Subjects -> METEOROLOGY (Total: 106 journals)
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 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  [2467 journals]
• Determination of suitable thermodynamic indices and prediction of
thunderstorm events for Eastern India

Abstract: Abstract We have studied the upper air RSRW data of 00 UTC during the pre-monsoon season, i.e. March–May of 2016–2018 for 6 capital cities viz. Kolkata, Bhubaneswar, Guwahati, Patna, Ranchi in the Eastern part of India and one island station, Port Blair. We have analyzed thermodynamic stability indices to identify the indices which have been most suitable for the prediction of thunderstorm events for each location. Based on the consensus of suitable indices and considering the spatial variation, we have proposed a scheme for predicting whether there would be any thunderstorm at a particular location within 24 hours. Verification has been carried out for 2019–2020 depending on availability of data and the performance of the proposed scheme has been compared with existing latest operational methods in India. We find that the proposed scheme can predict thunderstorms with reasonable accuracy and has better performance, mostly than that of existing operational methods.
PubDate: 2022-11-28

• Impact of sea-breeze circulation on the characteristics of convective
thunderstorms over southeast India

Abstract: Abstract The impact of Sea-breeze circulation on the convective thunderstorms over the southeast coast of Tamilnadu, India is studied using the Weather Research and Forecasting (WRF) model. High-resolution (2-km) simulations are conducted with WRF for two severe thunderstorm events on 24 April 2015 in summer 22 July 2015 in the southwest monsoon. Surface observations of Automated Weather Stations (AWS), gridded accumulated rainfall, radiosonde, and Doppler Weather Radar (DWR) reflectivity products are used for model evaluation. Simulations indicated that the moisture convergence in the sea breeze frontal zone and the presence of lower atmospheric wind shear during sea breeze are the main factors for the initiation of deep convection and intensification of the thunderstorms. Simulations reveal that the thunderstorms developed in summer are more intensive due to more intense and deep-sea breeze circulation cells developing under weak synoptic flow during summer compared to monsoon. Results show that simulated summer thunderstorms are associated with higher CAPE, lower CIN, stronger vertical motion in association with a stronger convergence, higher buoyancy and larger low-level wind shear and lower upper air shear compared to the monsoon thunderstorms. The presence of stronger lower atmospheric wind shear during summer sea-breeze favours the development of strong and deep convection compared to the monsoon season. Results also showed a simulation of more solid hydrometeors (ice, snow and graupel) due to intense convection in summer compared to the monsoon season.
PubDate: 2022-11-28

• Study of micrometeorological characteristics of the atmospheric surface
layer over a tropical coastal station in Goa

Abstract: Abstract This study presents turbulence characteristics of the atmospheric surface layer (ASL) observed during March 2015 to February 2016 over a tropical coastal site in Goa (15.46°N, 73.83°E), India. The primary datasets utilized are the 3D wind components and sonic temperature from sensors mounted on a 32-m meteorological tower at 10 and 20 m heights respectively. Eddy correlation technique has been adopted to study turbulence characteristics and is investigated under the framework of Monin–Obukhov Similarity Theory (MOST). Results revealed that normalized wind variances ( $${\upsigma }_{\mathrm{i}=\mathrm{u},\mathrm{ v},\mathrm{ w}}/{\mathrm{u}}_{*}$$ ) follow the ‘1/3’ power law in highly unstable and stable conditions and approach constant values close to near-neutral conditions. In the neutral limit, it is found that $${\upsigma }_{\mathrm{u}}/{\mathrm{u}}_{* }>{\upsigma }_{\mathrm{v}}/{\mathrm{u}}_{* }>{\upsigma }_{\mathrm{w}}/{\mathrm{u}}_{*}$$ . The normalized temperature variances ( $${\upsigma }_{\mathrm{T}}/{\mathrm{T}}_{*}$$ ) followed $${\left(\mathrm{z}/\mathrm{L}\right) }^{-1/3}$$ during unstable conditions and approach a constant value in the stable limit. The correlation coefficients for momentum (heat) flux with stability were small (high) under strong unstable and stable conditions. Also, the values of momentum flux increased as it approaches neutral conditions which are consistent with studies reported over coastal/urban locations.
PubDate: 2022-11-22

• Continuous monitoring of the atmospheric boundary layer (ABL) height from
micro pulse lidar over a tropical coastal station, Kattankulathur (12.82°
N, 80.04° E)

Abstract: Abstract The continuous monitoring of the atmospheric boundary layer (ABL) height and its diurnal variation over the coastal station is generally a challenging task due to the frequent occurrence of the thermal internal boundary layer (TIBL), neutral boundary layer, and boundary layer with a strong residual layer (RL). The wavelet covariance transform (WCT) method provides robust estimates of the ABL height; however, it fails for the cases with strong RL and TIBL. Therefore, an improved fuzzy logic algorithm has been developed incorporating the sea breeze membership function besides the six membership functions used in previous studies. Fuzzy logic classifies the signals according to the membership functions based on the quality score of the individual extracted features, making it a robust method for identifying the different types of ABL. In this study, 78 days of micropulse lidar (MPL) observations over Kattankulathur (12.82° N, 80.04°E) during 2018 are utilized to identify the diurnal variation of the ABL using a fuzzy logic algorithm. Out of 78 cases, we have observed 12 convective or unstable ABL cases, 10 neutral ABL, 24 convective cases with strong RL, and 32 convective cases dominated by TIBL. For the unstable ABL, both fuzzy logic and WCT detect a similar diurnal pattern. For the neutral ABL, the stable boundary layer (SBL) does not evolve, and hence again, both fuzzy logic and WCT detect a similar ABL pattern. However, for the strong RL and TIBL cases, the ABL height obtained using the WCT method overestimates the fuzzy logic algorithm. The ABL height for various diurnal patterns obtained using fuzzy logic algorithm compares well with radiosonde observations at 05:30 IST and 17:30 IST. The daytime mean ABL height obtained using fuzzy logic compares well with the Indian monsoon data assimilation and analysis (IMDAA) re-analysis product (generated for the Indian monsoon region); however, IMDAA underestimates the night-time mean ABL height.
PubDate: 2022-11-17

• Kalman filter sensitivity tests for the NWP and analog-based forecasts
post-processing

Abstract: Abstract The goal of this study is to perform a detailed sensitivity test to find the optimal value of the variance ratio r for four different post-processing forecasts that use the Kalman filter (KF) for the point-based wind gust predictions. The four forecasts analyzed in this paper are KF (KF applied to the raw NWP time series), KFAN (KF applied to the simple analog method time series), KFAS (KF applied to NWP forecasts in analog space), and KF-KFAS (KF applied to the KFAS time series). The wind gust impacts the severity of wind-related events. It is usually not a prognostic but a diagnostic variable in NWP models, which makes it an excellent candidate for post-processing. The results suggest that for the KF and KFAS forecasts the r value of 0.01 should be used, whereas for the KFAN and KF-KFAS forecasts the r value should be set to 0.001. The proposed values are considered optimal since they lead to excellent results for the overall data, and the results remain satisfactory even for strong wind. It, however, needs to be mentioned that the usage of different r values always comes with certain trade-offs. The r values smaller than proposed can sometimes slightly improve the overall result, but often lead to considerably worse results for the strong wind. On the other hand, the r values greater than proposed often show good quality of strong wind forecasts but lead to worse results overall. Even so, if the focus is set on extreme events, higher r values than proposed could be considered, but with caution.
PubDate: 2022-11-14

• Impact of Southern Oscillation and Indian Ocean Dipole on rainfall
variability over India: trends and interlinkages during 1871–2017

Abstract: Abstract This investigation highlights changes and various facets of inter-connections between rainfall over India and its prominent drivers such as Southern Oscillation (SO) and Indian Ocean Dipole (IOD). As the monsoon rainfall over majority of sub-divisions from Northeast India (NEI) and Central Northeast India regions (53% area) exhibits declining trend, which are reflected in annual rainfall (AR) as well. On the contrary, during the post-1971 period, the post-monsoon rainfall is observed to be decreasing over all the regions, except Peninsular India (PI). Moreover, the contradictory trends in monsoon and post-monsoon rainfall are registered over the PI, Northwest India (NWI) and West Central India regions. The significant increase in IOD (warming over Arabian Sea) is observed with a swift rise after 1960. Under changing climate conditions, a decline in rainfall and an increase in IOD Index (IODI) may aggravate the water scarcity challenge in semi-arid regions. More than 70% of sub-divisions has positive and negative relationship of SO with monsoon and post-monsoon rainfall, respectively. This contradiction is particularly observed over PI Region, which led to weaker SO-AR relationship. As compared to SO-rainfall relationship, almost opposite picture is observed in the case of sub-divisional and regional rainfall (monsoon and post-monsoon)-IOD relationship. The SO-AR relationship displays epochs of weak (1941–1970 and 1995–2016) and strong (1871–1941 and 1970–1995) connections. Interestingly, the strengthening of the IOD-AR relationship is responsible for the weakening of SO-AR and vice-versa, especially during the post-1970 period. It is evident that the strengthening of SO-IOD relationship results in good rainfall over India, as it shows a significant positive relationship and explains about 6 to 38% variations in regional and All-India annual rainfall.
PubDate: 2022-11-07

• Assessment of the impact of ocean mean temperature on numerical
simulations of tropical cyclones

Abstract: Abstract Heat energy, available within the upper oceanic layers known as ocean heat content (OHC), plays an important role in cyclone formation and progression. The mean temperature of ocean subsurface is one of the important parameters to be used in numerical simulation of tropical cyclones (TCs), which is considered the better parameterization of SST that takes account of OHC. In the present study, three TCs (viz, GAJA, FANI and VAYU) that formed over the North Indian Ocean during 2018–19, were simulated using Advanced Research version of the Weather Research and Forecast (WRF-ARW) model. Two numerical simulations have been performed for each of the three cyclones by ingesting SST and mean temperature from surface to 50 m depth (referred as ocean subsurface temperature (OST)) in WRF-ARW respectively to assess the impact of OST in comparison to SST on TCs simulations. WRF-ARW model has been configured here with vortex-following option. The impact of OST with respect to SST has been analyzed based on the associated parameters of TC like track, landfall position, intensity, wind fields and rainfall. Model simulated tracks and intensity obtained from each of the experiments have been verified against the available best tracks provided by India Meteorological Department (IMD). Our results show that the incorporation of OST leads to reduced track error, with a reduction of ~ 9% to 16% in 12 to 72 h simulations. Analysis of intensity also reveals the positive impact of OST on TCs over the North Indian Ocean in comparison to SST.
PubDate: 2022-11-06

• Influence of the indirect assimilation of radar reflectivity data using

PubDate: 2022-11-05

• Understanding the rapid intensification of extremely severe cyclonic storm
‘Tauktae’ using remote-sensing observations

Abstract: Abstract Despite substantial progress in the tropical cyclone (TC) intensity forecasting, the prediction of rapid intensification (RI) of TCs is still a key challenge to the operational forecasting agencies. Better understanding of the environmental processes associated with RI of TCs would essentially improve its forecasting capability. The physical processes contributing to RI are not well explored in the North Indian Ocean. In this study, the environmental and structural factors associated with RI of an Extremely Severe Cyclonic Storm (ESCS) ‘Tauktae’ over the Arabian Sea are investigated using remote-sensing satellites and Doppler weather radar observations. The TC-Tauktae underwent RI during 16–17 May, 2021, and it has wreaked havoc on India’s western coastal states as it moved parallel to the west coast with track length of about 1180 km. The TC-Tauktae exhibited 61 h of eye scenes during its lifetime, which is more than the eye scenes observed during the super cyclone ‘Amphan’ in May 2020 and double the long period (1982–2015) global average of 30 h. Remote sensing-based eye roundness value and upper tropospheric warm-core anomalies showed promising results for the prediction of TC intensity at very short time scale. In addition, several oceanic and environmental parameters, such as sea surface temperature, tropical cyclone heat potential, vertical wind shear, lower level convergence, upper level divergence, relative vorticity, and total precipitable water content, during different stages of the TC-Tauktae have been analyzed using satellite-derived products to identify their roles during RI of the TC. The findings of this study could serve as supplementary information to enhance the accuracy of operational forecasting of RI of TCs over the North Indian Ocean basins.
PubDate: 2022-10-14

• Macro- and microphysical characteristics of snowfall and non-snowfall
clouds in the West Tianshan Mountains of China based on cloud radar

Abstract: Abstract The macro- and microphysical characteristics of wintertime precipitating clouds and non-precipitating clouds over the West Tianshan Mountains, China, were analyzed with the use of Ka-band radar and weighing rain gauge observations. The data were collected from January to February 2019, December 2019, and from December 2020 to February 2021. Snowfall clouds mainly ranged from 0.15 ~ 2.50 km and had a reflectivity (Z) of mostly 10 ~ 33 dBZ. Non-snowfall clouds were primarily distributed within the height range of 2 ~ 8 km, and the Z values were within the range of − 22 ~ 15 dBZ. Compared with non-snowfall clouds, snowfall clouds have a higher particle water content (M) but a similar radial velocity (V). Light and moderate snowfall clouds were mainly located at heights of 0.15 ~ 3.50 km and had Z values concentrated from 5 ~ 24 dBZ. Heavy snowfall clouds were characterized by a Z of 5 ~ 30 dBZ below 3.5 km. The proportion of clouds with an M value > 0.1 g·m−3 below 2 km was noticeably higher for heavy snow events than for light and moderate snow events. The differences in the distributions and values of snowfall cloud V values were small among the different snow types, and descending motions occurred below 6 km, with V ranging − 1.4 ~ − 0.3 m·s−1. The heights of the non-snowfall cloud top and base during the day were lower than those at night. The snowfall cloud top did not show noticeable diurnal variations. The cloud top and base heights of the non-snowfall clouds both showed a single-peak distribution. The cloud top values of snowfall clouds exhibited bimodal distributions.
PubDate: 2022-10-14

• Changes in tropospheric ozone concentration over Indo-Gangetic Plains: the
role of meteorological parameters

Abstract: Abstract This study seeks to understand and quantify the changes in tropospheric ozone (O3) in lower troposphere (LT), middle troposphere (MT) and upper middle troposphere (UMT) over the Indo-Gangetic Plains (IGPs), India during the COVID-19 lockdown 2020 with that of pre-lockdown 2019. The gridded datasets of ozone from the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis product, ERA5 in combination with statistical interpolated (IDWs) surface NO2 observations, present a consistent picture and indicate a significant tropospheric ozone enhancement over IGP during COVID-19 lockdown restrictions in May 2020. The Paper also examines the influencing role of meteorological parameters on increasing ozone concentration. Over LT, an increase in O3 concentration (23%) is observed and in MT to UMT an enhancement of about 9–18% in O3 concentration have been seen during May 2020 with respect to May 2019. An investigation on causes of increasing  ozone concentration (35–85 ppbv) from MT to UMT during May 2020 reveals that there was significant rise (by 1–6%) in low cloud cover (LCC). Notably, higher LCC increases the backscattering of upward solar radiation from the top of the atmosphere. A positive difference of 5–25 W/m2 in upward solar radiation (USR) is observed across the entire study region. The result suggests that higher LCC significantly contributed to the enhanced USR. Thereby, resulting in higher photolysis rate that lead to an increase in mid tropospheric ozone concentration during May 2020. The results highlight the importance of LCC as an important pathway in ozone formation and aid in scientific understanding of it.
PubDate: 2022-10-12

• Assessment of hydrological drought return periods with bivariate copulas
in the Tigris river basin, Turkey

Abstract: Abstract Drought basically consists of four main components: duration, severity, intensity, and frequency. The fact that these different components having impact on drought are related to each other brings some difficulties in drought research. These parameters are generally evaluated univariate in drought analyses, however, a “joint multivariate distribution” of these parameters is required for a realistic drought assessment. Joint multivariate evaluation of drought parameters can be determined with Copula functions. In this study, hydrological drought analysis is conducted for 16 streamflow gauging stations in the Tigris Basin, Turkey, with the Streamflow Drought Index (SDI). The drought duration and severity values are extracted using Run Theory, and the best fitted marginal distribution functions of each parameter are determined among 13 distribution functions. The joint probabilities of drought duration and severity are evaluated using six different copulas (Ali-Mikhail-Haq, Clayton, Frank, Galambos, Gumbel-Hougaard and Joe), and the best representing copula is found as Galambos according to Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Univariate return periods and bivariate return periods calculated with Galambos copula are compared and the results are evaluated spatially. It is seen that the difference between univariate return periods and bivariate return periods is in the range of 5–10% in most of the stations. As a result of the spatial analysis of the drought duration and severity in the Tigris basin with bivariate copula, it is seen that the central and western parts of the basin have a high risk.
PubDate: 2022-10-07

• Successive probable maximum precipitation (SPMP) methodology and
applications

Abstract: Abstract PMP has two different estimation methods, namely statistical and hydro-meteorological approaches. The statistical method is based on the calculation of frequency factor (FF) by taking into account the arithmetic mean and standard deviation parameters. The classical probable maximum precipitation (PMP) is based on the (FF) calculated from the annual daily maximum precipitation (ADMP) time series records, which excludes the maximum recording. The classical method returns an FF value without any uncertainty. This paper suggests a successive FF (SFF) method that leads to a series of SFFs, starting with the first three records, and then scanning the entire time series. The probabilistic operation of the SFF sequence presents the uncertainty components in FF based on a set of preset exceedence probability levels and their corresponding return periods. The application of the methodology is presented for three ADMP records from Turkey, Algeria and Arabian Peninsula, which represent humid, semi-arid and arid regions, respectively. The arithmetic mean of the SSF values for the meteorology stations in each country was calculated as 3.07, 2.75 and 3.45, respectively. However, predetermined exceedence probability amounts are presented in the form of tables and graphics. It was concluded that the classical FF calculation provides a single value without any exceedence probability assessment, whereas the SFF method provides FF values with a range of exceedence probability levels.
PubDate: 2022-10-02

• Lightning over Tibetan Plateau and its relation with winds associated with
CAPE

Abstract: Abstract Association of lightning with winds over Tibetan Plateau (TP) is examined by analyzing lightning data during the period 1999–2013. The study reveals that nearly 92% lightning activity occurred during April to September is associated with the wind circulation, especially cyclonic circulation. Nearly 58% of lightning is found to happen during May (18.6%), June (19.29%), and July (19.56%). Less vertical wind shear (less than 10 m/s) and high CAPE (more than 400 J/kg) are found to be associated with lightning. Analysis shows that negative correlation exists between wind shear and lightning. Results reveal that high wind shear tends to restrict the growth of convection, resulting in lightning. On annual scale, there exist negative correlation between lightning and wind shear and insignificant correlation between lightning and CAPE for April-September. However, a new relationship is established when CAPE and shear are taken together, and a strong positive correlation is found between lightning and CAPE per shear (CAPE/shear). Hence, we propose that for better understanding on lightning over Tibetan Plateau, it would be much more useful to consider CAPE/shear rather than CAPE or wind shear alone.
PubDate: 2022-09-29

• Probabilistic prediction of SPI categories in Iran using sea surface
temperature climate indices

Abstract: Abstract This study examines probabilistic prediction of the standardized precipitation index (SPI) categories (i.e., dry, normal and wet conditions) in Iran regressed onto the combination of the North Atlantic Oscillation (NAO) index and several sea surface temperature (SST) indices including Niño4, Niño3.4, Niño3, Niño1 + 2, western Pacific (WP; 0º–15ºN, 130º–160ºE), the eastern Mediterranean Sea (EM; 30º–38ºN, 20º–35ºE) and the Indian Ocean Dipole (IOD). The ordinal regression models (ORM) based on the logistic function are applied to determine the best predictor variables. Seasonal precipitation during the two wet seasons of October-December (OND) and January-March (JFM) for 50 synoptic stations across Iran for the period 1967–2017 are used in this research. 3 month SPI at the end of December and March, which provides SPI values over OND and JFM, is constructed based on the Gamma probability distribution. The SPI categories for OND and JFM precipitation averaged over Iran are considered as the predictand variables in the ORM. The linear trend analysis of JFM SPI values indicates that the risk of drought has been enhanced in this season. Among all individual predictors, the SST anomalies over the central Pacific Ocean has the strongest teleconnection with OND SPI categories. Based on the minimum Akaike information criterion (AIC), the combination of Niño3.4 and WP gives the best model for probabilistic prediction of wet and dry events in OND. Unlike the OND, the SST anomalies over different parts of the Pacific Ocean are not strongly related to the SPI values of the JFM season in Iran. Among all indices, only the SST anomaly variations over the eastern Mediterranean Sea are statistically teleconnected to JFM SPI categories and can be used to predict dry and wet events probability in Iran.
PubDate: 2022-09-27

• Structure and development of the atmospheric boundary layer over a small
island (Mahé Island, Seychelles) in the equatorial Indian Ocean

Abstract: Abstract The island of Mahé, Seychelles (4.68oS, 55.53oE) is located close to the region responsible for the initiation and eastward propagation of the Madden Julian Oscillation in addition to being part of the Seychelles dome (an oceanic thermal dome) and the Seychelles–Chagos Thermocline Ridge each of which influences the atmosphere at multiple time scales. The representativeness of the island of the oceanic region surrounding it is limited by its atmospheric boundary layer (ABL). This tiny island (of area ~ 150 km−2) can be considered as a large ship permanently anchored at the equatorial Indian Ocean capable of making long-term atmospheric observations representing its surroundings provided its ABL structure and development is known. This study presents, for the first time, in situ observations of day-night variability of ABL over Mahé, Seychelles using high vertical resolution radiosonde ascents from November 2011 to January 2012. The ABL height (ABLH) was observed to vary in a range of 200–1300 m in the course of a day with a daytime mean of 855 ± 300 m and a nighttime mean of 165 ± 85 m. For an unstable boundary layer, a statistically significant positive (negative) correlation was observed between ABLH and near-surface temperature (near-surface relative humidity) with correlation coefficient R = 0.77 (R = − 0.45) indicating that a warmer island produces a deeper boundary layer subject to limits imposed by the marine influence. It also indicates the significant contribution of sensible heat flux to ABLH at the site. Observations indicate near-surface wind speeds greater than 5 m/s either disrupt stable air by mechanical wind shear or advect them out of the island.
PubDate: 2022-09-23

• Future projection for climate extremes in the North China plain using
multi-model ensemble of CMIP5

Abstract: Abstract Extreme climate event (ECE) had exerted great impacts on human life, and the study of extreme climate can reduce the risks caused by ECEs for social and economic development. In the study, we evaluated the spatiotemporal change characteristics of 26 extreme climate indices (ECIs) during 1971–2100 in the North China Plain (NCP) based on observed climate data and 33 Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The independence weighted mean (IWM) and arithmetic mean (AM) were used to compare with the performance of individual GCM. The projected ECIs from IWM had smaller normalized root-mean-square error (nRMSE) and mean absolute percentage error (MAPE) with observations compared to that from the individual GCM and AM, which can better reproduce the temporal trends of ECIs in the historical period (1971–2005). Across the NCP, the extreme low-temperature indices showed significant decreasing trends during 2031–2100 under both of Representative Concentration Pathway (RCP) 4.5 and RCP8.5. However, the extreme high-temperature indices showed significant increasing trends and the change amplitude was larger than that of the extreme low-temperature indices. Most extreme precipitation events (except drought events) will increase across the NCP. Moreover, the change magnitude under RCP8.5 was much higher than that under RCP4.5. Overall, the results indicated that there was great application potential in multi-model ensemble for IWM. Meanwhile, there would be more heat stress and intense precipitation across the NCP in the coming decades of the twenty-first century.
PubDate: 2022-09-23

• Probabilistic modeling and identifying fluctuations in annual extreme
heatwave regimes of Karachi

Abstract: Abstract Climatic warming in the global mean has significantly increased the probability of occurrence of heat extremes on time scales ranging from months to seasons. As extreme heat events are most likely to become intense and frequent over the next decades, it is important to examine these events to mitigate its negative impacts on public health and society. This study focuses on Karachi heat extremes over the last 23 years. The power spectral analyses of Karachi heat extremes records have been carried out by two indices: heat index (HI) and effective temperature index (TEE), which are also found to be significantly correlated. The result indicates a regular cyclic pattern of 4.5 years which is estimated to face a heat index of more than 73.63 °C, associated with the El Niño–Southern Oscillation (ENSO). Other peaks are observed at 2.8 and 2.2 years with the expected value of the Karachi heat index of 70.53 and 68.71 °C, respectively. The probabilistic approach is also used to predict the future heatwave events of Karachi. Generalized extreme value (GEV) distribution is found to be the best-fitted probability distribution for the extreme heatwave events on the basis of goodness-of-fit test. Furthermore, the estimation of the return period of the heatwave event reveals that Karachi will be facing a maximum heat index of 84.37 °C or more in the coming 33 years, which suggests an urgent need for mitigation strategies in Karachi to overcome the effects of extreme heatwave events.
PubDate: 2022-09-17
DOI: 10.1007/s00703-022-00927-0

• Characterization of meteorological parameters over Dokriani Glacier
catchment, Central Himalaya: implications for regional perspectives

Abstract: Abstract The Himalayan meteorology is important for understanding cryospheric-hydrological processes and climate change forecasts. The meteorological observations in the Indian Himalayan region (IHR), notably in glacierized catchments, are scarce. Therefore, the present study aims to demonstrate a comprehensive investigation of meteorological parameters (e.g., temperature, relative humidity, precipitation, wind speed and direction, radiation fluxes, albedo, and pressures) over the Dokriani Glacier catchment (DGC) using time-series data (2011–2016) obtained from a network of three automatic weather stations (AWSs). The study also provides new insights into characteristics of meteorological variables at inter- and intra-seasonal scales (winter: December–February, Pre-monsoon: March–May, Monsoon: June–September, and Post-monsoon: October–November). The results show that the albedo and outflux radiation decreases rapidly with the onset of monsoon season, while there is an increase of relative humidity (RH) and positive degree-days (PDDs). The positive temperature (> 2℃) at higher elevations (> 5500 m) raise serious concerns about the summer accumulation characteristics of the Dokriani glacier. The DGC has an average near-surface temperature lapse rate (NSTLR) of 6.0°C km−1, higher in the pre-monsoon and lower during the monsoon. The wind speed and albedo are more sensitive during winter and pre-monsoon seasons. The air temperature, rainfall, and relative humidity exhibit significant seasonal fluctuation, whereas other meteorological variables have a nearly comparable seasonal pattern. The Indian summer monsoon (ISM) significantly influences all climatic factors. This may be utilized to examine the Dokriani glacier's mass budget and melt rate with other dependent factors, such as glacier hypsometry, orientation, surface velocity, and the extent of debris-cover. Furthermore, the dataset of this study may be correlated with hydro-meteorological observations in various regions of the Himalaya and deciphered using a regional climate dataset; for example, the Kedarnath tragedy-2013 and the most recent flash flood that occurred in Raunthi valley, Tapovan on February 07, 2021.
PubDate: 2022-09-16
DOI: 10.1007/s00703-022-00923-4

• Analysis of precipitation temporal pattern of sub-daily ECMWF forecasts

Abstract: Abstract Temporal distribution of precipitation has various applications in flood studies. In particular, accurate estimates of temporal variation of precipitations are quite valuable in real-time flood warning. In this study, the performance of the ECMWF model in forecasting daily precipitation occurrence and sub-daily temporal distribution pattern was evaluated during the 2006–2021 period in eight regions in Iran. The forecasts were downscaled into the selected stations by using the inverse distance weighting method and further evaluated in three aspects. First, precipitation characteristics including start time, end time, and duration of 22,098 precipitation events in 49 stations were evaluated. Based on statistical analysis, 40.34%, 32.9%, and 14.4% of the events were correctly forecasted in start, end, and duration, respectively, where the best performance was associated with regions with high precipitation. Second, the dimensionless temporal pattern of both observed and forecasted 24-h precipitation events with 6-h time step were drawn and inter-compared in different precipitation regimes. The best-fitted pattern was identified in highland regions and the worst was associated with arid and semi-arid parts of Iran. In the third step, the quality of forecasts in each precipitation quartile were assessed via deterministic evaluation criteria. It was found that among all quartiles, the ECMWF forecasts in the second quartile scored highest (MP = 0.68), whereas the third quartile of precipitation events were poorly forecasted (MP = 0.36). In conclusion, the forecasts in regions with higher precipitation were of better quality in comparison with those of low precipitation regions although ground data of shorter time steps is needed for further evaluation. Also, in terms of synoptic analysis, forecasts associated with Mediterranean low-pressure systems yielded higher accuracy compared to those of other systems over Iran. The results might be utilized by flood experts to estimate and forecast floods more precisely and reduce disaster risk.
PubDate: 2022-09-13
DOI: 10.1007/s00703-022-00926-1

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