidelity in maintaining the accuracy of the dust detection. Results presented will show drastic improvement of the Saharan dust detection after the reduction of the electronic crosstalk in the 8.5 µm channel of T-MODIS.     

Impact of emissions from anthropogenic sources on satellite-derived reflectance

The present study deals with the impact of extensive anthropogenic activities associated with festivities and agricultural crop residues burning in the Indo-Gangetic Plains (IGP) on satellite-derived reflectance during November 2007. Intense smoke plumes were observed in the IRS-P4 OCM satellite data over IGP associated with agricultural crop residue burning during the study period. Terra-MODIS AOD and CALIPSO LIDAR backscatter datasets were analysed over the region to understand the spatial and temporal variation of the aerosol properties. Ground-based measurements on aerosol optical properties and black carbon (BC) mass concentration were carried out during 7–14 November 2007 over urban region of Hyderabad, India. Top of the Atmosphere (TOA) reflectance estimated from IRS-P4 Ocean Color Monitor (OCM) data showed large variations due to anthropogenic activities associated with crop residue burning and fireworks. Atmospheric corrections to OCM satellite data using 6S radiative transfer code with inputs from ground and satellite measurements could account for the variations due to differential aerosol loading. Results are discussed in this paper.     

Is there an abnormal enhancement of atmospheric aerosol before the 2008 Wenchuan earthquake?

There are extensive reports of ionospheric disturbances before the great 2008 Wenchuan earthquake, which are possibly explained by seismogenic electric field hypotheses linked with the aerosols injected in atmosphere. This paper attempts to investigate the possible change of atmospheric aerosol optical depth (AOD) associated with this earthquake by using MODIS data from both Terra and Aqua satellites. The result shows a clear enhancement of AOD along the Longmenshan faults 7 days before the quake, which is 1 day and 4 days earlier than the reported negative and positive ionospheric disturbances, respectively, and is 1 day earlier than or quasi-synchronism with other reported atmospheric anomalies including air temperature, outgoing longwave radiation and relative humidity. Particularly, the spatial distribution of AOD enhancement is very local and it is correlated well with the active faults and surface ruptures. We suggest that this unique enhancement could be associated with the Lithosphere–Atmosphere–Ionosphere coupling process during the preparation of the Wenchuan earthquake.     

Simulation of the land surface temperature from moon-based Earth observations

The land surface temperature (LST) is a key parameter for the Earth’s energy balance. As a natural satellite of the Earth, the orbital of the moon differs from that of current Earth observation satellites. It is a new way to measure the land surface temperature from the moon and has many advantages compared with artificial satellites. In this paper, we present a new method for simulating the LST measured by moon-based Earth observations. Firstly, a modified land-surface diurnal temperature cycle (DTC) method is applied to obtain the global LST at the same coordinated universal time (UTC) using the Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. The lunar elevation angles calculated using the ephemeris data (DE405) from the Jet Propulsion Laboratory (JPL) were then applied to simulate the Earth coverage observed from the moon. At the same time, the modified DTC model was validated using in situ data, MODIS LST products, and the FengYun-2F (FY-2F) LST, respectively. The results show that the fitting accuracy (root-mean-square error, RMSE) of the modified DTC model is not greater than 0.72?°C for eight in situ stations with different land cover types, and the maximum fitting RMSE of the modified model is smaller than that of current DTC models. By the comparison of the simulated LST with MODIS and FY-2F LST products, the errors of the results were feasible and accredited, and the simulated global LST has a reasonable spatiotemporal distribution and change trend. The simulated LST data can therefore be used as base datasets to simulate the thermal infrared imagery from moon-based Earth observations in future research.     

Remote sensing of aerosol and radiation from geostationary satellites

The paper presents a high-level overview of current and future remote sensing of aerosol and shortwave radiation budget carried out at the US National Oceanic and Atmospheric Administration (NOAA) from the US Geostationary Operational Environmental Satellite (GOES) series. The retrievals from the current GOES imagers are based on physical principles. Aerosol and radiation are estimated in separate processing from the comparison of satellite-observed reflectances derived from a single visible channel with those calculated from detailed radiative transfer. The radiative transfer calculation accounts for multiple scattering by molecules, aerosol and cloud and absorption by the major atmospheric gases. The retrievals are performed operationally every 30 min for aerosol and every hour for radiation for pixel sizes of 4-km (aerosol) and 15- to 50-km (radiation). Both retrievals estimate the surface reflectance as a byproduct from the time composite of clear visible reflectances assuming fixed values of the aerosol optical depth. With the launch of GOES-R NOAA will begin a new era of geostationary remote sensing. The Advanced Baseline Imager (ABI) onboard GOES-R will offer capabilities for aerosol remote sensing similar to those currently provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) flown on the NASA Earth Observing System (EOS) satellites. The ABI aerosol algorithm currently under development uses a multi-channel approach to estimate the aerosol optical depth and aerosol model simultaneously, both over water and land. Its design is strongly inspired by the MODIS aerosol algorithm. The ABI shortwave radiation budget algorithm is based on the successful GOES Surface and Insolation Product system of NOAA and the NASA Clouds and the Earth’s Radiant Energy System (CERES), Surface and Atmospheric Radiation Budget (SARB) algorithm. In all phases of the development, the algorithms are tested with proxy data generated from existing satellite observations and forward simulations. Final assessment of the performance will be made after the launch of GOES-R scheduled in 2012.     

Detection of aerosol pollution sources during sandstorms in Northwestern China using remote sensed and model simulated data

The present paper has used a comprehensive approach to study atmosphere pollution sources including the study of vertical distribution characteristics, the epicenters of occurrence and transport of atmospheric aerosol in North-West China under intensive dust storm registered in all cities of the region in April 2014. To achieve this goal, the remote sensing data using Moderate Resolution Imaging Spectroradiometer satellite (MODIS) as well as model-simulated data, were used, which facilitate tracking the sources, routes, and spatial extent of dust storms. The results of the study have shown strong territory pollution with aerosol during sandstorm. According to ground-based air quality monitoring stations data, concentrations of PM₁₀ and PM_2.5 exceeded 400?μg/m³ and 150?μg/m³, respectively, the ratio PM_2.5/PM₁₀ being within the range of 0.123–0.661. According to MODIS/Terra Collection 6 Level-2 aerosol products data and the Deep Blue algorithm data, the aerosol optical depth (AOD) at 550?nm in the pollution epicenter was within 0.75–1. The vertical distribution of aerosols indicates that the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) 532?nm total attenuates backscatter coefficient ranges from 0.01 to 0.0001?km^?1?×?sr^?1 with the distribution of the main types of aerosols in the troposphere of the region within 0–12.5?km, where the most severe aerosol contamination is observed in the lower troposphere (at 3–6?km). According to satellite sounding and model-simulated data, the sources of pollution are the deserted regions of Northern and Northwestern China.     

Estimation of vertically integrated water vapor in Hungary using MODIS imagery

Information about the amount and spatial structure of atmospheric water vapor is essential in understanding meteorology and the Earth environment. Space-borne remote sensing offers a relatively inexpensive method to estimate atmospheric water vapor in the form of integrated water vapor (IWV). The research activity reported in the present paper is based on the data acquired by the HRPT/MODIS (High Resolution Picture Transmission, MODerate resolution Imaging Spectroradiometer) receiving station established in Budapest (Hungary) by the Space Research Group of the Eötvös Loránd University. Integrated water vapor is estimated by the remotely sensed data of the MODIS instrument with different methods and also by the operational numerical weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF). Radiosonde data are used to evaluate the accuracy of the different IWV fields though it has been pointed out that the in situ data also suffers from uncertainties. It was found that both the MODIS and the ECMWF based fields are of good accuracy. The satellite data represent finer scale spatial structures while the ECMWF data have a relatively poor spatial resolution. The high quality IWV fields have proved to be useful for radiative transfer studies such as the atmospheric correction of other satellite data from times different than the overpass times of satellites Terra/Aqua and the forecast times of the model data. For this purpose the temporal variability of IWV is scrutinized both using ECMWF and MODIS data. Taking advantage of Terra and Aqua overpasses, the mean rate of change of IWV estimated by the near infrared method was found to be 0.47 ± 0.45 kg m⁻² h⁻¹, while it was 0.13 ± 0.65 kg m⁻² h⁻¹ based on the infrared method. The numerical weather prediction model’s analysis data estimated −0.01 ± 0.13 kg m⁻² h⁻¹ for the mean growth rate, while using forecast data it was 0.24 ± 0.18 kg m⁻² h⁻¹. MODIS data should be used when available for the estimation of the IWV in other studies. If no satellite data are available, or available data are only from one overpass, ECMWF based IWV can be used. In this case the analysis fields (or the satellite field) should be used for temporal extrapolation but the rate of change should be calculated from the forecast data due to its higher temporal resolution.     

POBI interpolation algorithm for CYGNSS near real time flood detection research: A case study of extreme precipitation events in Henan,China in 2021

In late 2016, NASA launched the first constellation of the global navigation satellite system reflectometry (GNSS-R) small satellites called the Cyclone Global Navigation Satellite System (CYGNSS). The stable data quality and continuous free availability of CYGNSS scientific data provided a new method for flood monitoring. However, owing to the pseudorandom distribution of CYGNSS data, researchers must always choose between high temporal resolution and high spatial resolution during the performance of flood monitoring based on CYGNSS data. For floods caused by extreme precipitation with sudden and short durations, the current flood mapping based on CYGNSS data cannot be updated in near real time. However, the near real time update of the flood distribution range is meaningful for postdisaster emergency response and rapid rescue. This study aimed to address this problem using a newly proposed spatial interpolation method based on previously observed behaviour (POBI). First, a method for calculating the surface reflectivity of the CYGNSS was introduced, followed by the principle of the POBI spatial interpolation method. The applicability of the POBI method in Henan Province, China, was then analysed, and by using the flood in Henan Province, China, in July 2021 as an example, the feasibility of CYGNSS near real time flood mapping based on the POBI method was evaluated. Based on the results, near real time and 3 km flood distribution monitoring results can be obtained using the proposed new method. The results were evaluated using MODIS (Moderate Resolution Imaging Spectroradiometer) images and compared with the observations of SMAP (Soil Moisture Active Passive) and GPM (Global Precipitation Measurement) in the same period. The results show that the flooded areas obtained by CYGNSS correspond to the inundated areas in MODIS images and are also in high agreement with the SMAP. In addition, CYGNSS allows for finer mapping and quantification of inundation areas and flood duration. Moreover, we also discussed the potential of CYGNSS to detect floods in shorter periods of time (a few hours) and did a preliminary evaluation using precipitation data from meteorological stations. The results are also highly consistent.     

Simultaneous determination of aerosol- and surface characteristics from top-of-atmosphere reflectance using MERIS on board of ENVISAT

The determination of aerosol optical thickness (AOT) from nadir scanning multi-spectral radiometers, like SeaWiFS, MERIS or MODIS, requires the separation of spectral atmospheric and surface properties. Since SeaWiFS and MERIS do not provide information at 2.1 μm, like MODIS, the estimation of the surface reflectance cannot be made by the cross correlation approach described by Kaufman et al., 1997. The BAER approach (Bremen AErosol Retrieval), von Hoyningen-Huene et al., 2003, uses a linear mixing model of spectra for ‘green vegetation’ and ‘bare soil’, tuned by the NDVI, determining an apparent surface to enable this separation of aerosol and surface properties from VIS and NIR channels. Thus AOT can be derived over a wide range of land surfaces for wavelengths <0.67 μm. Using MERIS L1 data over Europe, the AOT retrieved is comparable with ground-based observations, provided by AERONET. Regional variation of AOT can be observed, showing the atmospheric variability for clear sky conditions by: large scale variation of aerosol turbidity, regional pollution, urban regions, effects of contrails and cases of aerosol-cloud interaction. Simultaneously with the spectral AOT also spectral surface reflectance is obtained, where all atmospheric influences have been considered (molecules, aerosols and absorbing gases (O₃)) for channels with wavelengths <0.67 μm. The AOT is extrapolated by Angström power law to NIR channels and the atmospheric correction for land surface properties is performed, enabling the further investigation of land use and spectral land properties.