What One Can Learn From the Cloud Condensation Nuclei (CCN) Size Distributions as Monitored by the BEO Moussala?

In this proceeding we report initial studies into the big data set acquired by the Cloud Condensation Nuclei (CCN) counter of the Basic Environmental Observatory (BEO) Moussala over the whole 2016 year at a frequency of 1 Hz. First, we attempt to reveal correlations between the results for CCN number concentrations on the timescale of a whole year (2016) as averaged over 12 month periods with the meteorological parameters for the same period and with the same time step. Then, we zoom into these data and repeat the study on the timescale of a month for two months from 2016, January and July, with a day time step. For the same two months we show the CCN size distributions averaged over day periods. Finally, we arrive at our main result: typical, in terms of maximal and minimal number concentrations, CCN size distributions for chosen hours, one hour for each month of the year, hence 24 distributions in total. These data show a steady pattern of peaks and valleys independent of the concrete number concentration which moves up and down the number concentrations (y-axis) without significant shifts along the sizes (x-axis).Comment: 6 pages, 4 figure, The 10th Jubilee Conference of the Balkan Physical Union (BPU10), 26-30 August, Sofia, Bulgari

Vegetation greenness sensitivity to precipitation and its oceanic and terrestrial component in selected biomes and ecoregions of the world

In this study, we conducted a global assessment of the sensitivity of vegetation greenness (VGS) to precipitation and to the estimated Lagrangian precipitation time series of oceanic (PLO) and terrestrial (PLT) origin. The study was carried out for terrestrial ecosystems consisting of 9 biomes and 139 ecoregions during the period of 2001–2018. This analysis aimed to diagnose the vegetative response of vegetation to the dominant component of precipitation, which is of particular interest considering the hydroclimatic characteristics of each ecoregion, climate variability, and changes in the origin of precipitation that may occur in the context of climate change. The enhanced vegetation index (EVI) was used as an indicator of vegetation greenness. Without consideration of semi-arid and arid regions and removing the role of temperature and radiation, the results show the maximum VGS to precipitation in boreal high-latitude ecoregions that belong to boreal forest/taiga: temperate grasslands, savannas, and shrublands. Few ecoregions, mainly in the Amazon basin, show a negative sensitivity. We also found that vegetation greenness is generally more sensitive to the component that contributes the least to precipitation and is less stable throughout the year. Therefore, most vegetation greenness in Europe is sensitive to changes in PLT and less to PLO. In contrast, the boreal forest/taiga in northeast Asia and North America is more sensitive to changes in PLO. Finally, in most South American and African ecoregions, where PLT is crucial, the vegetation is more sensitive to PLO, whereas the contrast occurs in the northern and eastern ecoregions of Australia.Agencia Estatal de Investigación | Ref. PID2021-122314OB-I00Xunta de Galicia | Ref. ED431C 2021/44Xunta de Galicia | Ref. ED481B-2021/134Xunta de Galicia | Ref. ED481D 2022/020Agencia Estatal de Investigación | Ref. RYC2021-034044-

Chemical nonlinearities in relating intercontinental ozone pollution to anthropogenic emissions

Model studies typically estimate intercontinental influence on surface ozone by perturbing emissions from a source continent and diagnosing the ozone response in the receptor continent. Since the response to perturbations is non-linear due to chemistry, conclusions drawn from different studies may depend on the magnitude of the applied perturbation. We investigate this issue for intercontinental transport between North America, Europe, and Asia with sensitivity simulations in three global chemical transport models. In each region, we decrease anthropogenic emissions of NOx and nonmethane volatile organic compounds (NMVOCs) by 20% and 100%. We find strong nonlinearity in the response to NOx perturbations outside summer, reflecting transitions in the chemical regime for ozone production. In contrast, we find no significant nonlinearity to NOx perturbations in summer or to NMVOC perturbations year-round. The relative benefit of decreasing NOx vs. NMVOC from current levels to abate intercontinental pollution increases with the magnitude of emission reductions

Tropospheric Products from High-Level GNSS Processing in Latin America

ARTÍCULO PUBLICADO EN REVISTA EXTERNA. The present geodetic reference frame in Latin America and the Caribbean is given by a network of about 400 continuously operating GNSS stations. These stations are routinely processed by ten Analysis Centres following the guidelines and standards set up by the International Earth Rotation and Reference Systems Service (IERS) and International GNSS Service (IGS). The Analysis Centres estimate daily and weekly station positions and station zenith tropospheric path delays (ZTD) with an hourly sampling rate. This contribution presents some attempts aiming at combining the individual ZTD estimations to generate consistent troposphere solutions over the entire region and to provide reliable time series of troposphere parameters, to be used as a reference. The study covers ZTD and IWV series for a time-span of 5 years (2014–2018). In addition to the combination of the individual solutions, some advances based on the precise point positioning technique using BNC software (BKG NTRIP Client) and Bernese GNSS Software V.5.2 are presented. Results are validated using the IGS ZTD products and radiosonde IWV data. The agreement was evaluated in terms of mean bias and rms of the ZTD differences w.r.t IGS products (mean bias 1.5 mm and mean rms 6.8 mm) and w.r.t ZTD from radiosonde data (mean bias 2 mm and mean rms 7.5 mm). IWV differences w.r.t radiosonde IWV data (mean bias 0.41 kg/m2 and mean rms 3.5 kg/m2).Sitio de la revista: https://link.springer.com/chapter/10.1007/1345_2020_12

An evaluation of real-time troposphere estimation based on GNSS Precise Point Positioning

It is anticipated that the performance of real-time (RT) GNSS meteorology can be further improved by incorporating observations from multiple Global Navigation Satellite System (GNSS), including GPS, GLONASS, Galileo, and BeiDou. In this paper, an operational RT system for extracting zenith troposphere delay (ZTD) using a modified version of the Precise Point Positioning With Integer and Zero-difference Ambiguity Resolution Demonstrator (PPP-WIZARD) was established. GNSS, including GPS, GLONASS, and Galileo, observation streams were processed using RT Precise Point Positioning (PPP) strategy based on RT satellite orbit/clock products from the Centre National d'Etudes Spatiales. An experiment covering 30 days was conducted, in which the observation streams of 20 globally distributed stations were processed. The initialization time and accuracy of the RT troposphere results using single-system and multisystem observations were evaluated. The effect of PPP ambiguity resolution was also evaluated. Results reveal that RT troposphere estimates based on single-system observations can both be applied in weather nowcasting, in which the GPS-only solution is better than the GLONASS-only solution. The performance can also be improved by PPP ambiguity resolution and utilizing GNSS observations. Specifically, we notice that ambiguity resolution is more effective in improving the accuracy of ZTD, whereas the initialization process can be better accelerated by GNSS observations. Combining all techniques, the RT troposphere results with an average accuracy of about 8 mm in ZTD can be achieved after an initialization process of approximately 8.5 min, which demonstrates superior results for applying GNSS observations and ambiguity resolution for RT meteorological applications

GNSS Storm Nowcasting Demonstrator for Bulgaria

Global Navigation Satellite System (GNSS) is an established atmospheric monitoring technique delivering water vapour data in near-real time with a latency of 90 min for operational Numerical Weather Prediction in Europe within the GNSS water vapour service (E-GVAP). The advancement of GNSS processing made the quality of real-time GNSS tropospheric products comparable to near-real-time solutions. In addition, they can be provided with a temporal resolution of 5 min and latency of 10 min, suitable for severe weather nowcasting. This paper exploits the added value of sub-hourly real-time GNSS tropospheric products for the nowcasting of convective storms in Bulgaria. A convective Storm Demonstrator (Storm Demo) is build using real-time GNSS tropospheric products and Instability Indices to derive site-specific threshold values in support of public weather and hail suppression services. The Storm Demo targets the development of service featuring GNSS products for two regions with hail suppression operations in Bulgaria, where thunderstorms and hail events occur between May and September, with a peak in July. The Storm Demo real-time Precise Point Positioning processing is conducted with the G-Nut software with a temporal resolution of 15 min for 12 ground-based GNSS stations in Bulgaria. Real-time data evaluation is done using reprocessed products and the achieved precision is below 9 mm, which is within the nowcasting requirements of the World Meteorologic Organisation. For the period May–September 2021, the seasonal classification function for thunderstorm nowcasting is computed and evaluated. The probability of thunderstorm detection is 83%, with a false alarm ration of 38%. The added value of the high temporal resolution of the GNSS tropospheric gradients is investigated for a storm case on 24–30 August 2021. Real-time tropospheric products and classification functions are integrated and updated in real-time on a publicly accessible geoportal

A global model study of ozone enhancement during the August 2003 heat wave in Europe

The European summer of 2003 was characterised by intense heat, prolonged isolation and suppressed ventilation of the boundary layer which, combined with large anthropogenic emissions and strong fires, resulted in a build up of an unprecedentedly high and long-lasting photochemical smog over large parts of the continent. In this work, a global chemistry and transport model GEOS-Chern is compared with surface O-3 concentrations observed in 2003 in order to examine the extent to which the model is capable of reproducing such an extreme event. The GEOS-Chem reproduces the temporal variation of O-3 at the Jungfraujoch mountain site, Switzerland, including the enhanced concentrations associated with the August 2003 heat wave (r = 0.84). The spatial distribution of the enhanced surface O-3 over Spain, France, Germany and Italy is also captured to some extent (r = 0.63), although the largest concentrations appear to be located over the Italian Peninsula in the model rather than over Central Europe as suggested by the surface O-3 observations. In general, the observed differences between the European averaged O-3 concentrations in the summer of 2003 to those in 2004 are larger in the observations than in the model, as the model reproduces relatively well the enhanced levels in 2003 but overestimates those observed in 2004. Preliminary contributions of various sources to the O-3 surface concentrations over Europe during the heat wave indicate that anthropogenic emissions from Europe contribute the most to the O-3 build up near the surface (40 to 50%, i.e. 30 ppb). The contribution from anthropogenic emissions from the other major source regions of the northern hemisphere, in particular North America, tends to be smaller than those of other years. The model indicates that the large fires that occurred in that year contributed up to 5% (3 ppb) to surface O-3 in close proximity to the fire regions and less elsewhere in Europe. Biogenic volatile organic compounds (VOCs) emitted by grass and forest areas contributed up to 10% (5-6 ppb) of surface O-3 over France, Germany and northern Italy, which represents a contribution that is twice as large than that found in 2004. These results in terms of contributions from various sources, particularly biogenic emissions, should be seen as preliminary, as the response of vegetation to such extreme events may not be well represented in the model

Thunderstorm Classification Functions Based on Instability Indices and GNSS IWV for the Sofia Plain

Bulgaria is a country with a high frequency of hail and thunderstorms from May to September. For the May–September 2010–2015 period, statistical regression analysis was applied to identify predictors/classification functions that contribute skills to thunderstorm forecasting in the Sofia plain. The functions are based on (1) instability indices computed from radiosonde data from Sofia station F1, and (2) combination of instability indices and Integrated Water Vapor (IWV), derived from the Global Navigation Satellite System (GNSS) station Sofia-Plana, F2. Analysis of the probability of detection and the false alarm ratio scores showed the superiority of the F2 classification function, with the best performance in May, followed by June and September. F1 and F2 scores were computed for independent data samples in the period 2017–2018 and confirmed the findings for the 2010–2015 period. Analysis of IWV and lightning flash rates for a multicell and supercell thunderstorm in June and July 2014 showed that the monthly IWV thresholds are reached 14.5 and 3.5 hours before the thunderstorm, respectively. The supercell IWV peak registered 40 min before the thunderstorm, followed by a local IWV minimum corresponding to a peak in the flash rate. In both cases, an increase of IWV during severe hail was registered, which is likely related to the hydrometeor contribution to GNSS path delay. The results of this study will be integrated into the Bulgarian Integrated NowCAsting tool for thunderstorm forecasting in the warm/convective season

Foehn classification and climatology in Sofia for 1975–2014

Foehn is a warm, dry, and downslope wind blowing in the lee side of a mountain range. It is a well known example of a local atmospheric circulation. The foehn wind is also an extreme weather event, and its forecasting is an important task for the short-range weather forecaster. The foehn in Bulgaria is observed on the northern slopes of the mountains, as a result of warm air advection from the south and southwest. Its occurrence is highest north of the Vitosha and Balkan mountains. In this study, a synoptic classification of the meteorological conditions leading to foehn in the central meteorological station in Sofia for the period 1975–2014 is made. Foehn climatology is prepared, and in addition, an evaluation of the foehn as an extreme weather event by wind gust is presented. For the period 1975–2014, there were 298 days with foehn in Sofia, which resulted from 220 synoptic cases. A manual foehn classification was developed with four major types. Type I is associated with the Mediterranean cyclone with the highest frequency – 52% of the foehn days. Foehn climatology gives average annual number of 7.5 foehn days but with a large variance between decades. The lowest annual number of days (4.5) is registered for the 2005–2014 period, and it was associated with the lowest recorded wind gust (22 m/s)

Analysis of the 2014 Wet Extreme in Bulgaria: Anomalies of Temperature, Precipitation and Terrestrial Water Storage

Impact on the hydrology cycle is projected to be one of the most noticeable consequences of climate change. An increase in regional dry and wet extremes has already been observed, resulting in large socioeconomic losses. The 2014 wet conditions in Bulgaria present a valuable case study for analyzing the interaction between multiple drivers that are essential for early forecasting and warning of flood events. In this paper, time series analysis of temperature, precipitation and Terrestrial Water Storage Anomaly (TWSA) is performed and cross-correlations between observations and climate variability indices are computed for a 12-year period. In Bulgaria, a positive linear temperature trend was found with precipitation and TWSA exhibiting negative trends for the period 2003 - 2014. The year 2014 started with a drier and warmer than usual winter followed by five consecutive wet months from March to July. We found the following long-term variations: (1) temperature showing a local minimum in November 2014, (2) precipitation peaks in July 2014 and (3) a local TWSA maximum in December 2014. Over a 12-year period, weak to moderate negative correlations were observed between the long-term components of temperature, precipitation and TWSA. Moderate positive correlations with a 3 to 6-month lag were obtained between precipitation and TWSA long-term components. The long-term trends of temperature and precipitation from surface observations and atmospheric reanalysis showed very good alignment. Very large subseasonal precipitation residuals from observations and atmospheric reanalysis were obtained for April and September 2014. Two oscillation indices showed: (1) weak correlations with precipitation and (2) weak to moderate correlations with TWSA