Ground-based Observational Data Research Articles

Detection of atmosphere CCl<sub>2</sub>F<sub>2</sub> spatio-temporal variations by ground-based high resolution Fourier transform infrared spectroscopy

Atmospheric dichlorodifluoromethane (CCl<sub>2</sub>F<sub>2</sub>, CFC-12), as a synthetic chemical agent, is a main stratospheric ozone-depleting substance in atmosphere. Studies of the detection techniques and the temporal and spatial distribution of CFC-12 have great significance in understanding the variation trend of regional CFCs and their influence on stratospheric ozone. In this study, the method of retrieving the vertical profile and total column for CFC-12 is studied based on ground-based high-resolution Fourier transform infrared spectroscopy (FTIR). The spectral window for CFC-12 retrieval is selected as 922.5–923.6 cm<sup>–1</sup>, where the interfering gases are H<sub>2</sub>O, O<sub>3</sub>, and CO<sub>2</sub>. The result of error analysis shows that the average total error is 1.27%, including the systematic error 0.76% and random error 1.02%. The vertical profiles and total columns of atmospheric CFC-12 in Hefei during the period from 2017 to 2020 were retrieved based on the optimal estimation algorithm. The vertical profiles of CFC-12 show that the concentration of atmospheric CFC-12 is high in the troposphere and low stratosphere at the altitude of 0–20 km, and then decreases, very low at height above 40 km. The total column average kernel of retrieved CFC-12 profiles is higher at 15–20 km, and the typical signal degree of freedom of CFC-12 is 1.217. Moreover, the long-term total columns of atmosphere CFC-12 observed show obvious seasonal variation in Hefei. Total columns of atmosphere CFC-12 are higher in summer and lower in winter and early spring. The maximum monthly concentration of CFC-12 is about 1.13 × 10<sup>16</sup> mol·cm<sup>–2</sup> in July, and the minimum monthly concentration is 1.00 × 10<sup>16</sup> mol·cm<sup>–2</sup> in March. Also, the annual average total columns of atmospheric CFC-12 decreased slightly from 2017 to 2020, with an increasing rate of –0.68%. This reflects the effect of China's implementation of CFCs control ban policy. Furthermore, in order to verify the accuracy of ground-based FTIR observation, we compare our ground-based observation data with ACE-FTS/ SCISAT satellite version 4.1 level 2 data. There are 16 pairs of matching points between satellite observation and ground observation data, and the correlation coefficient is 0.73 for two CFC-12 partial columns at the height of 16–28 km, showing good agreement between ground-based FTIR data and satellite data. The long-term observations demonstrate the accuracy and reliability of ground-based high-resolution FTIR technology for detecting the vertical distribution and seasonal variation of atmosphere CFC-12.

A Novel Cloud Detection Algorithm Based on Simplified Radiative Transfer Model for Aerosol Retrievals: Preliminary Result on Himawari-8 Over Eastern China

Aerosol particles affect the Earth's radiative balance and represent one of the largest uncertainties in climate research. The removal of clouds is the first step and critical in the aerosol retrievals. However, the cloud detection is still challenging. Here, a novel simplified cloud detection algorithm (SCDA) is proposed to identify the cloud and clear-sky over land and based on a simplified radiative transfer model (RTM). The fewer input bands, dynamic thresholds, and only one parameter to be modified are the main advantages of the algorithm, which can be applied to different satellite sensors. In this article, we apply SCDA to the Himawari-8 data in 2016 for preliminary analysis. The detection results are validated using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) vertical feature mask (VFM) data and the National Centers for Environmental Information (NCEI) ground-based observation data. We also compare the results with the Himawari-8 cloud products from the Japan Aerospace Exploration Agency (JAXA). Compared with CALIPSO VFM data and NCEI ground-based observation data, the correct rate of SCDA cloud detection result is 86.08% and 79.86%, which are higher than that of Himawari-8 cloud products (85.71% and 78.89%). The correct rate of SCDA clear-sky detection result is 88.33% and 87.85%, which are close to the correct rate of Himawari-8 clear-sky products (90.54% and 88.63%). The overall performance of the SCDA is comparable to that of the threshold method for JAXA Himawari-8 cloud products. Therefore, the SCDA can provide accurate cloud mask with only one threshold to be modified and few input parameters.

Performance evaluation of Eta/HadGEM2-ES and Eta/MIROC5 precipitation simulations over Brazil

Climate change effects can have significant impacts worldwide. Extreme events can modify water availability and agricultural production, making climate change planning an essential task. The National Institute for Space Research (INPE in Portuguese) in Brazil has made a large dataset of regional climate model outputs (simulations and projections) available, which opens up many possibilities of carrying out high-resolution climate change studies. However, there is still no performance evaluation of the model-derived rainfall output against high-resolution ground-based observation data considering the Brazilian biomes. This paper attempts to fill this gap and evaluates the simulated precipitation throughout Brazil. We used gridded observed precipitation data and historical climate simulations from the Model for Interdisciplinary Research on Climate, version 5 (MIROC5) and from the Hadley Center Global Environment Model, version 2 (HadGEM2-ES), which were downscaled by the Eta RCM (Regional Climate Model). For the overlapping period (1980–2005), there is good agreement (PBIAS up to 10%) of downscaled annual simulations for the Amazon and Cerrado biomes and large biases (reaching 40%) in the Pampa biome, compared to the observations. Our results showed that HadGEM2-ES is capable of representing long-term mean monthly precipitation for large areas well, such as the Amazon and Cerrado. Furthermore, the Eta RCM has considerably improved the driving GCM MIROC5 simulations. In conclusion, we recommend using the HadGEM2-ES simulations for the Amazon, Eta/HadGEM2-ES for the Atlantic Forest, Cerrado, and Pampa, and Eta/MIROC5 for the Caatinga and Pantanal. Our study provides an overview of two downscaled simulation datasets in Brazil that may help verify the models' suitability for further climate change assessments.

Assessment of Direct Normal Irradiance Forecasts Based on IFS/ECMWF Data and Observations in the South of Portugal

Direct Normal Irradiance (DNI) predictions obtained from the Integrated Forecasting System of the European Centre for Medium-Range Weather Forecast (IFS/ECMWF) were compared against ground-based observational data for one location at the south of Portugal (Évora). Hourly and daily DNI values were analyzed for different temporal forecast horizons (1 to 3 days ahead) and results show that the IFS/ECMWF slightly overestimates DNI for the period of analysis (1 August 2018 until 31 July 2019) with a fairly good agreement between model and observations. Hourly basis evaluation shows relatively high errors, independently of the forecast day. Root mean square error increases as the forecast time increases with a relative error of ~45% between the first and the last forecast. Similar patterns are observed in the daily analysis with comparable magnitude errors. The correlation coefficients between forecast and observed data are above 0.7 for both hourly and daily data. A methodology based on a new DNI attenuation Index (DAI) was developed to estimate cloud fraction from hourly values integrated over a day and, with that, to correlate the accuracy of the forecast with sky conditions. This correlation with DAI reveals that in IFS/ECMWF model, the atmosphere as being more transparent than reality since cloud cover is underestimated in the majority of the months of the year, taking the ground-based measurements as a reference. The use of the DAI estimator confirms that the errors in IFS/ECMWF are larger under cloudy skies than under clear sky. The development and application of a post-processing methodology improves the DNI predictions from the IFS/ECMWF outputs, with a decrease of error of the order of ~30%, when compared with raw data.

Velocity distribution of larger meteoroids and small asteroids impacting Earth

Various meteor and fireball networks exist worldwide. Most data sets which include ground-based observational data of meteors are affected by biases. The larger and faster the entering meteoroid, the brighter is the produced meteor. Hence, small and slow objects often stay undetected. This bias of meteor observations towards faster meteoroids is a challenge if quantitative population and flux models are derived. In this work the velocity distribution of objects in space is analysed by using different data sets that are not affected by this velocity bias since they include only large objects, like the near-Earth object (NEO) risk list of ESA’s (European Space Agency) SSA (Space Situational Awareness) near-Earth object Coordination Centre (NEOCC), and the fireballs in NASA’s (National Aeronautics and Space Administration) CNEOS (Center for near-Earth object Studies) JPL (Jet Propulsion Laboratory) fireball database. Additionally, when only the largest objects recorded with the CILBO (Canary Island Long-Baseline Observatory) camera setup were analysed, a very similar distribution was shown. These velocity distributions are in good agreement with a widely used velocity distribution for smaller sporadic meteoroids in free space which was adopted as reference by the ECSS (European Cooperation for Space Standardisation) Space Environment Standard.

Influence of urban spatial configuration and sea breeze on land surface temperature on summer clear-sky days

Understanding the spatiotemporal characteristics of land surface temperature (LST), a physical quantity that greatly contributes to the formation of urban thermal environment, is essential for constructing a sustainable urban environment. This study explores the relationship between urban space, atmospheric conditions, and diurnal change characteristics of LST on summer clear-sky days in an urban area of Osaka Plain using a 10 min LST dataset retrieved from the Japanese geostationary satellite (Himawari-8) data. The principal temporal change patterns forming the diurnal cycle of LST were extracted through a principal component analysis, and their spatial variabilities were investigated through the exploitation of ground-based meteorological observation and land-use data. The result showed two temporal change patterns, identified as the amplitude and phase of the diurnal change, being extracted in different clear-sky days. A hierarchical cluster analysis confirmed that the spatial variations of such patterns corresponded to the sea breeze and urban land-use. Moreover, LST change at daytime was found to be larger in the high-density areas rather than in the low-density areas of low buildings, thereby suggesting the influence of building density on LST at daytime.

Case studies of atmospheric rivers over China and Australia: new insight into their rainfall generation

While the Australia–Asian (A-A) monsoon is a prominent feature of weather and climate in China and Australia, there are significant differences in their dominant weather patterns and climate drivers. In order to explore different characteristics of atmospheric rivers (ARs) affecting weather and climate in these two countries, this paper compares two typical AR events that occurred in the boreal summer (austral winter) in 2016. The event in China produced record-breaking rainfall in North China, whereas the event in Australia was accompanied by a classic Northwest Cloud Band (NWCB) and produced a rainfall belt across the continent. Using global reanalysis products and ground-based observational data, we analysed the synoptic backgrounds, vertical structures, water vapour sources and relationship between ARs and cloud distributions. In both China and Australia, heavy precipitation was triggered by strong water vapour transport by ARs ahead of midlatitude frontal systems. The main differences between these two AR events and their associated rainfall effectiveness were that (i) the AR intensity in the Asian summer monsoon was stronger than that in the austral winter season over Australia; (ii) the centre of AR maximum moisture transport in China was around 850 hPa, whereas in Australia, it was located at around 700 hPa; and (iii) the AR-induced rainfall was heavier in China than in Australia. These differences were caused by numerous factors, including a lack of topographic influence, a dry climate background in Australia, and different interactions between warm and moist air conveyed by ARs from the tropics with cold air from the midlatitudes. We paid particular attention to the relationship between the Australian AR and its associated cloud structure and rainfall to understand precipitation efficiency of the NWCB. In addition, we assessed the forecast skills of an Australian numerical weather prediction system (ACCESS-APS2) for the two events with different lead times. The model produced reasonable forecasts of the occurrence and intensity of both AR events several days in advance, and the AR forecast skill was better than its forecasts of rainfall location and intensity. This demonstrates the value of using AR analysis in guiding extreme rainfall forecasts with longer lead time.

Total Content of Water Vapor Over Yamal During the Warm Period of the Year

The spatial distribution of total water vapor content over the Yamal Peninsula and adjacent territories was analyzed using data of four-year-long measurements from the European Envisat satellite during warm periods of the year (June-August). Special attention was given to water vapor variations at the transition from little to abundant water-bearing areas of the underlying surface. It was found that for the five selected sites located in a dry tundra and in large water bodies the logarithmic rather than Gaussian form of the distribution functions of total water vapor content turned out to be typical according to the number of its measurements. Each function has at least two modes. The parameters of these modes were calculated and presented, and they are necessary for simulation of climatic conditions in the northern territories. Geometric mean values of total water vapor content over the Gulfs of Gydan and Baidaratsk, and especially over the Gulf of Ob, can be by a factor of 1.5 larger than those for the less water-abundant areas of tundra and have clear boundaries coincident with geographical contours of the water bodies. It is most likely that these boundaries exist at insignificant speeds of surface winds, which is indicative of weak turbulent mixing of the lower air layers. This conclusion is confirmed by results from processing published data of ground-based and satellite observations. For the five sites they were used to calculate and construct the wind roses for all five sections in the same time intervals when the satellite measurements of water vapor content were carried out. Wind rose analysis shows that the average velocity of predominantly N and NW winds on all the selected sites at a height of 10 m above the underlying surface are 5–6 m/s with a standard deviation of 1.5 m/s. Additional data are presented on the form of the distribution function of various parameters in other natural environments (water bodies and vegetation) which give support to what has been said above about water vapor.

Aerosol optical depth (AOD) retrieval for atmospheric correction in Landsat-8 imagery using second simulation of a satellite signal in the solar spectrum-vector (6SV)

Atmospheric correction has been challenging task in digital image processing. It requires several atmospheric parameters in order to obtain accurate surface reflectance of objects within the image scene. One of the most crucial parameters required for accurate atmospheric correction is aerosol optical depth (AOD). AOD can be obtained by in-situ measurement or estimated from remote sensing observation. In this experiment, atmospheric correction was performed using second simulation of a satellite signal in the solar spectrum-vector (6SV) algorithm on Landsat-8 imagery in which AOD parameter was retrieved from surface reflectance inversion involving daily-global surface reflectance product of moderate resolution imaging spectroradiometer (MODIS). Furthermore, AOD retrieved from surface reflectance inversion was also validated using ground-based sun photometer observation data from aerosol robotic network (AERONET) station in Bandung, Indonesia. Our experiment shows the consistency between AOD from surface reflectance inversion and AOD from ground-based observation. Finally, 6SV was performed on Landsat-8 imagery to obtain the surface reflectance. We further compared surface reflectance of 6SV atmospheric correction and surface reflectance of Landsat-8 Level 2 product. The atmospherically corrected image also shared agreeable result with Landsat 8 Level-2 product.

Spatial and Temporal Variations in Vegetation Cover and Responses to Climatic Variables in the Daqing River Basin, North China

Cui, H.; Xiao, W.; Zhou, Y.; Hou, B; Lu, F., and Pei, M., 2019. Spatial and temporal variations in vegetation cover and responses to climatic variables in the Daqing River Basin, North China. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 450–459. Coconut Creek (Florida), ISSN 0749-0208.The establishment of Xiong'an New Area in Hebei Province has gained immense attention from the whole scientific community. The Daqing River Basin (DRB), where the New Area is located, has become a new focus of hydrological scientists. The vegetation cover plays a key role in hydrological and biogeochemical cycles, serving as a reference to understand the ecological environment and water circulation status of the watershed. To analyse the current situation of climate and vegetation changes in the DRB, kriging interpolation, moving average, trend analysis of Theil–Sen median, and Mann-Kendall statistical test were used based on ground-based observation data and Moderate-resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data. The annual mean values of NDVI showed a significant upward trend from 2000 to 2015. The fluctuations in seasonal NDVI values followed this trend correspondingly to various extents. The variations in NDVI value positively correlated with those in temperature, both on the annual scale and during summer seasons (P ≤ 0.05). A large improvement in the vegetation cover of DRB was observed (54.21% of the areas), mainly distributed in the northeast of Mountainous Areas of Daqing River Basin and West Plain of Baiyangdian Lake. The findings might be helpful to understand the water and energy flux cycling in the changing environment of this region, providing guiding information on river basin management and the planning and construction of New Area.

Detailed Analysis of Estimated pH, Activity Coefficients, and Ion Concentrations between the Three Aerosol Thermodynamic Models.

In this work, we utilize a rich set of simulated and ground-based observational data in Tianjin, China to examine and compare the differences in aerosol acidity and composition predicted by three popular thermodynamic equilibrium models: ISORROPIA II, the Extended Aerosol Inorganics Model vision IV (E-AIM IV), and the Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients model (AIOMFAC). The species used to estimate aerosol acidity for both simulated and ambient data were NH4+, Na+, SO42-, NO3-, and Cl-. For simulated data, there is good agreement between ISORROPIA II and E-AIM IV predicted acidity in the forward and metastable mode, resulting from the hydrogen ion activity coefficient (γ(H+)) and the molality (m(H+)) showing opposite trends. While almost all other inorganic species concentrations are found to be similar among the three models, such is not the case for the bisulfate ion (HSO4-), which is linked to m(H+). We find that differences in predicted bisulfate between the three models primarily result from differences in the treatment of the HSO4- ↔ H+ + SO42- reaction for highly acidic conditions. This difference in bisulfate is responsible for much of the difference in estimated pH for the ambient data (average pH of 3.5 for ISORROPIA II and 3.0 for E-AIM IV).

Comparative Analyses of Vertical Structure of Deep Convective Clouds Retrieved from Satellites and Ground-Based Radars at Naqu over the Tibetan Plateau

In order to improve understanding of deep convective clouds over the Tibetan Plateau, characteristics of vertical structure of a deep strong convective cloud over Naqu station and a deep weak convective cloud approximately 100 km to the west of Naqu station, which occurred over 1300–1600 Beijing Time (BT) 9 July 2014 during the Third Tibetan Plateau Atmospheric Science Experiment (TIPEX-III), are analyzed, based on multi-source satellite data from TRMM, CloudSat, and Aqua, and radar data from ground-based vertically pointing radars (C-band frequency-modulated continuous-wave radar and KA-band millimeter wave cloud radar). The results are as follows. (1) The horizontal scales of both the deep strong and deep weak convective clouds were small (10–20 km), and their tops were high [15–16 km above sea level (ASL)]. Across the level of 0°C isotherm in the deep strong convective cloud, the reflectivity increased rapidly, suggesting that the melting process of solid precipitation particles through the 0°C level played an important role. A bright band located at 5.5 km ASL (i.e., 1 km above ground level) appeared during the period of convection weakening. (2) The reflectivity values from TRMM precipitation radar below 11 km were found to be overestimated compared to those derived from the C-band frequency-modulated continuous-wave radar. (3) Deep convective clouds were mainly ice clouds, and there were rich small ice particles above 10 km, while few large ice particles were found below 10 km. The microphysical processes of deep strong and deep weak convective clouds mainly included mixed-phase process and glaciated process, and the mixed-phase process can be divided into two types: one was the rimming process below the level of –25℃ (deep strong convective cloud) or –29℃ (deep weak convective cloud) and the other was aggregation and deposition process above that level. The latter process was accompanied with fast increase in ice particle effective radius. The above evidence from space-based and ground-based observational data further clarify the characteristics of vertical structure of deep convective clouds over the Tibetan Plateau, and provide a basis for the evaluation of simulation results of deep convective clouds by cloud models.

Analysis of the convective characteristics during the mutual evolution of an inverted trough/low vortex and its induced rainstorm over the northeastern Sichuan basin, China

Based on a variety of ground-based and satellite-derived observational data, we studied a flood-rainstorm event that occurred over northeastern Sichuan, China, from the 8th to the 14th of September 2014. Four periods of mesoscale convective system (MCS) activity were found during a mutual evolution process of an 850-hPa basin inverted trough (BIT) and 850-hPa basin low vortex (BLV). Among them, the first three periods occurred in an alternating evolution of the BIT and BLV (called the first stage), and then, the fourth period was stimulated by continuous activity of the BLV (called the second stage). During the first stage, MCSs enhanced (weakened) under the situation of the BIT (BLV), and then during the second stage MCSs developed to their strongest levels. Further analysis of the reasons behind the enhancement and weakening of MCSs revealed an obvious characteristic of upper level (lower level) positive (negative) divergence in the BIT situation of the first stage and BLV situation of the second stage. By comparison, under the BLV situation of the first stage, the vertical helicity was larger in the upward airflow of the zonal circulation, and the direction of the wet Q-vector was toward the ascending airflow in the vertical direction. In the horizontal direction, the negative divergence of the wet Q-vector corresponded to the position of water vapor flux convergence. In addition, in the early development of convection, sounding data showed a humidity profile of dry upper and wet lower levels, as well as a larger value of convective available potential energy, which triggered convective activity under the favorable dynamic conditions of atmosphere. When the above characteristics weakened, the convective activity also weakened. Therefore, the formation of multiple convective systems was closely related to the adjustment in atmospheric conditions around the BIT and BLV.

Favourable and Unfavourable Scenarii of Radiative Fog Formation Defined by Ground-Based and Satellite Observation Data

An innovative set of six observed predictors of fog formation by radiative cooling is proposed, which describes: 1) one of the main processes of fog formation that is the water uptake by aerosols at surface level; 2) the fog development along the vertical up to 30 meters, as well as the cloud cover; and 3) the temporal evolution of the parameters describing the water uptake by aerosols and the cloud cover. The visibility is used as a signal of atmospheric and surface processes affecting the water uptake by aerosols. The vertical fog development is described by the vertical thermal gradient along a 30-m meteorological mast. The cloud cover is described using a ceilometer for low and middle clouds above the instrument, and satellite data for clouds in a pixel and in a larger 9 × 9-pixel region around the site. The set of predictors can be observed in operational conditions, such as on airport fields. Data acquired at the SIRTA platform (Paris, France) during two autumns and two winters were analysed, and the cloud cover classification derived from the SEVIRI instrument on the METEOSAT Second Generation satellite by the EUMETSAT/NWCSAF program was also utilized. The training data set was acquired in November 2011 while the validation data set extended over 12 months. All situations were discriminated between favourable and unfavourable scenarii of radiative cooling fog formation, with a factor of 10 in probability. 246 moderate visibility events (with visibility between 5 and 10 km) were observed under a clear sky in 12 months at SIRTA. While developed fog formed according to one scenario, thin fog formed according to six scenarii. On the contrary to thin fog, developed fog did not form when cirrus clouds were observed above moderate visibility situations. The fog formation probability varied from 12 to 43%, and even reached 100% for one thin fog. As the training data set was acquired in autumn, the predictor set seems more appropriate to nowcast fog in humid autumn conditions, when the fog formation probability was multiplied by ~2. The predictive set could be enriched by predictors proposed in literature, and tests suggest that relative humidity would improve the fog formation probability in winter. Five predictors identify 65 of the 217 no-fog events counted in 12 months, with ~3 h anticipation time. If visibility decreased below 5 km, 88 additional no-fog events were identified. In this case, the formation probability was 35% for developed fog, and 24–60% for thin fog, but with an anticipation time reduced to ~1.5 h. Only one fog, which represents 3% of the fog events, would be missed with such a predictive scheme.

Space Weather Parameters: Modeling and Prediction from the Data of Groundbased Observations of Solar Activity

We consider the prospects for developing a forecast system for space weather (SPW) parameters with the use of home facilities for groundbased observations of solar activity. The space weather forecast can be conventionally divided into three components: (i) the prediction of recurrent, slowly changing events connected with the topology of the large-scale magnetic field, (ii) the estimation of fluxes of UV and high-energy radiation, and (iii) the observation of high-speed phenomena, such as solar flares and eruption processes, and the prediction of their consequences at the the Earth’s orbit. At present, to predict recurrent events, data from regular observations of the large-scale field of the Sun by the solar telescope–magnetographs for operative (realtime) prediction (STOP) are effectively used. To estimate high-energy fluxes, to register eruption events, and to estimate their geoefficiency, data from the patrol optical telescope–spectrographs may be used. Patrol telescopes operate in automatic mode and register the processes with an interval of approximately one minute. To detect eruption processes, we propose a method based on the difference between the intensity values in the wings of chromospheric spectral lines. The results of the use of the observational complex of the Kislovodsk Mountain Astronomical Station for the SW forecast are considered in the paper.

A possibility of determination of earth surface radiation budget from calculated and satellite data

The possibility is considered ofusing calculated and satellite data in addition to the results of direct actinometric observations in order to maintain the series of Earth surface radiation budget and to study its spatial variability. The empirical relationships are obtained based on the regression analysis of atmospheric radiation and meteorological parameters using the data of long-term observations in Lomonosov Moscow State University Meteorological Observatory (MSU MO). Satellite data needed to compute the Earth surface radiation budget are compared with the respective data of ground-based observations in MSU MO, and the possibility of using them is assessed.

The dust environment of comet 67P/Churyumov–Gerasimenko: results from Monte Carlo dust tail modelling applied to a large ground-based observation data set

We present an extensive data set of ground-based observations and models of the dust environment of comet 67P/Churyumov–Gerasimenko covering a large portion of the orbital arc from about 4.5 au pre-perihelion through 3.0 au post-perihelion, acquired during the current orbit. In addition, we have also applied the model to a dust trail image acquired during this orbit, as well as to dust trail observations obtained during previous orbits, in both the visible and the infrared. The results of the Monte Carlo modelling of the dust tail and trail data are generally consistent with the in situ results reported so far by the Rosetta instruments Optical, Spectroscopic, and Infrared Remote Imaging System (OSIRIS) and Grain Impact Analyser and Dust Accumulator (GIADA). We found the comet nucleus already active at 4.5 au pre-perihelion, with a dust production rate increasing up to ∼3000 kg s−1 some 20 d after perihelion passage. The dust size distribution at sizes smaller than r = 1 mm is linked to the nucleus seasons, being described by a power law of index −3.0 during the comet nucleus southern hemisphere winter but becoming considerably steeper, with values between −3.6 and −4.3, during the nucleus southern hemisphere summer, which includes perihelion passage (from about 1.7 au inbound to 2.4 au outbound). This agrees with the increase of the steepness of the dust size distribution found from GIADA measurements at perihelion showing a power index of −3.7. The size distribution at sizes larger than 1 mm for the current orbit is set to a power law of index −3.6, which is near the average value of in situ measurements by OSIRIS on large particles. However, in order to fit the trail data acquired during past orbits previous to the 2009 perihelion passage, a steeper power-law index of −4.1 has been set at those dates, in agreement with previous trail modelling. The particle sizes are set at a minimum of r = 10 μm, and a maximum size, which increases with decreasing heliocentric distance, in the 1–40 cm radius domain. The particle terminal velocities are found to be consistent with the in situ measurements as derived from the instrument GIADA on board Rosetta.

Many-year variations of river runoff in the Selenga basin

Many-year variations of river runoff in the Selenga basin are analyzed along with precipitation, potential evapotranspiration, and basin water storages. Data of ground-based (1932–2015) and satellite observations, as well as the analysis of literature data suggest the presence of within-century cycles in the series of annual and minimum runoff. Compared with 1934–1975, the Selenga Basin shows a general tendency toward a decrease in the maximum (by 5–35%) and mean annual (up to 15%) runoff at an increase in the minimum runoff (by 30%), a decrease in the mean annual precipitation (by 12%), and an increase in potential evapotranspiration by 4% against the background of a decrease in evaporation because of lesser soil moisture content and an increase in moisture losses for infiltration because of permafrost degradation. The observed changes in water balance may have unfavorable environmental effects.

Evaluation of snow storage in Western Siberia based on the land-surface model SPONSOR simulation using reanalysis data

Obtaining of reliable information about the characteristics of snow cover with high spatial and temporal resolution for large areas of Northern Eurasia, with rare or absent network of ground-based observations stations is an important and urgent task. Currently estimation of the value of the snow water equivalent (SWE) and the snow depth have a large degree of uncertainty, especially if we are moving from data at the point of observation stations to distributed space values. In this article, the simulations of SWE and the snow depth using Land-Surface Model (LSM) SPONSOR with input meteorological data taken from the ECMWF ERAInterim reanalysis was performed for Western Siberia for the period from 1979 to 2013. Fields of SWE and of the snow depth with high spatial and temporal resolution corresponding to the resolution of meteorological data of the ECMWF ERA-Interim reanalysis (time step of 6 hours, the grid resolution of 0.75° × 0.75° in latitude and longitude) were obtained. For the entire period SWE data were compared with observations, as simulated using the model and taken directly from the reanalysis ERA-Interim at points corresponding of observation stations. Also comparison of observations and satellite data of SWE for points of observation stations was performed. Correlation coefficients between observations and model and satellite data for SWE and the snow depth were calculated for the period from 1979 to 2013. These correlation coefficients between observations and results of simulations using LSM SPONSOR for SWE, and especially for the snow depth are the best of all methods. Maps with high spatial resolution for SWE, obtained by different methods, were constructed for February averaged. Comparing of constructed maps shows significant uncertainty of the SWE fields, besides field’s distortions are not evenly distributed across the region. It appears that no one of these methods currently can be used as a reference (unique) to determine SWE in the absence of data of ground-based observations. Overall, model simulations using LSM SPONSOR somewhat overstate SWE, however, this overestimation is not more than 10–20% for most part of the territory, except in the South. Model data are reasonably well reproduce SWE for Central, Eastern and, most probably, for Northern parts of the region, differing from a real at 10–15%. Data from used satellite archive a few underestimate of SWE. SWE data taken directly from the reanalysis ERA-Interim, give large distortions of the SWE field: these values for Northern parts of the region, are likely greatly underestimated, and for Western and Eastern parts of the region – inflated. It is shown that in general, the method of simulation of snow cover characteristics using LSM SPONSOR with input data taken from the ECMWF ERA-Interim reanalysis gives good results for the region of Western Siberia.

Мониторинг аэрозольного загрязнения снежного покрова на основе наземной и спутниковой информации

Мониторинг аэрозольного загрязнения снежного покрова на основе наземной и спутниковой информации