Hail suppression effectiveness for varying solubility of natural aerosols in water, Because of a production error, the black line in Figure 13c is incorrect. The correct Figure 13c is shown below.

Correction to: Projection of seasonal summer precipitation over Indian sub-continent with a high-resolution AGCM based on the RCP scenarios The authors want to acknowledge the Korea Meteorological Administration research and Development Program under Grant KMI 2018-07910.

Impacts of subgrid-scale orography parameterization on simulated atmospheric fields over Korea using a high-resolution atmospheric forecast model Abstract A substantial over-prediction bias at low-to-moderate wind speeds in the Weather Research and Forecasting (WRF) model has been reported in the previous studies. Low-level wind fields play an important role in dispersion of air pollutants, including radionuclides, in a high-resolution WRF framework. By implementing two subgrid-scale orography parameterizations (Jimenez and Dudhia in J Appl Meteorol Climatol 51:300–316, 2012; Mass and Ovens in WRF model physics: problems, solutions and a new paradigm for progress. Preprints, 2010 WRF Users’ Workshop, NCAR, Boulder, Colo. http://www.mmm.ucar.edu/wrf/users/workshops/WS2010/presentations/session%204/4-1_WRFworkshop2010Final.pdf, 2010), we tried to compare the performance of parameterizations and to enhance the forecast skill of low-level wind fields over the central western part of South Korea. Even though both subgrid-scale orography parameterizations significantly alleviated the positive bias at 10-m wind speed, the parameterization by Jimenez and Dudhia revealed a better forecast skill in wind speed under our modeling configuration. Implementation of the subgrid-scale orography parameterizations in the model did not affect the forecast skills in other meteorological fields including 10-m wind direction. Our study also brought up the problem of discrepancy in the definition of “10-m” wind between model physics parameterizations and observations, which can cause overestimated winds in model simulations. The overestimation was larger in stable conditions than in unstable conditions, indicating that the weak diurnal cycle in the model could be attributed to the representation error.

The impact of SST on the wind and air temperature simulations: a case study for the coastal region of the Rio de Janeiro state Abstract The impact of Sea Surface Temperature (SST) on the wind and air temperature numerical simulations over the coastal region of the state of Rio de Janeiro, Brazil, was investigated using the Weather Research and Forecasting (WRF) model. The study period comprised January 24–26, 2014, characterized by the occurrence of coastal upwelling. Two numerical experiments were performed. The first, called EGFS, used the Global Forecast System (GFS) results to prescribe the initial and boundary conditions. In the second, called EMUR, the SST was replaced by the Multi-scale Ultra-high-Resolution SST (MUR SST). The experiments showed significant differences between the SST fields, being higher than 10 °C. Through the comparison with observations, we verified that the upwelling was better represented in the EMUR, which consequently generated improvements in the temperature at 2 m above ground level (AGL) over this region. In the offshore region, over areas with higher SST, the wind speed at 10 m AGL was stronger, and opposite behavior was observed over low SST areas. In addition, in regions with higher SST differences between the experiments, differences of wind direction at 10 m AGL higher than 90° were detected. The SST influence on the air temperature and wind speed profiles was significant up to 300 and 900 m, respectively. The comparisons between the wind observations with the numerical results show that the land–sea breeze simulation (thermal forced) was underestimated in relation to the synoptic forcing (South Atlantic Subtropical Anticyclone), even with significant SST differences between experiments.

Use of large-scale atmospheric energetics for understanding the dynamics of contrasting Indian summer monsoon rainfall in different years Abstract An attempt has been made to understand the dynamics of contrasting Indian summer monsoon rainfall (ISMR) in different years during 1979–2017, from large-scale atmospheric energetics aspects. Daily values of eddy and zonal available potential energy (APE), their generation, eddy and zonal kinetic energy (KE), conversions of zonal KE and eddy APE to eddy KE, and conversions of zonal APE to zonal KE and eddy APE were computed over the region bounded by 65°E–95°E and 5°N–35°N during the period 1 May to 30 September for 39 years (1979–2017), using daily ECMWF reanalyzed atmospheric data at 0.125° × 0.125° resolution (3 components of wind and temperature). ISMR was classified into three categories, viz., deficient and below normal, normal and above normal and excess. The daily anomaly of these energetics parameters in each of these years was computed using jackknife method and then the composite of the daily anomalies of these parameters constructed for the years with the above-mentioned three categories of ISMR. The following salient features emerge from this study: Analysis of composite anomaly shows that in case of excess and above normal (below normal and deficient) ISMR, C(AZ, KZ) was less (more) than normal. In case of excess and above normal (below normal and deficient) ISMR, C(AE, KE) was more (less) than normal. Broadly, C(AZ, AE) was more than normal in the years with deficient and below normal ISMR, whereas it was less than normal for years with excess and above normal ISMR. Broadly, G(AZ) was below normal for the years with above normal and excess ISMR, whereas it was above normal for the years with below normal and deficient ISMR. Total kinetic energy and total conversion to eddy kinetic energy was above normal for the years with above normal and excess ISMR.

Overview of surface to near-surface atmospheric profiles over selected domain during the QWeCI project Abstract Assessing the evolution of surface to near-surface atmospheric fluxes is key to improving our understanding of their interactions, while further advancing climate applications. In this paper, an overview of the diurnal to seasonal evolution of some surface to near-surface atmospheric fluxes, coupled with their interactions, have been provided. Fluxes of downwelling and upwelling radiation ( \(SW_\downarrow\) , \(SW_\uparrow\) , \(LW_\downarrow\) , \(LW_\uparrow\) ), soil heat flux ( \(\Delta H\) ), relative humidity (RH), rainfall (RR) and surface air temperature (T), measured from two different locations (Owabi and KNUST) and at a temporal resolution of 10 min, encompassing the quantifying weather and climate impact (QWeCI) Project period (2011–2013), were used to assess their relationship on diurnal to seasonal scales. First, diurnal assessments of the various profiles were performed. These provided information on the relatively active daytime, with the earth surface exposed to substantial \(SW_\downarrow\) , initiating rising and sinking thermals which subsequently increased T and \(\Delta H\) , with reductions in RH until few hours after midday, beyond which a reversal was observed. Also, \(\Delta H\) from the vegetative terrain (Owabi) was found to be directed into the surface at daytime, and released from the sub-surface layer back into the atmosphere at night time, compensating the energy loss by \(LW_\uparrow\) from the surface. Furthermore, rainfall (RR) in both locations were found to be generally convective and occurring mostly between 1500 GMT and 2300 GMT. The relationship between net radiation ( \(R_N\) ) and RR is presently statistically unclear, although rainfall peaks were found to be occurring at low \(R_N\) and relatively warmer T, accompanied by high RH. Thereafter, seasonal assessments were performed to capture the monthly-averaged diurnal variabilities in the measured surface to near-surface parameters. These showed heightened daytime T, \(\Delta H\) and \(R_N\) , coupled with relatively low RHwithin the dry seasons, and more reduced profiles within the monsoon season. Additionally, countrywide assessments were performed using ERA-5 datasets which showed similarities with the in situ data. However, convective rains over the domain were not fully resolved in ERA-5. Nonetheless, the findings of this study are essential to understanding surface energy balance processes in tropical, humid climates, which is important for various climate-impact modeling applications and policy formulations over the region.

Stochastic modelling of the monthly average maximum and minimum temperature patterns in India 1981–2015 Abstract The paper investigates the stochastic modelling and forecasting of monthly average maximum and minimum temperature patterns through suitable seasonal auto regressive integrated moving average (SARIMA) model for the period 1981–2015 in India. The variations and distributions of monthly maximum and minimum temperatures are analyzed through Box plots and cumulative distribution functions. The time series plot indicates that the maximum temperature series contain sharp peaks in almost all the years, while it is not true for the minimum temperature series, so both the series are modelled separately. The possible SARIMA model has been chosen based on observing autocorrelation function (ACF), partial autocorrelation function (PACF), and inverse autocorrelation function (IACF) of the logarithmic transformed temperature series. The SARIMA (1, 0, 0) × (0, 1, 1)12 model is selected for monthly average maximum and minimum temperature series based on minimum Bayesian information criteria. The model parameters are obtained using maximum-likelihood method with the help of standard error of residuals. The adequacy of the selected model is determined using correlation diagnostic checking through ACF, PACF, IACF, and p values of Ljung–Box test statistic of residuals and using normal diagnostic checking through the kernel and normal density curves of histogram and Q–Q plot. Finally, the forecasting of monthly maximum and minimum temperature patterns of India for the next 3 years has been noticed with the help of selected model.

Regression analysis of aerosol optical properties with long-term MODIS data using forward selection method Abstract In this work, a new filtering method of forward selection (FS), has been employed for linear and multiple regression analysis of aerosol optical properties with meteorological parameters using long-term moderate resolution imaging spectroradiometer (MODIS) data for New Delhi area. Long-term observation (15 years, March 2000–December 2014) of aerosol optical depth (AOD) at 550 nm, fine mode fraction particles (FMF) and Angstrom exponent (AE) are analyzed to study their variability on annual and seasonal basis. The analysis reveals relatively high mean AOD (0.71 ± 0.25), associated with moderate AE (0.69 ± 0.13) for the overall period. Considerable higher values of AOD (0.89 ± 0.33) were reported in monsoon and AE (0.87 ± 0.10) during winter season. Likewise, seasonal fraction for AOD was also found to be higher (42%) during the monsoon season and for AE (31%) and for FMF (55%) during winter season. The peak value of AOD was during June–July and the lowest in the transitional months of February and September, while AE was high in January–February and low in May–June suggesting significant urban and biomass burning contribution. In general, the analysis shows a rather well-mixed type of aerosols present in the urban environment, which affect the regional air quality as well as climate associated with long-range transport of pollutants through the westerly winds from the Thar Desert and biomass burning in the western parts of India. The presence of AOD trend is evidence of air quality deterioration particularly in highly populated areas. The aerosol classification with relationship between AOD and alpha shows that urban/biomass burning aerosols are dominant in Delhi during winter and pre-monsoon. It is clearly seen that irrespective of constant emissions occurring each month, the estimated pollution is much higher in winter months and lower in summer months. It is concluded that fine particles exhibit much higher variations than urban aerosols annually and seasonally.

Equatorially/globally conditioned meteorological analysis of heaviest monsoon rains over India during 23–28 July 2005 Abstract The heaviest monsoon rainstorm of the period 1951–2007 over India occurred during 23–28 July 2005, mostly the peninsula received rainfall, and each day the rainwater over the country was 40.0 bcm (billion cubic meter) or more, highest 98.4 bcm fell on 25 July 2005. Present premise of monsoon genesis is that it evolves in association with spreading and intensification of equatorial atmospheric condition over Afro-Eurasian landmass and adjoining Indian and Pacific Oceans during boreal summer. Robust natural criteria have been applied to demarcate monsoon and other global weather regimes (GWRs) at standard levels (1000‒100 hPa). Global atmospheric (1000‒100 hPa) thermal condition and monsoon and general circulations during 23–28 July 2005 have been compared with normal features of respective parameters. Over tropics-subtropics (45°S–45°N), troposphere (1000‒250 hPa) was warmer-thicker and pressure lower than normal and mixed conditions of positive/negative departures in temperature, height/thickness and pressure over northern and southern mid-high latitudes. Noticeable changes in 3D monsoon structure were: horizontally spread and eastward-southward shifted over western North Pacific and stretched further southeastward across equatorial Pacific; intense warm-low lower tropospheric confluence-convergence across Asia–Pacific with vertical depth extending beyond 400 hPa; and intense warm-high upper tropospheric anticyclonic circulation zonally stretched and divided into three interconnected cells. Outflows from anticyclonic cells over Tibetan plateau and western North Pacific were mostly directed westward/southwestward/southward. Troposphere was warmer-thicker and pressure higher over eastern part of both subpolars-polars and cooler-thinner and pressure lower over western part. During the period, a deep cyclonic circulation moved from Bay of Bengal through central India while near-stationary atmospheric condition prevailed across the globe.

Synoptic thermodynamic and dynamic patterns associated with Quitandinha River flooding events in Petropolis, Rio de Janeiro (Brazil) Abstract Natural disasters are the result of extreme or intense natural phenomena that cause severe impacts on society. These impacts can be mitigated through preventive measures that can be aided by better knowledge of extreme phenomena and monitoring of forecasting and alert systems. The city of Petropolis (in a mountainous region of the state of Rio de Janeiro, Brazil) is prone to heavy rain events, often leading to River overflows, landslides, and loss of life. In that context, this work endeavored to characterize the thermodynamic and dynamic synoptic patterns that trigger heavy rainfall episodes and the corresponding flooding of Quitandinha River. More specifically, we reviewed events from the time period between January 2013 and December 2014 using reanalysis data. We expect that the overall description obtained of synoptic patterns should provide adequate qualitative aid to the decision-making processes involved in operational forecasting procedures. We noticed that flooding events were related to the presence of the South Atlantic Convergence Zone (SACZ), frontal systems (FS), and convective storms (CS). These systems showed a similar behavior on high-frequency wind components, notably with respect to northwest winds before precipitation and to a strong southwest wind component during rainfall events. Clustering analyses indicated that the main component for precipitation formation with regard to CS systems comes from daytime heating, with the dynamic component presenting greater efficiency for the FS configurations. The SACZ events were influenced by moisture availability along the vertical column of the atmosphere and also due to dynamic components of precipitation efficiency and daytime heating, the latter related to the continuous transport of moisture from the Amazon region and South Atlantic Ocean towards Rio de Janeiro state.