Subjects -> METEOROLOGY (Total: 106 journals)
 Showing 1 - 36 of 36 Journals sorted by number of followers Journal of Atmospheric and Solar-Terrestrial Physics       (Followers: 158) Nature Climate Change       (Followers: 150) Journal of the Atmospheric Sciences       (Followers: 79) Atmospheric Environment       (Followers: 72) Atmospheric Research       (Followers: 72) Climatic Change       (Followers: 71) Bulletin of the American Meteorological Society       (Followers: 62) Advances in Climate Change Research       (Followers: 59) Journal of Climate       (Followers: 55) Climate Policy       (Followers: 53) Climate Change Economics       (Followers: 50) Climate Dynamics       (Followers: 44) Advances in Atmospheric Sciences       (Followers: 43) Atmospheric Chemistry and Physics (ACP)       (Followers: 43) Weather and Forecasting       (Followers: 42) American Journal of Climate Change       (Followers: 41) Journal of Applied Meteorology and Climatology       (Followers: 40) Journal of Hydrology and Meteorology       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Similar Journals
 Meteorology and Atmospheric PhysicsJournal Prestige (SJR): 0.543 Citation Impact (citeScore): 1Number of Followers: 28      Hybrid journal (It can contain Open Access articles) ISSN (Print) 1436-5065 - ISSN (Online) 0177-7971 Published by Springer-Verlag  [2469 journals]
• Features of upper tropospheric temperature fluctuations during drought
years of Indian summer monsoon: results inferred from COSMIC GPS RO
observations

Abstract: Abstract Prolonged breaks during the Indian summer monsoon (ISM) season can cause a massive deficit in all-India rainfall, leading to drought conditions. The availability of long-term observations from radio occultation (RO) data, with a finer vertical resolution, provides a unique opportunity to explore the thermal anomalies in the upper troposphere (UT) during ISM season. The present work focuses on drought years during the period 2007–2016 using this RO data. Results show significant cold (warm) anomalies in the UT, extending from west-central Asia (20°E) to east-central Asia (160°E) during drought (near-excess) years of ISM with strongest fluctuations near the eastern and western side of the Caspian Sea. Result suggests that these anomalies modulate the north–south thermal contrast over the ISM region on a seasonal scale, impacting the monsoon performance. In 2009, before the occurrence of three break conditions over the ISM domain, three major blocking highs were formed in the UT (~ 10 km) over south-east Asia (30°–40°N, 100°–120°E). During the first dry spell of monsoon in 2009, an extremely cold anomaly (~ 12 K) appeared in the UT near the Caspian Sea, which brought cold dry air to north-west India leading to delayed northward advance of the monsoon. When compared to near-excess years, drought years exhibit substantial intraseasonal temperature fluctuations in the UT over the core monsoon zone, with the strongest variations during the severe drought year 2009. The prolonged second dry spell of 2009 during 26 July–10 August is a manifestation of two subsequent events characterized by upper tropospheric subsidence and warm anomalies advected from the east.
PubDate: 2022-07-30

• Trends and variabilities of precipitation and temperature extremes over
Southeast Asia during 1981–2017

Abstract: Abstract As one of the most populated agricultural habitats in the world, Southeast Asia has been highly exposed to extremes of weather and climate, posing great importance to figure out the trend and variability characteristics of extremes over there. The annual extreme precipitation and temperature over Southeast Asia during 1981–2017 are analyzed in this study using datasets based on daily observations derived from thousands of meteorological stations. Results show that the wet extremes decrease over the areas surrounding the South China Sea and increase over the south of the Philippines and Indonesia with the most significant trends detected over the east of Indochina and New Guinea. Extreme high temperatures decrease significantly over the middle of New Guinea and increase over Indochina, Sumatra, Java, and Kalimantan. Moreover, empirical orthogonal function (EOF) analyses show that the first principal components for most precipitation extremes are characterized by significant decadal changes relevant to the Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation, and the second principal components exhibit significant interannual variability associated with oceanic systems such as El Niño–Southern Oscillation (ENSO). As for temperature extremes, the leading EOF modes show non-significant trends or decadal variations, but significant interannual variations related to ENSO and the Indian Ocean Dipole are detected.
PubDate: 2022-07-28

• Extreme rainfall events in the Rio de Janeiro city (Brazil): description
and a numerical sensitivity case study

Abstract: Abstract Forecasting extreme rainfall events with high reliability has become increasingly important over the last decades, given their expressive impacts on society and properties. This study initially described the spatiotemporal patterns of rainfall climatology, identified extreme rainfall events, and categorized the meteorological systems related to the precipitation regimes in Rio de Janeiro city. Secondly, we evaluated the extreme rainfall event on 08–09 April 2019 over the Rio de Janeiro city and made a numerical sensitivity case study using the Weather, Research and Forecasting (WRF). For the numerical sensitivity study, we considered the combination of eight microphysics and eight cumulus schemes (totalizing 64 simulations) and four horizontal one-way grid nesting domains (27 km, 09 km, 03 km, and 01 km). The results showed that The New Tiedtke cumulus scheme might have presented the best performance from the quantitative and qualitative evaluation. We verified from the cloud microphysics schemes that the WRF single-moment 5-class and WRF single-moment 6-class schemes also presented better spatial characterization and intensity of rainfall. Lastly, this work sought to characterize the challenges faced by operational forecasters related to the extreme rainfall and natural hazards imminence warnings. It is also worth mentioning that the physical results and discussion made could present some intrinsic bias due to the only one extreme event analyzed. Thus, as future work, the simulations of other extreme rainfall events are expected to guarantee the reliability of the possible outcomes and their use by operational forecasters.
PubDate: 2022-07-25

• Distinct urban land cover response to meteorology in WRF simulated
pre-monsoon thunderstorms over the tropical city of Kolkata

Abstract: Abstract The Kolkata metropolitan region, located in eastern India, is one of the most densely urbanized areas, with significant thunderstorms reported during the pre-monsoon season. The Weather Research and Forecasting (WRF) model is used to investigate the influence of urban-induced land use and land cover (LULC) change over Kolkata during the pre-monsoon thunderstorms. Multiple thunderstorm events reported during 2014–2017 are simulated using a high (Hurb) and low (Lurb) urban LULC scenario. The presence of higher urban pixels in Hurb case favors the enhancement in precipitation mainly over central and northern parts of the city in the downwind direction. Urban Heat Island (UHI) effect is more evident during the nighttime, with a temperature difference of up to 0.5 °C. However, the UHI impacts the vertical structure of the boundary layer (BL) more during the daytime due to prevailing higher temperatures and dominant surface heating. The analysis reveals positive contributions of the ground and sensible heat fluxes to the near-surface UHI intensity. The surfaces over the urban patch and surrounding areas experience a relatively drier atmosphere than their rural counterparts. Over the identified urban patches, a significant impact on meteorological variables is seen near the surface and within the BL in the case of Hurb compared to Lurb LULC scenario. The urbanization over Kolkata stimulates the BL and the local meteorology encouraging nighttime UHI, afternoon or evening moist convection, and consequent occurrence of thunderstorms to result in enhanced and distinctly distributed rainfall over the city and its neighborhood during pre-monsoon months.
PubDate: 2022-07-23

• Analyzing the structural characteristics of the Sichuan basin vortex based
on CloudSat satellite data

Abstract: Abstract Using the CloudSat data for the Sichuan Basin vortices (SBVs) from June to August (2007–2016) and dividing the data based on whether the SBVs moved eastward, the cloud, precipitation, and thermal structural characteristics of the SVBs were comprehensively analyzed to cultivate a deeper understanding of these vortices. The results show that a direct correlation between vortex structure and precipitation intensity. The variations in radar reflectivity are completely opposite vertical distribution above and below a height of 5 km. The proportion of deep convective clouds is more than 30% of the total vortex depth, and the distribution differences are reflected by the middle and lower clouds. This occurs because stratiform precipitation commonly takes place in the Sichuan Basin. When an SBV moves eastward, the proportion of convective precipitation increases with increasing vortex enhancement. The distribution differences of ice particle parameters embody the effective precipitation mechanisms of sowing and supplying. The locations of intense vortices are indicative of the locations of rainfall centers. The instantaneous precipitation rate increases as the vortex center moves southward. There is a warm central region with a temperature of over 0 °C within 200 km of the vortex center for both type I and type III in the radial direction. The wet region appears below the warm region, and the vertical scope of the wet center is less than 4 km. The ranges and intensities of both the warm and wet centers increase gradually with the eastward development of the SBV.
PubDate: 2022-07-23

• Long-term trends in climate parameters and multiple indices for drought
monitoring over Pakistan

Abstract: Abstract Pakistan is facing extreme weather events like floods, droughts, heatwaves etc. for the last few decades. The variability of the climate parameters (temperature, precipitation, and evapotranspiration) is causing these extreme events and resulted in a lot of damage to infrastructure as well as the livelihood of people. To identify the future trends of these parameters, seasonal and annual trends were analyzed on the 60 observational stations from 1951 to 2019. Moreover, the variability of drought is also investigated by using multiple drought indices over different provinces of Pakistan. Non-parametric Mann–Kendall and Sen’s slope tests are utilized to estimate significance and magnitude in a trend of the meteorological parameters at a 95% confidence level. The results showed a remarkable increase in maximum temperature (0.008 °C/year) at Balochistan (0.019 °C/year), Azad Jammu Kashmir (0.010 °C/year), and Gilgit-Baltistan (0.011 °C/year). Similarly, a significant increase in the minimum temperature trend has been observed over Punjab, Sindh, and Balochistan, whereas a decrease over Gilgit-Baltistan (GB), Azad Jammu Kashmir (AJK), and Khyber Pakhtunkhwa (KP). A significant decrease in the evapotranspiration trend was observed over Punjab, while it was positive in Balochistan and AJK. Precipitation is significantly increasing during February and June, especially in KP (1.55 mm/year) and Punjab (2.45 mm/year). Also, drought indices trends were determined in different regions of the country by applying multiple drought indices namely standardized precipitation index, standardized precipitation evapotranspiration index, reconnaissance drought index, and deciles index. All the drought indices showed significant positive trends over Punjab and KP, whereas negative in AJK at 95% confidence level. The consensus of all drought indices indicated severe drought risk that occurred in 1952 and 2002. Moreover, all the drought indices show positive (wet) trends for Punjab and KP, whereas negative (dry) for AJK at a 95% significance level. These results provide useful information for developing drought adaptation measures for lower parts of Pakistan that may be more susceptible to drought in the future.
PubDate: 2022-07-23

• Sensitivity of surface roughness parameters on the simulation of boundary
layer winds over a complex terrain site Kaiga in western India

Abstract: Abstract Kaiga, in the Western Ghats region, has a hilly topography and dense forest canopy. In this study, the sensitivity of surface roughness length ( $$z_{\text{o}}$$ ) on the boundary layer winds over Kaiga is investigated using the Weather Research and Forecasting (WRF) model for summer and winter seasons. Observational analysis shows high frequency of calm winds due to the flow blockage by the surrounding hills and surface drag from forest cover in the Kaiga valley. To realistically simulate the surface winds, surface roughness length is estimated using the sonic anemometer data and tower wind speed measurements employing the logarithmic profile relationship under neutral stability conditions for different months. The estimated $$z_{o}$$ varies in the range of 0.96–1.84 m in different seasons. To study the effect of forest cover on the wind field, WRF simulations are conducted using various roughness factors within the range of default value for evergreen broadleaf forest in the MODIS land-cover data used in the model and the highest estimated value, i.e., $$z_{\text{o}}$$  = 0.5 m, 0.75 m, 1.0 m, 1.25 m, and 1.50 m. Simulations show considerable overestimation of wind speed in control run ( $$z_{\text{o}}$$ $$z_{o}$$  = 0.50 m) and experiments with increased roughness length reduced the bias in the surface wind speed, wind direction, and temperature. On average, the simulated winds are corrected by 2 m/s and 3 m/s for $$z_{\text{o}}$$  = 1.0 m and $$z_{\text{o}}$$  = 1.50 m, respectively. Increasing the surface roughness length also improved the prediction of the frequency of occurrence of calm winds to some extent. The assimilative capacity of the Kaiga valley atmosphere is evaluated by estimating the ventilation coefficient for the winter and summer seasons. It has been found that the model overestimated the surface winds and thus overpredicted the ventilation coefficient. By modifying the surface roughness length, the overestimation in the ventilation coefficient is corrected to an extent.
PubDate: 2022-07-21

• Numerical modeling of tropical cyclone size over the Bay of Bengal:
influence of microphysical processes and horizontal resolution

Abstract: Abstract The destructiveness of tropical cyclones (TCs) is associated with uneven distribution of winds, TC-size, rainfall and storm-surge. The TCs in the Bay of Bengal (BoB) have shown a steady increase in size, as measured by the 34-knot wind radius (R34) over the past two-decades. TC-size information is essential in estimating areas to be evacuated to minimize the damage and loss of life. The study addresses the significance of microphysical (MP) processes and horizontal grid-resolution for improved TC-size. The Weather Research and Forecasting model is run at different grid-resolutions and various MP-schemes. Results show that TC movement is less sensitive to MP-schemes, while the size is more sensitive. The simple-ice (WSM3) scheme produced smaller TCs in R34 (228-km) due to less MP-heating caused by the evaporation of rainwater and lesser efficiency of freezing. Due to absence of ice-treatment and more rainwater, the warm-rain (Kessler) scheme produced larger TC-size (295-km). The size simulated from other schemes is more or less the same (266–284 km). Analyses indicate that higher MP-heating induces intense vertical-velocities, absolute angular momentum and thus increases the TC-size. Finer model resolution results in smaller TC-size. Though WSM3 performed better for size simulation, it somewhat underestimates at finer resolutions. For any particular resolution, the simulated size differs by 30–50 km among the MP schemes, while the size changes 5–15 km (2–4 km) between 6-km and 2-km (3-km and 2-km) grid-resolutions for any MP scheme. The study concludes that better TC-size can be achieved with appropriate MP-schemes at higher/cloud-resolving grid-resolution.
PubDate: 2022-07-21

• Time-dependent intrinsic cross-correlation approach for multi-scale
teleconnection analysis for monthly rainfall of India

Abstract: Abstract This study proposes an efficient framework employing Ensemble Empirical Mode Decomposition (EEMD) algorithm coupled with Time-Dependent Intrinsic Cross Correlation (TDICC) method to detect the teleconnection between large scale climatic oscillations and monthly rainfall of India. Indian Ocean Dipole (IOD), El Niño Southern Oscillation (ENSO) and the enhanced convective phases of Madden Julian Oscillation (MJO) have taken into consideration as climatic oscillations for the teleconnection study. EEMD method decomposed each signal to a set of zero mean oscillatory modes namely Intrinsic Mode Functions (IMFs)with definite periodicity. The time-dependent running correlation analysis of the IMFs of ENSO and IOD showed strong negative correlation with the modes of rainfall, at inter annual scales. All the IMFs of MJO indices 8–10 showed very strong positive correlation while MJO indices 2 and 3 showed very strong negative correlations with the corresponding IMFs of rainfall. TDICC analysis found the most influential antecedent information of climatic oscillation in the prediction of IMFs of rainfall at different time scales. On considering the different lags in TDICC analysis, the high frequency modes are associated with transition in correlation from positive to negative and vice versa while low frequency modes display a stable pattern in the teleconnections of rainfall with climatic oscillations. The TDIC-based identification of relevant modes and TDICC-based identification of significant lags will substantially alleviate the computational complexities and help in improved predictions of monthly rainfall over India.
PubDate: 2022-07-21

• Tropical cyclones in the northern Mozambique Channel: composite
intra-seasonal forcing and 2019 event

Abstract: Abstract Tropical cyclone (TC) activity in the northern Mozambique Channel (nMC) during the satellite era is studied, culminating with the anomalous 2019 season. We identify 21 westward-moving TCs since 1979 and analyze regional to local conditions as they move over the nMC. As easterly flow is needed to steer these TC into the channel and over land, we look for scenarios under which this flow is established along with thermodynamic conditions necessary to support TCs. At seasonal scales there is a dichotomy between westward steering flow and reduced thermodynamic energy during Pacific La Niña and cool-phase Indian Ocean Dipole (–IOD). Equatorial convective systems (Madden Julian Oscillation, MJO) entering the west Indian Ocean can trigger TC formation and subtropical ridging, more effectively at the end of austral summer. Conditions in early 2019 favoured westward flow over Madagascar. The onset of warm phase + IOD was evident in the Walker circulation and downwelling ocean Rossby wave that warmed SST to 31 °C north of Madagascar. High-amplitude MJO triggered the genesis of TCs Idai (March) and Kenneth (April) and both TCs transited the Mozambique Channel causing unprecedented floods. TC Kenneth intensified rapidly, and satellite rainfall and upper level ozone indicated the presence of a southern spiral cloud band that shielded the TC from the sub-tropical jet over Madagascar. Numerical model forecasts of track and intensity are evaluated.
PubDate: 2022-07-12

• Efficacy of linear multiple regression and artificial neural network for
long-term rainfall forecasting in Western Australia

Abstract: Abstract Precipitation is one of the most intrinsic resources for manifold industrial activities all over Western Australia; consequently, immaculate rainfall prediction is indispensable for flood mitigation as well as water resources management. This study investigated the performance of artificial neural networks (ANN) and Linear multiple regression (LMR) analysis to forecast long-term seasonal spring rainfall in Western Australia, using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential climatic phenomena. The ANN was developed in the form of multilayer perceptron using Levenberg–Marquardt algorithm and subsequently LMR was used with statistical significance for future spring rainfall forecast. The total climatic dataset has been divided into calibration and testing phases to determine the efficacy of the developed models. Different statistical skill tests such as root mean square error (RMSE), mean absolute error (MAE), and Willmott index of agreement ‘d’ were used to assess the efficacy of LMR and ANN modelling. In general, LMR has lower MAE and RMSE values as compared to ANN for most of the stations during calibration and testing periods, whereas ANN models performed better than LMR models based on ‘d’ values. The overall statistical analysis paradigm suggests the efficacy of LMR over ANN models for rainfall forecasting using more climatic variables. As a result, the developed LMR model, incorporated with lagged global climate indices, will facilitate the adequate preparedness for the risks associated with potential droughts in the study region.
PubDate: 2022-07-11

• Assessment of WRF-3DVAR data assimilation on simulation of heavy rainfall
events associated with monsoon depressions over Bay of Bengal

Abstract: Abstract The present study examines the performance of the Advance Research Weather Research and Forecasting model with three-dimensional variational data assimilation (WRF-3DVAR) associated with four heavy rainfall events (HREs) in the presence of monsoon depressions (MDs) over the Bay of Bengal (BoB). We have carried out two numerical experiments, control experiment (CNTL; without data assimilation) and 3DV (assimilation of observations from Global Telecommunication system). The resultant high-resolution analysis obtained from the successful insertion of additional observations through 3DVAR assimilation technique recaptures the better convection and synoptic features associated with the MDs. The 3DV-simulated values of hydrometeors (rainwater, cloud water, and ice + snow + graupel) are found to be reasonably well captured, compared to CNTL simulation. The MDs evolution at various phases of its life span is reasonably well simulated in the 3DV compared to the CNTL experiment. The qualitative and quantitative precipitations are examined with respect to satellite-estimated rainfall data. The quantitative validation of model simulated 24-h accumulated precipitation is evaluated through the feature-based diagnostic evaluation method. Numerous statistical skill scores are evaluated by virtue of the object-oriented tool and results revealed that the simulated rainfall is remarkably improved in 3DV experiment. The study envisages that the assimilation of observations through 3DVAR have positive impact for simulation of HREs due to the presence of MDs.
PubDate: 2022-06-29

• Evaluation of reanalysis-based, satellite-based, and
“bias-correction”-based datasets for capturing extreme precipitation
in Iran

Abstract: Abstract This study compares seven global gridded daily precipitation datasets against gauged precipitation to evaluate their accuracy for capturing extreme precipitation in Iran. We evaluated the performance of satellite-based (CHIRPS and MSWEP-V220), reanalysis-based (CFSR and MERRA-2), ensemble-based (MRE3ensemble), and “bias-correction”-based (MRE3ensemble, EWEMBI, and W5E5) precipitation datasets for the period of 1980–2016. The extreme precipitation indices that we examined consist of intensity indices [the maximum consecutive 1-day precipitation (Rx1day) and simple precipitation intensity (SDII)], duration indices [the consecutive dry days (CDD) and the consecutive wet days (CWD)], and frequency indices [heavy precipitation events (R10mm) and very heavy precipitation events (R20mm)]. The results showed that MSWEP-V220 had the best performance in Iran and Bias-Correction W5E5 was the second-best dataset to estimate precipitation in Iran. Although RMSE and MBE statistics showed high error and bias for all precipitation datasets in northern Iran, the evaluation of the PBIAS showed the share of bias value in the northern regions of Iran compared to the total precipitation in the climate zone of Iran is less than 5%. In contrast, most datasets showed a high percentage of bias in the eastern and interior regions of Iran. The results showed that all the studied datasets in the rainy areas of Iran (Cfa, Csa, and Dsa) underestimate maximum one-day precipitation (Rx1day), precipitation intensity (SDII), and heavy and very heavy precipitation (precipitation > 10 and 20 mm). In addition, MERRA-2 and CFSR overestimate the indices related to intensity and frequency in the most desert (BW) and semi-desert (BS) climates of Iran, respectively. CHIRPS data in all climate zones of Iran—except the CWD index in Cfa climate zone – overestimate the CDD index and underestimated the CWD. Accordingly, CHIRPS data show a drier climate for Iran unrealistically.
PubDate: 2022-06-26

• Tropospheric radio refractivity trends over vegetation regions in Nigeria

Abstract: Abstract Refractivity is an important parameter in understanding radio wave propagation in the troposphere. We investigated both the monthly variations of refractivity and its trends over vegetation regions in Nigeria. Application of Matlab program was used to compute the values of radio refractivity from meteorological variables for a period 1979–2013, using ITU-R P 453-12 (The radio refractivity index; its formula and refractivity data. Recommendations and reports Geneva Switzerland, 2016) model. Results show that the pattern of radio refractivity variation at various locations in Nigeria is not the same due to the different vegetation regions. The states within the Freshwater and Rainforest regions were found to have higher refractivity values than those in the Guinea savannah, Sudan savannah and Sahel savannah regions in Nigeria. The Guinea savannah region of Nigeria (called the middle belt) has the same trend with the other parts of savannah regions in Nigeria. The only difference found is in the refractivity values. The mean refractivity values revealed that the Guinea and Sahel savannah regions have higher refractivity values than Sudan savannah region while, the Sahel savannah region has lower refractivity values than Guinea savannah region. The trends of refractivity show that refractivity increases by 0.1 N units per year in the Freshwater and Rainforest regions and decreases by 0.1 N units per year in the savannah regions of Nigeria. The average monthly value of refractivity increases from a value of approximately 356 N units in Sudan savannah region to maximum value of approximately 382 N units in Freshwater region. This indicates that the radio refractivity value increases from the savannah region to the Freshwater region of Nigeria. It was also observed that the Guinea savannah region radio refractivity values were lower than those of the Freshwater and Rainforest regions, but greater than those of the Sudan and Sahel regions. This observation is coherent with the knowledge that the Rainforests (south of the Nigeria) are more humid than the dry climates (north of the Nigeria), and so the Rainforests have greater refractivity values than the Sudan and Sahel regions. The Guinea savannah which is geographically located between these two sets of regions has moderate refractivity values.
PubDate: 2022-06-24

• Characteristics of the tropical cyclones over the North Indian Ocean
Basins from the long-term datasets

Abstract: Abstract This study examines the variabilities in the characteristics of the Tropical Cyclones (TCs), i.e., track, direction, maximum sustained wind (MSW), translation speed (TS), and radius of maximum wind (RMW) over the North Indian Ocean (NIO) Basins for pre-monsoon (PRE) and post-monsoon season (POST) from 60 years data. It is found that there is an increase in the frequency as well as the intensity of TCs over the Arabian Sea (AS) during both these seasons in recent 30 years. For POST, there is a large number of TCs moving in the NW direction for AS and Bay of Bengal (BoB). The percentage of intensified TC [Severe Cyclonic Storm (SCS) category and above] increases up to the stormy day (SD)-4 and then decreases. The TS of TCs has a declining trend over the AS; however, this pattern is only seen for POST over BoB. In addition, it is also noted that TC has the tendency to intensify as its TS slows down. The RMW is initially larger and reduced as TC gains strength, suggesting the intensity of the TCs is inversely proportional to RMW. The longevity of TC is found to be higher over the AS compared to the BoB. It is found that frequencies of simultaneous occurrence of TCs (SCS and above strength) for PRE and POST for the same year have increased over AS and reduced over BoB. The deep wind shear anomaly is stronger (weaker) during the PRE (POST) over both these basins. Unlike the high-pressure region over central India, which is prevailing during the SDs of AS, there are no such features noted for BoB, hence indicating more landfall movement of TC over the Indian mainland. The latent heat flux (LHF) and sensible heat flux (SHF) are higher over the BoB compared to AS, suggesting more intensified TCs over the BoB. The temperature at the two-meter (T2m) anomaly has been found to be higher (lower) over the Indian land region for SDs of AS (BoB). The specific humidity anomaly is found to be higher during the POST as compared to the PRE over both these basins. The findings of the study have a direct consequence toward improving the early warning and disaster mitigation strategies over the Indian region.
PubDate: 2022-06-21

• The association between particulate matter concentration and

Abstract: Abstract Detrended cross-correlation and multiple regression analyses were applied to a 5 year dataset (2013–2017) of concentration of particulate matter with aerodynamic diameters less than 2.5 (PM2.5) and 10 μm (PM10), and a set of meteorological parameters (rainfall, wind speed, temperature, solar radiation and relative humidity) to determine seasonal dependence of PM in Dhaka, Bangladesh. PM was negatively correlated with all meteorological parameters except for solar radiation. The response of PM to wind speed, relative humidity and rainfall had no lag, whereas a 1 day lagged response of PM was observed with temperature and solar radiation. Seasonal cross-correlation analysis suggests dispersion of PM by strong wind during pre-monsoon and monsoon seasons, while the increase of PM concentration occurs from local pollution sources during the less windy winter. The effect of relative humidity on the deposition of PM (especially the coarser fraction) is more pronounced than the effect of rainfall during pre-monsoon. The outcome of multiple regression analysis was consistent with the univariate analysis and showed that meteorological parameters could explain up to 76% and 73% of daily PM2.5 and PM10 variation, respectively. The association of PM with meteorological parameters in Dhaka city is similar to other countries located in subtropical climate regions. Our results serve as a reference for future studies to predict PM concentration through meteorological variation to facilitate air pollution management in Dhaka city.
PubDate: 2022-06-21

• Characteristics of rain events of different durations at a high-altitude
site in the Western Ghats of India

Abstract: Abstract We report duration-related properties of rain events at a high-altitude site in the Western Ghats (WG) of India during the summer monsoon (June–September) season. Duration of rain events is inferred from disdrometer data collected during the years 2015–18. Vertical profiles of events of different durations are studied using data of an X-band radar available for 2017–18 monsoon seasons. Durations of rain events span from 0.1 to 160 h. Rain intensity (i.e., rain rate), mass weighted drop diameter, and rain liquid water content decrease with duration up to 1 h, remain steady between 1 and 20 h, and then increase for larger durations. Rain drop number concentration shows an increasing trend with duration up to around 10 h and then decreases. Rain events are categorized into short- (< 10 h) and long-duration (> 10 h) events based on rain drop characteristics. The long-duration events account for ~ 15% of the total number of events and contribute ~ 75% to the monsoon rainfall. The long-duration events have association with the monsoon rainfall over the Indian core monsoon zone with a correlation coefficient of 0.77. The frequency distribution of 18 dBZ radar echo top height exhibits bimodal structure (around 2 km and 4 km) for both short and long events with a longer tail in the case of former. The study is primarily focused on the summer monsoon season; however, we also report the rain duration features during the pre-monsoon (March–May) season.
PubDate: 2022-06-16

• Modulation of boreal summer intraseasonal oscillation on tropical cyclone
genesis over the South China Sea

Abstract: Abstract The South China Sea (SCS) is affected by two components of boreal summer intraseasonal oscillation (BSISO): namely the 10–30d BSISO and 30–60d BSISO. In this study, the modulation of tropical cyclone genesis (TCG) over the SCS by individual and combined modes of BSISO is investigated from the view of dynamic and energy conversion. Results suggest that the number of TCG varies significantly with the life cycle of BSISO, with the influence of 30–60d mode being more significant than that of 10–30d mode. When 10–30d/30–60d BSISO is in convective phase, the cyclone triggered by active convection over the SCS leads to meridional shear of zonal winds and convergence of meridional winds, which favors synoptic-scale eddies gaining energy from BSISO flows through barotropic energy conversion. These growing eddies, together with beneficial environmental conditions such as low-level convergence and cyclonic vorticity, create a favorable environment for TCG over the SCS. Compared to 10–30d BSISO, synoptic-scale eddies gain more energy from 30–60d BSISO. When the SCS is under combined effect of dual modes, the modulation of 10–30d mode on TCG tends to be subjective to 30–60d mode. The impact of 10–30d BSISO is less obvious during nonconvective phase of 30–60d BSISO when compared to the convective counterparts over the SCS.
PubDate: 2022-06-16

• Vulnerability of tropical Indian cities to augmenting heat stress during
summer and monsoon season months (1969–2015)

Abstract: Abstract Human beings are adversely affected by climate extremes, pertinent to an increase in frequency and intensity of warm temperatures, eventually inducing warming on a global and regional scale. In a tropical nation like India, high summer temperature and increased moisture with the arrival of the southwest monsoon (hereafter referred to as monsoon) aggravate the sultriness of the ambient environment. Irrespective of global climate change, cities alter their climate due to urban materials' impervious surfaces and thermal properties, which upsurge moisture and temperature in urban settings. Thus, urban dwellers are peculiarly vulnerable to heat stress health hazards. Heat stress indices allow quantitative assessment of thermal stress to determine the safe limits of thermal exposure. In the present study, statistical trends in Heat Index were evaluated to analyze heat stress over 41 urban stations of southern peninsular India over the summer and monsoon season from 1969 to 2015. Results indicated that almost all stations registered a significant increase at 95% confidence level in heat stress except for an insignificant decrease at a few stations. Changepoint detection depicted an increase in heat stress initiated in the late 1990s and early years of the decade 2000 at most urban stations. Hierarchical cluster analysis partitioned data into seven spatial units. Accordingly, the highest magnitude of increase was observed over cities located in the northeastern part of the study area and the southern tip of peninsular India. The study demands attention to perilous health risks related to India's increasing heat stress casualties and the need for an indigenous thermal stress alerts system.
PubDate: 2022-06-14

• Identification and analysis of terrain-induced low-level windshear at Hong
Kong International Airport based on WRF–LES combining method

Abstract: Abstract Terrain-induced low-level windshear is characterized by high variability and small spatiotemporal scales. It seriously threatens the safety of aircrafts and reduces the operational efficiency of airports. The objective of the study was to identify terrain-induced low-level windshear over the airport area. A large-eddy simulation (LES) based on the data from WRF (weather research and forecasting) model was used to design a high-resolution WRF–LES simulation method. This method was applied to simulate a typical case of windshear at Hong Kong International Airport (HKIA) on 5 March 2015. The model results were compared with anemometer measurements and LiDAR scanning data of HKIA, which was found to capture many intra-airport wind features and microscale flows. The F-factor was employed to quantitatively describe the probability and range of windshear. This study demonstrates that the WRF–LES system is a valuable tool for simulating real-world microscale weather flows, which could be useful for the development of the real-time windshear forecasting system. Although further LES model refinements are highly desired, it presents a new idea for studying the characteristics of flow field with unsteady boundary conditions.
PubDate: 2022-06-10

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