Results of instrumental observations of tidal wave propagation in the atmosphere

This paper presents the results of processing and analysis of acoustic waves in the surface layer of the atmosphere, registered at the Mikhnevo Geophysical Observatory, Institute of Geosphere Dynamics, Russian Academy of Sciences (IGD RAS). Using the autoregression model of digital series, the spectrum of acoustic oscillations was evaluated and the tidal waves in the envelopes of acoustic oscillations were distinguished. The tidal components with similar periods were separated using the method of extraction of harmonic components by using adaptive notch filters. The observed features of the spectrum of acoustic oscillations open up new opportunities for instrumental control over meteorological conditions and the establishment of general regularities controlling the regimes of energy-exchange processes in the Earth’s atmosphere.     

Derivation of tropospheric aerosol properties from satellite observations

Here we review the methods presently available and expected in the near future for retrieving the tropospheric aerosol properties using remote sensing. Since all aerosol properties cannot be derived from space, measurements performed from the surface of the Earth are used to adjust the parameters that are not directly accessible and to limit the variability of the parameters that present a weaker sensitivity. The aerosol properties derived include the column concentration (expressed by the aerosol optical depth), the size (given by distribution of the aerosol in 2 to 3 size modes or measurement of the Angström coefficient), composition (expressed by the refractive index), shape and vertical profile. The article is restricted to aerosols that are within the troposphere since the techniques used for stratospheric aerosols are very specific.     

实测与卫星观测德基水库水质变化

德基水库集水区的气候条件适合温带水果及高冷蔬菜、茶叶的种植,德基水库集水区上游遍布果园、菜园与茶园。因此,每逢大雨来临时,大量的残留肥料常遭冲刷至水库中。这些残留的肥料中含有大量的氮、磷等营养盐,足以提供水库微生物的生长繁殖所需,也因此造成水库中二角多甲藻的大量繁殖,进而形成藻华现象。研究使用Landsat TM卫星数据,搭配传统监测模式,以监督式影像分类法分析与监测德基水库1995年的藻华现象。研究结果显示,以Landsat TM卫星数据监测德基水库的藻华现象,其准确率可达87.5%以上。由影像分类的结果可得知,德基水库二角多甲藻之藻华现象发生较严重的时期为夏天,而冬天则较为轻微。此现象发生的原因,应与集水区上游的农业经营模式息息相关。此外,德基水库藻华现象发生的区域及其程度也经由实地调查与卫星影像监测,一一获得证实。     

Enhancement and identification of dust events in the south-west region of Iran using satellite observations

South-west Asia including the Middle East is one of the most prone regions to dust storm events. In recent years, there was an increase in the occurrence of these environmental and meteorological phenomena. Remote sensing could serve as an applicable method to detect and also characterise these events. In this study, two dust enhancement algorithms were used to investigate the behaviour of dust events using satellite data, compare with numerical model output and other satellite products and finally validate with in-situ measurements. The results show that the use of thermal infrared algorithm enhances dust more accurately. The aerosol optical depth from MODIS and output of a Dust Regional Atmospheric Model (DREAM8b) are applied for comparing the results. Ground-based observations of synoptic stations and sun photometers are used for validating the satellite products. To find the transport direction and the locations of the dust sources and the synoptic situations during these events, model outputs (HYSPLIT and NCEP/NCAR) are presented. Comparing the results with synoptic maps and the model outputs showed that using enhancement algorithms is a more reliable way than any other MODIS products or model outputs to enhance the dust.     

Assimilation of Indian Doppler Weather Radar observations for simulation of mesoscale features of a land-falling cyclone

In this paper, impact of Indian Doppler Weather Radar (DWR) data, i.e., reflectivity (Z), radial velocity (Vr) data individually and in combination has been examined for simulation of mesoscale features of a land-falling cyclone with Advance Regional Prediction System (ARPS) Model at 9-km horizontal resolution. The radial velocity and reflectivity observations from DWR station, Chennai (lat. 13.0°N and long. 80.0°E), are assimilated using the ARPS Data Assimilation System (ADAS) and cloud analysis scheme of the model. The case selected for this study is the Bay of Bengal tropical cyclone NISHA of 27–28 November 2008. The study shows that the ARPS model with the assimilation of radial wind and reflectivity observations of DWR, Chennai, could simulate mesoscale characteristics, such as number of cells, spiral rain band structure, location of the center and strengthening of the lower tropospheric winds associated with the land-falling cyclone NISHA. The evolution of 850 hPa wind field super-imposed vorticity reveals that the forecast is improved in terms of the magnitude and direction of lower tropospheric wind, time, and location of cyclone in the experiment when both radial wind and reflectivity observations are used. With the assimilation of both radial wind and reflectivity observations, model could reproduce the rainfall pattern in a more realistic way. The results of this study are found to be very promising toward improving the short-range mesoscale forecasts.     

Spatio-temporal variability of dust aerosols over the Sistan region in Iran based on satellite observations

Satellite remote sensing provides important observational constraints for monitoring dust life cycle and improving the understanding of its effects on local to global scales. The present work analyzes the dust aerosol patterns over the arid environment of the Sistan region in southeastern Iran, by means of multiple satellite platforms aiming to reveal the spatio-temporal distribution and trends. The dataset includes records of Aerosol Index (AI) from Total Ozone Mapping Spectrometer (TOMS) (1978–2001) and 6-year AI records from the Ozone Monitoring Instrument (OMI) aboard Aura. Moreover, the aerosol optical depth is analyzed through 11-year records from Multi-angle Imaging Spectroradiometer (MISR) aboard Terra (2000–2010) and from Moderate-resolution Imaging Spectroradiometer (MODIS) onboard Terra (2000–2007) and Aqua (2002–2011). The main focus is to determine the similarities and differences in dust variability over southwest Asia, in general, and the Sistan region, in particular. The results show a marked seasonal cycle with high aerosol loading during summer and lower in winter, while MISR, MODIS, and TOMS/OMI observations agree in both terms of monthly and seasonally mean spatial and temporal patterns. The higher aerosol concentrations during summer are interpreted as a result of the combined effect of the seasonal drying of the Hamoun lakes and the strong northerly Levar winds favoring dust erosion from the alluvial deposits in Sistan. After prolonged drought period, the dust aerosol load over the area has increased in the beginning of the 2000 s and decreased after 2004, thereby leading to an overall declining trend during the last decade. Such a trend is absent during the winter period when dust emission over the region is minimal.     

Space observations of Transient Luminous Events and associated emissions in the upper atmosphere above thunderstorm areas

Sprites, jets and elves called Transient Luminous Events (TLE), observed in the middle and upper atmosphere above thunderstorms, are the manifestation of intense energy exchanges between the troposphere, stratosphere and mesosphere. Different types of luminous emissions have been identified by ground-based observations, showing the complexity of these phenomena. Space missions showed that transient emissions in the Earth atmosphere are very broad including Radio Frequency (RF), IR to FUV radiations and X-gamma ray emissions called Terrestrial Gamma Flashes (TGF) with energies reaching 30 Mev. However, there are no global observations of these events together. This paper reviews space observations performed up to now and emphasizes the challenges of the future space missions in global measurements of all possible emissions together for the understanding of the physical mechanisms at the origin of these phenomena and their effects on the Earth environment.     

Development of a parameterization for simulating the urban temperature hazard using satellite observations in climate model

Urban surface temperature is hazardously higher than surrounding regions (so-called urban heat island effect UHI). Accurately simulating urbanization-induced temperature hazard is critical for realistically representing urban regions in the land surface-atmosphere climate system. However, inclusion of urban landscapes in regional or global climate models has been overlooked due to the coarse spatial resolution of these models as well as the lack of observations for urban physical properties. Recently, National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) observations illustrate important urban physical properties, including skin temperature, surface albedo, surface emissivity, and leaf area index, It is possible to identify the unique urban features globally and thus simulate global urban processes. An urban scheme is designed to represent the urban-modified physical parameters (albedo, emissivity, land cover, roughness length, thermal and hydraulic properties) and to include new, unique physical processes that exist in urban regions. The urban scheme is coupled with National Center for Atmospheric Research (NCAR) Community Land Model Version 2 (CLM2) and single column coupled NCAR Community Atmosphere Model CAM2/CLM2 to assess the mechanisms responsible for UHI. There are two-steps in our model development. First, satellite observations of albedo, emissivity, LAI, and in situ observed thermal properties are updated in CLM2 to represent the first-order urban effects. Second, new terms representing the urban anthropogenic heat flux, storage heat flux, and roughness length are calculated in the model. Model simulations suggest that human activity-induced surface temperature hazard results in overlying atmosphere instability and convective rainfall, which may enhance the possibility of urban flood hazard.

Assimilation of Doppler weather radar observations in a mesoscale model for the prediction of rainfall associated with mesoscale convective systems

Obtaining an accurate initial state is recognized as one of the biggest challenges in accurate model prediction of convective events. This work is the first attempt in utilizing the India Meteorological Department (IMD) Doppler radar data in a numerical model for the prediction of mesoscale convective complexes around Chennai and Kolkata. Three strong convective events both over Chennai and Kolkata have been considered for the present study. The simulation experiments have been carried out using fifth-generation Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) mesoscale model (MM5) version 3.5.6. The variational data assimilation approach is one of the most promising tools available for directly assimilating the mesoscale observations in order to improve the initial state. The horizontal wind derived from the DWR has been used alongwith other conventional and non-conventional data in the assimilation system. The preliminary results from the three dimensional variational (3DVAR) experiments are encouraging. The simulated rainfall has also been compared with that derived from the Tropical Rainfall Measuring Mission (TRMM) satellite. The encouraging result from this study can be the basis for further investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present study indicates that Doppler radar data assimilation improves the initial field and enhances the Quantitative Precipitation Forecasting (QPF) skill.     

Regional soil moisture retrievals and simulations from assimilation of satellite microwave brightness temperature observations

Low-frequency microwave satellite observations are sensitive to land surface soil moisture (SM). Using satellite microwave brightness temperature observations to improve SM simulations of numerical weather, climate and hydrological predictions is one of the most active research areas of the geoscience community. In this paper, Yan and Jins’ (J Radio Sci 19(4):386–392, 2004) theory on the relationship between satellite microwave remote sensing polarization index and SM is used to estimate land surface SM values from the advanced microwave scanning radiometer-E (AMSR-E) brightness temperature data. With consideration of soil texture, surface roughness, optical thickness, and the monthly means of NASA AMSR-E SM data products, the regional daily land surface SM values are estimated over the eastern part of the Qinghai-Tibet Plateau. The resulting SM retrievals are better than the NASA daily AMSR-E SM product. The retrieved SM values are generally lower than the ground measurements from the Maqu Station (33.85°N, 102.57°E) and the Tanglha Station (33.07°N, 91.94°E) and the US NCEP reanalysis data, but the temporal variations of the retrieved SM demonstrate more realistic response to the observed precipitation events. In order to improve the land surface SM simulating ability of the weather research and forecasting model, the retrieved SM was assimilated into the Noah land surface model by the Newtonian relaxation (NR) method. A direct insertion method was also applied for comparison. The results indicate that fine-tuning the quality factor in the NR method improves the simulated SM values most for desert areas, followed by grasslands, and shrub and grass mixed zones at the regional scale. At the temporal scale, the NR method decreased the root mean square error between the simulated SM and actual observed SM by 0.03 and 0.07 m³/m³ at the Maqu and Tanglha Stations, respectively, and the temporal variation of simulated SM values was much closer to the ground-measured SM values.     

Seismotectonic deformations related to the 2010 Maule earthquake at different stages of the seismic cycle from satellite geodetic observations

Doklady Earth Sciences - The interpretation of multiannual satellite geodetic observations after the 2010 Maule earthquake is given on the basis of the keyboard concept of the subduction region...     

Predicting the response of leaf stomatal frequency to a future CO2-enriched atmosphere: constraints from historical observations

The majority of the water flux from the earth’s land surface to the atmosphere passes through the tiny pores (stomata) in the leaves of land plants. The maximum conductance to diffusion of the leaves, determined by the number and geometry of stomata, has a profound effect on the terrestrial water and energy balance. Among tree species, there is ever increasing evidence that anthropogenic increase in atmospheric CO₂ concentrations results in a decrease in stomatal frequency. The rate of historical CO₂ responsiveness of individual tree species can be used to calibrate empirical models of non-linear (sigmoid) stomatal frequency response to CO₂ increase. Modelled response curves for European tree birches (Betula pendula, Betula pubescens) and Durmast oak (Quercus petraea) predict different response limits to CO₂ increase (～350 and ～400?ppmv, respectively), indicating that non-linear stomatal frequency responses may vary from one tree species to another. Information on a wider selection of species is needed, but the models suggest that the maximum effect of anthropogenic CO₂ increase on stomatal frequency has already been reached. Further research is required to establish the effect of rapidly declining response rates on future stomatal conductance of the ecologically contrasting trees of boreal, temperate, subtropical and tropical forests.     

Recent hydrological behavior of the East African great lakes region inferred from GRACE,satellite altimetry and rainfall observations

We have jointly analysed space gravimetry data from the GRACE space mission, satellite altimetry data and precipitation over the East African Great Lakes region, in order to study the spatiotemporal variability of hydrological parameters (total water storage, lake water volume and rainfall). We find that terrestrial water storage (TWS) from GRACE and precipitation display a common mode of variability at interannual time scale, with a minimum in late 2005, followed by a rise in 2006–2007. We argue that this event is due to forcing by the strong 2006 Indian Ocean Dipole (IOD) on East African rainfall. We also show that GRACE TWS is linked to the El Niño-Southern Oscillation cycle. Combination of the altimetry-based lake water volume with TWS from GRACE over the lakes drainage basins allows estimating soil moisture and groundwater volume variations. Comparison with the WGHM hydrological model outputs is performed and discussed.     

Extreme waves induced by cyclone Nargis at Myanmar coast: numerical modeling versus satellite observations

Natural Hazards - The deltaic coast of Myanmar was severely hit by tropical cyclone Nargis in May 2008. In the present study, a top-down numerical simulation approach using the Weather Research and...     

长江中下游六省大气甲烷柱浓度时空分布

甲烷(CH₄)是造成气候变暖的主要温室气体之一。为了了解长江中下游水稻种植区CH₄浓度的分布情况,本次研究基于温室气体观测卫星(greenhousegasesobservingsatellite,GOSAT)和大气红外探测仪(atmospheric infraredsounder,AIRS)卫星反演的数据产品,对我国长江中下游六省大气CH₄柱浓度的时空分布特征进行了研究。研究结果表明,由GOSAT反演的长江中下游六省大气CH₄浓度呈逐年增长趋势,其年均浓度由2011年的1817×10^-9增长至2018年的1875×10^-9,高于东三省、华北平原和全国平均水平。区域平均年增长量为8.2×10^-9 a^-1。各省年际增长幅度略有差异,纬度偏低的江西、湖南和浙江三省大气CH₄浓度高且增长量偏大,纬度偏高的湖北、安徽和江苏三省大气CH₄浓度略低且增长量偏小。长江中下游六省大气CH...     

Data augmentation for bias correction in mapping PM2.5 based on satellite retrievals and ground observations

As most air quality monitoring sites are in urban areas worldwide, machine learning models may produce substantial estimation bias in rural areas when deriving spatiotemporal distributions of air pollutants. The bias stems from the issue of dataset shift, as the density distributions of predictor variables differ greatly between urban and rural areas. We propose a data-augmentation approach based on the multiple imputation by chained equations (MICE-DA) to remedy the dataset shift problem. Compared with the benchmark models, MICE-DA exhibits superior predictive performance in deriving the spatiotemporal distributions of hourly PM_2.5 in the megacity (Chengdu) at the foot of the Tibetan Plateau, especially for correcting the estimation bias, with the mean bias decreasing from –3.4 µg/m³ to –1.6 µg/m³. As a complement to the holdout validation, the semi-variance results show that MICE-DA decently preserves the spatial autocorrelation pattern of PM_2.5 over the study area. The essence of MICE-DA is strengthening the correlation between PM_2.5 and aerosol optical depth (AOD) during the data augmentation. Consequently, the importance of AOD is largely enhanced for predicting PM_2.5, and the summed relative importance value of the two satellite-retrieved AOD variables increases from 5.5% to 18.4%. This study resolved the puzzle that AOD exhibited relatively lower importance in local or regional studies. The results of this study can advance the utilization of satellite remote sensing in modeling air quality while drawing more attention to the common dataset shift problem in data-driven environmental research.     

Recent terrestrial and satellite observations to model deformations at Colli Albani volcano (central Italy)

The Colli Albani volcanic complex (Rome, Italy) has been dominated by episodic eruptions commencing around 561?ka and ending with the most recent activity of the Albano maar phase (<70?ka). Earthquakes of moderate intensity, gas emissions and significant ground deformations are the recent evidences of a residual activity. Former geodetic data from leveling surveys, GPS stations and InSAR observations tracked ongoing significant uplift of the order of few mm/year near the Colli Albani western flank. Different uplift rates were detected by each technique in different time spans, suggesting also the possibility of sporadic recharge of the hydrothermal system. The renewed high precision leveling data from IGMI survey carried out in 1997/1999 and the last leveling survey carried out in 2006 show that the uplift along the route is currently significant at an average rate of ~3?mm/year. Radar interferograms from ALOS satellite show uplift rate of ~6?mm/year, southwest of the central sector of the leveling route. We have undertaken a joint inversion of the various geodetic data (vertical rates from leveling surveys, GPS site velocities and InSAR observations acquired by ALOS satellite) using a nonlinear inversion technique to estimate the parameters of a point-pressure source, possibly capable of explaining the ongoing deformation at Colli Albani volcano.     

Numerical simulation of cyclonic storms FANOOS, NARGIS with assimilation of conventional and satellite observations using 3-DVAR

In this work, the impact of assimilation of conventional and satellite data is studied on the prediction of two cyclonic storms in the Bay of Bengal using the three-dimensional variational data assimilation (3D-VAR) technique. The FANOOS cyclone (December 6?C10, 2005) and the very severe cyclone NARGIS (April 28?CMay 2, 2008) were simulated with a double-nested weather research and forecasting (WRF-ARW) model at a horizontal resolution of 9?km. Three numerical experiments were performed using the WRF model. The back ground error covariance matrix for 3DVAR over the Indian region was generated by running the model for a 30-day period in November 2007. In the control run (CTL), the National Centers for Environmental Prediction (NCEP) global forecast system analysis at 0.5° resolution was used for the initial and boundary conditions. In the second experiment called the VARCON, the conventional surface and upper air observations were used for assimilation. In the third experiment (VARQSCAT), the ocean surface wind vectors from quick scatterometer (QSCAT) were used for assimilation. The CTL and VARCON experiments have produced higher intensity in terms of sea level pressure, winds and vorticity fields but with higher track errors. Assimilation of conventional observations has meager positive impact on the intensity and has led to negative impact on simulated storm tracks. The QSCAT vector winds have given positive impact on the simulations of intensity and track positions of the two storms, the impact is found to be relatively higher for the moderate intense cyclone FANOOS as compared to very severe cyclone NARGIS.     

Rainfall analysis for Indian monsoon region using the merged rain gauge observations and satellite estimates: Evaluation of monsoon rainfall features

Objective analysis of daily rainfall at the resolution of 1° grid for the Indian monsoon region has been carried out merging dense land rainfall observations and INSAT derived precipitation estimates. This daily analysis, being based on high dense rain gauge observations was found to be very realistic and able to reproduce detailed features of Indian summer monsoon. The inter-comparison with the observations suggests that the new analysis could distinctly capture characteristic features of the summer monsoon such as north-south oriented belt of heavy rainfall along the Western Ghats with sharp gradient of rainfall between the west coast heavy rain region and the rain shadow region to the east, pockets of heavy rainfall along the location of monsoon trough/low, over the east central parts of the country, over north-east India, along the foothills of Himalayas and over the north Bay of Bengal. When this product was used to assess the quality of other available standard climate products (CMAP and ECMWF reanalysis) at the gird resolution of 2.5°, it was found that the orographic heavy rainfall along Western Ghats of India was poorly identified by them. However, the GPCC analysis (gauge only) at the resolution of 1° grid closely discerns the new analysis. This suggests that there is a need for a higher resolution analysis with adequate rain gauge observations to retain important aspects of the summer monsoon over India. The case studies illustrated show that the daily analysis is able to capture large-scale as well as mesoscale features of monsoon precipitation systems. This study with data of two seasons (2001 and 2003) has shown sufficiently promising results for operational application, particularly for the validation of NWP models.