Avifauna diversity and phenology in a Ramsar site: Lake Tonga (Northeastern Algeria)

Between 2013 and 2016 we conducted an inventory and characterization of aquatic avifauna at Lake Tonga, a Ramsar site. We identified 61 species belonging to 17 families, dominated by Anatidae with 14 species. The inventoried species have different phenological status. Some are known for their regular wintering and some for their summer concentrations, while others are residents year round. Population analysis showed the presence of endangered species such as Oxyura leucocephala, Marmaronetta angustirostris and Aythya nyroca, that are protected by national and/or international laws. Bird counts showed monthly variations in total abundance and richness, peaking during winter. Peak numbers were recorded in February and January, reflecting gatherings to prepare for prenuptial migration. Analysis of diversity and equitability indices indicated that maximum values ​​were generally recorded during the pre– and post–nuptial passages (H’= 3.51 and E = 0.72). Our results reflect the importance of this wetland as a wintering site and nesting site for numerous waterbirds species.

Investigating the Campylobacter enteritis winter peak in Germany, 2018/2019

Surveillance of notified Campylobacter enteritis in Germany revealed a recurrent annual increase of cases with disease onset several days after the Christmas and New Year holidays (“winter peak”). We suspected that handling and consumption of chicken meat during fondue and raclette grill meals on the holidays were associated with winter peak Campylobacter infections. The hypothesis was investigated in a case–control study with a case-case design where notified Campylobacter enteritis cases served as case-patients as well as control-patients, depending on their date of disease onset (case-patients: 25/12/2018 to 08/01/2019; control-patients: any other date between 30/11/2018 and 28/02/2019). The study was conducted as an online survey from 21/01/2019 to 18/03/2019. Adjusted odds ratios (aOR) were determined in single-variable logistic regression analyses adjusted for age group and sex. We analysed 182 data sets from case-patients and 260 from control-patients and found associations of Campylobacter infections after the holidays with meat fondue (aOR 2.2; 95% confidence interval (CI) 1.2–3.8) and raclette grill meals with meat (aOR 1.5; 95% CI 1.0–2.4) consumed on the holidays. The associations were stronger when chicken meat was served at these meals (fondue with chicken meat: aOR 2.7; 95% CI 1.4–5.5; raclette grill meal with chicken meat: aOR 2.3; 95% CI 1.3–4.1). The results confirmed our initial hypothesis. To prevent Campylobacter winter peak cases in the future, consumers should be made more aware of the risks of a Campylobacter infection when handling raw meat, in particular chicken, during fondue or raclette grill meals on the holidays.

Contributions to Polar Amplification in CMIP5 and CMIP6 Models

As a step towards understanding the fundamental drivers of polar climate change, we evaluate contributions to polar warming and its seasonal and hemispheric asymmetries in Coupled Model Intercomparison Project phase 6 (CMIP6) as compared with CMIP5. CMIP6 models broadly capture the observed pattern of surface- and winter-dominated Arctic warming that has outpaced both tropical and Antarctic warming in recent decades. For both CMIP5 and CMIP6, CO2 quadrupling experiments reveal that the lapse-rate and surface albedo feedbacks contribute most to stronger warming in the Arctic than the tropics or Antarctic. The relative strength of the polar surface albedo feedback in comparison to the lapse-rate feedback is sensitive to the choice of radiative kernel, and the albedo feedback contributes most to intermodel spread in polar warming at both poles. By separately calculating moist and dry atmospheric heat transport, we show that increased poleward moisture transport is another important driver of Arctic amplification and the largest contributor to projected Antarctic warming. Seasonal ocean heat storage and winter-amplified temperature feedbacks contribute most to the winter peak in warming in the Arctic and a weaker winter peak in the Antarctic. In comparison with CMIP5, stronger polar warming in CMIP6 results from a larger surface albedo feedback at both poles, combined with less-negative cloud feedbacks in the Arctic and increased poleward moisture transport in the Antarctic. However, normalizing by the global-mean surface warming yields a similar degree of Arctic amplification and only slightly increased Antarctic amplification in CMIP6 compared to CMIP5.

Pollen antigens and atmospheric circulation driven seasonal respiratory viral outbreak and its implication to the Covid-19 pandemic

The patterns of respiratory virus illness are expressed differently between temperate and tropical climates. Tropical outbreaks often peak in wet seasons. Temperate outbreaks typically peak during the winter. The prevailing causal hypotheses focus on sunlight, temperature and humidity variations. Yet no consistent factors have been identified to sufficiently explain seasonal virus emergence and decline at any latitude. Here we demonstrate close connections among global-scale atmospheric circulations, IgE antibody enhancement through seasonal pollen inhalation, and respiratory virus patterns at any populated latitude, with a focus on the US. Pollens emerge each Spring, and the renewed IgE titers in the population are argued to terminate each winter peak of respiratory illness. Globally circulated airborne viruses are postulated to subsequently deposit across the Southern US during lower zonal geostrophic winds each late Summer. This seasonally refreshed viral load is postulated to trigger a new influenza outbreak, once the existing IgE antibodies diminish to a critical value each Fall. Our study offers a new and consistent explanation for the seasonal diminishment of respiratory viral illnesses in temperate climates, the subdued seasonal signature in the tropics, the annually circulated virus phenotypes, and the northerly migration of influenza across the US every year. Our integrated geospatial and IgE hypothesis provides a new perspective for prediction, mitigation and prevention of the outbreak and spread of seasonal respiratory viruses including Covid-19 pandemic.

The “Inverse” Seasonal Blood Pressure Variability Phenotype

The seasonal blood pressure variability (BPV) is known to demonstrate a typical winter peak. Recently, more attention is paid to the opposite situation: the summer BP levels being higher than those in winter. This phenomenon is called inverse BPV. The present article summarizes recent data on this topic. The data of the HOMED-BP project, as well as the results of the original prospective study in 770 hypertensive patients from two Russian Federation regions (mean follow-up duration 6.4 years), were used. According to the preliminary knowledge, the prevalence of inverse BPV in hypertensive patients is relatively high (15-25%). This phenomenon is more typical for treated patients, particularly for those on combination therapy, and is associated with beta-blocker intake. Higher duration of hypertension and higher levels of some risk factors (smoking) characterize the patients with inverse BPV. According to the HOMED-BP data, patients with inverse BPV had the highest overall cardiovascular risk (hazard ratio in comparison with the reference group of “minimal” “normal” BPV was 3.07; p=0.004). In summary, inverse BPV is a potentially unfavorable BP phenotype. However, its reproducibility and prospective value deserve further investigation. The absolute magnitude of seasonal BPV in these patients, calculated using different BP measurement methods, warrants special attention.

Comparison of seasonal and longitudinal variation of daytime MSTID activity using GPS observation and GAIA simulations

The total electron content (TEC) data derived from the GAIA (Ground-to-topside model of Atmosphere Ionosphere for Aeronomy) is used to study the seasonal and longitudinal variation of occurrence of medium-scale traveling ionospheric disturbances (MSTIDs) during daytime (09:00–15:00 LT) for the year 2011 at eight locations in northern and southern hemispheres, and the results are compared with ground-based Global Positioning System (GPS)-TEC. To derive TEC variations caused by MSTIDs from the GAIA (GPS) data, we obtained detrended TEC by subtracting 2-h (1-h) running average from the TEC, and calculated standard deviation of the detrended TEC in 2 h (1 h). MSTID activity was defined as a ratio of the standard deviation to the averaged TEC. Both GAIA simulation and GPS observations data show that daytime MSTID activities in the northern and southern hemisphere (NH and SH) are higher in winter than in other seasons. From the GAIA simulation, the amplitude of the meridional wind variations, which could be representative of gravity waves (GWs), shows two peaks in winter and summer. The winter peak in the amplitude of the meridional wind variations coincides with the winter peak of the daytime MSTIDs, indicating that the high GW activity is responsible for the high MSTID activity. On the other hand, the MSTID activity does not increase in summer. This is because the GWs in the thermosphere propagate poleward in summer, and equatorward in winter, and the equatorward-propagating GWs cause large plasma density perturbations compared to the poleward-propagating GWs. Longitudinal variation of daytime MSTID activity in winter is seen in both hemispheres. The MSTID activity during winter in the NH is higher over Japan than USA, and the MSTID activity during winter in the SH is the highest in South America. In a nutshell, GAIA can successfully reproduce the seasonal and longitudinal variation of the daytime MSTIDs. This study confirms that GWs cause the daytime MSTIDs in GAIA and amplitude and propagation direction of the GWs control the noted seasonal variation. GW activities in the middle and lower atmosphere cause the longitudinal variation.

Regionalization of seasonal precipitation over the Tibetan Plateau and associated large-scale atmospheric systems

Precipitation over the Tibetan Plateau (TP) has major societal impacts in South and East Asia, but its spatiotemporal variations are not well understood mainly because of the sparsely distributed in-situ observation sites. With help of the Global Precipitation Measurement satellite product IMERG and ERA5 reanalysis, distinct precipitation seasonality features over the TP were objectively classified using a self-organizing map algorithm fed with ten-day averaged precipitation from 2000 to 2019. The classification reveals three main precipitation regimes with distinct seasonality of precipitation: winter peak, centered at the western plateau; early summer peak, found on the eastern plateau; and late summer peak, mainly located on the southwestern plateau. On a year-to-year basis, the winter peak regime is relatively robust, while the early summer and late summer peak regimes tend to shift mainly between the central and northern TP, but are robust in the eastern and southwestern TP. A composite analysis shows that the winter peak regime experiences larger amounts of precipitation in winter and early spring when the westerly jet is anomalously strong to the north of the TP. Precipitation variations in the late summer peak regime are associated with intensity changes in the South Asian High and Indian summer monsoon. The precipitation in the early summer peak regime is correlated with the Indian summer monsoon together with anticyclonic circulation over the western North Pacific. The results provide a basic understanding of precipitation seasonality variations over the TP and associated large-scale conditions.

Analysis of Solar Power and Energy Variability Through Site Adaptation of Satellite Data With Quality Controlled Measured Solar Radiation Data

Satellite-based solar power data is becoming more and more important because of its continuous temporal and spatial availability. However, its reliability can be enhanced through quality control and calibration against ground-based measurement data. Here, a holistic methodology is employed for the adaptation of satellite-based data for estimating solar energy. For the purpose, high-quality ground-based measurement data and satellite-based datasets are assessed across 12 sites in three small islands located in the Indian Ocean. Initially, both datasets go through a rigorous quality control process. A quantitative analysis of irradiance and insolation data is then conducted. Eventually, site adaptation of satellite-based data is performed using bias removal technique and statistical analysis of datasets. A set of seven statistical performance indicators is used to support the assessment. Analysis of datasets shows that adaptation of peak values should be performed separately. Results showed that despite the small surface areas of the islands studied, a spatial variation of insolation can be depicted. A temporal variation of insolation is also noted with a peak in the summer and low insolation levels in winter. Peak irradiance values tend to exceed solar constant for all sites. Variations of peak irradiance can only be noticed in ground-based measurement data. While insolation levels are comparable in the summer season for all the sites, insolation levels in the winter season are higher in the sites with lower latitudes. Calibration factors for peak irradiance, monthly and annual average irradiance as well as yearly insolation are presented.