Previous work has demonstrated interannual variability in the intensity and occurrence of snowfalls in different regions of the USA, although some long-term trends in these characteristics were revealed as well.

In our previous work we considered snowfall-events it as a factor of formation of snow-cover distribution (inhomogeneity of snow cover thickness) on the territory of Russia and also its stratigraphy.

Under the term of snowfall we understand an event of solid atmospheric precipitation (snow) with duration of certain period of time (up to one or several days) with intensity of not less than 0.1 mm per day and negative ambient temperature, i.e. under condition of presence of snow cover. Snowfalls’ intensity is characterized as a sum of precipitation (its snow water equivalent) during this snowfall.

For the time period of 1961-2016 on the basis of meteorological data for 45 stations situated on the territory of Russia (not less than two in each of 19 climatic regions) the events of snowfalls are determined, as well as theirs frequency and averaged intensity for each winter season.

Snowfalls’ spatial and temporal distribution is analyzed on the basis of the compiled maps of averaged values of snowfall’s frequency and intensity and the graphs of relation of snowfall’s frequency and intensity.

The materials of obtained distribution allow revealing of peculiarities in distribution of snowfalls on intensity for different regions and their possible impact on stratigraphy of snow thickness.

The materials of obtained distribution allow revealing of peculiarities in distribution of snowfalls on intensity for different regions and their possible impact on stratigraphy of snow thickness.

Russian State Hydrometeorological University

Keywords: GNSS, GLONASS, GPS, ionosphere, receiver, Internet of Things

Section A: Atmospheric Physics. Remote Sensing

Nowadays, the Internet of Things (IoT) is a rapidly growing technology that allows to integrate digital devices into a network. Using the IoT technology to collect information from a variety of Internet connected GNSS receivers provides a unique opportunity to obtain real-time information about the special and temporal distribution of ionospheric characteristics with high resolution. The ability to create a dense sensor network is achieved through the usage of cheap single-frequency GNSS receivers based on the Arduino technology. This approach can be implemented to obtain real-time data on the total electron content (TEC) of the ionosphere. The determination of the ionospheric delay of the radio signal of GLONASS/GPS satellite and the calculation of the ionospheric TEC are carried out directly in the GNSS receiver. The results are transmitted over a wireless communication channel via Internet to a cloud server, where maps of the TEC of the ionosphere are constructed.

All precipitation, falling above the trees, do not reach the ground. Part of it is retained in the canopy and eventually evaporates back into the atmosphere. This is known as intercepted rainfall. The process is influenced by various meteorological parameters of which we have mainly focused on drop size distribution.
Drop size distribution and rainfall in the open and throughfall under birch and pine trees have been measured since 2014 in Ljubljana, Slovenia. The results demonstrate that birch has intercepted 40% (± 32) and pine 68% (± 24) of rainfall on average per event. During the 146 individual events between 297 and 724,905 rain drops were recorded with the average drop diameter 0.73 mm (± 0.23) and average drop velocity 3.71 m/s (± 0.49).
We have closely analyzed the effect of DSD on interception by pine during two rainfall events of similar duration in June and July 2014. The June event was 75 minutes long heavy rainfall (10.2 mm) with short term intensity up to 0.36 mm/min. The July event was a moderate rainfall of 5.6 mm in 72 minutes with lower intensity up to 0.2 mm/min. The rainfall interception by pine was 53% and 65% during the first and the second event, respectively.
The rain drop diameter and velocity strongly affect the rainfall interception. In June event after 15 minutes drops with larger drop diameter (6.5 - 8.5 mm) were observed in the open causing an instant reduction of rainfall interception by pine for 30%. After that larger numbers of drops with diameter higher than average induced throughfall greater than the rainfall in the clearing. Similarly twice during the both events the groups of drops with higher velocity (7.6 - 10.4 m/s) were observed, causing the reduction in rainfall interception and for the June event inducing throughfall greater than the rainfall.

The evaluation of parameterization schemes in the WRF model for estimating temperature and precipitation during January and July 2015 is assessed all over Europe running in multinesting mode with grid resolutions of 108Km and 36Km. A step-wise decision approach is followed, beginning with 18 simulations for the various microphysics schemes followed by 45 more, concerning all of the model’s PBL, Cumulus, Long-wave, Short-wave and Land Surface schemes. Model evaluation is performed using gridded precipitation and temperature data from the ECA&D 0.25deg regular grid. The best performing scheme at each step is chosen by integrating the entropy weighting method ‘Technique for Order Performance by Similarity to Ideal Solution’ (TOPSIS). The results suggest that different climate variables are found to be sensitive to different physical parameterizations. Furthermore, improvement of the model’s performance is possible and highly region-related. The concluding scheme set consists of the Mansell-Ziegler-Bruning microphysics scheme, the Bougeault-Lacarrere PBL scheme, the Kain-Fritsch cumulus scheme and the RRTMG schemes for short-wave and long-wave radiation and a seasonal-variable sensitive option for the Land Surface scheme. Regarding 2m-temperature, a significant reduction of the maximum daily bias is achieved. Precipitation forecast is also improved reaching a reduction of the maximum daily bias for both months studied.

In this study, we conducted synoptic and mesoscale analyses to study the cause of the Japan Tsukuba tornado development, which occurred on 0340 UTC 6 May 2012. We analyzed surface and upper-level weather charts, thermodynamic diagram with hodograph and stability indices, moisture flux, SREH, isentropic analysis, PV, and Froude number. Prior to the tornado event, there was a circular jet stream over Japan and the surface was moist due to overnight precipitation. Circular jet stream brought cold and dry air to the upper-level and sky clearing with strong solar radiation heating the ground. A tornadic supercell developed in an area that was potentially unstable. Sounding data at Tateno showed a capping inversion at 900hPa on 0000 UTC 06 May. Strong insolation in the early morning hours and removal of the capping inversion instigated vigorous updraft with rotation due to vertical shear in the upper-level. This caused multiple tornadoes to occur from 0220 to 0340 UTC 6 May 2012. When comparing Tateno’s climatological temperature and dew-point temperature profile with that of the day of tornado, the mid-level was more moist than typical tornado sounding. This study shows that Tsukuba tornado development is due to a combination of a) topography and PV anomaly, which increased vorticity over the Kanto Plain; b) vertical shear, which produced horizontal vortex line; and c) thermal instability, which triggered supercell and tilted the vortex line in the vertical.

Seasonal range prediction over North America has been based on intraseasonal variability related to the Pacific North America (PNA) pattern as well as the interannual variability related to El Nino and Southern Oscillation (ENSO). These teleconnective phenomena have an impact on atmospheric blocking which also have an impact on long-term conditions for North America. Similar relationships may be of use for seasonal range prediction over South America as well. Previous studies have examined ENSO-related variability on the South Pacific Jetstream as well as that of atmospheric blocking. Using the National Centers for Environmental Prediction / National Center for Atmospheric Research (NCEP / NCAR) reanalyses, the character of the winter and summer season circulations were studied over the South Pacific / South America sector from 2000 – 2016. Initial results show that there is a negative correlation in the upper air circulation over the East Pacific and South America from winter to summer. Also, the interannual variability in the jet-stream pattern for the region as related to ENSO shows a 180 degrees phase difference. Finally, there is evidence that the circulation pattern for the 2000 – 2016 may be different from that of the latter part of the 20^th century as indicated by a recent reversal of the internannual variability of atmospheric blocking over the South Pacific Region.

A physical model representation of hydrogen, methane, radon, and elements of surface atmospheric electricity is constructed. Bubble formations of volatile gases capture from the depth of 4-6 m soil radon and carry it into the near-surface layers of the soil and atmosphere. In the process of ionization of atmospheric air, light ions responsible for polar air conduction are formed, and recombination of light ions with neutral condensation nuclei leads to the appearance of heavy ions, which determine the atmospheric electric field. The concentration of ground radon is at least 100 times greater than the radon concentration of the atmosphere. This means that elements of surface atmospheric electricity are extremely sensitive to the density of hydrogen and methane fluxes.
The increased content of methane over the oil deposit leads to an increase in radon exhalation, to a fall in the atmospheric electric field. Increased discharge of hydrogen and methane into the atmosphere is observed in fault zones, above the karst cavities. This, in turn, leads to an increase in the electrical conductivity of air and the fall of the atmospheric electric field.
The pumping of artesian water minimizes the release of volatile gases into the atmosphere, which causes an increase in the atmospheric electric field. The injection of fluid into the ground leads to the reverse process - the fall of the atmospheric electric field.

Increasing the amount of anthropogenic aerosols over the Himalayas modulate cloud properties, thereby altering cloud phase and cloud height, consequently influence formation and distribution of orographic precipitation. Moreover, further rises in global temperature may influence cloud properties by the ‘Clausius – Clapeyron effect’, which increases moisture holding capacity of air.

This study presents sensitivity of simulated cloud properties to aerosol and temperature perturbations using the Weather Research and Forecasting (WRF) model, coupled with a bulk microphysics scheme, in a convection permitting configuration applied to a complex topographical region, the Nepal Himalayas. We find that the effect of aerosol on the simulated rainfall is nonlinear, ranging from -3% to +4% depending on the investigated aerosol perturbation scenarios. The model results highlight a realistic simulation of the 1^st indirect (Twomey) effect. However,  the rainfall was not overly sensitive to the aerosol perturbations and not statistically significant at the 95% confidence interval. The oversimplified parameterization of ice phase processes, a dominant cloud formation process over the Himalayas, appears to play a crucial role in buffering the sensitivity to increased aerosol loading. Our results, however, show that aerosol perturbations may modify shape, size and spatial distribution of individual cloud and their precipitation production. In contrast, the impact of temperature perturbations is more than the aerosol effect, ranging from -17% to +93%, which is statistically significant at the 95% confidence interval, suggesting that more intense rain events are likely as the climate warms in this region.

The main objective of this paper is to implement different methods to assess the salient features of the data trend for a CO₂ and CH₄ data series. Said series was obtained at the Low Atmosphere Research Centre (41°48′49″ N, 4°55′59″ W) using a Picarro analyzer (G1301). Semi-hourly measurements from 15 October 2010 to 29 February 2016 were considered and divided into diurnal and nocturnal records.

Different functions with two terms, one for the trend and another for the annual cycle, were employed. The first was a harmonic function based on a third-degree polynomial and a series of four harmonics that considers the amplitude as a fixed and variable term over time. An increasing trend was reported, and was below 2.30 ppm year^-1 for CO₂ and below 11.90 ppb year^-1 for CH₄. Nocturnal amplitudes were higher than diurnal ones for both gases, except in winter due to anthropogenic emissions and lower assimilation rates. The second function was based on the kernel procedure. Epanechnikov, Gaussian, biweight, tricubic, rectangular and triangle kernels, were applied with a 500-day bandwidth for the trend. The best fit was obtained by the biweight kernel (r>0.38), with an increasing trend around 1.80 ppm year^-1 for CO₂ and around 7.15 ppb year^-1 for CH₄. The final analysis, which included local linear regression functions also applying a 500-day bandwidth, revealed increasing trends for both CO₂, around 1.98 ppm year^-1, and CH₄, around 10.85 ppb year^-1. Trend values were far more accelerated in the latter years of the series regardless of the chosen function.

Finally, the application of these functions to other terrestrial ecosystems would improve current knowledge of these gases in different environments, thereby increasing the effectiveness of climate change policies.

Global warming and changes in precipitation patterns are among the major effects of climate change. In this study, the long-term variability in ambient surface temperature and precipitation were evaluated in the north central region of Nigeria (Abuja, Kogi, Kwara, Niger, and Plateau) using meteorological observations obtained from 1975-2008. Daily precipitation data from synoptic weather stations were carefully quality-controlled using the RClimdex 1.1 developed by Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI). The quality-controlled dataset were homogenized using RHtestsV4 and the detected change points were adjusted. Results showed a decrease in cool nights and cool days (TN10P, TX10P), and increasing trend in warm nights and days (TN90P, TX90P). The trend in rainfall is variable compared to changes in temperature. The precipitation indices indicated increasing trend in total annual precipitation (PRCPTOT), and a significant decrease in the number of consecutive wet days (CWD) in this region. In general, regional changes in climate temperature and precipitation extremes were significant (p<0.05) and could result in serious climate induced effects.