Climate changes and trends over India

Based on the instrumental observations of over a century available in India, attempt is made to study if there is a clear-cut evidence of any climate change or trend over .India with particular reference to rainfall, surface temperature, atmospheric pressure and total ozone. The study concludes that while there are year to year random. fluctuations in these atmospheric variables and there are certain epochal increases and decreases in respect of rainfall and .surface temperature, .there appears to be no systematic climate charge or trend over India. There IS also no evidence of ozone depletion over India.

MODELING THE DEVELOPMENTS IN URBANISATION AND RELATIONSHIP WITH VEGETATION COVER IN ALANYA

The increase in the world population and the migration of people from rural to urban areas causes an increase in artificial surfaces and causes many negative effects on the ecosystem, regional climate variations and global diversity. Nowadays, as the effects of climate change are felt more and more, it has gained importance in researches on this subject. Therefore, the estimation of the change in the vegetation density for the coming years and the determination of the land use / land cover (LULC) change in cities are very essential for urban planning. In this study, the effects of regional urbanization on vegetation are examined by using satellite data and atmospheric variables. In the vegetation analysis, multi-time index values obtained from TERRA-MODIS satellite, EVI (Enhanced Vegetation Index) and LST (Land Surface Temperature) were taken into account between the years of 2005 and 2018 in Alanya, Turkey. Temperature and precipitation were selected as the atmospheric variables and expected variations in EVI value until 2030 were estimated. In the study employed a wavelet-transformed artificial neural network (WANN) model to generate long-term (12-year) EVI forecasts using LST, temperature and precipitation. The relationship between land use / land cover and urbanization is investigated with NDBI (Normalized Difference Built-up Index) data obtained from the Landsat 8 OLI / TIRS satellite sensor. The simulation results show that The EVI value, which was 0.30 in 2018, will decrease to 0.25 in 2030.

Ensemble Forecasting Experiments Using the Breeding of Growing Modes with Perturbed Land Variables

Although land surface influences atmospheric processes significantly, insufficient studies have been conducted on the ensemble forecasts using the breeding of growing modes (BGM) with perturbed land surface variables. To investigate the practicability of perturbed land variables for ensemble forecasting, we used the ARWv3 mesoscale model to generate ensembles for an event of 24 h heavy rainfall with perturbed atmospheric and land variables by the BGM method. Results show that both atmospheric and land variables can generate initial perturbations with BGM, except that they differ in time and saturation characteristics, e.g., saturation is generally achieved in approximately 30 h with a growth rate of ~1.30 for atmospheric variables versus 102 h and growth rate of 1.02 for land variables. With the increase in precipitation, the importance of the perturbations of land variables also increases as compared to those of atmospheric variables. Moreover, the influence of the perturbations of land variables on simulated precipitation is still relatively large, although smaller than that of atmospheric variables, e.g., the spreads of perturbed atmospheric and land subsets were 7.3 and 3.8 mm, respectively. The benefits of perturbed initialisation can also be observed in terms of probability forecast. All findings indicate that the BGM method with perturbed land variables has the potential to ensemble forecasts for precipitation.

A study of atmospheric boundary layer characteristics with ground snow cover - numerical method

ABSTRACT. A one-dimensional version of a mesoscale model was used to simulate the atmospheric variables over ground snow cover after incorporating suitable modifications. Modifications to include the effect of cloud on shortwave and long wave radiation were also made in the model. The model takes into account both the heat balance at the snow surface and at various layers of the snow pack and calculates the melt rate in situ. Srinagar (Jammu & Kashmir) winter data was used for the simulations. The diurnal variation of snowmelt rate and other atmospheric variables were simulated simultaneously by the model. Melt rate values were verified with the values obtained from standard empirical formula. The model-simulated profiles of potential temperature, specific humidity and wind speed were found to be in reasonable agreement with available observations. The results were found to be insensitive to changes in surface drag coefficients.

Multi-sensor analyses of the skin temperature for the assimilation of satellite radiances in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS, cycle 47R1)

The assimilation of clear-sky radiance in the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric analysis relies on the clear-sky radiances observation operator. Some of these radiances have frequencies that make them sensitive to both the surface and atmosphere. Because the atmospheric and surface analyses are currently not strongly coupled, a specific treatment of the surface is required. The observation operator specifically expects a skin temperature value at the observation location and time as well as the profiles of the atmospheric variables along the viewing path. This skin temperature is added to the control variable and optimised simultaneously with all of the atmospheric variables to produce optimal simulated radiances. We present two approaches to add the skin temperature to the control variable. In the current TOVS Control Variable (TOVSCV) approach, a series of skin temperature values per observation location is added to the control variable. Effectively, in the optimisation process, the skin temperature acts as a sink variable in observation space and is uncoupled from the skin temperature at other locations. In the novel SKin Temperature in the Extended Control Vector (SKTECV) approach, two-dimensional skin temperature fields are added to the control variable. All clear-sky radiances then participate in the optimisation of these two-dimensional fields, and the analysis produces temporally and spatially consistent skin temperature fields. We compare the two approaches over two seasons of 3 months each. Overall, there is a neutral impact of the new approach on the analysis and forecast. Moreover, there is some evidence that the contribution of the subsurface layers should be represented in the new approach for the skin temperature associated with the microwave instruments.

Satellite Observation of Spatio-temporal Variations in Nitrogen Dioxide over West Africa and Implications for Regional Air Quality

Background. Nitrogen dioxide (NO2) is known to affect human health, causing heart and cardiovascular diseases, and it has been shown that locations with long term NO2 pollution recorded a high number of fatalities due to the COVID-19 pandemic. There are no ground stations monitoring emissions of NO2 over West Africa. The present study aimed to use satellite observations to examine pollutant trends over this region. Objective. To examine the trend of NO2 over the entire West Africa sub region in relationship to contributions to environmental emissions using satellite-derived data. This enables the assessment of West Africa regional air pollution hot spots in relationship to enhancing atmospheric factors. The results from this study will also be useful guidance for setting air quality standards for air pollution controls to minimize health hazards. Methods. The present study examined thirteen years of average monthly values of nitrogen dioxide (NO2) to determine the spatio-temporal variation of this pollutant over West Africa. Satellite data for NO2 between 2005 and 2017 were used to determine the variation in pollution levels over West Africa. Correlations between NO2 and meteorological variables (wind speed, rainfall and air temperature) were obtained to explain the influence of West African weather on the region's pollution accumulation. Results. The present study observed that NO2 concentrations varied from place to place and from season to season. Nitrogen dioxide concentrations during the dry season were higher (sometimes 200% higher) than values observed in the wet season which ranged between 0.5 and 6×1015 molec/cm2. Nitrogen dioxide north-south oscillation during the course of a year is largely controlled by the inter-tropical discontinuity (ITD) zone as high concentrations of NO2 are found in the vicinity of the ITD where wind speeds and horizontal vorticity approaches zero. Correlation analysis between NO2 and some atmospheric variables indicated NO2 concentrations are well influenced by atmospheric variables showing bipolar signals depending on the season. An increasing trend of NO2 was also found over selected cities of the region. This indicated that regional air quality is gradually deteriorating. Conclusions. The implications of worsening regional air quality were examined in the light of the prevailing COVID-19 pandemic. The dominant atmospheric factor determining pollution episodes in the region is the inter-tropical discontinuity line which marks the meeting point between the two wind regimes over the region. Densely populated areas are characteristically prone to elevated pollution and have experienced high fatalities during the COVID-19 pandemic. Competing Interests. The authors declare no competing financial interests.

Relationship Between Sea Surface Temperature Anomalies In The Southwestern Atlantic Continental Shelf And Atmospheric Variability On Intraseasonal Timescales

The intraseasonal (IS) variability of the sea surface temperature (SST) in the Southwestern Atlantic Northern Argentinean Continental Shelf (SWACS NACS, 45-33°S - 70-50°W), and its relationship with that in the atmosphere, was studied for the austral warm season. SST satellite data (11-km resolution NOAA CoastWatch Program) and data of different atmospheric variables (Reanalysis1 NCEP/NCAR and ERA-Interim) were used. Data were filtered using a 10-90day filter to isolate the IS variability. A Principal Component analysis was applied then to the filtered SST anomalies (SSTA) and the activity of the leading modes was described through the corresponding temporal series. The first three modes are significant. EOF1 (25.7% of variance) exhibits SSTA of opposite sign to the north/south of 42°S. EOF2 (9.0%) and EOF3 (5.1%) are related with centers of SSTA of opposite sign located off the Uruguayan coast and in the middle shelf. Composites of SSTA and of key atmospheric variables were made considering the days in which the main modes were active. They show that the SSTA described by the three modes are associated with distinctive regional sea level pressure anomalies that, in turn, seem to be related to atmospheric Rossby wave trains extending from the Australia area towards South America. The corresponding atmospheric wave sources vary depending on the mode. These results show, therefore, that the SSTA in the SWACS NACS exhibit significant IS variability that is, in part, locally and remotely influenced by atmospheric anomalies oscillating on similar timescales. These ocean-atmosphere teleconnections could help to improve ocean predictability at those timescales in the future.

Atmospheric variables and subarachnoid hemorrhage: narrative review

Background Stroke is a neurological emergency that tends to be the first cause of death in many countries. Atmospheric variables are strongly associated with stroke, in which subarachnoid hemorrhage (SAH) has been associated in many studies to meteorological risk factors such as air pollution, air pressure, weather changes, and ambient temperature. These characteristics may influence the brain circulation and cause SAH, being diagnosed as idiopathic SAH or SAH with unknown cause. Objective The main objective of this review is to present the most relevant meteorological risk factors that may develop subarachnoid hemorrhage according to the current evidence that supports the strong association. Conclusion Brain vessel circulation may be influenced by atmospheric variables such as air pollution and weather changes, generating intrinsic changes in the intima of the vessels which leads to vasospasm and with comorbidities associated may develop SAH.